Tue, 23 Apr 2019

New package socviz with initial version 1.0.0
Package: socviz
Type: Package
Title: Utility Functions and Data Sets for Data Visualization
Version: 1.0.0
Authors@R: person("Kieran", "Healy", email = "kjhealy@gmail.com", role = c("aut", "cre"))
Maintainer: Kieran Healy <kjhealy@gmail.com>
Description: Supporting materials for a course and book on data visualization. It contains utility functions for graphs and several sample data sets. See Healy (2019) <ISBN 978-0691181622>.
License: MIT + file LICENSE
Depends: R (>= 3.1)
Imports: dplyr, fs, graphics, magrittr, rlang, tibble
Suggests: ggplot2
Encoding: UTF-8
LazyData: true
URL: https://github.com/kjhealy/socviz
BugReports: https://github.com/kjhealy/socviz/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-18 15:20:47 UTC; kjhealy
Author: Kieran Healy [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-23 12:00:03 UTC

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New package shinybusy with initial version 0.1.1
Package: shinybusy
Title: Busy Indicator for 'Shiny' Applications
Version: 0.1.1
Authors@R: c(person("Fanny", "Meyer", email = "fanny.meyer@dreamrs.fr", role = c("aut")), person("Victor", "Perrier", email = "victor.perrier@dreamrs.fr", role = c("aut", "cre")), person("Silex Technologies", comment = "https://www.silex-ip.com", role = "fnd"), person("Tobias", "Ahlin", role = "cph", comment = "spin.css"), person("Chris", "Antonellis", role = "cph", comment = "freezeframe.js"), person("Jacobo", "Tabernero", role = "cph", comment = "nanobar.js"))
Description: Add a global indicator (spinner, progress bar, gif) in your 'shiny' applications to show the user that the server is busy.
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
Imports: htmltools, shiny, jsonlite
RoxygenNote: 6.1.1
URL: https://github.com/dreamRs/shinybusy
BugReports: https://github.com/dreamRs/shinybusy/issues
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-04-17 20:43:14 UTC; perri
Author: Fanny Meyer [aut], Victor Perrier [aut, cre], Silex Technologies [fnd] (https://www.silex-ip.com), Tobias Ahlin [cph] (spin.css), Chris Antonellis [cph] (freezeframe.js), Jacobo Tabernero [cph] (nanobar.js)
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>
Repository: CRAN
Date/Publication: 2019-04-23 11:40:03 UTC

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New package RobStatTM with initial version 1.0.0
Package: RobStatTM
Version: 1.0.0
Date: 2019-03-03
Title: Robust Statistics: Theory and Methods
Authors@R: c(person("Matias", "Salibian-Barrera", role = c("cre"), email = "matias@stat.ubc.ca"), person("Victor", "Yohai", role = "aut", email = "vyohai@gmail.com"), person("Ricardo", "Maronna", role="aut", email= "rmaronna@retina.ar"), person("Doug", "Martin", role="aut", email="martinrd3d@gmail.com"), person("Gregory", "Brownson", role="aut", email="gregory.brownson@gmail.com", comment="ShinyUI"), person("Kjell", "Konis", role="aut", email="kjellk@gmail.com"), person("Kjell", "Konis", role="cph", email="kjellk@gmail.com", comment="erfi"), person("Christophe", "Croux", role="ctb", email="christophe.croux@edhec.edu", comment="WBYlogreg, BYlogreg"), person("Gentiane", "Haesbroeck", role="ctb", email="G.Haesbroeck@uliege.be", comment="WBYlogreg, BYlogreg"), person("Martin", "Maechler", role="cph", email="maechler@stat.math.ethz.ch", comment="lmrob.fit, lmrob..M..fit, lmrob.S"), person("Manuel", "Koller", role="cph", email="koller.manuel@gmail.com", comment="lmrob.fit, .vcov.avar1, lmrob.S, lmrob.lar"), person("Matias", "Salibian-Barrera", role="aut", email="matias@stat.ubc.ca") )
Description: Companion package for the book: "Robust Statistics: Theory and Methods, second edition", <http://www.wiley.com/go/maronna/robust>. This package contains code that implements the robust estimators discussed in the recent second edition of the book above, as well as the scripts reproducing all the examples in the book.
Depends: R (>= 3.0.2), fit.models
Imports: stats, graphics, utils, methods, DEoptimR, pyinit, rrcov, robustbase, shiny, shinyjs, PerformanceAnalytics, DT, ggplot2, gridExtra, robust, xts
Suggests: knitr
LazyData: yes
License: GPL (>= 3)
RoxygenNote: 6.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-04-23 04:48:58 UTC; Matias
Author: Matias Salibian-Barrera [cre], Victor Yohai [aut], Ricardo Maronna [aut], Doug Martin [aut], Gregory Brownson [aut] (ShinyUI), Kjell Konis [aut], Kjell Konis [cph] (erfi), Christophe Croux [ctb] (WBYlogreg, BYlogreg), Gentiane Haesbroeck [ctb] (WBYlogreg, BYlogreg), Martin Maechler [cph] (lmrob.fit, lmrob..M..fit, lmrob.S), Manuel Koller [cph] (lmrob.fit, .vcov.avar1, lmrob.S, lmrob.lar), Matias Salibian-Barrera [aut]
Maintainer: Matias Salibian-Barrera <matias@stat.ubc.ca>
Repository: CRAN
Date/Publication: 2019-04-23 11:30:06 UTC

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New package GetBCBData with initial version 0.5
Package: GetBCBData
Type: Package
Title: Imports Datasets from BCB (Central Bank of Brazil) using Its Official API
Version: 0.5
Date: 2019-04-15
Authors@R: person("Marcelo", "Perlin", email = "marceloperlin@gmail.com", role = c("aut", "cre"))
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>
Description: Downloads and organizes datasets using BCB's API <https://www.bcb.gov.br/>. Offers options for caching with the 'memoise' package and , multicore/multisession with 'furrr' and format of output data (long/wide).
Depends: R (>= 3.3.0)
Imports: stringr,stats, RCurl, lubridate, readr, utils, curl,dplyr, future, furrr, jsonlite, memoise, purrr
License: GPL-2
BugReports: https://github.com/msperlin/GetBCBData/issues
URL: https://github.com/msperlin/GetBCBData/
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat, ggplot2, tidyverse
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-04-16 13:06:28 UTC; msperlin
Author: Marcelo Perlin [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-23 10:10:29 UTC

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New package rIntervalTree with initial version 0.1.0
Package: rIntervalTree
Type: Package
Title: An Interval Tree Tool for Real Numbers
Version: 0.1.0
Authors@R: c(person("Shuye", "Pu", role = c("aut", "cre"), email = "shuye2009@gmail.com"))
Author: Shuye Pu [aut, cre]
Maintainer: Shuye Pu <shuye2009@gmail.com>
Description: This tool can be used to build binary interval trees using real number inputs. The tree supports queries of intervals overlapping a single number or an interval (start, end). Intervals with same bounds but different names are treated as distinct intervals. Insertion of intervals is also allowed. Deletion of intervals is not implemented at this point. See Mark de Berg, Otfried Cheong, Marc van Kreveld, Mark Overmars (2008). Computational Geometry: Algorithms and Applications, for a reference.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Collate: 'Interval.R' 'IntervalTree.R'
Imports: methods
NeedsCompilation: no
Packaged: 2019-04-18 16:34:12 UTC; greenblatt
Repository: CRAN
Date/Publication: 2019-04-23 09:20:03 UTC

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New package polyreg with initial version 0.6.4
Package: polyreg
Title: Polynomial Regression
Version: 0.6.4
Authors@R: c(person("Norm", "Matloff", email = "matloff@cs.ucdavis.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-9179-6785")), person("Xi", "Cheng", email = "xicheng0821@gmail.com", role = c("aut")), person("Pete", "Mohanty", email = "pmohanty@stanford.edu", role = c("aut"), comment = c(ORCID = "0000-0001-8531-3345")), person("Bohdan", "Khomtchouk", email = "bohdan@stanford.edu", role = c("aut")), person("Matthew", "Kotila", email = "mrkotila@ucdavis.edu", role = c("aut")), person("Robin", "Yancey", email = "reyancey@ucdavis.edu", role = c("aut")), person("Robert", "Tucker", email = "ratucker@ucdavis.edu", role = c("aut")), person("Allan", "Zhao", email = "awxzhao@ucdavis.edu", role = c("aut")), person("Tiffany", "Jiang", email = "thjiang@ucdavis.edu", role = c("ctb")))
Maintainer: Norm Matloff <matloff@cs.ucdavis.edu>
Description: Automate formation and evaluation of polynomial regression models. Provides support for cross-validating categorical variables. The motivation for this package is described in 'Polynomial Regression As an Alternative to Neural Nets' by Xi Cheng, Bohdan Khomtchouk, Norman Matloff, and Pete Mohanty (<arXiv:1806.06850>).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends:
URL: https://github.com/matloff/polyreg
BugReports: https://github.com/matloff/polyreg/issues
RoxygenNote: 6.0.1
Imports: nnet,dummies, parallel, partools, RSpectra, stats, utils
NeedsCompilation: no
Packaged: 2019-04-16 06:32:12 UTC; mohanty
Author: Norm Matloff [aut, cre] (<https://orcid.org/0000-0001-9179-6785>), Xi Cheng [aut], Pete Mohanty [aut] (<https://orcid.org/0000-0001-8531-3345>), Bohdan Khomtchouk [aut], Matthew Kotila [aut], Robin Yancey [aut], Robert Tucker [aut], Allan Zhao [aut], Tiffany Jiang [ctb]
Repository: CRAN
Date/Publication: 2019-04-23 09:30:03 UTC

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New package nptest with initial version 1.0-0
Package: nptest
Type: Package
Title: Nonparametric Tests
Version: 1.0-0
Date: 2019-04-15
Author: Nathaniel E. Helwig <helwig@umn.edu>
Maintainer: Nathaniel E. Helwig <helwig@umn.edu>
Depends: parallel
Description: Robust permutation tests for location, correlation, and regression problems, as described in Helwig (2019) <doi:10.1002/wics.1457>. Univariate and multivariate tests are supported. For each problem, exact tests and Monte Carlo approximations are available. Parallel computing is implemented via the 'parallel' package.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-04-16 04:44:19 UTC; Nate
Repository: CRAN
Date/Publication: 2019-04-23 09:20:32 UTC

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New package cmocean with initial version 0.1-1
Package: cmocean
Encoding: UTF-8
Version: 0.1-1
Title: Beautiful Colour Maps for Oceanography
Authors@R: c(person('Kristen', 'Thyng', email = 'kthyng@gmail.com', role = 'aut'), person('Clark', 'Richards', email = 'clark.richards@gmail.com', role = 'ctb'), person('Ivan', 'Krylov', email = 'krylov.r00t@gmail.com', role = 'cre'))
Maintainer: Ivan Krylov <krylov.r00t@gmail.com>
Imports: grDevices
Depends: R (>= 3.0.0)
Suggests: knitr
LazyData: no
Description: Perceptually uniform palettes for commonly used variables in oceanography as functions taking an integer and producing character vectors of colours. See Thyng, K.M., Greene, C.A., Hetland, R.D., Zimmerle, H.M. and S.F. DiMarco (2016) <doi:10.5670/oceanog.2016.66> for the guidelines adhered to when creating the palettes.
License: MIT + file LICENSE
URL: https://matplotlib.org/cmocean/
BugReports: https://github.com/aitap/cmocean
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-16 10:11:16 UTC; aitap
Author: Kristen Thyng [aut], Clark Richards [ctb], Ivan Krylov [cre]
Repository: CRAN
Date/Publication: 2019-04-23 09:50:03 UTC

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New package PROBShiny with initial version 0.1.0
Package: PROBShiny
Type: Package
Title: Interactive Document for Working with Basic Probability
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of basic probability using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://analyticmodels.shinyapps.io/BayesShiny/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,LaplacesDemon,shinyMatrix,rpivotTable,epitools
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-18 17:10:53 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-04-23 08:30:03 UTC

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Mon, 22 Apr 2019

New package MLRShiny with initial version 0.1.0
Package: MLRShiny
Type: Package
Title: Interactive Application for Working with Multiple Linear Regression
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive application for working with multiple linear regression technique. The application has a template for solving problems on multiple linear regression. Runtime examples are provided in the package function as well as at <https://kartikeyastat.shinyapps.io/MLR_WEB_K/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,shinyAce,dplyr,psych,QuantPsyc,forecast,corrgram
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-11 05:30:07 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-04-22 19:20:03 UTC

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Sun, 21 Apr 2019

New package tcie with initial version 0.3
Package: tcie
Type: Package
Title: Topologically Correct Isosurface Extraction
Version: 0.3
Date: 2019-04-19
Author: Lis Custódio
Maintainer: Lis Custodio <liscustodio.uerj@gmail.com>
URL: http://liscustodio.github.io/
Description: Isosurfaces extraction algorithms are a powerful tool in the interpretation of volumetric data. The isosurfaces play an important role in several scientific fields, such as biology, medicine, chemistry and computational fluid dynamics. And, for the data to be correctly interpreted, it is crucial that the isosurface be correctly represented. The Marching Cubes algorithm, proposed by Lorensen and Cline <doi:10.1145/37401.37422> in 1987, is clearly one of the most popular isosurface extraction algorithms, and an important tool for many visualization specialists and researchers. The generalized adoption of the Marching Cubes has resulted in many improvements in its algorithm, including, the establishment of the topological correctness of the generated mesh. In 2013, Custodio et al. <doi:10.1016/j.cag.2013.04.004> noted and corrected algorithmic inaccuracies that compromised the topological correctness of the mesh generated by the last version of the Marching Cubes Algorithm: the Marching Cubes 33 proposed by Chernyaev in 1995, implemented in 2003 by Lewiner et al. <doi:10.1080/10867651.2003.10487582>. In 2019, Custodio et al. (in the work An Extended Triangulation to the Marching Cubes 33 Algorithm) proposed an extended triangulation to the Marching Cubes 33 algorithm, in the proposed algorithm the grid vertex are labeled with "+", "-" and "=", according to the relationship between its scalar field value and the isovalue.The inclusion of the "=" grid vertex label naturally avoids degenerate triangles, a well-known issue in meshes generated by the Marching Cubes. The Marching Cubes algorithm has been implemented using many software programs and compilers: C++, proposed by Lewiner et al. (2003); 'MATLAB', proposed by Hammer (2011); and R, proposed by Feng and Tierney (2008). Marching Cubes is also integrated into many visualization toolkits. The complexity of an algorithm increases considerably when it aims to reproduce the topology of the trilinear interpolant correctly. This complexity can sometimes result in errors in the algorithm or in its implementation. During our experiments we observe that all the implementations mentioned have critical issues that compromise the continuity and the topological correctness of the generated mesh. The 'tcie' package is a toolkit with a topologically correct implementation of the Marching Cubes algorithm, based on the Custodio et al. work, which implements the most recent improvements of the algorithm.
LazyData: TRUE
LinkingTo: Rcpp,RcppArmadillo
Imports: nat(>= 1.8.11), rgl(>= 0.99.9), Rvcg (>= 0.17), geomorph (>= 3.0.5)
Depends: R (>= 3.2.3)
RoxygenNote: 6.1.1
License: GPL
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-04-20 01:26:55 UTC; lis
X-CRAN-Archive: Archived on 2019-04-21 as update had exactly the same check problems as before.
Repository: CRAN
Date/Publication: 2019-04-21 15:10:03 UTC

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Wed, 17 Apr 2019

New package gRc with initial version 0.4-3.2
Package: gRc
Version: 0.4-3.2
Title: Inference in Graphical Gaussian Models with Edge and Vertex Symmetries
Author: Søren Højsgaard <sorenh@math.aau.dk>, Steffen L. Lauritzen <steffen@stats.ox.ac.uk>
Maintainer: Søren Højsgaard <sorenh@math.aau.dk>
Description: Estimation, model selection and other aspects of statistical inference in Graphical Gaussian models with edge and vertex symmetries (Graphical Gaussian models with colours). Documentation about 'gRc' is provided in the paper by Hojsgaard and Lauritzen (2007, <doi:10.18637/jss.v023.i06>) and the paper by Hojsgaard and Lauritzen (2008, <doi:10.1111/j.1467-9868.2008.00666.x>).
License: GPL
Encoding: UTF-8
Depends: methods, gRbase
Imports: MASS,
Suggests: Rgraphviz, RBGL, microbenchmark, knitr
URL: http://people.math.aau.dk/~sorenh/software/gR/
Repository: CRAN
ByteCompile: Yes
biocViews:
NeedsCompilation: yes
Packaged: 2019-04-17 04:24:38 UTC; sorenh
Date/Publication: 2019-04-17 10:00:02 UTC

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Tue, 16 Apr 2019

New package holodeck with initial version 0.2.0
Package: holodeck
Title: A Tidy Interface for Simulating Multivariate Data
Version: 0.2.0
Authors@R: person(given = "Eric", family = "Scott", role = c("aut", "cre"), email = "scottericr@gmail.com")
Description: Provides pipe-friendly (%>%) functions to create simulated multivariate data sets with groups of variables with different degrees of variance, covariance, and effect size.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
biocViews:
Imports: dplyr, tibble, MASS, purrr, rlang, assertthat
RoxygenNote: 6.1.1
URL: https://github.com/Aariq/holodeck
BugReports: https://github.com/Aariq/holodeck/issues
Suggests: testthat, covr, knitr, rmarkdown, iheatmapr, mice, ropls, ggplot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-15 19:56:19 UTC; scottericr
Author: Eric Scott [aut, cre]
Maintainer: Eric Scott <scottericr@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-16 12:12:40 UTC

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New package HDMT with initial version 1.0
Package: HDMT
Type: Package
Title: A Multiple Testing Procedure for High-Dimensional Mediation Hypotheses
Version: 1.0
Date: 2019-04-07
Authors@R: c(person("James", "Dai", role = c("aut", "cre"), email = "jdai@fredhutch.org"), person("Xiaoyu", "Wang", role = c("aut")))
Author: James Dai [aut, cre], Xiaoyu Wang [aut]
Maintainer: James Dai <jdai@fredhutch.org>
Description: A multiple-testing procedure for high-dimensional mediation hypotheses. Mediation analysis is of rising interest in epidemiology and clinical trials. Among existing methods for mediation analyses, the popular joint significance (JS) test yields an overly conservative type I error rate and therefore low power. In the R package 'HDMT' we implement a multiple-testing procedure that accurately controls the family-wise error rate (FWER) and the false discovery rate (FDR) when using JS for testing high-dimensional mediation hypotheses. The core of our procedure is based on estimating the proportions of three component null hypotheses and deriving the corresponding mixture distribution of null p-values. Results of the data examples include better-behaved quantile-quantile plots and improved detection of novel mediation relationships on the role of DNA methylation in genetic regulation of gene expression. With increasing interest in mediation by molecular intermediaries such as gene expression and epigenetic markers, the proposed method addresses an unmet methodological challenge.
Depends: R (>= 3.4.0)
Imports: cp4p,fdrtool
LazyLoad: no
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-04-15 20:16:02 UTC; xwang234
Repository: CRAN
Date/Publication: 2019-04-16 12:42:43 UTC

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New package dstat with initial version 1.0.4
Package: dstat
Type: Package
Title: Conditional Sensitivity Analysis for Matched Observational Studies
Version: 1.0.4
Author: Paul R. Rosenbaum
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>
Description: A d-statistic tests the null hypothesis of no treatment effect in a matched, nonrandomized study of the effects caused by treatments. A d-statistic focuses on subsets of matched pairs that demonstrate insensitivity to unmeasured bias in such an observational study, correcting for double-use of the data by conditional inference. This conditional inference can, in favorable circumstances, substantially increase the power of a sensitivity analysis (Rosenbaum (2010) <doi:10.1007/978-1-4419-1213-8_14>). There are two examples, one concerning unemployment from Lalive et al. (2006) <doi:10.1111/j.1467-937X.2006.00406.x>, the other concerning smoking and periodontal disease from Rosenbaum (2017) <doi:10.1214/17-STS621>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: stats
NeedsCompilation: no
Packaged: 2019-04-15 13:23:56 UTC; Rosenbaum
Repository: CRAN
Date/Publication: 2019-04-16 09:42:41 UTC

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New package cmmr with initial version 0.1.2
Package: cmmr
Type: Package
Title: CEU Mass Mediator RESTful API
Version: 0.1.2
Date: 2019-03-26
Depends: R (>= 3.1.0)
Imports: httr (>= 1.3.1), progress (>= 1.2.0), RJSONIO (>= 1.3-0)
Author: Yaoxiang Li <yl814@georgetown.edu>, Charles P. Hinzman <cph51@georgetown.edu>, Amrita K Cheema <akc27@georgetown.edu>
Maintainer: Yaoxiang Li <yl814@georgetown.edu>
Description: CEU (CEU San Pablo University) Mass Mediator is an on-line tool for aiding researchers in performing metabolite annotation. 'cmmr' (CEU Mass Mediator RESTful API) allows for programmatic access in R: batch search, batch advanced search, MS/MS (tandem mass spectrometry) search, etc. For more information about the API Endpoint please go to <https://github.com/lzyacht/cmmr>.
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/lzyacht/cmmr
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-04-01 00:49:07 UTC; bach
Repository: CRAN
Date/Publication: 2019-04-16 09:42:44 UTC

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New package frequentdirections with initial version 0.1.0
Package: frequentdirections
Type: Package
Title: Implementation of Frequent-Directions Algorithm for Efficient Matrix Sketching
Version: 0.1.0
Authors@R: c( person("Shinichi", "Takayanagi", , "shinichi.takayanagi@gmail.com", role = c("aut", "cre")), person("Nagi", "Teramo", , "teramonagi@gmail.com", role = c("aut")) )
Description: Implement frequent-directions algorithm for efficient matrix sketching. (Edo Liberty (2013) <doi:10.1145/2487575.2487623>).
URL: https://github.com/shinichi-takayanagi/frequentdirections
BugReports: https://github.com/shinichi-takayanagi/frequentdirections/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2,
Suggests: testthat, knitr, rmarkdown
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-15 13:03:42 UTC; stakaya
Author: Shinichi Takayanagi [aut, cre], Nagi Teramo [aut]
Maintainer: Shinichi Takayanagi <shinichi.takayanagi@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-16 08:52:42 UTC

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Mon, 15 Apr 2019

New package Irescale with initial version 0.2.6
Package: Irescale
Type: Package
Title: Calculate and Scale Moran's I
Version: 0.2.6
Author: Ivan Fuentes, Thomas DeWitt, Thomas Ioerger, Michael Bishop
Maintainer: Ivan Fuentes <jivfur@tamu.edu>
Description: Provides a scaling method to obtain a standardized Moran's I measure. Moran's I is a measure for the spatial autocorrelation of a data set, it gives a measure of similarity between data and its surrounding. The range of this value must be [-1,1], but this does not happen in practice. This package scale the Moran's I value and map it into the theoretical range of [-1,1]. Once the Moran's I value is rescaled, it facilitates the comparison between projects, for instance, a researcher can calculate Moran's I in a city in China, with a sample size of n1 and area of interest a1. Another researcher runs a similar experiment in a city in Mexico with different sample size, n2, and an area of interest a2. Due to the differences between the conditions, it is not possible to compare Moran's I in a straightforward way. In this version of the package, the spatial autocorrelation Moran's I is calculated as proposed in Chen(2009) <arXiv:1606.03658>.
License: GPL (>= 2)
URL: https://github.tamu.edu/jivfur/Irescale
Encoding: UTF-8
LazyData: true
Imports: Rcpp, ggplot2, sp, e1071, graphics, grDevices, stats, utils,Rdpack
RoxygenNote: 6.1.1
RdMacros: Rdpack
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-15 20:34:16 UTC; jivfur
Repository: CRAN
Date/Publication: 2019-04-15 21:22:56 UTC

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New package allelematch with initial version 2.5.1
Package: allelematch
Title: Identifying Unique Multilocus Genotypes where Genotyping Error and Missing Data may be Present
Version: 2.5.1
Authors@R: c( person("Paul", "Galpern", email = "pgalpern@gmail.com", role = "aut"), person("Todd", "Cross", email = "todd.cross@gmail.com", role = c("cre", "ctb")), person("Katie", "Zarn", email = "katie.zarn@gmail.com", role = "ctb") )
Maintainer: Todd Cross <todd.cross@gmail.com>
Description: Tools for the identification of unique of multilocus genotypes when both genotyping error and missing data may be present. The package is targeted at those working with large datasets and databases containing multiple samples of each individual, a situation that is common in conservation genetics, and particularly in non-invasive wildlife sampling applications. Functions explicitly incorporate missing data, and can tolerate allele mismatches created by genotyping error. If you use this tool, please cite the package using the journal article in Molecular Ecology Resources (Galpern et al., 2012). Please use citation('allelematch') to call the full citation. For users with access to the associated journal article, tutorial material is also available as supplementary material to the article describing this software, the citation for which can be called using citation('allelematch').
Depends: graphics, stats, utils
Imports: dynamicTreeCut
Suggests: R.rsp
VignetteBuilder: R.rsp
License: GPL-3
LazyLoad: yes
Packaged: 2019-04-15 16:01:22 UTC; tbcross
NeedsCompilation: no
Repository: CRAN
Author: Paul Galpern [aut], Todd Cross [cre, ctb], Katie Zarn [ctb]
Date/Publication: 2019-04-15 21:22:47 UTC

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New package glcm with initial version 1.6.3
Package: glcm
Version: 1.6.3
Date: 2019-04-15
Title: Calculate Textures from Grey-Level Co-Occurrence Matrices (GLCMs)
Authors@R: person("Alex", "Zvoleff", email="azvoleff@conservation.org", role=c("aut", "cre"))
Maintainer: Alex Zvoleff <azvoleff@conservation.org>
Depends: R (>= 2.10.0)
Imports: Rcpp (>= 0.11.0)
Suggests: raster, testthat (>= 0.8.0)
LinkingTo: Rcpp, RcppArmadillo
Description: Enables calculation of image textures (Haralick 1973) <doi:10.1109/TSMC.1973.4309314> from grey-level co-occurrence matrices (GLCMs). Supports processing images that cannot fit in memory.
License: GPL (>= 3)
URL: http://www.azvoleff.com/glcm
BugReports: https://github.com/azvoleff/glcm/issues
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-15 15:40:58 UTC; azvol
Author: Alex Zvoleff [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-15 18:12:44 UTC

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New package DiSSMod with initial version 1.0.0
Package: DiSSMod
Type: Package
Title: Fitting Sample Selection Models for Discrete Response Variables
Version: 1.0.0
Date: 2019-04-15
Author: Sang Kyu Lee <lsk0816@gmail.com>, Adelchi Azzalini <adelchi.azzalini@unipd.it>, Hyoung-Moon Kim <hmk966a@gmail.com>
Maintainer: Sang Kyu Lee <lsk0816@gmail.com>
Description: Tools to fit sample selection models in case of discrete response variables, through a parametric formulation which represents a natural extension of the well-known Heckman selection model are provided in the package. The response variable can be of Bernoulli, Poisson or Negative Binomial type. The sample selection mechanism allows to choose among a Normal, Logistic or Gumbel distribution.
Depends: R (>= 2.10)
Imports: sfsmisc, matrixcalc, psych, MASS
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-15 10:14:28 UTC; user
Repository: CRAN
Date/Publication: 2019-04-15 10:42:40 UTC

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New package TSSS with initial version 1.2.3
Package: TSSS
Version: 1.2.3
Title: Time Series Analysis with State Space Model
Author: The Institute of Statistical Mathematics, based on the program by Genshiro Kitagawa
Maintainer: Masami Saga <msaga@mtb.biglobe.ne.jp>
Depends: R (>= 3.4.0), datasets, stats
Suggests: utils
Imports: graphics
Description: Functions for statistical analysis, modeling and simulation of time series with state space model, based on the methodology in Kitagawa (1993, ISBN: 4-00-007703-1 and 2005, ISBN: 4-00-005455-4).
License: GPL (>= 2)
MailingList: Please send bug reports to ismrp@jasp.ism.ac.jp
NeedsCompilation: yes
Packaged: 2019-04-14 23:38:47 UTC; msaga
Repository: CRAN
Date/Publication: 2019-04-15 08:22:42 UTC

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New package JamendoR with initial version 0.1.0
Package: JamendoR
Type: Package
Title: Access to 'Jamendo' API
Version: 0.1.0
Authors@R: c(person("Maximilian", "Greil", role = c("aut", "cre"), email = "maximilian_greil@web.de"), person("Benedikt", "Greil", role = "aut", email = "grbene99@web.de"))
Maintainer: Maximilian Greil <maximilian_greil@web.de>
Description: Provides an interface to 'Jamendo' API <https://developer.jamendo.com/v3.0>. Pull audio, features and other information for a given 'Jamendo' user (including yourself!) or enter an artist's -, album's -, or track's name and retrieve the available information in seconds.
Depends: R (>= 3.3.0)
Imports: httr,dplyr,jsonlite,stats
Suggests: knitr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
URL: http://github.com/MaxGreil/JamendoR
BugReports: http://github.com/MaxGreil/JamendoR/issues
NeedsCompilation: no
Packaged: 2019-04-14 19:40:14 UTC; Maximilian
Author: Maximilian Greil [aut, cre], Benedikt Greil [aut]
Repository: CRAN
Date/Publication: 2019-04-15 08:12:39 UTC

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Sun, 14 Apr 2019

New package pts2polys with initial version 0.1.0
Package: pts2polys
Type: Package
Title: Construct Polygons Summarising the Location and Variability of Point Sets
Version: 0.1.0
Date: 2019-04-11
Authors@R: c(person("Jonathan", "Keith", role = c("aut", "cre"), email = "jonathan.keith@monash.edu"), person("Ken", "Clarkson", role = "aut"), person("Eric", "Hufschmid", role = "ctb"), person("AT&T", role = "cph"))
Description: Various applications in invasive species biology, conservation biology, epidemiology and elsewhere involve sampling of sets of 2D points from a posterior distribution. The number of such point sets may be large, say 1000 or 10000. This package facilitates visualisation of such output by constructing seven nested polygons representing the location and variability of the point sets. This can be used, for example, to visualise the range boundary of a species, and uncertainty in the location of that boundary.
License: GPL (>= 2)
Imports: Rcpp (>= 1.0.1)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-04-13 09:43:19 UTC; jkeith
Author: Jonathan Keith [aut, cre], Ken Clarkson [aut], Eric Hufschmid [ctb], AT&T [cph]
Maintainer: Jonathan Keith <jonathan.keith@monash.edu>
Repository: CRAN
Date/Publication: 2019-04-14 11:02:40 UTC

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New package localModel with initial version 0.3.11
Package: localModel
Title: LIME-Based Explanations with Interpretable Inputs Based on Ceteris Paribus Profiles
Version: 0.3.11
Author: Mateusz Staniak [aut, cre], Przemyslaw Biecek [aut], Krystian Igras [ctb], Alicja Gosiewska [ctb]
Maintainer: Mateusz Staniak <m.staniak@mini.pw.edu.pl>
Description: Local explanations of machine learning models describe, how features contributed to a single prediction. This package implements an explanation method based on LIME (Local Interpretable Model-agnostic Explanations, see Tulio Ribeiro, Singh, Guestrin (2016) <doi:10.1145/2939672.2939778>) in which interpretable inputs are created based on local rather than global behaviour of each original feature.
URL: https://github.com/ModelOriented/localModel
BugReports: https://github.com/ModelOriented/localModel/issues
Depends: R (>= 3.5)
License: GPL
Encoding: UTF-8
LazyData: true
Imports: glmnet, ggplot2, partykit, ingredients
RoxygenNote: 6.1.0
Suggests: covr, knitr, rmarkdown, randomForest, DALEX, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-13 09:45:17 UTC; mstaniak
Repository: CRAN
Date/Publication: 2019-04-14 11:02:43 UTC

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New package gexp with initial version 0.1-4
Package: gexp
Title: Generator of Experiments
Version: 0.1-4
Date: 2019-04-13
Author: Ivan Bezerra Allaman <ivanalaman@gmail.com> and Jos Cludio Faria <joseclaudio.faria@gmail.com>
Maintainer: Ivan Bezerra Allaman <ivanalaman@gmail.com>
Depends: R (>= 3.5.0), mvtnorm, tcltk, jpeg, png
Description: Generates experiments - simulating structured or experimental data as: completely randomized design, randomized block design, latin square design, factorial and split-plot experiments (Ferreira, 2008, ISBN:8587692526; Naes et al., 2007 <doi:10.1002/qre.841>; Rencher et al., 2007, ISBN:9780471754985; Montgomery, 2001, ISBN:0471316490).
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
License: GPL (>= 2)
URL: https://github.com/ivanalaman/gexp
Encoding: latin1
NeedsCompilation: no
Packaged: 2019-04-14 01:46:17 UTC; ivan
Repository: CRAN
Date/Publication: 2019-04-14 11:32:39 UTC

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New package DChaos with initial version 0.1-1
Type: Package
Package: DChaos
Version: 0.1-1
Date: 2019-04-13
Title: Chaotic Time Series Analysis
Authors@R: c(person("Julio E.","Sandubete", role=c("aut","cre"), email="jsandube@ucm.es"), person("Lorenzo","Escot", role="aut", email="escot@ucm.es"))
Author: Julio E. Sandubete [aut, cre], Lorenzo Escot [aut]
Maintainer: Julio E. Sandubete <jsandube@ucm.es>
Imports: xts, zoo, outliers, entropy, nnet, pracma, sandwich, NeuralNetTools
Description: Provides several algorithms for the purpose of detecting chaotic signals inside univariate time series. We focus on methods derived from chaos theory which estimate the complexity of a dataset through exploring the structure of the attractor. We have taken into account the Lyapunov exponents as an ergodic measure. We have implemented the Jacobian method by a fit through neural networks in order to estimate both the largest and the spectrum of Lyapunov exponents. We have considered the full sample and three different methods of subsampling by blocks (non-overlapping, equally spaced and bootstrap) to estimate them. In addition, it is possible to make inference about them and know if the estimated Lyapunov exponents values are or not statistically significant. This library can be used with time series whose time-lapse is fixed or variable. That is, it considers time series whose observations are sampled at fixed or variable time intervals. For a review see David Ruelle and Floris Takens (1971) <doi:10.1007/BF01646553>, Ramazan Gencay and W. Davis Dechert (1992) <doi:10.1016/0167-2789(92)90210-E>, Jean-Pierre Eckmann and David Ruelle (1995) <doi:10.1103/RevModPhys.57.617>, Mototsugu Shintani and Oliver Linton (2004) <doi:10.1016/S0304-4076(03)00205-7>, Jeremy P. Huke and David S. Broomhead (2007) <doi:10.1088/0951-7715/20/9/011>.
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-13 12:40:12 UTC; julioemilio
Repository: CRAN
Date/Publication: 2019-04-14 11:02:46 UTC

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Sat, 13 Apr 2019

New package tcie with initial version 0.2
Package: tcie
Type: Package
Title: Topologically Correct Isosurface Extraction
Version: 0.2
Date: 2019-04-10
Author: Lis Custódio
Maintainer: Lis Custodio <liscustodio.uerj@gmail.com>
URL: http://liscustodio.github.io/
Description: Isosurfaces extraction algorithms are a powerful tool in the interpretation of volumetric data. The isosurfaces play an important role in several scientific fields, such as biology, medicine, chemistry and computational fluid dynamics. And, for the data to be correctly interpreted, it is crucial that the isosurface be correctly represented. The Marching Cubes algorithm, proposed by Lorensen and Cline <doi:10.1145/37401.37422> in 1987, is clearly one of the most popular isosurface extraction algorithms, and an important tool for many visualization specialists and researchers. The generalized adoption of the Marching Cubes has resulted in many improvements in its algorithm, including, the establishment of the topological correctness of the generated mesh. In 2013, Custodio et al. <doi:10.1016/j.cag.2013.04.004> noted and corrected algorithmic inaccuracies that compromised the topological correctness of the mesh generated by the last version of the Marching Cubes Algorithm: the Marching Cubes 33 proposed by Chernyaev in 1995, implemented in 2003 by Lewiner et al. <doi:10.1080/10867651.2003.10487582>. In 2019, Custodio et al. (in the work An Extended Triangulation to the Marching Cubes 33 Algorithm) proposed an extended triangulation to the Marching Cubes 33 algorithm, in the proposed algorithm the grid vertex are labeled with "+", "-" and "=", according to the relationship between its scalar field value and the isovalue.The inclusion of the "=" grid vertex label naturally avoids degenerate triangles, a well-known issue in meshes generated by the Marching Cubes. The Marching Cubes algorithm has been implemented using many software programs and compilers: C++, proposed by Lewiner et al. (2003); 'MATLAB', proposed by Hammer (2011); and R, proposed by Feng and Tierney (2008). Marching Cubes is also integrated into many visualization toolkits. The complexity of an algorithm increases considerably when it aims to reproduce the topology of the trilinear interpolant correctly. This complexity can sometimes result in errors in the algorithm or in its implementation. During our experiments we observe that all the implementations mentioned have critical issues that compromise the continuity and the topological correctness of the generated mesh. The 'tcie' package is a toolkit with a topologically correct implementation of the Marching Cubes algorithm, based on the Custodio et al. work, which implements the most recent improvements of the algorithm.
LazyData: TRUE
LinkingTo: Rcpp,RcppArmadillo
Imports: nat(>= 1.8.11), rgl(>= 0.99.9), Rvcg (>= 0.17), geomorph (>= 3.0.5)
Depends: R (>= 3.2.3)
RoxygenNote: 6.1.1
License: GPL
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-04-11 22:22:21 UTC; lis
Repository: CRAN
Date/Publication: 2019-04-13 23:02:41 UTC

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New package sos4R with initial version 0.3.0
Package: sos4R
Type: Package
Title: Client for OGC Sensor Observation Services
Version: 0.3.0
Date: 2019-04-13
Authors@R: c(person(given = "Daniel", family = "Nuest", role = c("cre", "aut"), email = "daniel.nuest@uni-muenster.de", comment = c(ORCID = "0000-0002-0024-5046")), person(given = "Edzer", family = "Pebesma", role = "ctb", comment = c(ORCID = "0000-0001-8049-7069")), person(given = "Ben", family = "Graeler", role = "ctb", comment = c(ORCID = "0000-0001-5443-4304")), person(given = "Benjamin", family = "Pross", role = "ctb"), person(given = "Eike Hinderk", family = "Juerrens", role = "ctb"), person(given = "52°North Initiative for Geospatial Open Source Software GmbH", email = "info@52north.org", role = "cph"))
Depends: R (>= 3.4.0)
Imports: httr, methods, sp, stringr, xml2,
Suggests: readr, spacetime, gstat, maps, maptools, mapdata, cshapes, xtable, xts, testthat, rgdal, knitr, rmarkdown
Description: A client for Sensor Observation Services (SOS, see <https://www.opengeospatial.org/standards/sos>) as specified by the Open Geospatial Consortium (OGC). With the package users can retrieve (meta)data from SOS instances and interactively create requests for near real-time observation data based on the available sensors, phenomena, observations etc. using thematic, temporal, and spatial filtering.
License: GPL-2
URL: https://github.com/52North/sos4R
Encoding: UTF-8
LazyLoad: TRUE
ByteCompile: TRUE
BugReports: https://github.com/52North/sos4R/issues
Collate: Constants.R R-Helper.R Class-XML.R Class-OWS.R Class-GML.R Class-SWE.R Class-OM.R Class-SA.R Class-SAMS.R Class-WML_200.R Class-OM_20.R Class-OGC.R Class-SOS.R Class-SOS_100.R Class-SOS_200.R Class-SOS_200_GDA.R Class-SML.R Generic-methods.R OWS-methods.R OWS-methods-parsing.R SOS-methods-parsing.R OM-methods.R OM-methods-coercion.R OM-methods-parsing.R OM_20-methods-parsing.R OM_20-methods.R SA-methods.R GML-methods.R SWE-methods.R SML-methods.R GML-methods-parsing.R SA-methods-parsing.R SWE-methods-parsing.R OGC-methods.R SOS-methods-accessor.R PrintShowStructureSummmary-methods.R SOS-methods-util.R SOS-methods.R SOS-methods-plotting.R SOS-methods-coercion.R SML-methods-util.R SML-methods-coercion.R SOS_200-methods-impl.R SOS_200-methods.R SOS_200-methods-parsing.R SOS_200_methods-gda.R WML_200-methods-parsing.R WML_200-methods.R SAMS-methods-parsing.R Defaults.R Development.R
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-13 14:08:40 UTC; daniel
Author: Daniel Nuest [cre, aut] (<https://orcid.org/0000-0002-0024-5046>), Edzer Pebesma [ctb] (<https://orcid.org/0000-0001-8049-7069>), Ben Graeler [ctb] (<https://orcid.org/0000-0001-5443-4304>), Benjamin Pross [ctb], Eike Hinderk Juerrens [ctb], 52°North Initiative for Geospatial Open Source Software GmbH [cph]
Maintainer: Daniel Nuest <daniel.nuest@uni-muenster.de>
Repository: CRAN
Date/Publication: 2019-04-13 22:42:42 UTC

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New package fic with initial version 1.0.0
Package: fic
Title: Focused Information Criteria for Model Comparison
Version: 1.0.0
Date: 2019-04-09
Authors@R: c(person("Christopher","Jackson", role=c("cre","aut"), email="chris.jackson@mrc-bsu.cam.ac.uk", comment="package design and programming"), person("Gerda","Claeskens", role="aut", email="gerda.claeskens@kuleuven.be", comment="method development and design advice"), person("Howard","Thom",email="howard.thom@bristol.ac.uk", role="ctb") )
Description: Compares how well different models estimate a quantity of interest (the "focus") so that different models may be preferred for different purposes. Comparisons within any class of models fitted by maximum likelihood are supported, with shortcuts for commonly-used classes such as generalised linear models and parametric survival models. The methods originate from Claeskens and Hjort (2003) <doi:10.1198/016214503000000819> and Claeskens and Hjort (2008, ISBN:9780521852258).
Maintainer: Christopher Jackson <chris.jackson@mrc-bsu.cam.ac.uk>
Depends: R (>= 2.10)
Imports: stats, numDeriv, mvtnorm, ggplot2, scales, survival, tensor, abind
URL: https://github.com/chjackson/fic
BugReports: https://github.com/chjackson/fic/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat, msm(>= 1.6.6), flexsurv, sn, gapminder, GGally
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-12 11:20:35 UTC; chris
Author: Christopher Jackson [cre, aut] (package design and programming), Gerda Claeskens [aut] (method development and design advice), Howard Thom [ctb]
Repository: CRAN
Date/Publication: 2019-04-13 08:32:39 UTC

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New package equivUMP with initial version 0.1.1
Package: equivUMP
Type: Package
Title: Uniformly Most Powerful Invariant Tests of Equivalence
Version: 0.1.1
Authors@R: person("Thoralf", "Mildenberger", email = "mild@zhaw.ch", role = c("aut", "cre"))
Description: Implementation of uniformly most powerful invariant equivalence tests for one- and two-sample problems (paired and unpaired) as described in Wellek (2010, ISBN:978-1-4398-0818-4). Also one-sided alternatives (non-inferiority and non-superiority tests) are supported. Basically a variant of a t-test with (relaxed) null and alternative hypotheses exchanged.
License: GPL (>= 2)
URL: https://github.com/thmild/equivUMP
BugReports: https://github.com/thmild/equivUMP/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-12 09:45:27 UTC; thoralf
Author: Thoralf Mildenberger [aut, cre]
Maintainer: Thoralf Mildenberger <mild@zhaw.ch>
Repository: CRAN
Date/Publication: 2019-04-13 08:22:52 UTC

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New package CTAShiny with initial version 0.1.0
Package: CTAShiny
Type: Package
Title: Interactive Application for Working with Contingency Tables
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive application for working with contingency Tables. The application has a template for solving contingency table problems like chisquare test of independence,association plot between two categorical variables. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/CategoricalDataAnalysis/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,shinyMatrix,epitools,rpivotTable
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-12 08:47:04 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-04-13 08:22:55 UTC

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Fri, 12 Apr 2019

New package qualtRics with initial version 3.1.0
Package: qualtRics
Type: Package
Title: Download 'Qualtrics' Survey Data
Version: 3.1.0
Authors@R: c(person("Jasper", "Ginn", role = c("aut"), email = "jasperginn@gmail.com"), person("Samuel", "Kaminsky", role = c("ctb"), email = "samuel.e.kaminsky@gmail.com"), person("Eric", "Knudsen", role = c("ctb"), email = "ericknud1@gmail.com"), person("Julia", "Silge", role = c("aut", "cre"), email = "julia.silge@gmail.com", comment = c(ORCID = "0000-0002-3671-836X")), person("Phoebe", "Wong", role = c("ctb"), email = "phoebe.wong@berkeley.edu"))
Description: Provides functions to access survey results directly into R using the 'Qualtrics' API. 'Qualtrics' <https://www.qualtrics.com/about/> is an online survey and data collection software platform. See <https://api.qualtrics.com/> for more information about the 'Qualtrics' API. This package is community-maintained and is not officially supported by 'Qualtrics'.
URL: https://ropensci.github.io/qualtRics/, https://github.com/ropensci/qualtRics
BugReports: https://github.com/ropensci/qualtRics/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
Imports: httr, stringr, readr, jsonlite, assertthat, sjlabelled, yaml, dplyr, rlang
Suggests: knitr, rmarkdown, testthat, httptest
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-11 18:51:08 UTC; juliasilge
Author: Jasper Ginn [aut], Samuel Kaminsky [ctb], Eric Knudsen [ctb], Julia Silge [aut, cre] (<https://orcid.org/0000-0002-3671-836X>), Phoebe Wong [ctb]
Maintainer: Julia Silge <julia.silge@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-12 10:13:49 UTC

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New package frost with initial version 0.0.4
Package: frost
Type: Package
Title: Prediction of Minimum Temperature for Frost Forecasting in Agriculture
Version: 0.0.4
Authors@R: c(person(given = "Ana Laura", family = "Diedrichs", role = c("cre", "aut"), comment = c(ORCID = "0000-0001-9973-4554"), email = "ana.diedrichs@frm.utn.edu.ar" ), person(given = "Facundo", family = "Bromberg", role = c("ths") ), person(given = "Diego", family = "Dujovne", role = c("ths"), comment = c(ORCID = "0000-0003-4207-633X") ))
Description: A compilation of empirical methods used by farmers and agronomic engineers to predict the minimum temperature to detect a frost night. These functions use variables such as environmental temperature, relative humidity, and dew point. See <http://sedici.unlp.edu.ar/handle/10915/72102> <http://www.fao.org/docrep/008/y7223e/y7223e0b.htm#bm11.8> for details.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr,rmarkdown,ggplot2, testthat
Imports: methods
VignetteBuilder: knitr
URL: https://github.com/anadiedrichs/frost
BugReports: https://github.com/anadiedrichs/frost/issues
Date: 2019-04-08
NeedsCompilation: no
Packaged: 2019-04-11 22:25:53 UTC; anadiedrichs
Author: Ana Laura Diedrichs [cre, aut] (<https://orcid.org/0000-0001-9973-4554>), Facundo Bromberg [ths], Diego Dujovne [ths] (<https://orcid.org/0000-0003-4207-633X>)
Maintainer: Ana Laura Diedrichs <ana.diedrichs@frm.utn.edu.ar>
Repository: CRAN
Date/Publication: 2019-04-12 10:23:17 UTC

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New package HS with initial version 1.0
Package: HS
Type: Package
Title: Homogenous Segmentation for Spatial Lines Data
Date: 2019-04-07
Version: 1.0
Authors@R: person("Yongze Song", email = "yongze.song@postgrad.curtin.edu.au", comment = c(ORCID = "0000-0003-3420-9622"), role = c("aut", "cre"))
Maintainer: Yongze Song <yongze.song@postgrad.curtin.edu.au>
Description: Methods of homogenous segmentation for spatial lines data, such as pavement performance indicators and traffic volumes. A moving coefficient of variation method is available for homogenous segmentation.
Imports: zoo
Depends: R (>= 3.4.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-04-09 02:55:05 UTC; zack
Author: Yongze Song [aut, cre] (<https://orcid.org/0000-0003-3420-9622>)
Repository: CRAN
Date/Publication: 2019-04-12 09:02:42 UTC

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New package trackeRapp with initial version 1.0
Package: trackeRapp
Title: Interface for the Analysis of Running, Cycling and Swimming Data from GPS-Enabled Tracking Devices
Version: 1.0
Authors@R: c(person(given = "Ioannis", family = "Kosmidis", role = c("aut", "cre"), email = "ioannis.kosmidis@warwick.ac.uk", comment = c(ORCID = "0000-0003-1556-0302")), person(given = "Robin", family = "Hornak", role = c("aut"), email = "robinhornak@gmail.com"))
Description: Provides an integrated user interface and workflow for the analysis of running, cycling and swimming data from GPS-enabled tracking devices through the 'trackeR' <https://CRAN.R-project.org/package=trackeR> R package.
Depends: R (>= 3.5.0), trackeR (>= 1.5.0)
Imports: colorspace, zoo, foreach, mgcv, plotly, DT, changepoint, shiny, shinyjs, shinydashboard, shinyWidgets, sf, mapdeck, V8
License: GPL-3
URL: https://github.com/trackerproject/trackeRapp
BugReports: https://github.com/trackerproject/trackeRapp/issues
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-04-10 23:15:24 UTC; yiannis
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>), Robin Hornak [aut]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>
Repository: CRAN
Date/Publication: 2019-04-12 08:02:41 UTC

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New package rsparse with initial version 0.3.3
Package: rsparse
Type: Package
Title: Statistical Learning on Sparse Matrices
Version: 0.3.3
Authors@R: c( person("Dmitriy", "Selivanov", role=c("aut", "cre", "cph"), email="selivanov.dmitriy@gmail.com", comment = c(ORCID = "0000-0001-5413-1506")), person("Drew", "Schmidt", role="ctb", comment="configure script for BLAS, LAPACK detection"), person("Wei-Chen", "Chen", role="ctb", comment="configure script and work on linking to float package") )
Maintainer: Dmitriy Selivanov <selivanov.dmitriy@gmail.com>
Description: Implements many algorithms for statistical learning on sparse matrices - matrix factorizations, matrix completion, elastic net regressions, factorization machines. Also 'rsparse' enhances 'Matrix' package by providing methods for multithreaded <sparse, dense> matrix products and native slicing of the sparse matrices in Compressed Sparse Row (CSR) format. List of the algorithms for regression problems: 1) Elastic Net regression via Follow The Proximally-Regularized Leader (FTRL) Stochastic Gradient Descent (SGD), as per McMahan et al(, <doi:10.1145/2487575.2488200>) 2) Factorization Machines via SGD, as per Rendle (2010, <doi:10.1109/ICDM.2010.127>) List of algorithms for matrix factorization and matrix completion: 1) Weighted Regularized Matrix Factorization (WRMF) via Alternating Least Squares (ALS) - paper by Hu, Koren, Volinsky (2008, <doi:10.1109/ICDM.2008.22>) 2) Maximum-Margin Matrix Factorization via ALS, paper by Rennie, Srebro (2005, <doi:10.1145/1102351.1102441>) 3) Fast Truncated Singular Value Decomposition (SVD), Soft-Thresholded SVD, Soft-Impute matrix completion via ALS - paper by Hastie, Mazumder et al. (2014, <arXiv:1410.2596>) 4) Linear-Flow matrix factorization, from 'Practical linear models for large-scale one-class collaborative filtering' by Sedhain, Bui, Kawale et al (2016, ISBN:978-1-57735-770-4) 5) GlobalVectors (GloVe) matrix factorization via SGD, paper by Pennington, Socher, Manning (2014, <https://www.aclweb.org/anthology/D14-1162>) Package is reasonably fast and memory efficient - it allows to work with large datasets - millions of rows and millions of columns. This is particularly useful for practitioners working on recommender systems.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.1.0), methods
Imports: Matrix (>= 1.2), Rcpp (>= 0.11), mlapi (>= 0.1.0), data.table (>= 1.10.0), float (>= 0.2-2), RhpcBLASctl, lgr (>= 0.2)
LinkingTo: Rcpp, RcppArmadillo (>= 0.9.100.5.0)
Suggests: testthat, covr
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2019-04-11 09:41:34 UTC; dselivanov
Author: Dmitriy Selivanov [aut, cre, cph] (<https://orcid.org/0000-0001-5413-1506>), Drew Schmidt [ctb] (configure script for BLAS, LAPACK detection), Wei-Chen Chen [ctb] (configure script and work on linking to float package)
Repository: CRAN
Date/Publication: 2019-04-12 08:42:39 UTC

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New package RSCAT with initial version 1.0.0
Package: RSCAT
Title: Shadow-Test Approach to Computerized Adaptive Testing
Version: 1.0.0
Authors@R: c( person("Bingnan", "Jiang", email = "bnjiangece@gmail.com", role = c("aut", "cre")), person("ACT, Inc.", role = "cph") )
Author: Bingnan Jiang [aut, cre], ACT, Inc. [cph]
Maintainer: Bingnan Jiang <bnjiangece@gmail.com>
BugReports: https://github.com/act-org/RSCAT/issues
Description: As an advanced approach to computerized adaptive testing (CAT), shadow testing (van der Linden(2005) <doi:10.1007/0-387-29054-0>) dynamically assembles entire shadow tests as a part of selecting items throughout the testing process. Selecting items from shadow tests guarantees the compliance of all content constraints defined by the blueprint. 'RSCAT' is an R package for the shadow-test approach to CAT. The objective of 'RSCAT' is twofold: 1) Enhancing the effectiveness of shadow-test CAT simulation; 2) Contributing to the academic and scientific community for CAT research.
Depends: R (>= 3.4.0), rJava, shiny, shinycssloaders, shinyjs
License: CC BY-NC 4.0
Encoding: UTF-8
RoxygenNote: 6.1.1
Imports: Metrics, ggplot2, gridExtra, grid, methods, stats, utils
Collate: 'EAPConfig.R' 'SimResult.R' 'configClasses.R' 'launchApp.R' 'runSim.R' 'scoreMethodConfig.R' 'shinyAppServer.R' 'shinyAppUI.R' 'utilFunctions.R' 'zzz.R'
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-04-11 03:23:40 UTC; Bingnan
Repository: CRAN
Date/Publication: 2019-04-12 08:32:42 UTC

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New package R.SamBada with initial version 0.1.0
Package: R.SamBada
Type: Package
Title: Processing Pipeline for 'SamBada' from Pre- To Post-Processing
Version: 0.1.0
Date: 2019-03-18
Author: Solange Duruz, Sylvie Stucki, Oliver Selmoni, Elia Vajana
Maintainer: Solange Duruz <solange.duruz@alumni.epfl.ch>
Description: Processing pipeline for 'SamBada' from pre- to post-processing. 'SamBada' is a landscape genomic software designed to run univariate or multivariate logistic regression between the presence of a genotype and one or several environmental variables. See Stucki (2017) <doi:10.1111/1755-0998.12629> and <https://github.com/Sylvie/sambada>. The package provides functions that can be classified into four categories: 1) Install 'SamBada' 2) Preprocessing (prepare genomic file into standards compatible with 'SamBada' and apply quality-control; retrieve environmental conditions at sampling location; prepare environmental file including removal of correlated variables and computation of population structure) 3) Processing (run 'SamBada' on multiple cores using 'Supervision') 4) Post-processing (calculate p-values and q-values, produce interactive Manhattan plots and query 'Ensembl' database, produce maps).
License: GPL (>= 2)
Imports: SNPRelate, gdsfmt
LinkingTo:
RoxygenNote: 6.1.0
Suggests: Rcpp, utils, data.table, shiny, plotly, httr, biomaRt, ggplot2, sp, packcircles, raster, mapplots, spdep, rgdal, gdalUtils, rworldmap, doParallel, foreach, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-11 11:35:30 UTC; Solange
Repository: CRAN
Date/Publication: 2019-04-12 08:52:40 UTC

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New package CloneSeeker with initial version 1.0.4
Package: CloneSeeker
Version: 1.0.4
Date: 2019-04-11
Title: Seeking and Finding Clones in Copy Number and Sequencing Data
Author: Kevin R. Coombes, Mark Zucker
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Description: Defines the classes and functions used to simulate and to analyze data sets describing copy number variants and, optionally, sequencing mutations in order to detect clonal subsets. See Zucker et al. (2019) <doi:10.1093/bioinformatics/btz057>.
Depends: R (>= 3.0)
Imports: methods, graphics, combinat, gtools, quantmod, cluster, sirt
License: Apache License (== 2.0)
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2019-04-11 11:09:47 UTC; Kevin
Repository: CRAN
Date/Publication: 2019-04-12 08:52:44 UTC

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New package Irescale with initial version 0.1.4
Package: Irescale
Type: Package
Title: Calculate and Scale Moran's I
Version: 0.1.4
Author: Ivan Fuentes, Thomas DeWitt
Maintainer: Ivan Fuentes <jivfur@tamu.edu>
Description: Provides a scaling method to obtain a standardized Moran's I measure. Moran's I is a measure for the spatial autocorrelation of a data set, it gives a measure of similarity between data and its surrounding. Researchers calculate Moran's I to express the spatial autocorrelation of their data. The range of this value must be [-1,1], but this does not happen in practice. This package scale the Moran's I value and map it into the theoretical range of [-1,1]. Once the Moran's I value is rescaled, it facilitates the comparison between projects, for instance, a researcher can calculate Moran's I in a city in China, with a sample size of n1 and area of interest a1. Another researcher runs a similar experiment in a city in Mexico with different sample size, n2, and an area of interest a2. Due to the differences between the conditions, it is not possible to compare Moran's I in a straightforward way. In this version of the package, the spatial autocorrelation Moran's I is calculated as proposed in Chen(2009) <arXiv:1606.03658>.
License: GPL (>= 2)
URL: https://github.tamu.edu/jivfur/Irescale
Encoding: UTF-8
LazyData: true
Imports: testthat, rgeos
Depends: graphics, Rdpack, sp, e1071
RoxygenNote: 6.1.1
RdMacros: Rdpack
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-10 19:48:11 UTC; jivfur
Repository: CRAN
Date/Publication: 2019-04-12 07:53:53 UTC

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Thu, 11 Apr 2019

New package eiPartialID with initial version 0.1.2
Package: eiPartialID
Type: Package
Title: Ecological Regression with Partial Identification
Version: 0.1.2
Author: Wenxin Jiang, Gary King, Allen Schmaltz, Martin A. Tanner
Maintainer: Allen Schmaltz <schmaltz@fas.harvard.edu>
Contact: <wjiang@northwestern.edu,king@harvard.edu,schmaltz@fas.harvard.edu,mat132@northwestern.edu>
Description: Estimate district-level bounds for 2x2 ecological inference based on the approach described in the forthcoming article Jiang et al. (2019), "Ecological Regression with Partial Identification", Political Analysis. Interval data regression is used to bound the nonidentified regression parameter in a linear contextual effects model, from which district-level bounds are derived. The approach here can be useful as a baseline of comparison for future work on ecological inference.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: sandwich, stats, MASS, eco
RoxygenNote: 6.1.1.9000
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-11 00:08:22 UTC; a
Repository: CRAN
Date/Publication: 2019-04-11 16:32:38 UTC

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New package cmfilter with initial version 0.9.0
Package: cmfilter
Type: Package
Title: Coordinate-Wise Mediation Filter
Version: 0.9.0
Date: 2019-04-09
Author: Erik-Jan van Kesteren <e.vankesteren1@uu.nl>
Maintainer: Erik-Jan van Kesteren <e.vankesteren1@uu.nl>
Description: Functions to discover, plot, and select multiple mediators from an x -> M -> y linear system. This exploratory mediation analysis is performed using the Coordinate-wise Mediation Filter as introduced by Van Kesteren and Oberski (2019) <arXiv: 1810.06334>.
License: MIT + file LICENCE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: Matrix, sparseMVN, expm, pbapply, MASS, parallel, Rcpp (>= 0.12.13)
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
Suggests: testthat
NeedsCompilation: yes
Packaged: 2019-04-11 08:24:37 UTC; 3665364
Repository: CRAN
Date/Publication: 2019-04-11 15:55:22 UTC

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New package glmaag with initial version 0.0.3
Package: glmaag
Type: Package
Title: Adaptive LASSO and Network Regularized Generalized Linear Models
Version: 0.0.3
Date: 2019-04-08
Author: Kaiqiao Li [aut, cre], Pei Fen Kuan [aut], Xuefeng Wang [aut]
Maintainer: Kaiqiao Li <kaiqiao.li@stonybrook.edu>
Description: Efficient procedures for adaptive LASSO and network regularized for Gaussian, logistic, and Cox model. Provides network estimation procedure (combination of methods proposed by Ucar, et al. (2007) <doi:10.1093/bioinformatics/btm423> and Meinshausen and Buhlmann (2006) <doi:10.1214/009053606000000281>), cross validation and stability selection proposed by Meinshausen and Buhlmann (2010) <doi:10.1111/j.1467-9868.2010.00740.x> and Liu, Roeder and Wasserman (2010) <arXiv:1006.3316> methods. Interactive R app is available.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.0), methods, stats, Matrix, ggplot2, gridExtra, maxstat, survminer, plotROC, shiny, foreach, pROC, huge, OptimalCutpoints, data.table
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.5.0), survival
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-09 16:54:37 UTC; lik15
Repository: CRAN
Date/Publication: 2019-04-11 14:22:37 UTC

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New package CoSMoS with initial version 0.4.1
Package: CoSMoS
Type: Package
Title: Complete Stochastic Modelling Solution
Version: 0.4.1
Authors@R: c(person("Filip", "Strnad", role = c("aut", "cre"), email = "strnadf@fzp.czu.cz"), person("Simon Michael", "Papalexiou", role = c("aut")), person("Yannis", " Markonis", role = "ctb"))
Description: A single framework, unifying, extending, and improving a general-purpose modelling strategy, based on the assumption that any process can emerge by transforming a specific 'parent' Gaussian process Papalexiou (2018) <doi:10.1016/j.advwatres.2018.02.013>.
License: GPL-3
Depends: R (>= 3.4.0), ggplot2, pracma, methods, moments, reshape2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-09 17:14:39 UTC; phill
Author: Filip Strnad [aut, cre], Simon Michael Papalexiou [aut], Yannis Markonis [ctb]
Maintainer: Filip Strnad <strnadf@fzp.czu.cz>
Repository: CRAN
Date/Publication: 2019-04-11 14:25:21 UTC

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New package CaPO4Sim with initial version 0.1.0
Package: CaPO4Sim
Type: Package
Title: A Virtual Patient Simulator in the Context of Calcium and Phosphate Homeostasis
Version: 0.1.0
Authors@R: c( person("David", "Granjon", role = c("aut", "cre", "cph"), email = "dgranjon@ymail.com"), person("Diane", "de Zélicourt", role = "cph"), person("Vartan", "Kurtcuoglu", role = "cph"), person("Olivier", "Bonny", role = "cph"), person("François", "Verrey", role = "cph"), person(family = "University of Lausanne", role = "fnd"), person(family = "University of Zurich", role = "fnd"), person(family = "Kidney NCCR.CH", role = "fnd"), person(family = "The Interface Group", role = "cph", comment = "Hosting Group"), person(family = "RinteRface", role = "cph", comment = "R/HTML Templates") )
Maintainer: David Granjon <dgranjon@ymail.com>
Description: Explore calcium (Ca) and phosphate (Pi) homeostasis with two novel 'Shiny' apps, building upon on a previously published mathematical model written in C, to ensure efficient computations. The underlying model is accessible here <https://www.ncbi.nlm.nih.gov/pubmed/28747359>. The first application explores the fundamentals of Ca-Pi homeostasis, while the second provides interactive case studies for in-depth exploration of the topic, thereby seeking to foster student engagement and an integrative understanding of Ca-Pi regulation. These applications are hosted at <https://rinterface.com/AppsPhysiol.html>.
Imports: shiny, htmltools, shinyjs, shinyWidgets, shinydashboard, shinydashboardPlus, shinyjqui, plotly, rintrojs, shinycssloaders, visNetwork, purrr, DT, magrittr, utils
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-10 22:10:17 UTC; macdavidgranjon
Author: David Granjon [aut, cre, cph], Diane de Zélicourt [cph], Vartan Kurtcuoglu [cph], Olivier Bonny [cph], François Verrey [cph], University of Lausanne [fnd], University of Zurich [fnd], Kidney NCCR.CH [fnd], The Interface Group [cph] (Hosting Group), RinteRface [cph] (R/HTML Templates)
Repository: CRAN
Date/Publication: 2019-04-11 14:55:39 UTC

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New package bdclean with initial version 0.1.15
Package: bdclean
Type: Package
Title: A User-Friendly Biodiversity Data Cleaning App for the Inexperienced R User
Description: Provides features to manage the complete workflow for biodiversity data cleaning. Uploading data, gathering input from users (in order to adjust cleaning procedures), cleaning data and finally, generating various reports and several versions of the data. Facilitates user-level data cleaning, designed for the inexperienced R user. T Gueta et al (2018) <doi:10.3897/biss.2.25564>. T Gueta et al (2017) <doi:10.3897/tdwgproceedings.1.20311>.
Version: 0.1.15
Date: 2019-04-10
License: GPL-3
URL: https://github.com/bd-R/bdclean, https://bd-r.github.io/The-bdverse/index.html
BugReports: https://github.com/bd-R/bdclean/issues
Authors@R: c( person( "Thiloshon", "Nagarajah", email = "thiloshon@gmail.com", role = c("aut","cre")), person( "Tomer", "Gueta", email = "tomer.gu@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0003-1557-8596')), person( "Vijay", "Barve", , email = "vijay.barve@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0002-4852-2567')), person( "Ashwin", "Agrawal", email = "ashwin.agrawal.met14@itbhu.ac.in", role = c("aut")), person( "Povilas", "Gibas", email = "povilasgibas@gmail.com", role = c("aut"), comment = c(ORCID = '0000-0001-5311-6021')), person( "Yohay", "Carmel", email = "yohay@cv.technion.ac.il", role = c("aut"), comment = c(ORCID = '0000-0002-5883-0184')) )
Maintainer: Thiloshon Nagarajah <thiloshon@gmail.com>
Imports: rmarkdown, knitr, shiny, shinydashboard, shinyjs, leaflet, DT, data.table, rgbif, spocc, finch, bdDwC, bdchecks, methods, tools
Depends: R (>= 2.10)
RoxygenNote: 6.1.1
Suggests: testthat, roxygen2, covr
LazyData: true
NeedsCompilation: no
Packaged: 2019-04-10 08:16:43 UTC; Thiloshon
Author: Thiloshon Nagarajah [aut, cre], Tomer Gueta [aut] (<https://orcid.org/0000-0003-1557-8596>), Vijay Barve [aut] (<https://orcid.org/0000-0002-4852-2567>), Ashwin Agrawal [aut], Povilas Gibas [aut] (<https://orcid.org/0000-0001-5311-6021>), Yohay Carmel [aut] (<https://orcid.org/0000-0002-5883-0184>)
Repository: CRAN
Date/Publication: 2019-04-11 14:45:17 UTC

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New package ksNN with initial version 0.1.2
Encoding: UTF-8
Package: ksNN
Type: Package
Title: K* Nearest Neighbors Algorithm
Version: 0.1.2
Authors@R: c( person("Kei","Nakagawa",email="kei.nak.0315@gmail.com",role=c("aut","cre"),comment = c(ORCID = "0000-0001-5046-8128")), person("Shingo","Sashida",email="gs449901@gmail.com",role=c("aut")) )
Description: Prediction with k* nearest neighbor algorithm based on a publication by Anava and Levy (2016) <arXiv:1701.07266>.
License: GPL (>= 2)
Author: Kei Nakagawa [aut, cre] (<https://orcid.org/0000-0001-5046-8128>), Shingo Sashida [aut]
Maintainer: Kei Nakagawa <kei.nak.0315@gmail.com>
LazyData: TRUE
Imports: Rcpp
Depends: R(>= 3.0.2)
LinkingTo: Rcpp(>= 0.10.6)
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-03-28 09:53:44 UTC; SSunix
Repository: CRAN
Date/Publication: 2019-04-11 12:02:37 UTC

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Wed, 10 Apr 2019

New package CDECRetrieve with initial version 0.1.4
Package: CDECRetrieve
Type: Package
Title: Retrieve Historical and Near Realtime Data from CDEC
Version: 0.1.4
Authors@R: person("Emanuel", "Rodriguez", email = "erodriguez@flowwest.com", role = c("aut", "cre"))
Description: CDEC maintains a set of web services at <http://cdec.water.ca.gov/queryTools.html>. In order to better interact and analyze the data this R packages allows users to quickly and easily retrieve data.
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.1.2)
Imports: dplyr (>= 0.7.0), tidyr (>= 0.7), magrittr (>= 1.5), purrr (>= 0.2), readr (>= 1.1.1), roxygen2, rvest (>= 0.3), xml2, stringr (>= 1.2.0), tibble, lubridate (>= 1.6.0), httr (>= 1.3.1), lazyeval, glue
Suggests: testthat, leaflet, knitr, rmarkdown, ggplot2
License: MIT + file LICENSE
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-10 20:20:31 UTC; emanuel
Author: Emanuel Rodriguez [aut, cre]
Maintainer: Emanuel Rodriguez <erodriguez@flowwest.com>
Repository: CRAN
Date/Publication: 2019-04-10 21:47:42 UTC

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New package SVN with initial version 1.0
Package: SVN
Type: Package
Title: Statistically Validated Networks
Version: 1.0
Date: 2019-04-10
Author: Damien Challet
Maintainer: Damien Challet <damien.challet@gmail.com>
Description: Determines networks of significant synchronization between the discrete states of nodes; see Tumminello et al <doi:10.1371/journal.pone.0017994>.
License: GPL (>= 2.0)
Depends: data.table, igraph, memoise
Imports:
RoxygenNote: 6.1.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-04-10 07:30:44 UTC; damien
Repository: CRAN
Date/Publication: 2019-04-10 18:25:30 UTC

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New package dtpcrm with initial version 0.1.0
Package: dtpcrm
Type: Package
Title: Dose Transition Pathways for Continual Reassessment Method
Version: 0.1.0
Authors@R: c(person("Christina", "Yap", email = "yapchristina17@gmail.com", role = c("aut", "cre")), person("Daniel", "Slade", email = "D.Slade@bham.ac.uk", role = c("aut")), person("Kristian", "Brock", email = "k.brock@bham.ac.uk", role = c("aut")), person("Yi", "Pan", email = "ypan1988@gmail.com", role = c("aut")))
Maintainer: Christina Yap <yapchristina17@gmail.com>
Description: Provides the dose transition pathways (DTP) to project in advance the doses recommended by a model-based design for subsequent patients (stay, escalate, deescalate or stop early) using all the accumulated toxicity information; See Yap et al (2017) <doi: 10.1158/1078-0432.CCR-17-0582>. DTP can be used as a design and an operational tool and can be displayed as a table or flow diagram. The 'dtpcrm' package also provides the modified continual reassessment method (CRM) and time-to-event CRM (TITE-CRM) with added practical considerations to allow stopping early when there is sufficient evidence that the lowest dose is too toxic and/or there is a sufficient number of patients dosed at the maximum tolerated dose.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: diagram, dfcrm
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-09 14:53:44 UTC; yipan
Author: Christina Yap [aut, cre], Daniel Slade [aut], Kristian Brock [aut], Yi Pan [aut]
Repository: CRAN
Date/Publication: 2019-04-10 17:56:04 UTC

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New package cinterpolate with initial version 1.0.0
Package: cinterpolate
Title: Interpolation From C
Version: 1.0.0
Description: Simple interpolation methods designed to be used from C code. Supports constant, linear and spline interpolation. An R wrapper is included but this package is primarily designed to be used from C code using 'LinkingTo'. The spline calculations are classical cubic interpolation, e.g., Forsythe, Malcolm and Moler (1977) <ISBN: 9780131653320>.
License: MIT + file LICENSE
Encoding: UTF-8
Authors@R: person("Rich", "FitzJohn", role = c("aut", "cre"), email = "rich.fitzjohn@gmail.com")
URL: https://github.com/mrc-ide/cinterpolate
BugReports: https://github.com/mrc-ide/cinterpolate/issues
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
Language: en-GB
NeedsCompilation: yes
Packaged: 2019-04-09 18:08:48 UTC; rfitzjoh
Author: Rich FitzJohn [aut, cre]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-10 17:05:44 UTC

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New package bzinb with initial version 1.0.0
Package: bzinb
Type: Package
Title: Bivariate Zero-Inflated Negative Binomial Model Estimator
Version: 1.0.0
Author: Hunyong Cho, Chuwen Liu, Jinyoung Park, Di Wu
Maintainer: Hunyong Cho <hunycho@live.unc.edu>
Description: Provides a maximum likelihood estimation of Bivariate Zero-Inflated Negative Binomial (BZINB) model or the nested model parameters. Also estimates the underlying correlation of the a pair of count data. See Cho, H., Preisser, J., Liu, C., and Wu, D. (In preparation) for details.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: Rcpp (>= 0.11.0)
LinkingTo: Rcpp, BH
NeedsCompilation: yes
Packaged: 2019-04-10 05:03:29 UTC; hycho
Repository: CRAN
Date/Publication: 2019-04-10 16:56:01 UTC

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New package TR8 with initial version 0.9.20
Package: TR8
Type: Package
Title: A Tool for Downloading Functional Traits Data for Plant Species
Version: 0.9.20
Date: 2019-04-09
Author: Gionata Bocci <boccigionata@gmail.com>
Maintainer: Gionata Bocci <boccigionata@gmail.com>
Description: Plant ecologists often need to collect "traits" data about plant species which are often scattered among various databases: TR8 contains a set of tools which take care of automatically retrieving some of those functional traits data for plant species from publicly available databases (Biolflor, The Ecological Flora of the British Isles, LEDA traitbase, Ellenberg values for Italian Flora, Mycorrhizal intensity databases, Catminat, BROT, PLANTS, Jepson Flora Project). The TR8 name, inspired by "car plates" jokes, was chosen since it both reminds of the main object of the package and is extremely short to type.
License: GPL (>= 2)
LazyData: true
Encoding: UTF-8
URL: https://github.com/GioBo/TR8
BugReports: https://github.com/GioBo/TR8/issues
Depends: R (>= 2.10), methods
Imports: RCurl, XML, plyr, reshape, rappdirs, gWidgets, gWidgetstcltk, readxl, taxize
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2019-04-09 22:13:20 UTC; gionata
Repository: CRAN
Date/Publication: 2019-04-10 08:25:25 UTC

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Tue, 09 Apr 2019

New package TULIP with initial version 1.0
Package: TULIP
Title: A Toolbox for Linear Discriminant Analysis with Penalties
Version: 1.0
Description: Integrates several popular high-dimensional methods based on Linear Discriminant Analysis (LDA) and provides a comprehensive and user-friendly toolbox for linear, semi-parametric and tensor-variate classification as mentioned in Yuqing Pan, Qing Mai and Xin Zhang (2019) <arXiv:1904.03469>. Functions are included for covariate adjustment, model fitting, cross validation and prediction.
Depends: R (>= 3.1.1)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: tensr, Matrix, MASS, glmnet, methods
NeedsCompilation: yes
Packaged: 2019-04-09 14:36:54 UTC; yp15c
Author: Yuqing Pan <yuqing.pan@stat.fsu.edu>, Qing Mai <mai@stat.fsu.edu>, Xin Zhang <henry@stat.fsu.edu>
Maintainer: Yuqing Pan <yuqing.pan@stat.fsu.edu>
Repository: CRAN
Date/Publication: 2019-04-09 21:46:25 UTC

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New package rabhit with initial version 0.1.0.0
Package: rabhit
Type: Package
Title: Inference Tool for Antibody Haplotype
Version: 0.1.0.0
Authors@R: c(person("Ayelet", "Peres", role=c("aut","cre"), email="peresay@biu.ac.il"), person("Moriah", "Gidoni", role=c("aut"), email="moriah.cohen@biu.ac.il"), person("Gur", "Yaari", role=c("aut","cph"), email="gur.yaari@biu.ac.il"))
Description: Infers V-D-J haplotypes and gene deletions from AIRR-seq data, based on IGHJ, IGHD or IGHV as anchor, by adapting a Bayesian framework. It also calculates a Bayes factor, a number that indicates the certainty level of the inference, for each haplotyped gene. Citation: Gidoni, et al (2019) <doi:10.1038/s41467-019-08489-3>.
License: CC BY-SA 4.0
URL: https://yaarilab.bitbucket.io/RAbHIT/
BugReports: https://bitbucket.org/yaarilab/haplotyper/issues
LazyData: true
BuildVignettes: true
VignetteBuilder: knitr
Encoding: UTF-8
Depends: R (>= 3.2.5), ggplot2 (>= 2.0.0)
Imports: dplyr (>= 0.5.0), reshape2, plotly (>= 4.7.1), gtools (>= 3.5.0), cowplot (>= 0.9.1), stats, dendextend (>= 1.9.0), data.table, ggdendro (>= 0.1.20), gridExtra, alakazam (>= 0.2.10), tigger (>= 0.2.11), methods, htmlwidgets, gtable, grDevices, rlang, RColorBrewer, tidyr
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.1
NeedsCompilation: no
Collate: 'Data.R' 'rabhit.R' 'internal_functions.R' 'functions.R' 'graphic_functions.R'
Packaged: 2019-04-09 15:01:26 UTC; ayelet
Author: Ayelet Peres [aut, cre], Moriah Gidoni [aut], Gur Yaari [aut, cph]
Maintainer: Ayelet Peres <peresay@biu.ac.il>
Repository: CRAN
Date/Publication: 2019-04-09 16:13:02 UTC

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New package noaastormevents with initial version 0.1.1
Package: noaastormevents
Type: Package
Title: Explore NOAA Storm Events Database
Version: 0.1.1
Authors@R: c(person("Brooke", "Anderson", email = "brooke.anderson@colostate.edu", role = c("aut", "cre")), person("Ziyu", "Chen", email = "zailchen17@icloud.com", role = "aut"))
Description: Allows users to explore and plot data from the National Oceanic and Atmospheric Administration (NOAA) Storm Events database through R for United States counties. Functionality includes matching storm event listings by time and location to hurricane best tracks data. This work was supported by grants from the Colorado Water Center, the National Institute of Environmental Health Sciences (R00ES022631) and the National Science Foundation (1331399).
URL: https://github.com/geanders/noaastormevents
BugReports: https://github.com/geanders/noaastormevents/issues
License: GPL (>= 2)
LazyData: TRUE
Imports: choroplethr (>= 3.6.3), choroplethrMaps (>= 1.0.1), data.table (>= 1.12.0), dplyr (>= 0.8.0), forcats (>= 0.4.0), ggplot2 (>= 3.1.0), htmltab (>= 0.7.1), hurricaneexposure (>= 0.1.0), lubridate (>= 1.7.4), maps (>= 3.3.0), plyr (>= 1.8.4), RColorBrewer (>= 1.1.2), rlang (>= 0.3.3), stringr (>= 1.4.0), tidyr (>= 0.8.3), viridis (>= 0.5.1), XML (>= 3.98-1.18)
RoxygenNote: 6.1.1
Depends: R (>= 3.5)
Suggests: hurricaneexposuredata (>= 0.0.2), knitr (>= 1.22.0), pander (>= 0.6.3), rmarkdown (>= 1.12.0), testthat (>= 2.0.1), tibble (>= 2.0.1)
VignetteBuilder: knitr
Additional_repositories: https://geanders.github.io/drat
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-04-02 23:26:44 UTC; georgianaanderson
Author: Brooke Anderson [aut, cre], Ziyu Chen [aut]
Maintainer: Brooke Anderson <brooke.anderson@colostate.edu>
Repository: CRAN
Date/Publication: 2019-04-09 16:32:43 UTC

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New package SurrogateOutcome with initial version 1.0
Package: SurrogateOutcome
Type: Package
Title: Estimation of the Proportion of Treatment Effect Explained by Surrogate Outcome Information
Version: 1.0
Date: 2019-04-04
Author: Layla Parast
Maintainer: Layla Parast <parast@rand.org>
Description: Provides functions to estimate the proportion of treatment effect on a censored primary outcome that is explained by the treatment effect on a censored surrogate outcome/event. All methods are described in detail in "Assessing the Value of a Censored Surrogate Outcome" by Parast L, Tian L, and Cai T which is currently in press at Lifetime Data Analysis. The main functions are (1) R.q.event() which calculates the proportion of the treatment effect (the difference in restricted mean survival time at time t) explained by surrogate outcome information observed up to a selected landmark time, (2) R.t.estimate() which calculates the proportion of the treatment effect explained by primary outcome information only observed up to a selected landmark time, and (3) IV.event() which calculates the incremental value of the surrogate outcome information.
License: GPL
Imports: stats, survival
NeedsCompilation: no
Packaged: 2019-04-05 16:34:29 UTC; parast
Repository: CRAN
Date/Publication: 2019-04-09 15:05:21 UTC

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New package STRAH with initial version 1.0
Package: STRAH
Type: Package
Title: Short Tandem Repeats Analysis of Hotspot Zones
Version: 1.0
Authors@R: c(person("Philipp", "Hermann", role = c("aut", "cre"), email = "philipp.hermann@jku.at", comment = c(ORCID = "https://orcid.org/0000-0003-4556-6297")), person("Monika", "Heinzl", role = "aut", email = "monika.heinzl@edumail.at"), person("Angelika", "Heissl", role = "ctb"), person("Irene", "Tiemann-Boege", role = "ctb", comment = c(ORCID = "https://orcid.org/0000-0002-3621-7020")), person("Andreas", "Futschik", role = "ctb", comment = c(ORCID = "https://orcid.org/0000-0002-7980-0304")))
Author: Philipp Hermann [aut, cre] (<https://orcid.org/0000-0003-4556-6297>), Monika Heinzl [aut], Angelika Heissl [ctb], Irene Tiemann-Boege [ctb] (<https://orcid.org/0000-0002-3621-7020>), Andreas Futschik [ctb] (<https://orcid.org/0000-0002-7980-0304>)
Maintainer: Philipp Hermann <philipp.hermann@jku.at>
Description: Searches for short tandem repeats (STR) in a specified region of any genome. This analysis can be expanded such that several regions (chromosomes) are studied. These STRs can be grouped into hotspot as well as flanking regions of user specified width. Hotspots are defined by the double strand break maps from Pratto et al. (2014) <doi:10.1126/science.1256442>. Moreover, the user can also search for a specified motif in a DNAStringSet-object, or a fasta-file, or a specified region of any genome. For an application of STR detections please see Heissl et al. (2018) <doi:10.1101/431841>.
Imports: Biostrings (>= 2.38.4), BSgenome, BSgenome.Hsapiens.UCSC.hg19, BiocManager, methods
Suggests: BSgenome.Ptroglodytes.UCSC.panTro5
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: TRUE
BugReports: https://github.com/PhHermann/STRAH/issues
RoxygenNote: 6.1.1
URL: https://github.com/PhHermann/STRAH
NeedsCompilation: no
Packaged: 2019-04-08 06:58:00 UTC; philipp
Repository: CRAN
Date/Publication: 2019-04-09 15:05:25 UTC

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New package MBCbook with initial version 0.1
Encoding: UTF-8
Package: MBCbook
Type: Package
Title: Companion Package for the Book "Model-Based Clustering and Classification for Data Science" by Bouveyron et al. (2019, ISBN:9781108644181).
Version: 0.1
Date: 2019-04-11
Author: Charles Bouveyron and Gilles Celeux and T. Brendan Murphy and Adrian E. Raftery
Maintainer: Charles Bouveyron <charles.bouveyron@gmail.com>
Depends: R (>= 3.1.0), mclust, Rmixmod, MASS, mvtnorm
Suggests: network, jpeg
Description: The companion package provides all original data sets and functions that are used in the book "Model-Based Clustering and Classification for Data Science" by Charles Bouveyron, Gilles Celeux, T. Brendan Murphy and Adrian E. Raftery (2019, ISBN:9781108644181).
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2019-04-09 13:39:59 UTC; bouveyro
Repository: CRAN
Date/Publication: 2019-04-09 15:15:17 UTC

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New package CEAmarkov with initial version 0.1.0
Package: CEAmarkov
Type: Package
Title: Cost-Effectiveness Analysis using Markov Models
Version: 0.1.0
Author: Noga Gershon, Yakir Berchenko
Maintainer: Noga Gershon <nogagers@post.bgu.ac.il>
Description: Provides an accurate, fast and easy way to perform cost-effectiveness analyses. This package can be used to validate results generated using different methods and can help create a standard for cost-effectiveness analyses, that will help compare results from different studies.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: stringr, WHO, xml2
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-08 17:04:09 UTC; noga
Repository: CRAN
Date/Publication: 2019-04-09 15:15:21 UTC

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New package mvgraphnorm with initial version 1.81
Package: mvgraphnorm
Type: Package
Title: Multivariate Gaussian Graphical Model Analysis
Version: 1.81
Date: 2019-03-30
Author: Shailesh Tripathi, Frank Emmert-Streib
Maintainer: Shailesh Tripathi <shailesh.tripathy@gmail.com>
Description: Generate constrained covariance matrix for a given graph to generate samples from a Gaussian graphical model using different algorithms for the analysis of complex network structure. We use three algorithms which are (1) Kim, K. I. et. al. (2008), <doi: 10.1186/1471-2105-9-114> (2) IPF, Speed, T. et. al. (1986) <doi: 10.1214/aos/1176349846>, (3) HTF, Hastie, T. et. al. (2009) <isbn: 9780387848570>.
Depends: R(>= 2.12.0), igraph, mvtnorm, qpgraph(>= 1.9.2)
Imports: Matrix, bnlearn, corpcor
LazyLoad: yes
License: GPL-2
Packaged: 2019-04-08 21:30:25 UTC; shailesh
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-09 13:20:03 UTC

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New package cogmapr with initial version 0.9
Package: cogmapr
Title: Cognitive Mapping Tools Based on Coding of Textual Sources
Version: 0.9
Date: 2019-04-02
Authors@R: c(person("Frédéric M.", "Vanwindekens", role = c("aut", "cre"), email = "f.vanwindekens@cra.wallonie.be", comment = c(ORCID = "0000-0002-9117-7543")), person("Didier", "Stilmant", role = c("aut","ths"), email = "d.stimant@cra.wallonie.be"), person("Philippe V.", "Baret",role = c("aut","ths"), email = "philippe.baret@uclouvain.be") )
Description: Functions for building cognitive maps based on qualitative data. Inputs are textual sources (articles, transcription of qualitative interviews of agents,...). These sources have been coded using relations and are linked to (i) a table describing the variables (or concepts) used for the coding and (ii) a table describing the sources (typology of agents, ...). Main outputs are Individual Cognitive Maps (ICM), Social Cognitive Maps (all sources or group of sources) and a list of quotes linked to relations. This package is linked to the work done during the PhD of Frederic M. Vanwindekens (CRA-W / UCL) hold the 13 of May 2014 at University of Louvain in collaboration with the Walloon Agricultural Research Centre (project MIMOSA, MOERMAN fund).
URL: https://frdvnw.gitlab.io/cogmapr/
BugReports: https://gitlab.com/FrdVnW/cogmapr/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Imports: DBI, grDevices, methods, utils, graph, Rgraphviz, grid, ggplot2, magrittr, car, dplyr, tidyr, knitr, pander
Suggests: testthat, rmarkdown
Maintainer: Frédéric M. Vanwindekens <f.vanwindekens@cra.wallonie.be>
NeedsCompilation: no
Packaged: 2019-04-08 15:28:30 UTC; fred
Author: Frédéric M. Vanwindekens [aut, cre] (<https://orcid.org/0000-0002-9117-7543>), Didier Stilmant [aut, ths], Philippe V. Baret [aut, ths]
Repository: CRAN
Date/Publication: 2019-04-09 13:02:51 UTC

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New package spinifex with initial version 0.1.0
Package: spinifex
Title: Manual Tours, Manual Control of Dynamic Projections of Numeric Multivariate Data
Version: 0.1.0
Authors@R: c( person("Nicholas", "Spyrison", email = "spyrison@gmail.com", role = c("aut", "cre")), person("Dianne", "Cook", role = c("aut", "ths")) )
Description: Generates the path for manual tours ['Cook' & 'Buja' (1997) <doi:10.2307/1390747>]. Tours are generally available in the 'tourr' package ['Wickham' 'et' 'al.' (2011) <doi:10.18637/jss.v040.i02>]. The grand tour is an algorithm that shows all possible projections given sufficient time. Guided uses projection pursuit to steer the tour towards interesting projections. The 'spinifex' package implements manual control, where the contribution of a selected variable can be adjusted between -1 to 1, to examine the sensitivity of structure in the data to that variable. The result is an animation where the variable is toured into and out of the projection completely, which can be rendered using the 'gganimate' and 'plotly' packages.
Depends: R (>= 3.4.0), tourr
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/nspyrison/spinifex/
BugReports: https://github.com/nspyrison/spinifex/issues
Imports: dplyr, GGally, ggplot2, plotly, tibble, webshot
Suggests: gganimate, gifski, knitr, png, rmarkdown, RColorBrewer
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-05 03:50:28 UTC; spyri
Author: Nicholas Spyrison [aut, cre], Dianne Cook [aut, ths]
Maintainer: Nicholas Spyrison <spyrison@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-09 12:00:04 UTC

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New package rainfarmr with initial version 0.1
Package: rainfarmr
Title: Stochastic Precipitation Downscaling with the RainFARM Method
Version: 0.1
Authors@R: person("Jost", "von Hardenberg", email = "j.vonhardenberg@isac.cnr.it", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-5312-8070"))
URL: https://github.com/jhardenberg/rainfarmr
BugReports: https://github.com/jhardenberg/rainfarmr
Description: An implementation of the RainFARM (Rainfall Filtered Autoregressive Model) stochastic precipitation downscaling method (Rebora et al. (2006) <doi:10.1175/JHM517.1>). Adapted for climate downscaling according to D'Onofrio et al. (2018) <doi:10.1175/JHM-D-13-096.1> and for complex topography as in Terzago et al. (2018) <doi:10.5194/nhess-18-2825-2018>. The RainFARM method is based on the extrapolation to small scales of the Fourier spectrum of a large-scale precipitation field, using a fixed logarithmic slope and random phases at small scales, followed by a nonlinear transformation of the resulting linearly correlated stochastic field. RainFARM allows to generate ensembles of spatially downscaled precipitation fields which conserve precipitation at large scales and whose statistical properties are consistent with the small-scale statistics of observed precipitation, based only on knowledge of the large-scale precipitation field.
Depends: R (>= 3.1.0)
License: Apache License 2.0
LazyData: true
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-04-08 09:12:16 UTC; jost
Author: Jost von Hardenberg [aut, cre, cph] (<https://orcid.org/0000-0002-5312-8070>)
Maintainer: Jost von Hardenberg <j.vonhardenberg@isac.cnr.it>
Repository: CRAN
Date/Publication: 2019-04-09 12:10:03 UTC

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New package ingredients with initial version 0.3.1
Package: ingredients
Title: Effects and Importances of Model Ingredients
Version: 0.3.1
Authors@R: c(person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8423-1823")), person("Hubert", "Baniecki", role = "ctb"))
Description: Collection of tools for assessment of feature importance and feature effects. Key functions are: feature_importance() for assessment of global level feature importance, ceteris_paribus() for calculation of the what-if plots, partial_dependency() for partial dependency plots, conditional_dependency() for conditional dependency plots, accumulated_dependency() for accumulated local effects plots, aggregate_profiles() and cluster_profiles() for aggregation of ceteris paribus profiles, theme_drwhy() with a 'ggplot2' skin for all plots, generic print() and plot() for better usability of selected explainers. The package 'ingredients' is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Depends: R (>= 3.0)
License: GPL
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: DALEX, ggplot2
Suggests: gbm, gower, randomForest, titanic, xgboost, testthat, dplyr, r2d3, ggpubr, jsonlite
URL: https://ModelOriented.github.io/ingredients/
BugReports: https://github.com/ModelOriented/ingredients/issues
NeedsCompilation: no
Packaged: 2019-04-06 11:31:56 UTC; pbiecek
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>), Hubert Baniecki [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-09 12:10:08 UTC

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New package gluvarpro with initial version 1.0
Package: gluvarpro
Type: Package
Title: Glucose Variability Measures from Continuous Glucose Monitoring Data
Version: 1.0
Imports: ggplot2, pracma, scales, stats, tidyr, zoo
Author: Sergio Contador
Maintainer: Sergio Contador <scontador@ucm.es>
Description: Calculate different glucose variability measures, including average measures of glycemia, measures of glycemic variability and measures of glycemic risk, from continuous glucose monitoring data obtained from diabetic patients. Boris P. Kovatchev, Erik Otto, Daniel Cox, Linda Gonder-Frederick, and William Clarke (2006) <doi:10.2337/dc06-1085>. Jean-Pierre Le Floch, Philippe Escuyer, Eric Baudin, Dominique Baudon, and Leon Perlemuter (1990) <doi:10.2337/diacare.13.2.172>. C.M. McDonnell, S.M. Donath, S.I. Vidmar, G.A. Werther, and F.J. Cameron (2005) <doi:10.1089/dia.2005.7.253>. Everitt, Brian (1998) <doi:10.1111/j.1751-5823.2011.00149_2.x>. Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) <doi:10.2307/2234167>. Dougherty, R. L., Edelman, A. and Hyman, J. M. (1989) <doi:10.1090/S0025-5718-1989-0962209-1>. Tukey, J. W. (1977) <doi:10.1016/0377-2217(86)90209-2>. F. John Service (2013) <doi:10.2337/db12-1396>. Edmond A. Ryan, Tami Shandro, Kristy Green, Breay W. Paty, Peter A. Senior, David Bigam, A.M. James Shapiro, and Marie-Christine Vantyghem (2004) <doi:10.2337/diabetes.53.4.955>. Seniz Sevimer Tuncan, Mehmet Uzunlulu, Ozge telci caklili, Hasan Huseyin Mutlu, and Aytekin Oguz (2016) <doi:10.5152/cjms.2016.109>. Sarah E. Siegelaar, Frits Holleman, Joost B. L. Hoekstra, and J. Hans DeVries (2010) <doi:10.1210/er.2009-0021>. Gabor Marics, Zsofia Lendvai, Csaba Lodi, Levente Koncz, David Zakarias, Gyorgy Schuster, Borbala Mikos, Csaba Hermann, Attila J. Szabo, and Peter Toth-Heyn (2015) <doi:10.1186/s12938-015-0035-3>.
License: GPL-2
Encoding: UTF-8
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
LazyData: true
NeedsCompilation: no
Packaged: 2019-04-05 10:57:30 UTC; master
Repository: CRAN
Date/Publication: 2019-04-09 12:00:08 UTC

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New package DET with initial version 1.0.0
Package: DET
Type: Package
Title: Representation of DET Curve with Confidence Intervals
Version: 1.0.0
Authors@R: c( person("García-Ródenas, Álvaro", role = c("aut","cre"), email = "alvaro.garcia9@um.es"), person("Franco, Manuel", role = c("aut"), email = "mfranco@um.es"), person("Vivo, Juana-María", role = c("aut"), email = "jmvivomo@um.es"), person("Fernández-Breis, Jesualdo T.", role = c("aut"), email = "jfernand@um.es"), person("Font, Roberto", role = c("aut"), email = "roberto.font@biometricvox.com"))
Description: Builds both ROC (Receiver Operating Characteristic) and DET (Detection Error Tradeoff) curves from a set of predictors, which are the results of a binary classification system. The curves give a general vision of the performance of the classifier, and are useful for comparing performance of different systems.
License: GPL-2
Encoding: UTF-8
Imports: pROC, doParallel, parallel
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-08 10:42:01 UTC; meteo
Author: García-Ródenas, Álvaro [aut, cre], Franco, Manuel [aut], Vivo, Juana-María [aut], Fernández-Breis, Jesualdo T. [aut], Font, Roberto [aut]
Maintainer: "García-Ródenas, Álvaro" <alvaro.garcia9@um.es>
Repository: CRAN
Date/Publication: 2019-04-09 12:12:53 UTC

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New package reinforcelearn with initial version 0.2.1
Package: reinforcelearn
Type: Package
Title: Reinforcement Learning
Version: 0.2.1
Authors@R: person("Markus", "Dumke", email = {"markusdumke@gmail.com"}, role = c("aut", "cre"))
Description: Implements reinforcement learning environments and algorithms as described in Sutton & Barto (1998, ISBN:0262193981). The Q-Learning algorithm can be used with function approximation, eligibility traces (Singh & Sutton (1996) <doi:10.1007/BF00114726>) and experience replay (Mnih et al. (2013) <arXiv:1312.5602>).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
RoxygenNote: 6.1.1
BugReports: https://github.com/markusdumke/reinforcelearn/issues
URL: http://markusdumke.github.io/reinforcelearn
SystemRequirements: (Python and gym only required if gym environments are used)
Imports: checkmate (>= 1.8.4), R6 (>= 2.2.2), nnet (>= 7.3-12), purrr (>= 0.2.4)
Suggests: reticulate, keras, knitr, rmarkdown, testthat, covr, lintr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-08 19:08:56 UTC; Markus
Author: Markus Dumke [aut, cre]
Maintainer: Markus Dumke <markusdumke@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-09 11:50:08 UTC

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New package gremlin with initial version 0.1.0.1
Package: gremlin
Type: Package
Title: Mixed-Effects REML Incorporating Generalized Inverses
Version: 0.1.0.1
Authors@R: person("Matthew", "Wolak", email = "matthewwolak@gmail.com", role = c("cre", "aut"), comment = c(ORCID="0000-0002-7962-0071"))
URL: http://github.com/matthewwolak/gremlin
BugReports: http://github.com/matthewwolak/gremlin/issues
Depends: Matrix
Imports: methods
Suggests: nadiv
LazyData: yes
NeedsCompilation: no
Description: Fit linear mixed-effects models using restricted (or residual) maximum likelihood (REML) and with generalized inverse matrices to specify covariance structures for random effects. In particular, the package is suited to fit quantitative genetic mixed models, often referred to as 'animal models' (Kruuk. 2004 <DOI: 10.1098/rstb.2003.1437>). Implements the average information algorithm as the main tool to maximize the restricted likelihood, but with other algorithms available (Meyer. 1997. Genet Sel Evol 29:97; Meyer and Smith. 1998. Genet Sel Evol 28:23.).
License: GPL-3
RoxygenNote: 6.1.1
Packaged: 2019-04-08 21:36:15 UTC; matthew
Author: Matthew Wolak [cre, aut] (<https://orcid.org/0000-0002-7962-0071>)
Maintainer: Matthew Wolak <matthewwolak@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-09 11:50:14 UTC

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New package tbm with initial version 0.3-0
Package: tbm
Title: Transformation Boosting Machines
Version: 0.3-0
Date: 2019-04-03
Authors@R: person("Torsten", "Hothorn", role = c("aut", "cre"), email = "Torsten.Hothorn@R-project.org", comment = c(ORCID = "0000-0001-8301-0471"))
Description: Boosting the likelihood of conditional and shift transformation models.
Depends: mlt (>= 1.0-2), mboost (>= 2.8-2)
Imports: variables, basefun, sandwich, coneproj, methods
Suggests: TH.data (>= 1.0-9), tram (>= 0.2-3), survival, partykit, lattice, latticeExtra, knitr, colorspace, gamlss.data, trtf
VignetteBuilder: knitr
License: GPL-2
NeedsCompilation: no
Packaged: 2019-04-03 11:43:14 UTC; hothorn
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Repository: CRAN
Date/Publication: 2019-04-09 09:03:12 UTC

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Mon, 08 Apr 2019

New package PDFEstimator with initial version 0.1-2
Package: PDFEstimator
Version: 0.1-2
Date: 2019-04-07
Title: Nonparametric Probability Density Estimator
Author: Jenny Farmer <jfarmer6@uncc.edu> and Donald Jacobs <djacobs1@uncc.ecu>
Maintainer: Jenny Farmer <jfarmer6@uncc.edu>
Description: Farmer, J., D. Jacobs (2108) <DOI:10.1371/journal.pone.0196937>. A nonparametric density estimator based on the maximum-entropy method. Accurately predicts a probability density function (PDF) for random data using a novel iterative scoring function to determine the best fit without overfitting to the sample.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2019-04-08 01:15:27 UTC; jenny
Repository: CRAN
Date/Publication: 2019-04-08 12:02:46 UTC

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New package bayestestR with initial version 0.1.0
Package: bayestestR
Type: Package
Title: Understand and Describe Bayesian Models and Posterior Distributions
Version: 0.1.0
Authors@R: c( person("Dominique", "Makowski", email = "dom.makowski@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5375-9967")), person("Daniel", "Lüdecke", role = c("aut"), email = "d.luedecke@uke.de", comment = c(ORCID = "0000-0002-8895-3206")) )
Maintainer: Dominique Makowski <dom.makowski@gmail.com>
URL: https://github.com/easystats/bayestestR
BugReports: https://github.com/easystats/bayestestR/issues
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2014 <doi:10.1016/B978-0-12-405888-0.09999-2>) and indices used for null-hypothesis testing (such as ROPE percentage and pd).
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0), stats
Imports: insight
Suggests: brms, broom, covr, dplyr, tidyr, ggplot2, ggridges, knitr, rmarkdown, rstanarm, stringr, testthat
RoxygenNote: 6.1.1
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-08 07:48:00 UTC; Dom
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>)
Repository: CRAN
Date/Publication: 2019-04-08 09:42:41 UTC

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New package BayesSenMC with initial version 0.1.0
Package: BayesSenMC
Title: Different Models of Posterior Distributions of Adjusted Odds Ratio
Version: 0.1.0
Author: Jinhui Yang
Maintainer: Jinhui Yang <yangj2@carleton.edu>
Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed by Chu et al. (2006) <doi:10.1016/j.annepidem.2006.04.001> and Chu et al. (2010) <doi:10.1177/0272989X09353452>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, rstan (>= 2.16.2), lme4,
Depends: Rcpp (>= 0.12.19)
Suggests: gridExtra
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-08 03:46:58 UTC; james
Repository: CRAN
Date/Publication: 2019-04-08 08:52:53 UTC

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Sun, 07 Apr 2019

New package r2pmml with initial version 0.22.0
Package: r2pmml
Version: 0.22.0
Date: 2019-04-05
Type: Package
License: AGPL-3
Title: Convert R Models to PMML
Description: R wrapper for the JPMML-R library <https://github.com/jpmml/jpmml-r>, which converts R models to Predictive Model Markup Language (PMML).
Author: Villu Ruusmann <villu.ruusmann@gmail.com>
Maintainer: Villu Ruusmann <villu.ruusmann@gmail.com>
URL: https://github.com/jpmml/r2pmml
LazyLoad: yes
NeedsCompilation: no
RoxygenNote: 6.1.1
Suggests: caret, e1071, earth, evtree, glmnet, mlbench, partykit, randomForest, ranger, xgboost
Packaged: 2019-04-05 20:44:10 UTC; vfed
Repository: CRAN
Date/Publication: 2019-04-07 22:40:07 UTC

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New package pendensity with initial version 0.2.13
Package: pendensity
Type: Package
Title: Density Estimation with a Penalized Mixture Approach
Version: 0.2.13
Date: 2019-04-07
Depends: R (>= 2.15.1), lattice, fda
Author: Christian Schellhase
Maintainer: Christian Schellhase <christian.schellhase@gmx.net>
Description: Estimation of univariate (conditional) densities using penalized B-splines with automatic selection of optimal smoothing parameter.
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2019-04-07 21:11:37 UTC; christian
Repository: CRAN
Date/Publication: 2019-04-07 22:10:10 UTC

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New package countToFPKM with initial version 1.0
Package: countToFPKM
Title: Convert Counts to Fragments per Kilobase of Transcript per Million (FPKM)
Version: 1.0
Date: 2019-03-22
Authors@R: c(person("Ahmed", "Alhendi", email = "asna4@le.ac.uk",role = c("aut","cre")))
Author: Ahmed Alhendi [aut, cre]
Maintainer: Ahmed Alhendi <asna4@le.ac.uk>
Depends: R (>= 3.1.0), ComplexHeatmap, circlize, stats
Description: Implements the algorithm described in Trapnell,C. et al. (2010) <doi: 10.1038/nbt.1621>. This function takes read counts matrix of RNA-Seq data, feature lengths which can be retrieved using 'biomaRt' package, and the mean fragment lengths which can be calculated using the 'CollectInsertSizeMetrics(Picard)' tool. It then returns a matrix of FPKM normalised data by library size and feature effective length. It also provides the user with a quick and reliable function to generate FPKM heatmap plot of the highly variable features in RNA-Seq dataset.
License: GPL-3
URL: https://github.com/AAlhendi1707/countToFPKM
BugReports: https://github.com/AAlhendi1707/countToFPKM/issues
NeedsCompilation: no
Packaged: 2019-04-07 16:59:02 UTC; asna4
Repository: CRAN
Date/Publication: 2019-04-07 17:42:43 UTC

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New package postinfectious with initial version 0.1.0
Package: postinfectious
Type: Package
Title: Estimating the Incubation Period Distribution of Post-Infectious Syndrome
Version: 0.1.0
Author: Char Leung
Maintainer: Char Leung <charleung@hotmail.fr>
Description: Functions to estimate the incubation period distribution of post-infectious syndrome which is defined as the time between the symptom onset of the antecedent infection and that of the post-infectious syndrome.
License: GPL-2
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-04-07 05:01:52 UTC; Char
Repository: CRAN
Date/Publication: 2019-04-07 16:30:02 UTC

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New package plothelper with initial version 0.1.0
Package: plothelper
Type: Package
Title: New Plots Based on 'ggplot2' and Functions to Create Regular Shapes
Version: 0.1.0
Date: 2019-04-06
Authors@R: c(person("Jiang", "Wu", role = c("aut", "cre"), email = "textidea@sina.com", comment = "from Capital Normal University"))
Maintainer: Jiang Wu <textidea@sina.com>
Description: An extension to 'ggplot2' with miscellaneous functions. It contains two groups of functions: Functions in the first group draw 'ggplot2' - based plots: gg_shading_bar() draws barplot with shading colors in each bar. geom_rect_cm(), geom_circle_cm() and geom_ellipse_cm() draw rectangles, circles and ellipses with centimeter as their unit. Thus their sizes do not change when the coordinate system or the aspect ratio changes. Functions in the second group generate coordinates for regular shapes and make linear transformations.
License: GPL-3
URL: https://github.com/githubwwwjjj/plothelper/blob/master/README.md
Depends: R (>= 3.5.0), ggplot2 (>= 3.0.0)
Imports: plyr, ggfittext, magick, grid, gridExtra
Encoding: UTF-8
LazyLoad: true
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-06 15:16:19 UTC; useruser
Author: Jiang Wu [aut, cre] (from Capital Normal University)
Repository: CRAN
Date/Publication: 2019-04-07 16:20:03 UTC

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New package leafpop with initial version 0.0.1
Package: leafpop
Type: Package
Title: Include Tables, Images and Graphs in Leaflet Pop-Ups
Version: 0.0.1
Date: 2019-04-05
Authors@R: c(person(given = "Tim", family = "Appelhans", role = c("cre", "aut"), email = "tim.appelhans@gmail.com"), person(given = "Florian", family = "Detsch", role = "aut", email = "fdetsch@web.de"))
Maintainer: Tim Appelhans <tim.appelhans@gmail.com>
Description: Creates 'HTML' strings to embed tables, images or graphs in pop-ups of interactive maps created with packages like 'leaflet' or 'mapview'. Handles local images located on the file system or via remote URL. Handles graphs created with 'lattice' or 'ggplot2' as well as interactive plots created with 'htmlwidgets'.
License: MIT + file LICENSE
Imports: base64enc, brew, gdalUtils, htmlwidgets, Rcpp (>= 1.0.0), svglite, uuid
Suggests: lattice, leaflet (>= 2.0.0), sf, sp
LinkingTo: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2019-04-07 08:54:20 UTC; timpanse
Author: Tim Appelhans [cre, aut], Florian Detsch [aut]
Repository: CRAN
Date/Publication: 2019-04-07 15:20:18 UTC

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New package biclique with initial version 1.0.2
Package: biclique
Title: Maximal Biclique Enumeration in Bipartite Graphs
Version: 1.0.2
Authors@R: c( person("Yuping", "Lu", , "yupinglu89@gmail.com", role = c("aut", "cre", "cph")), person("Charles", "Phillips", role = "aut"), person("Michael", "Langston", role = "aut"), person("Department of Computer Science, University of Tennessee, Knoxville", role = "cph") )
Encoding: UTF-8
Description: A tool for enumerating maximal complete bipartite graphs. The input should be a edge list file or a binary matrix file. The output are maximal complete bipartite graphs. Algorithms used can be found in this paper Y Zhang et al. BMC Bioinformatics 2014 15:110 <doi:10.1186/1471-2105-15-110>.
URL: https://github.com/YupingLu/biclique
BugReports: https://github.com/YupingLu/biclique/issues
Depends: R (>= 3.4.0)
Imports: graphics, utils
License: GPL-2 | file LICENSE
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2019-03-30 04:30:38 UTC; yupinglu
Author: Yuping Lu [aut, cre, cph], Charles Phillips [aut], Michael Langston [aut], Department of Computer Science, University of Tennessee, Knoxville [cph]
Maintainer: Yuping Lu <yupinglu89@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-07 08:32:40 UTC

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Sat, 06 Apr 2019

New package FinTS with initial version 0.4-6
Package: FinTS
Type: Package
Title: Companion to Tsay (2005) Analysis of Financial Time Series
Version: 0.4-6
Date: 2019-04-05
Author: Spencer Graves
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>
Description: R companion to Tsay (2005) Analysis of Financial Time Series, second edition (Wiley). Includes data sets, functions and script files required to work some of the examples. Version 0.3-x includes R objects for all data files used in the text and script files to recreate most of the analyses in chapters 1-3 and 9 plus parts of chapters 4 and 11.
License: GPL (>= 2)
URL: https://r-forge.r-project.org/projects/fints/
Depends: R (>= 2.10), zoo, graphics
Suggests: moments, distrEx, tseries, urca, lmtest, sandwich, psych, GPArotation, chron, polynom, e1071
Repository: CRAN
Repository/R-Forge/Project: fints
Repository/R-Forge/Revision: 123
Repository/R-Forge/DateTimeStamp: 2019-04-06 20:52:58
Date/Publication: 2019-04-06 22:33:32 UTC
NeedsCompilation: no
Packaged: 2019-04-06 21:10:10 UTC; rforge

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New package virtuoso with initial version 0.1.3
Package: virtuoso
Type: Package
Title: Interface to 'Virtuoso' using 'ODBC'
Version: 0.1.3
Authors@R: c(person("Carl", "Boettiger", email = "cboettig@gmail.com", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-1642-628X")), person("Bryce", "Mecum", role = "ctb", email = "brycemecum@gmail.com", comment = c(ORCID = "0000-0002-0381-3766")))
Description: Provides users with a simple and convenient mechanism to manage and query a 'Virtuoso' database using the 'DBI' (DataBase Interface) compatible 'ODBC' (Open Database Connectivity) interface. 'Virtuoso' is a high-performance "universal server," which can act as both a relational database, supporting standard Structured Query Language ('SQL') queries, while also supporting data following the Resource Description Framework ('RDF') model for Linked Data. 'RDF' data can be queried using 'SPARQL' ('SPARQL' Protocol and 'RDF' Query Language) queries, a graph-based query that supports semantic reasoning. This allows users to leverage the performance of local or remote 'Virtuoso' servers using popular 'R' packages such as 'DBI' and 'dplyr', while also providing a high-performance solution for working with large 'RDF' triplestores from 'R.' The package also provides helper routines to install, launch, and manage a 'Virtuoso' server locally on 'Mac', 'Windows' and 'Linux' platforms using the standard interactive installers from the 'R' command-line. By automatically handling these setup steps, the package can make using 'Virtuoso' considerably faster and easier for a most users to deploy in a local environment. Managing the bulk import of triples from common serializations with a single intuitive command is another key feature of this package. Bulk import performance can be tens to hundreds of times faster than the comparable imports using existing 'R' tools, including 'rdflib' and 'redland' packages.
License: MIT + file LICENSE
URL: https://github.com/ropensci/virtuoso
BugReports: https://github.com/ropensci/virtuoso/issues
Encoding: UTF-8
LazyData: true
Imports: odbc, processx, DBI, utils, ini, rappdirs, curl, fs, digest, ps
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, nycflights13, testthat, covr, jsonld, dplyr, spelling
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2019-03-13 17:28:51 UTC; cboettig
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Bryce Mecum [ctb] (<https://orcid.org/0000-0002-0381-3766>)
Maintainer: Carl Boettiger <cboettig@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-06 12:00:03 UTC

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New package uwot with initial version 0.1.2
Package: uwot
Title: The Uniform Manifold Approximation and Projection (UMAP) Method for Dimensionality Reduction
Version: 0.1.2
Authors@R: person("James", "Melville", email = "jlmelville@gmail.com", role = c("aut", "cre"))
Description: An implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018) <arXiv:1802.03426>. It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) <arXiv:1602.00370> is also provided. This is a complete re-implementation in R (and C++, via the 'Rcpp' package): no Python installation is required. See the uwot website (<https://github.com/jlmelville/uwot>) for more documentation and examples.
License: GPL-3
URL: https://github.com/jlmelville/uwot
BugReports: https://github.com/jlmelville/uwot/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat, covr
RoxygenNote: 6.1.1
Depends: Matrix
LinkingTo: Rcpp, RcppProgress, RcppParallel, RcppAnnoy, dqrng
Imports: Rcpp, methods, FNN, RSpectra, RcppAnnoy (>= 0.0.11), RcppParallel, irlba
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2019-04-06 04:28:16 UTC; jlmel
Author: James Melville [aut, cre]
Maintainer: James Melville <jlmelville@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-06 11:40:03 UTC

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New package tradestatistics with initial version 0.1
Package: tradestatistics
Type: Package
Title: Open Trade Statistics API Wrapper and Utility Program
Version: 0.1
Authors@R: c( person(given = "Mauricio", family = "Vargas", role = c("aut", "cre", "cph"), email = "mvargas@dcc.uchile.cl", comment = c(ORCID = "0000-0003-1017-7574")), person(given = "Joshua", family = "Kunst", role = "ctb"), person(given = "Emily", family = "Riederer", role = "rev"), person(given = "Mark", family = "Padgham", role = "rev", comment = c(ORCID = "0000-0003-1017-7574")), person(given = "Amanda", family = "Dobbyn", role = "rev"), person(given = "Jorge", family = "Cimentada", role = "rev"), person(family = "United Nations International Trade Statistics Database", role = "dtc"), person(family = "Center for International Development at Harvard University", role = "dtc"), person(family = "The Observatory of Economic Complexity", role = "dtc") )
URL: https://ropensci.github.io/tradestatistics
BugReports: https://github.com/ropensci/tradestatistics/issues
Description: Access Open Trade Statistics API from R to download international trade data.
License: GPL-3
LazyData: TRUE
Depends: R (>= 3.2)
Imports: rlang, magrittr, dplyr, stringr, crul, purrr, jsonlite
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, testthat, styler, pkgdown, vcr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-04-05 15:49:57 UTC; pacha
Author: Mauricio Vargas [aut, cre, cph] (<https://orcid.org/0000-0003-1017-7574>), Joshua Kunst [ctb], Emily Riederer [rev], Mark Padgham [rev] (<https://orcid.org/0000-0003-1017-7574>), Amanda Dobbyn [rev], Jorge Cimentada [rev], United Nations International Trade Statistics Database [dtc], Center for International Development at Harvard University [dtc], The Observatory of Economic Complexity [dtc]
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>
Repository: CRAN
Date/Publication: 2019-04-06 11:30:03 UTC

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New package syntaxr with initial version 0.8.0
Package: syntaxr
Type: Package
Title: An 'SPSS' Syntax Generator for Multi-Variable Manipulation
Version: 0.8.0
Author: Alix Lahuec <alix.lahuec@mail.mcgill.ca>
Maintainer: Alix Lahuec <alix.lahuec@mail.mcgill.ca>
URL: https://github.com/greenmeen/syntaxr
BugReports: https://github.com/greenmeen/syntaxr/issues
Description: A set of functions for generating 'SPSS' syntax files from the R environment.
Imports: magrittr
Suggests: covr, haven, testthat
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-05 14:55:54 UTC; lahue
Repository: CRAN
Date/Publication: 2019-04-06 11:10:03 UTC

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New package ProPublicaR with initial version 0.9.2
Package: ProPublicaR
Type: Package
Title: Access Functions for ProPublica's APIs
Version: 0.9.2
Authors@R: c( person("Aleksander", "Dietrichson", email = "dietrichson@gmail.com", role=c("aut", "cre")), person("Joselina", "Davit", email = "joselinadavyt@gmail.com", role = c("aut")) )
Description: Provides wrapper functions to access the ProPublica's Congress and Campaign Finance APIs. The Congress API provides near real-time access to legislative data from the House of Representatives, the Senate and the Library of Congress. The Campaign Finance API provides data from United States Federal Election Commission filings and other sources. The API covers summary information for candidates and committees, as well as certain types of itemized data. For more information about these APIs go to: <https://www.propublica.org/datastore/apis>.
License: GPL-3 | file LICENSE
BugReports: https://github.com/dietrichson/ProPublicaR/issues
Depends: R (>= 3.1)
Imports: dplyr, stringr, httr, config, lubridate
Suggests: testthat, httptest, knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1.9000
Collate: 'a_get_new_members.R' 'bills_legislation_by_keyword.R' 'compare_two_member_bill_sponsorships.R' 'compare_two_member_vote_positions.R' 'data.R' 'get_a_bill.R' 'get_amendments_bill.R' 'get_bills_cosponsored_member.R' 'get_candidate.R' 'get_candidate_by_name.R' 'get_candidates_in_race.R' 'get_committee.R' 'get_committee_by_name.R' 'get_committee_electioneering_communications.R' 'get_committee_filings.R' 'get_committee_leadership.R' 'get_congress_member.R' 'get_congressional_statement_by_bill.R' 'get_congressional_statement_by_member.R' 'get_congressional_statement_by_subjects.R' 'get_cosponsors_specific_bill.R' 'get_current_members_by_statedistrict.R' 'get_electioneering_communications_by_date.R' 'get_electioneering_communications_committee.R' 'get_electronic_filing_byDate.R' 'get_electronic_filing_by_committees.R' 'get_electronic_filing_by_types.R' 'get_electronic_filing_form_types.R' 'get_hearing_specific_committee.R' 'get_house_senate_floor_actions_by_date.R' 'get_independent_expenditure_by_committee.R' 'get_independent_expenditure_by_date.R' 'get_independent_expenditure_office_totals.R' 'get_independent_expenditure_race_totals_committee.R' 'get_independent_expenditure_support_candidate.R' 'get_independent_expenditure_support_presidential_candidate.R' 'get_lobbyist_bundlers.R' 'get_member_vote_position.R' 'get_members_leaving.R' 'get_nominees_by_state.R' 'get_quarter_office_expenses_by_category_house_member.R' 'get_quarter_office_expenses_house_member.R' 'get_races_for_state.R' 'get_recent_amendments.R' 'get_recent_committee_hearing.R' 'get_recent_congressional_statements.R' 'get_recent_congressional_statements_by_date.R' 'get_recent_congressional_statements_by_term.R' 'get_recent_electioneering_communications.R' 'get_recent_house_senate_floor_actions.R' 'get_recent_independent_expend.R' 'get_recent_late_contributions.R' 'get_recent_late_contributions_candidate.R' 'get_recent_late_contributions_committee.R' 'get_recent_late_contributions_date.R' 'get_recent_lobbying_representation_filings.R' 'get_recent_nominations_by_category.R' 'get_recent_official_communications.R' 'get_recent_official_communications_by_category.R' 'get_recent_official_communications_by_chamber.R' 'get_recent_official_communications_by_date.R' 'get_recent_personal_explanations.R' 'get_recent_personal_explanations_specific_member.R' 'get_recent_personal_explanations_votes.R' 'get_recent_personal_explanations_votes_by_category.R' 'get_recent_personal_explanations_votes_specific_member.R' 'get_recent_personal_explanations_votes_specific_member_by_category.R' 'get_recent_votes.R' 'get_recently_added_independent_expenditure_committees.R' 'get_recently_candidates.R' 'get_recently_committees.R' 'get_related_bills.R' 'get_senate_nomination_votes.R' 'get_specific_bill.R' 'get_specific_bill_subject.R' 'get_specific_committee.R' 'get_specific_lobbying_representation_filings.R' 'get_specific_nominations.R' 'get_specific_roll_call_vote.R' 'get_specific_subcommittee.R' 'get_state_party_counts.R' 'get_statement_subjects.R' 'get_subjects_for_bill.R' 'get_top20_candidate_of_FinancialCategory.R' 'get_upcoming_bills.R' 'get_votes_by_date.R' 'get_votes_by_date_range.R' 'get_votes_by_type.R' 'list_members_chamber_congress.R' 'lists_of_committees.R' 'pp_convert_to_data_frame.R' 'pp_query.R' 'recent_bills_by_member.R' 'recent_bills_by_subject.R' 'recent_bills_by_type.R' 'search_lobbying_representation_filings.R' 'validate_cycle.R' 'validate_district.R' 'validate_state.R'
NeedsCompilation: no
Packaged: 2019-04-05 16:29:22 UTC; sasha
Author: Aleksander Dietrichson [aut, cre], Joselina Davit [aut]
Maintainer: Aleksander Dietrichson <dietrichson@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-06 10:43:00 UTC

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New package MatTransMix with initial version 0.1.1
Package: MatTransMix
Version: 0.1.1
Date: 2019-03-24
Title: Clustering with Matrix Gaussian and Matrix Transformation Mixture Models
Authors@R: c(person("Xuwen", "Zhu", role = c("aut", "cre"), email = "xuwen.zhu@louisville.edu"), person("Volodymyr", "Melnykov", role = "aut"), person("Shuchismita", "Sarkar", role = "ctb"), person("Michael", "Hutt", role = c("ctb", "cph")), person("Stephen", "Moshier", role = c("ctb", "cph")), person("Rouben", "Rostamian", role = c("ctb", "cph")), person("Carl Edward", "Rasmussen", role = c("ctb", "cph")), person("Dianne", "Cook", role = c("ctb", "cph")))
Depends: R (>= 3.0.0)
LazyLoad: yes
LazyData: no
Description: Provides matrix Gaussian mixture models, matrix transformation mixture models and their model-based clustering results. The parsimonious models of the mean matrices and variance covariance matrices are implemented with a total of 196 variations.
License: GPL (>= 2)
Packaged: 2019-04-05 19:51:11 UTC; zhu
Author: Xuwen Zhu [aut, cre], Volodymyr Melnykov [aut], Shuchismita Sarkar [ctb], Michael Hutt [ctb, cph], Stephen Moshier [ctb, cph], Rouben Rostamian [ctb, cph], Carl Edward Rasmussen [ctb, cph], Dianne Cook [ctb, cph]
Maintainer: Xuwen Zhu <xuwen.zhu@louisville.edu>
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2019-04-06 09:22:44 UTC

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New package tRophicPosition with initial version 0.7.7
Package: tRophicPosition
Type: Package
Title: Bayesian Trophic Position Calculation with Stable Isotopes
Version: 0.7.7
Date: 2019-04-05
Depends: R (>= 3.4.0)
Imports: coda, data.table, ggplot2, gridExtra, hdrcde, MCMCglmm, plyr, rjags, stats
Author: Claudio Quezada-Romegialli, Andrew L Jackson, Chris Harrod
URL: https://github.com/clquezada/tRophicPosition
BugReports: https://groups.google.com/d/forum/trophicposition-support
Maintainer: Claudio Quezada-Romegialli <clquezada@harrodlab.net>
Description: Estimates the trophic position of a consumer relative to a baseline species. It implements a Bayesian approach which combines an interface to the 'JAGS' MCMC library of 'rjags' and stable isotopes. Users are encouraged to test the package and send bugs and/or errors to trophicposition-support@googlegroups.com.
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 6.1.1
Suggests: dplyr, knitr, rmarkdown, testthat, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-06 04:03:26 UTC; clquezada
Repository: CRAN
Date/Publication: 2019-04-06 06:00:02 UTC

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New package ggdmc with initial version 0.2.5.8
Package: ggdmc
Type: Package
Title: Cognitive Models
Version: 0.2.5.8
Date: 2019-04-06
Author: Yi-Shin Lin [aut, cre], Andrew Heathcote [aut]
Maintainer: Yi-Shin Lin <yishinlin001@gmail.com>
Description: Hierarchical Bayesian models. The package provides tools to fit two response time models, using the population-based Markov Chain Monte Carlo.
License: GPL-2
URL: https://github.com/yxlin/ggdmc
BugReports: https://github.com/yxlin/ggdmc/issues
LazyData: TRUE
Imports: Rcpp (>= 0.12.10), coda, stats, utils, ggplot2, matrixStats, data.table (>= 1.10.4)
Depends: R (>= 3.3.0)
LinkingTo: Rcpp (>= 0.12.10), RcppArmadillo (>= 0.7.100.3.0)
Suggests: testthat
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2019-04-06 02:00:12 UTC; yslin
Repository: CRAN
Date/Publication: 2019-04-06 06:00:07 UTC

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Fri, 05 Apr 2019

New package RadData with initial version 1.0.0
Package: RadData
Version: 1.0.0
Type: Package
Title: Nuclear Decay Data for Dosimetric Calculations - ICRP 107
Authors@R: c(person("Mark", "Hogue", role = c("aut", "cre"), email = "mark.hogue.chp@gmail.com"), person("KF", "Eckerman", role = c("dtc", "cph")), person("A", "Endo", role = c("dtc", "cph")))
Description: Nuclear Decay Data for Dosimetric Calculations from the International Commission on Radiological Protection from ICRP Publication 107. Ann. ICRP 38 (3). Eckerman, Keith and Endo, Akira 2008 <doi:10.1016/j.icrp.2008.10.004> <http://www.icrp.org/publication.asp?id=ICRP%20Publication%20107>. This is a database of the physical data needed in calculations of radionuclide-specific protection and operational quantities. The data is prescribed by the ICRP, the international authority on radiation dose standards, for estimating dose from the intake of or exposure to radionuclides in the workplace and the environment. The database contains information on the half-lives, decay chains, and yields and energies of radiations emitted in nuclear transformations of 1252 radionuclides of 97 elements.
License: GPL-2
Copyright: Source data from ICRP 107 copyright 2008 Eckerman and Endo. See the file license.txt file for details.
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.3.0)
Suggests: radsafer
URL: https://github.com/markhogue/RadData
BugReports: https://github.com/markhogue/RadData/issues
NeedsCompilation: no
Packaged: 2019-04-05 03:01:07 UTC; mark
Author: Mark Hogue [aut, cre], KF Eckerman [dtc, cph], A Endo [dtc, cph]
Maintainer: Mark Hogue <mark.hogue.chp@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-05 13:12:45 UTC

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New package DataSpaceR with initial version 0.6.3
Package: DataSpaceR
Type: Package
Title: Interface to 'the CAVD DataSpace'
Version: 0.6.3
Authors@R: c(person("Ju Yeong", "Kim", email = "jkim2345@fredhutch.org", role = c("aut", "cre", "cph")), person("Sean", "Hughes", comment = "Sean reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/261>", role = "rev"))
Description: Provides a convenient API interface to access immunological data within 'the CAVD DataSpace'(<https://dataspace.cavd.org>), a data sharing and discovery tool that facilitates exploration of HIV immunological data from pre-clinical and clinical HIV vaccine studies.
URL: https://github.com/ropensci/DataSpaceR
BugReports: https://github.com/ropensci/DataSpaceR/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: utils, R6, Rlabkey (>= 2.2.0), curl, httr, assertthat, digest, jsonlite, data.table
Suggests: testthat, covr, knitr, pryr
VignetteBuilder: knitr
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-04 05:03:44 UTC; jkim
Author: Ju Yeong Kim [aut, cre, cph], Sean Hughes [rev] (Sean reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/261>)
Maintainer: Ju Yeong Kim <jkim2345@fredhutch.org>
Repository: CRAN
Date/Publication: 2019-04-05 13:22:46 UTC

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New package CLONETv2 with initial version 2.0
Package: CLONETv2
Type: Package
Title: Clonality Estimates in Tumor
Version: 2.0
Authors@R: c(person("Davide", "Prandi", email = "davide.prandi@unitn.it",role = c("aut", "cre")), person("Alessandro", "Romanel", email = "alessandro.romanel@unitn.it",role = c("ctb")), person("Tarcisio", "Fedrizzi", email = "tarcisio.fedrizzi@unitn.it",role = c("ctb")))
Author: Davide Prandi [aut, cre], Alessandro Romanel [ctb], Tarcisio Fedrizzi [ctb]
Maintainer: Davide Prandi <davide.prandi@unitn.it>
Description: Analyze data from next-generation sequencing experiments on genomic samples. 'CLONETv2' offers a set of functions to compute allele specific copy number and clonality from segmented data and SNPs position pileup. The package has also calculated the clonality of single nucleotide variants given read counts at mutated positions. The package has been developed at the laboratory of Computational and Functional Oncology, Department of CIBIO, University of Trento (Italy), under the supervision of prof Francesca Demichelis. References: Prandi et al. (2014) <doi:10.1186/s13059-014-0439-6>; Carreira et al. (2014) <doi:10.1126/scitranslmed.3009448>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 3.1)
Imports: parallel, sets, ggplot2, ggrepel, arules
NeedsCompilation: no
Packaged: 2019-04-05 08:53:21 UTC; prandi
Repository: CRAN
Date/Publication: 2019-04-05 13:12:49 UTC

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New package rfVarImpOOB with initial version 1.0
Package: rfVarImpOOB
Title: Unbiased Variable Importance for Random Forests
Version: 1.0
Date: 2019-03-22
Depends: R (>= 3.2.2), stats, randomForest
Imports: ggplot2, binaryLogic, dplyr,titanic,prob,ggpubr,magrittr
Suggests: knitr,rmarkdown
Author: Markus Loecher <Markus.Loecher@gmail.com>
Maintainer: Markus Loecher <Markus.Loecher@gmail.com>
Description: Computes a novel variable importance for random forests: Impurity reduction importance scores for out-of-bag (OOB) data complementing the existing inbag Gini importance, see also Strobl et al (2007) <doi:10.1186/1471-2105-8-25>, Strobl et al (2007) <doi:10.1016/j.csda.2006.12.030> and Breiman (2001) <DOI:10.1023/A:1010933404324>. The Gini impurities for inbag and OOB data are combined in three different ways, after which the information gain is computed at each split. This gain is aggregated for each split variable in a tree and averaged across trees.
License: GPL (>= 2)
Repository: CRAN
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-05 12:30:07 UTC; loecherm
Date/Publication: 2019-04-05 12:50:06 UTC

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New package geonetwork with initial version 0.3
Package: geonetwork
Type: Package
Title: Geographic Networks
Version: 0.3
Date: 2019-03-22
Encoding: UTF-8
Authors@R: person("Facundo", "Muñoz", email = "facundo.munoz@cirad.fr", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5061-4241"))
Description: Provides classes and methods for handling networks or graphs whose nodes are geographical (i.e. locations in the globe). The functionality includes the creation of objects of class geonetwork as a graph with node coordinates, the computation of network measures, the support of spatial operations (projection to different Coordinate Reference Systems, handling of bounding boxes, etc.) and the plotting of the geonetwork object combined with supplementary cartography for spatial representation.
Depends: R (>= 3.2)
License: GPL-3 | file LICENSE
Language: en-GB
LazyData: true
Imports: geosphere, igraph, methods, rgdal, sp, sf
Suggests: devtools, ggmap, knitr, maps, mapview, rmarkdown, roxygen2, spData, testthat
RoxygenNote: 6.1.1
URL: https://github.com/Cirad-ASTRE/geonetwork
BugReports: https://github.com/Cirad-ASTRE/geonetwork/issues
NeedsCompilation: no
Packaged: 2019-04-05 12:00:46 UTC; facu
Author: Facundo Muñoz [aut, cre] (<https://orcid.org/0000-0002-5061-4241>)
Maintainer: Facundo Muñoz <facundo.munoz@cirad.fr>
Repository: CRAN
Date/Publication: 2019-04-05 12:32:45 UTC

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New package Recon with initial version 0.1.0.0
Package: Recon
Title: Computational Tools for Economics
Version: 0.1.0.0
Authors@R: c(person(given = "Pedro", family = "Cavalcante Oliveira", email = "pedrocolrj@gmail.com", role = c("aut", "cre")), person(given = "Diego", family = "S. Cardoso", email = "mail@diegoscardoso.com", role = "aut"), person(given = "Marcelo", family = "Gelati", role = "aut", email = "marcelogelati@gmail.com"))
Description: Implements solutions to canonical models of Economics such as Monopoly Profit Maximization, Cournot's Duopoly, Solow (1956, <doi:10.2307/1884513>) growth model and Mankiw, Romer and Weil (1992, <doi:10.2307/2118477>) growth model.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: rootSolve, stats
Suggests: plot3D, dplyr, ggplot2
NeedsCompilation: no
Packaged: 2019-04-04 16:41:06 UTC; pedro
Author: Pedro Cavalcante Oliveira [aut, cre], Diego S. Cardoso [aut], Marcelo Gelati [aut]
Maintainer: Pedro Cavalcante Oliveira <pedrocolrj@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-05 11:02:49 UTC

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New package geoviz with initial version 0.2.0
Package: geoviz
Type: Package
Title: Elevation and GPS Data Visualisation
Version: 0.2.0
Author: Neil Charles
Maintainer: Neil Charles <neil.d.charles@gmail.com>
Description: Simpler processing of digital elevation model and GPS trace data for use with the 'rayshader' package.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Language: en-GB
Imports: dplyr, magrittr, tidyr, readr, tibble, purrr, stringr, raster, chron, sp, sf, rgeos, glue, png, abind, rgl, slippymath, curl, progress, methods, rlang, ggplot2, rgdal
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-04 19:33:17 UTC; Neil.Charles
Repository: CRAN
Date/Publication: 2019-04-05 11:12:46 UTC

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New package cplots with initial version 0.4-0
Package: cplots
Title: Plots for Circular Data
Version: 0.4-0
Date: 2019-04-05
Author: Danli Xu <dxu452@aucklanduni.ac.nz>, Yong Wang <yongwang@auckland.ac.nz>
Maintainer: Yong Wang <yongwang@auckland.ac.nz>
Imports: circular, grDevices, graphics, stats
Description: Provides functions to produce some circular plots for circular data, in a height- or area-proportional manner. They include barplots, smooth density plots, stacked dot plots, histograms, multi-class stacked smooth density plots, and multi-class stacked histograms. The new methodology for general area-proportional circular visualization is described in an article submitted (after revision) to Journal of Computational and Graphical Statistics.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-04-05 01:41:26 UTC; yong
Repository: CRAN
Date/Publication: 2019-04-05 11:22:46 UTC

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New package argo with initial version 2.0.0
Package: argo
Type: Package
Title: Accurate Estimation of Influenza Epidemics using Google Search Data
Version: 2.0.0
Date: 2019-03-16
Author: Shaoyang Ning, Shihao Yang, S. C. Kou
Maintainer: Shihao Yang <shihaoyang@g.harvard.edu>
Description: Augmented Regression with General Online data (ARGO) for accurate estimation of influenza epidemics in United States on both national level and regional level. It replicates the method introduced in paper Yang, S., Santillana, M. and Kou, S.C. (2015) <doi:10.1073/pnas.1515373112> and Ning, S., Yang, S. and Kou, S.C. (2019) <doi:10.1038/s41598-019-41559-6>.
License: GPL-2
LazyData: TRUE
Imports: xts, glmnet, zoo, XML, xtable, Matrix, boot
Suggests: testthat
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-04 17:03:57 UTC; shihaoyang
Repository: CRAN
Date/Publication: 2019-04-05 11:02:45 UTC

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New package mnlfa with initial version 0.1-53
Package: mnlfa
Type: Package
Title: Moderated Nonlinear Factor Analysis
Version: 0.1-53
Date: 2019-04-04 18:31:54
Author: Alexander Robitzsch [aut,cre] (<https://orcid.org/0000-0002-8226-3132>)
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>
Description: Conducts moderated nonlinear factor analysis (e.g., Curran et al., 2014, <doi:10.1080/00273171.2014.889594>). Regularization methods are implemented for assessing non-invariant items. Currently, the package includes dichotomous items and unidimensional item response models. Extensions will be included in future package versions.
Depends: R (>= 3.1)
Imports: CDM (>= 7.0-4), stats, utils
LinkingTo: Rcpp, RcppArmadillo
Enhances: aMNLFA, GPCMlasso, sirt
URL: https://github.com/alexanderrobitzsch/mnlfa, https://sites.google.com/site/alexanderrobitzsch2/software
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2019-04-04 16:32:19 UTC; sunpn563
Repository: CRAN
Date/Publication: 2019-04-05 10:50:03 UTC

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New package hopit with initial version 0.9.0
Package: hopit
Type: Package
Title: Hierarchical Ordered Probit Models with Application to Reporting Heterogeneity
Version: 0.9.0
Depends: R (>= 3.4.0), survey (>= 3.35)
Imports: MASS, Rcpp, Matrix, Rdpack, graphics, stats, grDevices
LinkingTo: Rcpp, RcppEigen
Authors@R: person("Maciej J.", "Danko", role = c("aut", "cre"), email = "Maciej.Danko@gmail.com", comment = c(ORCID = "0000-0002-7924-9022"))
Description: Self-reported health, happiness, attitudes, and other statuses or perceptions are often the subject of biases that may come from different sources. For example, the evaluation of own health may depend on previous medical diagnoses, functional status, and symptoms and signs of illness, as well as life-style behaviors including contextual social, gender, age-specific, linguistic and other cultural factors (Jylha 2009 <doi:10.1016/j.socscimed.2009.05.013>; Oksuzyan et al. 2019 <doi:10.1016/j.socscimed.2019.03.002>). This package offers versatile functions for analyzing different self-reported ordinal variables and helping to estimate their biases. Specifically, the package provides the function to fit a generalized ordered probit model that regresses original self-reported status measures on two sets of independent variables (King et al. 2004 <doi:10.1017/S0003055403000881>; Jurges 2007 <doi:10.1002/hec.1134>; Oksuzyan et al. 2019 <doi:10.1016/j.socscimed.2019.03.002>). In contrast to standard ordered probit models, generalized ordered probit models relax the assumption that individuals use a common scale when rating their own statuses, and thus allow for distinguishing between the status (e.g., health) and reporting differences based on other individual characteristics. In other words, the model accounts for heterogeneity in reporting behaviors. The first set of variables (e.g., health variables) included in the regression are individual statuses and characteristics that are directly related to the self-reported variable. In case of self-reported health, these could be chronic conditions, mobility level, difficulties with daily activities, performance on grip strength tests, anthropometric measures, and lifestyle behaviors. The second set of independent variables (threshold variables) is used to model cut-points between adjacent self-reported response categories as functions of individual characteristics, such as gender, age group, education, and country (Oksuzyan et al. 2019 <doi:10.1016/j.socscimed.2019.03.002>). The model helps adjust for these specific socio-demographic and cultural differences in how the continuous latent health is projected onto the ordinal self-rated measure. The fitted model can be used to calculate an individual latent status variable that serves as a proxy of the true status. In case of self-reported health, the predicted latent health variable can be standardized to a health index, which varies from 0 representing the (model-based) worst health state to 1 representing the (model-based) best health in the sample. The standardized latent coefficients (disability weights for the case of self-rated health) provide information about the individual impact of the specific latent (e.g., health) variables on the latent (e.g., health) construct. For example, they indicate the extent to which the latent health index is reduced by the presence of Parkinson’s disease, poor mobility, and other specific health measures (Jurges 2007 <doi:10.1002/hec.1134>; Oksuzyan et al. 2019 <doi:10.1016/j.socscimed.2019.03.002>). The latent index can in turn be used to reclassify the categorical status measure that has been adjusted for inter-individual differences in reporting behavior. Two methods for doing so are available, one which uses model estimated cut-points, and a second which reclassifies responses according to the percentiles of the original categorical response distribution (Jurges 2007 <doi:10.1002/hec.1134>; Oksuzyan et al. 2019 <doi:10.1016/j.socscimed.2019.03.002>).
License: GPL-3
Encoding: UTF-8
LazyData: TRUE
RoxygenNote: 6.1.1
SystemRequirements: C++11
Suggests: knitr, rmarkdown, roxygen2, pander, testthat, usethis
VignetteBuilder: knitr
RdMacros: Rdpack
NeedsCompilation: yes
Packaged: 2019-04-04 15:08:38 UTC; maciej
Author: Maciej J. Danko [aut, cre] (<https://orcid.org/0000-0002-7924-9022>)
Maintainer: Maciej J. Danko <Maciej.Danko@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-05 10:50:07 UTC

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New package graphlayouts with initial version 0.1.0
Package: graphlayouts
Title: Additional Layout Algorithms for Network Visualizations
Version: 0.1.0
Authors@R: person("David", "Schoch", email = "david.schoch@manchester.ac.uk", role = c("aut", "cre"))
Maintainer: David Schoch <david.schoch@manchester.ac.uk>
Description: Several new layout algorithms to visualize networks are provided which are not part of 'igraph'. Most are based on the concept of stress majorization by Gansner et al. (2004) <doi:10.1007/978-3-540-31843-9_25>. Some more specific algorithms allow to emphasize hidden group structures in networks or focus on specific nodes.
URL: https://github.com/schochastics/graphlayouts
BugReports: https://github.com/schochastics/graphlayouts/issues
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: igraph, Rcpp, oaqc, gbp, scales
Suggests: testthat, ggraph, ggplot2, knitr, rmarkdown
LinkingTo: Rcpp
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-04-04 16:09:52 UTC; david
Author: David Schoch [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-05 10:50:11 UTC

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New package rankFD with initial version 0.0.2
Package: rankFD
Type: Package
Title: Rank-Based Tests for General Factorial Designs
Version: 0.0.2
Date: 2019-04-04
Author: Frank Konietschke, Sarah Friedrich, Edgar Brunner, Markus Pauly
Maintainer: Frank Konietschke <frank.konietschke@charite.de>
Depends: R (>= 3.2.2)
Description: The rankFD() function calculates the Wald-type statistic (WTS) and the ANOVA-type statistic (ATS) for nonparametric factorial designs, e.g., for count, ordinal or score data in a crossed design with an arbitrary number of factors.
License: GPL-2 | GPL-3
Imports: lattice (>= 0.20-33), MASS (>= 7.3-43), Matrix (>= 1.2-2), coin (>= 1.1-2)
LazyData: TRUE
Suggests: RGtk2 (>= 2.20.31)
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-05 08:03:09 UTC; sarah
Repository: CRAN
Date/Publication: 2019-04-05 09:40:03 UTC

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New package lconnect with initial version 0.1.0
Package: lconnect
Title: Simple Tools to Compute Landscape Connectivity Metrics
Version: 0.1.0
Authors@R: c( person("Frederico", "Mestre", email = "mestre.frederico@gmail.com", role = c("aut","cre")), person("Bruno", "Silva", email = "bmsasilva@gmail.com", role = "aut"))
Description: Provides functions to upload vectorial data and derive landscape connectivity metrics in habitat or matrix systems. Additionally, includes an approach to assess individual patch contribution to the overall landscape connectivity, enabling the prioritization of habitat patches. The computation of landscape connectivity and patch importance are very useful in Landscape Ecology research. The metrics available are: number of components, number of links, size of the largest component, mean size of components, class coincidence probability, landscape coincidence probability, characteristic path length, expected cluster size, area-weighted flux and integral index of connectivity. Pascual-Hortal, L., and Saura, S. (2006) <doi:10.1007/s10980-006-0013-z> Urban, D., and Keitt, T. (2001) <doi:10.2307/2679983> Laita, A., Kotiaho, J., Monkkonen, M. (2011) <doi:10.1007/s10980-011-9620-4>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: sf, igraph
BugReports: https://github.com/FMestre1/lconnect/issues
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-02 07:36:33 UTC; bruno
Author: Frederico Mestre [aut, cre], Bruno Silva [aut]
Maintainer: Frederico Mestre <mestre.frederico@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-05 09:30:03 UTC

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Thu, 04 Apr 2019

New package genpwr with initial version 1.0.0
Package: genpwr
Title: Power Calculations Under Genetic Model Misspecification
Version: 1.0.0
Authors@R: c(person("Camille", "Moore", email = "moorec@njhealth.org", role = c("aut", "cre")), person("Sean", "Jacobson", email = "jacobsons@njhealth.org", role = "aut"))
Description: Power and sample size calculations for genetic association studies allowing for misspecification of the model of genetic susceptibility. Power and/or sample size can be calculated for logistic (case/control study design) and linear (continuous phenotype) regression models, using additive, dominant, recessive or degree of freedom coding of the genetic covariate while assuming a true dominant, recessive or additive genetic effect. In addition, power and sample size calculations can be performed for gene by environment interactions. These methods are extensions of Gauderman (2002) <doi:10.1093/aje/155.5.478> and Gauderman (2002) <doi:10.1002/sim.973> and are described in: Moore CM, Jacobson S, Fingerlin TE. Power and Sample Size Calculations for Genetic Association Studies in the Presence of Genetic Model Misspecification. American Society of Human Genetics. October 2018, San Diego. Poster Presentation: <http://www.ashg.org/2018meeting/listing/PosterSessions.shtml>.
Depends: R (>= 3.5.0)
License: GPL-3
Imports: ggplot2, nleqslv, MASS, stats, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-03 17:10:19 UTC; Sean
Author: Camille Moore [aut, cre], Sean Jacobson [aut]
Maintainer: Camille Moore <moorec@njhealth.org>
Repository: CRAN
Date/Publication: 2019-04-04 17:40:03 UTC

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New package saotd with initial version 0.2.0
Package: saotd
Type: Package
Title: Sentiment Analysis of Twitter Data
Version: 0.2.0
Date: 2019-04-02
Authors@R: c( person("Evan", "Munson", email = "evan.l.munson@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-9958-6800")), person("Christopher", "Smith", email = "Cms3am@virginia.edu", role = c("aut"), comment = c(ORCID = "0000-0002-8288-270X")), person("Bradley", "Boehmke", email = "bradleyboehmke@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0002-3611-8516")), person("Jason", "Freels", email = "auburngrads@live.com", role = c("aut"), comment = c(ORCID = "0000-0002-2415-0340")) )
Maintainer: Evan Munson <evan.l.munson@gmail.com>
BugReports: https://github.com/evan-l-munson/saotd/issues
Description: This analytic is an in initial foray into sentiment analysis. This analytic will allow a user to access the Twitter API (once they create their own developer account), ingest tweets of their interest, clean / tidy data, perform topic modeling if interested, compute sentiment scores utilizing the x bing Lexicon, and output visualizations.
License: GPL (>= 2)
Imports: plyr, dplyr, widyr, stringr, tidytext, twitteR, purrr, tidyr, igraph, maps, ggplot2, ggraph, scales, reshape2, lubridate, utils, stats, magrittr, ldatuning, topicmodels
RoxygenNote: 6.1.1
Suggests: testthat, knitr, rmarkdown, httr, base64enc
Depends: R (>= 3.3.0)
VignetteBuilder: knitr
SystemRequirements: GSL (>=2.4), MPFR (>= 4.0.0), udunits2 (>=2.2.26-3)
Encoding: UTF-8
LazyLoad: true
NeedsCompilation: no
Packaged: 2019-04-03 02:50:23 UTC; eklm
Author: Evan Munson [aut, cre] (<https://orcid.org/0000-0002-9958-6800>), Christopher Smith [aut] (<https://orcid.org/0000-0002-8288-270X>), Bradley Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Jason Freels [aut] (<https://orcid.org/0000-0002-2415-0340>)
Repository: CRAN
Date/Publication: 2019-04-04 16:30:03 UTC

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New package llbayesireg with initial version 1.0.0
Package: llbayesireg
Title: The L-Logistic Bayesian Regression
Version: 1.0.0
Date: 2019-03-06
Authors@R: c(person("Sara", "Alexandre Fonsêca", role = "aut", email = "saralexandre@alu.ufc.br"), person("Rosineide", "Fernando da Paz", role = c("aut", "cre"), email = "rfpaz2@gmail.com"), person("Jorge Luís", "Bazán", role = "ctb"))
Author: Sara Alexandre Fonsêca [aut], Rosineide Fernando da Paz [aut, cre], Jorge Luís Bazán [ctb]
Maintainer: Rosineide Fernando da Paz <rfpaz2@gmail.com>
Description: R functions and data sets for the work Paz, R.F., Balakrishnan, N and Bazán, J.L. (2018). L-logistic regression models: Prior sensitivity analysis, robustness to outliers and applications. Brazilian Journal of Probability and Statistics, <https://www.imstat.org/wp-content/uploads/2018/05/BJPS397.pdf>.
Imports: llogistic, rstan, MCMCpack, MASS, coda, stats
Depends: R (>= 3.4.0), ggplot2 (>= 2.0.0), StanHeaders (>= 2.18.0), Rcpp (>= 0.12.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-02 22:08:18 UTC; Sara
Repository: CRAN
Date/Publication: 2019-04-04 16:20:03 UTC

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New package hydra with initial version 0.1.0
Package: hydra
Type: Package
Title: Hyperbolic Embedding
Version: 0.1.0
Author: Martin Keller-Ressel
Maintainer: Martin Keller-Ressel <martin.keller-ressel@tu-dresden.de>
Description: Calculate an optimal embedding of a set of data points into low-dimensional hyperbolic space. This uses the strain-minimizing hyperbolic embedding of Keller-Ressel and Nargang (2019), see <arXiv:1903.08977>.
Suggests: igraph, igraphdata, Matrix, RSpectra
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-01 14:55:36 UTC; mkeller
Repository: CRAN
Date/Publication: 2019-04-04 16:10:07 UTC

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New package hglm with initial version 2.2-1
Package: hglm
Type: Package
Title: Hierarchical Generalized Linear Models
Version: 2.2-1
Date: 2019-04-04
Author: Moudud Alam, Lars Ronnegard, Xia Shen
Maintainer: Xia Shen <xia.shen@ki.se>
Description: Implemented here are procedures for fitting hierarchical generalized linear models (HGLM). It can be used for linear mixed models and generalized linear mixed models with random effects for a variety of links and a variety of distributions for both the outcomes and the random effects. Fixed effects can also be fitted in the dispersion part of the mean model. As statistical models, HGLMs were initially developed by Lee and Nelder (1996) <https://www.jstor.org/stable/2346105?seq=1>. We provide an implementation (Ronnegard, Alam and Shen 2010) <https://journal.r-project.org/archive/2010-2/RJournal_2010-2_Roennegaard~et~al.pdf> following Lee, Nelder and Pawitan (2006) <ISBN: 9781420011340> with algorithms extended for spatial modeling (Alam, Ronnegard and Shen 2015) <https://journal.r-project.org/archive/2015/RJ-2015-017/RJ-2015-017.pdf>.
BugReports: https://r-forge.r-project.org/tracker/?group_id=558
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 3.0), utils, Matrix, MASS, hglm.data
Packaged: 2019-04-04 15:36:54 UTC; xia
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-04 16:20:07 UTC

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New package dynparam with initial version 1.0.0
Package: dynparam
Type: Package
Title: Creating Meta-Information for Parameters
Version: 1.0.0
Authors@R: c( person( "Robrecht", "Cannoodt", email = "rcannood@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-3641-729X", github = "rcannood") ), person( "Wouter", "Saelens", email = "wouter.saelens@ugent.be", role = c("aut"), comment = c(ORCID = "0000-0002-7114-6248", github = "zouter") ) )
URL: https://github.com/dynverse/dynparam
BugReports: https://github.com/dynverse/dynparam/issues
Description: Provides tools for describing parameters of algorithms in an abstract way. Description can include an id, a description, a domain (range or list of values), and a default value. 'dynparam' can also convert parameter sets to a 'ParamHelpers' format, in order to be able to use 'dynparam' in conjunction with 'mlrMBO'.
License: GPL-3
LazyData: TRUE
RoxygenNote: 6.1.1
Encoding: UTF-8
Depends: R (>= 3.0.0)
Imports: assertthat, carrier, dplyr, dynutils (>= 1.0.2), Hmisc, magrittr, purrr, stringr, testthat, tibble, tidyr
Suggests: ParamHelpers, lhs
NeedsCompilation: no
Packaged: 2019-04-02 11:22:16 UTC; rcannood
Author: Robrecht Cannoodt [aut, cre] (<https://orcid.org/0000-0003-3641-729X>, rcannood), Wouter Saelens [aut] (<https://orcid.org/0000-0002-7114-6248>, zouter)
Maintainer: Robrecht Cannoodt <rcannood@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-04 16:10:10 UTC

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New package changedetection with initial version 0.1.0
Package: changedetection
Type: Package
Title: Nonparametric Change Detection in Multivariate Linear Relationships
Version: 0.1.0
Date: 2019-03-11
Author: Olga Gorskikh, Pekka Malo, Pauliina Ilmonen, Lauri Viitasaari, Joni Virta
Maintainer: Olga Gorskikh <olga.a.gorskikh@gmail.com>
Description: Contains implementation of the Nonparametric Splitting Algorithm (NSA), which estimates a set of structural change points (change dates) within a multivariate time-wise linear regression. Additionally, it contains utility functions to estimate corresponding changing linear model, moving energy distance and a change-detection test. For more information, see Malo et. al (2019) <arXiv:1805.08512>.
Encoding: UTF-8
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Imports: Rdpack, L1pack, glmnet
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2019-04-03 11:38:50 UTC; Olga
Repository: CRAN
Date/Publication: 2019-04-04 16:40:07 UTC

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New package sleepwalk with initial version 0.1.0
Package: sleepwalk
Type: Package
Title: Interactively Explore Dimension-Reduced Embeddings
Version: 0.1.0
Date: 2019-04-01
Authors@R: c( person( "Svetlana", "Ovchinnikova", role=c("aut","cre"), email = "s.ovchinnikova@zmbh.uni-heidelberg.de" ), person( "Simon", "Anders", role="aut", email = "sanders@fs.tum.de" ) )
Description: A tool to interactively explore the embeddings created by dimension reduction methods such as Principal Components Analysis (PCA), Multidimensional Scaling (MDS), T-distributed Stochastic Neighbour Embedding (t-SNE), Uniform Manifold Approximation and Projection (UMAP) or any other.
License: GPL-3
Imports: jrc, cowplot, httpuv, jsonlite, scales, ggplot2
RoxygenNote: 6.1.1
URL: https://anders-biostat.github.io/sleepwalk/
BugReports: https://github.com/anders-biostat/sleepwalk/issues
NeedsCompilation: no
Packaged: 2019-04-03 14:34:55 UTC; tyranchik
Author: Svetlana Ovchinnikova [aut, cre], Simon Anders [aut]
Maintainer: Svetlana Ovchinnikova <s.ovchinnikova@zmbh.uni-heidelberg.de>
Repository: CRAN
Date/Publication: 2019-04-04 15:10:03 UTC

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New package radsafer with initial version 1.0.0
Package: radsafer
Type: Package
Title: Radiation Safety
Version: 1.0.0
Author: Mark Hogue <mark.hogue.chp@gmail.com>
Maintainer: Mark Hogue <mark.hogue.chp@gmail.com>
Description: Provides functions for radiation safety, also known as "radiation protection" and "radiological control". The science of radiation protection is called "health physics" and its engineering functions are called "radiological engineering". Functions in this package cover many of the computations needed by radiation safety professionals. Examples include: obtaining updated calibration and source check values for radiation monitors to account for radioactive decay in a reference source, simulating instrument readings to better understand measurement uncertainty, correcting instrument readings for geometry and ambient atmospheric conditions. Many of these functions are described in Johnson and Kirby (2011, ISBN-13: 978-1609134198). Utilities are also included for developing inputs and processing outputs with radiation transport codes, such as MCNP, a general-purpose Monte Carlo N-Particle code that can be used for neutron, photon, electron, or coupled neutron/photon/electron transport (Werner et. al. (2018) <doi:10.2172/1419730>).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, tidyverse, scatterplot3d, dplyr
Imports: ggplot2, readr, stats, graphics
Depends: R (>= 3.3)
URL: https://github.com/markhogue/radsafer
BugReports: https://github.com/markhogue/radsafer/issues
NeedsCompilation: no
Packaged: 2019-04-02 02:20:17 UTC; mark
Repository: CRAN
Date/Publication: 2019-04-04 15:50:03 UTC

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New package flagr with initial version 0.3.2
Package: flagr
Type: Package
Title: Implementation of Flag Aggregation
Version: 0.3.2
Date: 2019-04-02
Authors@R: c(person("Mátyás", "Mészáros", email = "matyas.meszaros@ec.europa.eu", role = c("aut", "cre")), person("Matteo", "Salvati", email = "salvati.matteo@hotmail.fr", role = "aut"))
Description: Three methods are implemented in R to facilitate the aggregations of flags in official statistics. From the underlying flags the highest in the hierarchy, the most frequent, or with the highest total weight is propagated to the flag(s) for EU or other aggregates. Below there are some reference documents for the topic: <https://sdmx.org/wp-content/uploads/CL_OBS_STATUS_v2_1.docx>, <https://sdmx.org/wp-content/uploads/CL_CONF_STATUS_1_2_2018.docx>, <http://ec.europa.eu/eurostat/data/database/information>, <http://www.oecd.org/sdd/33869551.pdf>, <https://sdmx.org/wp-content/uploads/CL_OBS_STATUS_implementation_20-10-2014.pdf>.
License: EUPL-1.1
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: tidyr, eurostat, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-02 08:47:10 UTC; meszama
Author: Mátyás Mészáros [aut, cre], Matteo Salvati [aut]
Maintainer: Mátyás Mészáros <matyas.meszaros@ec.europa.eu>
Repository: CRAN
Date/Publication: 2019-04-04 16:00:02 UTC

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New package CRFCSD with initial version 1.0
Package: CRFCSD
Type: Package
Title: Mixture Cure Generalized Odds Ratio Frailty Models for Clustered Current Status Data
Version: 1.0
Date: 2019-03-24
Author: Tong Wang, Kejun He, Wei Ma, Dipankar Bandyopadhyay, Samiran Sinha
Maintainer: Tong Wang<tong@stat.tamu.edu>
Description: A methodology to estimate the parameters for the cure rate frailty models with clustered current status data.
License: GPL-2
Encoding: UTF-8
Imports: Rcpp (>= 0.12.18), numDeriv, splines2, orthopolynom
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-01 19:53:05 UTC; tong
Repository: CRAN
Date/Publication: 2019-04-04 15:40:14 UTC

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New package chartql with initial version 0.1.0
Package: chartql
Type: Package
Title: Simplified Language for Plots and Charts
Version: 0.1.0
Imports: ggplot2 (>= 2.1.0), stringr, stats
Maintainer: Rohail Syed <rohailsyed@gmail.com>
Authors@R: person("Rohail", "Syed", email = "rohailsyed@gmail.com", role = c("aut", "cre"))
Description: Provides a very simple syntax for the user to generate custom plot(s) without having to remember complicated 'ggplot2' syntax. The 'chartql' package uses 'ggplot2' and manages all the syntax complexities internally. As an example, to generate a bar chart of company sales faceted by product category further faceted by season of the year, we simply write: "CHART bar X category, season Y sales".
License: GPL-3
Encoding: UTF-8
URL: https://github.com/rmsyed/chartql
LazyData: true
NeedsCompilation: no
Packaged: 2019-04-01 18:46:44 UTC; rohailsyed
Author: Rohail Syed [aut, cre]
Repository: CRAN
Date/Publication: 2019-04-04 15:40:03 UTC

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New package CeRNASeek with initial version 1.0
Package: CeRNASeek
Type: Package
Title: Identification and Analysis of ceRNA Regulation
Version: 1.0
Date: 2019-03-28
Author: Mengying Zhang,Yongsheng Li,Juan Xu*,Xia Li*
Maintainer: Mengying Zhang <zhangmengying@hrbmu.edu.cn>
Description: Provides several functions to identify and analyse miRNA sponge, including popular methods for identifying miRNA sponge interactions, two types of global ceRNA regulation prediction methods and three types of context-specific prediction methods( Li Y et al.(2017) <doi:10.1093/bib/bbx137>), which are based on miRNA-messenger RNA regulation alone, or by integrating heterogeneous data, respectively. In addition, this package provides several network analysis modules for viewing the constructed ceRNA-ceRNA network and analysis of the topological features.
License: GPL-3
Encoding: UTF-8
LazyData: true
biocViews: competing endogenous RNA (ceRNA), GeneExpression,triplet,function,Software
Depends: R (>= 3.1.0)
Imports: gtools ,igraph
Packaged: 2019-04-02 00:49:23 UTC; dell
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-04 15:50:07 UTC

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New package armspp with initial version 0.0.1
Package: armspp
Title: Adaptive Rejection Metropolis Sampling (ARMS) via 'Rcpp'
Version: 0.0.1
Authors@R: person("Michael", "Bertolacci", email = "m.bertolacci@gmail.com", role = c("aut", "cre"))
Description: An efficient 'Rcpp' implementation of the Adaptive Rejection Metropolis Sampling (ARMS) algorithm proposed by Gilks, W. R., Best, N. G. and Tan, K. K. C. (1995) <doi:10.2307/2986138>. This allows for sampling from a univariate target probability distribution specified by its (potentially unnormalised) log density.
Depends: R (>= 3.2.3)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, progress
Imports: Rcpp, progress
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, covr, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-04-01 08:09:23 UTC; mgnb
Author: Michael Bertolacci [aut, cre]
Maintainer: Michael Bertolacci <m.bertolacci@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-04 15:40:10 UTC

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New package armada with initial version 0.1.0
Package: armada
Type: Package
Title: A Statistical Methodology to Select Covariates in High-Dimensional Data under Dependence
Version: 0.1.0
Authors@R: c(person("Aurelie", "Gueudin", email = "aurelie.gueudin@univ-lorraine.fr", role = c("aut", "cre")), person("Anne", "Gegout-Petit", email = "anne.gegout-petit@univ-lorraine.fr", role = c("aut")))
Description: Two steps variable selection procedure in a context of high-dimensional dependent data but few observations. First step is dedicated to eliminate dependence between variables (clustering of variables, followed by factor analysis inside each cluster). Second step is a variable selection using by aggregation of adapted methods. Bastien B., Chakir H., Gegout-Petit A., Muller-Gueudin A., Shi Y. A statistical methodology to select covariates in high-dimensional data under dependence. Application to the classification of genetic profiles associated with outcome of a non-small-cell lung cancer treatment. 2018. <https://hal.archives-ouvertes.fr/hal-01939694>.
License: GPL-3
LazyData: true
RoxygenNote: 6.1.1
Imports: stats, mvtnorm, ClustOfVar, FAMT, graphics, VSURF, glmnet, anapuce, qvalue, parallel, doParallel, impute, ComplexHeatmap, circlize
NeedsCompilation: no
Packaged: 2019-04-04 13:14:39 UTC; muller16
Author: Aurelie Gueudin [aut, cre], Anne Gegout-Petit [aut]
Maintainer: Aurelie Gueudin <aurelie.gueudin@univ-lorraine.fr>
Repository: CRAN
Date/Publication: 2019-04-04 16:00:06 UTC

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New package SparkR with initial version 2.4.1
Package: SparkR
Type: Package
Version: 2.4.1
Title: R Front End for 'Apache Spark'
Description: Provides an R Front end for 'Apache Spark' <https://spark.apache.org>.
Authors@R: c(person("Shivaram", "Venkataraman", role = c("aut", "cre"), email = "shivaram@cs.berkeley.edu"), person("Xiangrui", "Meng", role = "aut", email = "meng@databricks.com"), person("Felix", "Cheung", role = "aut", email = "felixcheung@apache.org"), person(family = "The Apache Software Foundation", role = c("aut", "cph")))
License: Apache License (== 2.0)
URL: https://www.apache.org/ https://spark.apache.org/
BugReports: https://spark.apache.org/contributing.html
SystemRequirements: Java (== 8)
Depends: R (>= 3.0), methods
Suggests: knitr, rmarkdown, testthat, e1071, survival
Collate: 'schema.R' 'generics.R' 'jobj.R' 'column.R' 'group.R' 'RDD.R' 'pairRDD.R' 'DataFrame.R' 'SQLContext.R' 'WindowSpec.R' 'backend.R' 'broadcast.R' 'catalog.R' 'client.R' 'context.R' 'deserialize.R' 'functions.R' 'install.R' 'jvm.R' 'mllib_classification.R' 'mllib_clustering.R' 'mllib_fpm.R' 'mllib_recommendation.R' 'mllib_regression.R' 'mllib_stat.R' 'mllib_tree.R' 'mllib_utils.R' 'serialize.R' 'sparkR.R' 'stats.R' 'streaming.R' 'types.R' 'utils.R' 'window.R'
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-04 12:39:14 UTC; ligges
Author: Shivaram Venkataraman [aut, cre], Xiangrui Meng [aut], Felix Cheung [aut], The Apache Software Foundation [aut, cph]
Maintainer: Shivaram Venkataraman <shivaram@cs.berkeley.edu>
Repository: CRAN
Date/Publication: 2019-04-04 12:50:05 UTC

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New package RBesT with initial version 1.3-8
Package: RBesT
Type: Package
Title: R Bayesian Evidence Synthesis Tools
Description: Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> for details on the methodology.
Version: 1.3-8
Date: 2019-04-03
Authors@R: c(person("Novartis", "Pharma AG", role = "cph") ,person("Sebastian", "Weber", email="sebastian.weber@novartis.com", role=c("aut", "cre")) ,person("Beat", "Neuenschwander", email="beat.neuenschwander@novartis.com", role="ctb") ,person("Heinz", "Schmidli", email="heinz.schmidli@novartis.com", role="ctb") ,person("Baldur", "Magnusson", email="baldur.magnusson@novartis.com", role="ctb") ,person("Yue", "Li", email="yue-1.li@novartis.com", role="ctb") ,person("Satrajit", "Roychoudhury", email="satrajit.roychoudhury@novartis.com", role="ctb") ,person("Trustees of", "Columbia University", role="cph", comment="src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win") )
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0), methods
Imports: assertthat, mvtnorm, Formula, checkmate, rstan (>= 2.18.1), bayesplot (>= 1.4.0), ggplot2, dplyr, stats, utils
LinkingTo: StanHeaders (>= 2.18.0), rstan (>= 2.18.1), BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0)
License: GPL (>= 3) | file LICENSE
LazyData: true
NeedsCompilation: yes
Suggests: rmarkdown, knitr, testthat (>= 2.0.0), foreach, tidyverse, purrr, rstanarm (>= 2.17.2), scales, tools, broom, tidyr
VignetteBuilder: knitr
SystemRequirements: GNU make, pandoc (>= 1.12.3), pandoc-citeproc
Encoding: UTF-8
RoxygenNote: 6.1.1
Packaged: 2019-04-04 07:48:14 UTC;
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Trustees of Columbia University [cph] (src/init.cpp, tools/make_cc.R, R/stanmodels.R, src/Makevars, src/Makevars.win)
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>
Repository: CRAN
Date/Publication: 2019-04-04 12:10:10 UTC

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New package muRty with initial version 0.1.2
Package: muRty
Type: Package
Title: Murty's Algorithm for k-Best Assignments
Version: 0.1.2
Author: Aljaz Jelenko <aljaz.jelenko@amis.net>
Maintainer: Aljaz Jelenko <aljaz.jelenko@amis.net>
BugReports: https://github.com/arg0naut91/muRty/issues
Description: Calculates k-best solutions and costs for an assignment problem following the method outlined in Murty (1968) <doi:10.1287/opre.16.3.682>.
URL: https://github.com/arg0naut91/muRty
License: MIT + file LICENSE
Depends: R (>= 3.1.0)
Imports: lpSolve
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-03 08:49:59 UTC; Aljaz
Repository: CRAN
Date/Publication: 2019-04-04 12:50:03 UTC

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New package iBreakDown with initial version 0.9.5
Package: iBreakDown
Title: Model Agnostic Instance Level Variable Attributions
Version: 0.9.5
Authors@R: c(person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut", "cre")), person("Alicja", "Gosiewska", email = "alicjagosiewska@gmail.com", role = c("aut")), person("Dariusz", "Komosinski", role = c("ctb")))
Description: Model agnostic tool for decomposition of predictions from black boxes. Supports additive attributions and attributions with interactions. The Break Down Table shows contributions of every variable to a final prediction. The Break Down Plot presents variable contributions in a concise graphical way. This package works for classification and regression models. It is an extension of the 'breakDown' package (Staniak and Biecek 2018) <doi:10.32614/RJ-2018-072>, with new and faster strategies for orderings. It supports interactions in explanations and has interactive visuals (implemented with 'D3.js' library). The methodology behind is described in the 'iBreakDown' article (Gosiewska and Biecek 2019) <arXiv:1903.11420> This package is a part of the 'DrWhy.AI' universe (Biecek 2018) <arXiv:1806.08915>.
Depends: R (>= 3.0)
Date: 2019-04-01
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: ggplot2, DALEX
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown, caret, randomForest, e1071, xgboost, ranger, nnet, testthat, r2d3
VignetteBuilder: knitr
URL: https://ModelOriented.github.io/iBreakDown/
BugReports: https://github.com/ModelOriented/iBreakDown/issues
NeedsCompilation: no
Packaged: 2019-04-01 20:19:10 UTC; pbiecek
Author: Przemyslaw Biecek [aut, cre], Alicja Gosiewska [aut], Dariusz Komosinski [ctb]
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-04 12:20:03 UTC

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New package glmdisc with initial version 0.1
Package: glmdisc
Type: Package
Title: Discretization and Grouping for Logistic Regression
Version: 0.1
Date: 2019-04-01
Authors@R: c(person("Adrien", "Ehrhardt", email = "adrien.ehrhardt@inria.fr", role = c("aut", "cre")), person("Vincent", "Vandewalle", email = "vincent.vandewalle@inria.fr", role = c("aut")), person("Christophe", "Biernacki", email = "christophe.biernacki@inria.fr", role = c("ctb")), person("Philippe", "Heinrich", email = "philippe.heinrich@univ-lille1.fr", role = c("ctb")))
Maintainer: Adrien Ehrhardt <adrien.ehrhardt@inria.fr>
Description: A Stochastic-Expectation-Maximization (SEM) algorithm (Celeux et al. (1995) <https://hal.inria.fr/inria-00074164>) associated with a Gibbs sampler which purpose is to learn a constrained representation for logistic regression that is called quantization (Ehrhardt et al. (2019) <arXiv:1903.08920>). Continuous features are discretized and categorical features' values are grouped to produce a better logistic regression model. Pairwise interactions between quantized features are dynamically added to the model through a Metropolis-Hastings algorithm (Hastings, W. K. (1970) <doi:10.1093/biomet/57.1.97>).
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: caret (>= 6.0-82), gam, nnet, RcppNumerical, methods, MASS, graphics, Rcpp (>= 0.12.13)
LinkingTo: Rcpp, RcppEigen, RcppNumerical
URL: https://adimajo.github.io
BugReports: https://github.com/adimajo/glmdisc/issues
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Collate: 'RcppExports.R' 'allClasses.R' 'cut.dataset.R' 'discretize.link.R' 'generic_cutpoints.R' 'generic_discretize.R' 'glmdisc.R' 'method_cutpoints.R' 'method_discretize.R' 'method_plot.R' 'method_predict.R' 'methods_disc.R' 'normalizedGini.R' 'semDiscretization.R'
NeedsCompilation: yes
Packaged: 2019-04-01 20:18:50 UTC; adrien
Author: Adrien Ehrhardt [aut, cre], Vincent Vandewalle [aut], Christophe Biernacki [ctb], Philippe Heinrich [ctb]
Repository: CRAN
Date/Publication: 2019-04-04 12:10:03 UTC

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New package fhidata with initial version 2019.4.2
Package: fhidata
Title: Structural Data for Norway
Version: 2019.4.2
Authors@R: person("Richard", "White", email = "w@rwhite.no", role = c("aut", "cre"))
Description: Provides structural data for Norway. Datasets relating to maps, population in municipalities, municipality/county matching, and how different municipalities have merged/redistricted over time from 2006 to 2019.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: data.table
Suggests: testthat, knitr, rmarkdown, geojsonio, broom, rmapshaper, rgeos, mapproj, ggplot2, stringr, glue, lubridate, readxl, zoo, crayon, fs, utils
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-02 14:39:19 UTC; rstudio
Author: Richard White [aut, cre]
Maintainer: Richard White <w@rwhite.no>
Repository: CRAN
Date/Publication: 2019-04-04 10:10:03 UTC

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New package hglm.data with initial version 1.0-1
Package: hglm.data
Type: Package
Title: Data for the 'hglm' Package
Version: 1.0-1
Date: 2019-03-03
Author: Xia Shen, Moudud Alam, Lars Ronnegard
Maintainer: Xia Shen <xia.shen@ki.se>
Description: This data-only package was created for distributing data used in the examples of the 'hglm' package.
BugReports: https://r-forge.r-project.org/tracker/?group_id=558
License: GPL (>= 2)
LazyLoad: yes
Depends: R (>= 3.0), utils, Matrix, MASS, sp
Packaged: 2019-04-03 12:09:31 UTC; xia
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-04-04 09:20:03 UTC

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New package ebirdst with initial version 0.1.0
Type: Package
Package: ebirdst
Title: Access and Analyze eBird Status and Trends Data
Version: 0.1.0
Authors@R: c(person(given = "Tom", family = "Auer", role = c("aut", "cre"), email = "mta45@cornell.edu", comment = c(ORCID = "0000-0001-8619-7147")), person(given = "Daniel", family = "Fink", role = "aut", email = "df36@cornell.edu", comment = c(ORCID = "0000-0002-8368-1248")), person(given = "Matthew", family = "Strimas-Mackey", role = "aut", email = "mes335@cornell.edu", comment = c(ORCID = "0000-0001-8929-7776")), person(given = "Cornell Lab of Ornithology", role = "cph"))
Description: Tools to download, map, plot and analyze eBird Status and Trends data (<https://ebird.org/science/status-and-trends>). eBird (<https://ebird.org>) is a global database of bird observations collected by citizen scientists. eBird Status and Trends uses these data to analyse continental bird abundances, range boundaries, habitats, and trends.
License: GPL-3
URL: https://github.com/CornellLabofOrnithology/ebirdst
BugReports: https://github.com/CornellLabofOrnithology/ebirdst/issues
Depends: R (>= 3.3.0)
Imports: car, data.table, dplyr (>= 0.7.0), fasterize, gbm (>= 2.1.5), ggplot2, grDevices, gridExtra, methods, mgcv, PresenceAbsence, rappdirs, raster, scales, sf, stats, stringr, tidyr, tools, utils, viridisLite, xml2, rgdal
Suggests: covr, fields, knitr, rmarkdown, rnaturalearth, smoothr, testthat, velox
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-04-02 20:43:32 UTC; mes335
Author: Tom Auer [aut, cre] (<https://orcid.org/0000-0001-8619-7147>), Daniel Fink [aut] (<https://orcid.org/0000-0002-8368-1248>), Matthew Strimas-Mackey [aut] (<https://orcid.org/0000-0001-8929-7776>), Cornell Lab of Ornithology [cph]
Maintainer: Tom Auer <mta45@cornell.edu>
Repository: CRAN
Date/Publication: 2019-04-04 09:50:03 UTC

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Tue, 02 Apr 2019

New package MetaSKAT with initial version 0.71
Package: MetaSKAT
Type: Package
Title: Meta Analysis for SNP-Set (Sequence) Kernel Association Test
Version: 0.71
Date: 2019-04-02
Author: Seunggeun (Shawn) Lee
Maintainer: Seunggeun (Shawn) Lee <leeshawn@umich.edu>
Description: Functions for Meta-analysis Burden test, SKAT and SKAT-O by Lee et al. (2013) <doi: 10.1016/j.ajhg.2013.05.010>. These methods use summary-level score statistics to carry out gene-based meta-analysis for rare variants.
License: GPL (>= 2)
SystemRequirements: Little Endian
Depends: R (>= 2.13.0)
Imports: SKAT
NeedsCompilation: yes
Packaged: 2019-04-02 17:54:20 UTC; lee7801
Repository: CRAN
Date/Publication: 2019-04-02 22:00:41 UTC

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New package ukpolice with initial version 0.1.2
Package: ukpolice
Title: Download Data on UK Police and Crime
Version: 0.1.2
Authors@R: person(given = "Evan", family = "Odell", role = c("aut", "cre"), email = "evanodell91@gmail.com", comment = c(ORCID = "0000-0003-1845-808X"))
Description: Downloads data from the 'UK Police' public data API, the full docs of which are available at <https://data.police.uk/docs/>. Includes data on police forces and police force areas, crime reports, and the use of stop-and-search powers.
URL: https://github.com/EvanOdell/ukpolice/, https://docs.evanodell.com/ukpolice
BugReports: https://github.com/EvanOdell/ukpolice/issues
License: MIT + file LICENSE
Imports: jsonlite, tibble, purrr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, covr, knitr, rmarkdown, ggplot2, dplyr, leaflet, htmltools, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-01 17:44:38 UTC; evanodell
Author: Evan Odell [aut, cre] (<https://orcid.org/0000-0003-1845-808X>)
Maintainer: Evan Odell <evanodell91@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-02 16:00:03 UTC

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New package tsdb with initial version 0.6-2
Package: tsdb
Type: Package
Title: Terribly-Simple Data Base for Time Series
Version: 0.6-2
Date: 2019-03-31
Maintainer: Enrico Schumann <es@enricoschumann.net>
Authors@R: person(given = "Enrico", family = "Schumann", role = c("aut", "cre"), email = "es@enricoschumann.net", comment = c(ORCID = "0000-0001-7601-6576"))
Description: A terribly-simple data base for numeric time series, written purely in R, so no external database-software is needed. Series are stored in plain-text files (the most-portable and enduring file type) in CSV format. Timestamps are encoded using R's native numeric representation for 'Date'/'POSIXct', which makes them fast to parse, but keeps them accessible with other software. The package provides tools for saving and updating series in this standardised format, for retrieving and joining data, for summarising files and directories, and for coercing series from and to other data types (such as 'zoo' series).
License: GPL-3
Imports: datetimeutils, fastmatch, utils, zoo
Suggests: DBI, MonetDBLite, data.table
URL: http://enricoschumann.net/R/packages/tsdb, https://github.com/enricoschumann/tsdb, https://gitlab.com/enricoschumann/tsdb
NeedsCompilation: no
Packaged: 2019-03-31 19:14:22 UTC; es19
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Repository: CRAN
Date/Publication: 2019-04-02 15:40:02 UTC

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New package SCBiclust with initial version 1.0.0
Package: SCBiclust
Title: Identifies Mean, Variance, and Hierarchically Clustered Biclusters
Version: 1.0.0
Date: 2019-03-27
Author: Erika S. Helgeson, Qian Liu, Guanhua Chen, Michael R. Kosorok , and Eric Bair
Maintainer: Erika S. Helgeson <helge@umn.edu>
Description: Identifies a bicluster, a submatrix of the data such that the features and observations within the submatrix differ from those not contained in submatrix, using a two-step method. In the first step, observations in the bicluster are identified to maximize the sum of weighted between cluster feature differences. The observations are identified in a similar fashion as in Witten and Tibshirani (2010) <doi:10.1198/jasa.2010.tm09415> except with a modified objective function and no feature sparsity constraint. In the second step, features in the bicluster are identified based on their contribution to the clustering of the observations. The cluster significance test of Liu, Hayes, Nobel, and Marron (2008): <doi:10.1198/016214508000000454> can then be used to test the strength of the identified bicluster. 'SCBiclust' can be used to identify biclusters which differ based on feature means, feature variances, or more general differences.
Depends: R (>= 3.4.0)
Imports: sparcl, sigclust
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2019-04-01 16:51:45 UTC; eshel
Repository: CRAN
Date/Publication: 2019-04-02 15:50:07 UTC

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New package ptsuite with initial version 1.0.0
Package: ptsuite
Title: Tail Index Estimation for Power Law Distributions
Version: 1.0.0
Authors@R: c(person("Ranjiva", "Munasinghe", email = "ranjiva@mindlanka.org", role = "aut"), person("Pathum", "Kossinna", email = "pathum@mindlanka.org", role = c("cre", "aut")), person("Dovini", "Jayasinghe", email = "dovini@mindlanka.org", role = "aut"), person("Dilanka", "Wijeratne", email = "dilanka@mindlanka.org", role = "aut"))
Description: Various estimation methods for the shape parameter of Pareto distributed data. This package contains functions for various estimation methods such as maximum likelihood (Newman, 2005)<doi:10.1016/j.cities.2012.03.001>, Hill's estimator (Hill, 1975)<doi:10.1214/aos/1176343247>, least squares (Zaher et al., 2014)<doi:10.9734/BJMCS/2014/10890>, method of moments (Rytgaard, 1990)<doi:10.2143/AST.20.2.2005443>, percentiles (Bhatti et al., 2018)<doi:10.1371/journal.pone.0196456>, and weighted least squares (Nair et al., 2019) to estimate the shape parameter of Pareto distributed data. It also provides both a heuristic method (Hubert et al., 2013)<doi:10.1016/j.csda.2012.07.011> and a goodness of fit test (Gulati and Shapiro, 2008)<doi:10.1007/978-0-8176-4619-6> for testing for Pareto data as well as a method for generating Pareto distributed data.
Depends: R (>= 3.5.0)
License: GPL-3
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp
RoxygenNote: 6.1.1
Suggests: plotly
NeedsCompilation: yes
Packaged: 2019-04-01 10:00:35 UTC; Asus
Author: Ranjiva Munasinghe [aut], Pathum Kossinna [cre, aut], Dovini Jayasinghe [aut], Dilanka Wijeratne [aut]
Maintainer: Pathum Kossinna <pathum@mindlanka.org>
Repository: CRAN
Date/Publication: 2019-04-02 15:10:03 UTC

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New package foieGras with initial version 0.2.0
Package: foieGras
Title: Fit Continuous-Time State-Space Models for Filtering Argos Satellite (and Other) Telemetry Data
Version: 0.2.0
Authors@R: c( person(given = "Ian", family = "Jonsen", role = c("aut", "cre"), email = "ian.jonsen@mq.edu.au"), person(given = "Toby", family = "Patterson", role = c("aut", "ctb"), email = "toby.patterson@cisro.au") )
Author: Ian Jonsen [aut, cre], Toby Patterson [aut, ctb]
Maintainer: Ian Jonsen <ian.jonsen@mq.edu.au>
Description: Fits continuous-time random walk and correlated random walk state-space models to filter Argos satellite location data. Template Model Builder ('TMB') is used for fast estimation. The Argos data can be: (older) least squares-based locations; (newer) Kalman filter-based locations with error ellipse information; or a mixture of both. Separate measurement models are used for these two data types. The models estimate two sets of location states corresponding to: 1) each observation, which are (usually) irregularly timed; and 2) user-specified time intervals (regular or irregular). Jonsen I, McMahon CR, Patterson TA, Auger-Methe M, Harcourt R, Hindell MA, Bestley S (2019) Movement responses to environment: fast inference of variation among southern elephant seals with a mixed effects model. Ecology 100:e02566 <doi:10.1002/ecy.2566>.
License: AGPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
LinkingTo: TMB, RcppEigen
Imports: dplyr, tibble, argosfilter, ggplot2, gridExtra, lubridate, TMB, sf, stringr, magrittr
Suggests: testthat, covr, knitr, rmarkdown, rnaturalearth, rgeos, ggspatial, units
VignetteBuilder: knitr
Depends: R (>= 3.3.0)
NeedsCompilation: yes
Packaged: 2019-04-01 15:23:02 UTC; jonsen
Repository: CRAN
Date/Publication: 2019-04-02 15:50:02 UTC

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New package calcWOI with initial version 1.0.1
Package: calcWOI
Type: Package
Title: Calculates the Wavelet-Based Organization Index
Version: 1.0.1
Date: 2019-03-27
Author: Sebastian Brune, Sebastian Buschow, Florian Kapp, Petra Friederichs
Maintainer: Sebastian Brune <sbrune@uni-bonn.de>
Depends: R (>= 3.5.0), wavethresh (>= 4.5), LS2W (>= 1.3.4)
Description: Calculates the original wavelet-based organization index, the modified wavelet-based organization index and the local wavelet-based organization index of an arbitrary 2D array using Wavelet Transform of Eckley et al (2010) (<doi:10.1111/j.1467-9876.2009.00721.x>) and Eckley and Nason (2011) (<doi:10.18637/jss.v043.i03>).
License: GPL-3
LazyData: true
NeedsCompilation: yes
Packaged: 2019-04-01 13:50:20 UTC; Seb
Repository: CRAN
Date/Publication: 2019-04-02 12:30:03 UTC

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New package dynr with initial version 0.1.14-9
Package: dynr
Date: 2019-04-01
Title: Dynamic Modeling in R
Authors@R: c(person("Lu", "Ou", role="aut", email="lzo114@psu.edu"), person(c("Michael", "D."), "Hunter", role=c("aut", "cre"), email="mhunter.ou@gmail.com"), person("Sy-Miin", "Chow", role="aut"))
Author: Lu Ou [aut], Michael D. Hunter [aut, cre], Sy-Miin Chow [aut]
Maintainer: Michael D. Hunter <mhunter.ou@gmail.com>
Depends: R (>= 3.0.0), ggplot2
Imports: MASS, Matrix, numDeriv, xtable, latex2exp, grid, reshape2, plyr, mice, magrittr, Rdpack, methods
Suggests: testthat, roxygen2 (>= 3.1), knitr, rmarkdown
VignetteBuilder: knitr
Description: Intensive longitudinal data have become increasingly prevalent in various scientific disciplines. Many such data sets are noisy, multivariate, and multi-subject in nature. The change functions may also be continuous, or continuous but interspersed with periods of discontinuities (i.e., showing regime switches). The package 'dynr' (Dynamic Modeling in R) is an R package that implements a set of computationally efficient algorithms for handling a broad class of linear and nonlinear discrete- and continuous-time models with regime-switching properties under the constraint of linear Gaussian measurement functions. The discrete-time models can generally take on the form of a state- space or difference equation model. The continuous-time models are generally expressed as a set of ordinary or stochastic differential equations. All estimation and computations are performed in C, but users are provided with the option to specify the model of interest via a set of simple and easy-to-learn model specification functions in R. Model fitting can be performed using single- subject time series data or multiple-subject longitudinal data.
SystemRequirements: GNU make
NeedsCompilation: yes
License: GPL-3
LazyLoad: yes
LazyData: yes
Collate: 'dynrData.R' 'dynrRecipe.R' 'dynrModelInternal.R' 'dynrModel.R' 'dynrCook.R' 'dynrPlot.R' 'dynrFuncAddress.R' 'dynrMi.R' 'dynrTaste.R' 'dynrVersion.R' 'dataDoc.R'
RdMacros: Rdpack
Biarch: true
Version: 0.1.14-9
RoxygenNote: 5.0.1
Packaged: 2019-04-01 23:36:10 UTC; mhunter
Repository: CRAN
Date/Publication: 2019-04-02 07:50:03 UTC

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New package crblocks with initial version 1.0-0
Package: crblocks
Version: 1.0-0
Date: 2019-03-27
Title: Categorical Randomized Block Data Analysis
Author: David Allingham, D.J. Best
Maintainer: David Allingham <David.Allingham@newcastle.edu.au>
Description: Implements a statistical test for comparing bar plots or histograms of categorical data derived from a randomized block repeated measures layout.
License: GPL-3
URL: https://carma.newcastle.edu.au/davida/
Imports: stats, utils
NeedsCompilation: no
Packaged: 2019-04-02 00:47:01 UTC; davida
Repository: CRAN
Date/Publication: 2019-04-02 07:50:09 UTC

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Mon, 01 Apr 2019

New package hurricaneexposure with initial version 0.1.0
Package: hurricaneexposure
Type: Package
Title: Explore and Map County-Level Hurricane Exposure in the United States
Version: 0.1.0
Date: 2019-03-29
Authors@R: c(person("Brooke", "Anderson", email = "brooke.anderson@colostate.edu", role = c("aut", "cre")), person("Meilin", "Yan", email = "meilin.yan@colostate.edu", role = "aut"), person("Joshua", "Ferreri", email = "joshua.m.ferreri@gmail.com", role = "aut"), person("William", "Crosson", email = "bill.crosson@nasa.gov", role = "ctb"), person("Mohammad", "Al-Hamdan", email = "mohammad.alhamdan@nasa.gov", role = "ctb"), person("Andrea", "Schumacher", email = "andrea.schumacher@colostate.edu", role = "ctb"), person("Dirk", "Eddelbuettel", email = "edd@debian.org", role = "ctb") )
Description: Allows users to create time series of tropical storm exposure histories for chosen counties for a number of hazard metrics (wind, rain, distance from the storm, etc.). This package interacts with data available through the 'hurricaneexposuredata' package, which is available in a 'drat' repository. To access this data package, see the instructions at <https://github.com/geanders/hurricaneexposure>. The size of the 'hurricaneexposuredata' package is approximately 25 MB. This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), and a NASA Applied Sciences Program/Public Health Program Grant (NNX09AV81G).
URL: https://github.com/geanders/hurricaneexposure
BugReports: https://github.com/geanders/hurricaneexposure/issues
License: GPL (>= 2)
LazyData: TRUE
Imports: data.table (>= 1.12.0), dplyr (>= 0.8.0.1), ggmap (>= 3.0.0), ggplot2 (>= 3.1.0), lazyeval (>= 0.2.2), lubridate (>= 1.7.4), mapproj (>= 1.2.6), maps (>= 3.3.0), purrr (>= 0.3.2), RColorBrewer (>= 1.1.2), rlang (>= 0.3.3), stringr (>= 1.4.0), tidyr (>= 0.8.3)
RoxygenNote: 6.1.1
Encoding: UTF-8
Depends: R (>= 3.5)
Suggests: hurricaneexposuredata (>= 0.0.2), knitr, pander, rmarkdown, weathermetrics
VignetteBuilder: knitr
Additional_repositories: https://geanders.github.io/drat
Language: en-US
NeedsCompilation: no
Packaged: 2019-04-01 20:30:38 UTC; georgianaanderson
Author: Brooke Anderson [aut, cre], Meilin Yan [aut], Joshua Ferreri [aut], William Crosson [ctb], Mohammad Al-Hamdan [ctb], Andrea Schumacher [ctb], Dirk Eddelbuettel [ctb]
Maintainer: Brooke Anderson <brooke.anderson@colostate.edu>
Repository: CRAN
Date/Publication: 2019-04-01 21:40:03 UTC

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New package opencv with initial version 0.1
Package: opencv
Type: Package
Title: Bindings to 'OpenCV' Computer Vision Library
Version: 0.1
Authors@R: c(person("Jeroen", "Ooms", role = c("aut", "cre"), email = "jeroen@berkeley.edu", comment = c(ORCID = "0000-0002-4035-0289")))
Description: Experimenting with computer vision and machine learning in R. This package exposes some of the available 'OpenCV' vision algorithms, such as edge, body or face detection. These can either be applied to analyze static images, or to filter live video footage from a camera device.
License: MIT + file LICENSE
SystemRequirements: OpenCV: libopencv-dev (Debian, Ubuntu) or opencv-devel (Fedora)
URL: https://github.com/ropensci/opencv
BugReports: https://github.com/ropensci/opencv/issues
LinkingTo: Rcpp
Imports: Rcpp, magrittr
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-04-01 14:08:54 UTC; jeroen
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Repository: CRAN
Date/Publication: 2019-04-01 18:20:03 UTC

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New package grplassocat with initial version 1.0
Package: grplassocat
Type: Package
Title: Standardization for Group Lasso Models with Categorical Predictors
Version: 1.0
Date: 2019-02-28
Author: Felicitas Detmer and Martin Slawski
Maintainer: Felicitas Detmer <fdetmer@gmu.edu>
Description: Implements the simple and computationally efficient standardization scheme for group lasso models with categorical predictors described in Detmer, Cebral, Slawski (2019) <arXiv:1805.06915>.
Depends: grplasso
License: GPL-3
NeedsCompilation: no
Packaged: 2019-03-30 18:50:27 UTC; fdetmer
Repository: CRAN
Date/Publication: 2019-04-01 18:20:06 UTC

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New package spatialreg with initial version 1.1-3
Package: spatialreg
Version: 1.1-3
Date: 2019-04-01
Title: Spatial Regression Analysis
Encoding: UTF-8
Authors@R: c(person("Roger", "Bivand", role = c("cre", "aut"), email = "Roger.Bivand@nhh.no", comment=c(ORCID="0000-0003-2392-6140")), person(given = "Gianfranco", family = "Piras", role = c("aut"), email = "gpiras@mac.com"), person("Luc", "Anselin", role = "ctb"), person("Andrew", "Bernat", role = "ctb"), person("Eric", "Blankmeyer", role = "ctb"), person("Yongwan", "Chun", role = "ctb"), person("Virgilio", "Gómez-Rubio", role = "ctb"), person("Daniel", "Griffith", role = "ctb"), person("Martin", "Gubri", role = "ctb"), person("Rein", "Halbersma", role = "ctb"), person("James", "LeSage", role = "ctb"), person("Angela", "Li", role = "ctb"), person("Jielai", "Ma", role = "ctb"), person("Abhirup", "Mallik", role = c("ctb", "trl")), person("Giovanni", "Millo", role = "ctb"), person("Kelley", "Pace", role = "ctb"), person("Pedro", "Peres-Neto", role = "ctb"), person("Michael", "Tiefelsdorf", role = "ctb"), person(given = "Mauricio", family = "Sarrias", role = c("ctb"), email = "mauricio.sarrias@ucn.cl"), person(given = "JuanTomas", family = "Sayago", role = c("ctb"), email = "juantomas.sayago@gmail.com"), person("Michael", "Tiefelsdorf", role = "ctb"))
Depends: R (>= 3.3.0), spData, Matrix
Imports: spdep, expm, coda, methods, MASS, boot, splines, LearnBayes, nlme, gmodels
Suggests: parallel, RSpectra, sf, tmap, foreign, spam, knitr, lmtest, sandwich
Description: A collection of all the estimation functions for spatial cross-sectional models (on lattice/areal data using spatial weights matrices) contained up to now in 'spdep', 'sphet' and 'spse'. These model fitting functions include maximum likelihood methods for cross-sectional models proposed by 'Cliff' and 'Ord' (1973, ISBN:0850860369) and (1981, ISBN:0850860814), fitting methods initially described by 'Ord' (1975) <doi:10.1080/01621459.1975.10480272>. The models are further described by 'Anselin' (1988) <doi:10.1007/978-94-015-7799-1>. Spatial two stage least squares and spatial general method of moment models initially proposed by 'Kelejian' and 'Prucha' (1998) <doi:10.1023/A:1007707430416> and (1999) <doi:10.1111/1468-2354.00027> are provided. Impact methods and MCMC fitting methods proposed by 'LeSage' and 'Pace' (2009) <doi:10.1201/9781420064254> are implemented for the family of cross-sectional spatial regression models. Methods for fitting the log determinant term in maximum likelihood and MCMC fitting are compared by 'Bivand et al.' (2013) <doi:10.1111/gean.12008>, and model fitting methods by 'Bivand' and 'Piras' (2015) <doi:10.18637/jss.v063.i18>; both of these articles include extensive lists of references. 'spatialreg' >= 1.1-* correspond to 'spdep' >= 1.1-1, in which the model fitting functions are deprecated and pass through to 'spatialreg', but will mask those in 'spatialreg'. From versions 1.2-*, the functions will be made defunct in 'spdep'.
License: GPL-2
URL: https://github.com/r-spatial/spatialreg/, https://r-spatial.github.io/spatialreg/
BugReports: https://github.com/r-spatial/spatialreg/issues/
VignetteBuilder: knitr
NeedsCompilation: yes
RoxygenNote: 6.1.1
Packaged: 2019-04-01 13:56:03 UTC; rsb
Author: Roger Bivand [cre, aut] (<https://orcid.org/0000-0003-2392-6140>), Gianfranco Piras [aut], Luc Anselin [ctb], Andrew Bernat [ctb], Eric Blankmeyer [ctb], Yongwan Chun [ctb], Virgilio Gómez-Rubio [ctb], Daniel Griffith [ctb], Martin Gubri [ctb], Rein Halbersma [ctb], James LeSage [ctb], Angela Li [ctb], Jielai Ma [ctb], Abhirup Mallik [ctb, trl], Giovanni Millo [ctb], Kelley Pace [ctb], Pedro Peres-Neto [ctb], Michael Tiefelsdorf [ctb], Mauricio Sarrias [ctb], JuanTomas Sayago [ctb], Michael Tiefelsdorf [ctb]
Maintainer: Roger Bivand <Roger.Bivand@nhh.no>
Repository: CRAN
Date/Publication: 2019-04-01 18:00:03 UTC

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New package RNewsflow with initial version 1.1.0
Package: RNewsflow
Type: Package
Title: Tools for Comparing Text Messages Across Time and Media
Version: 1.1.0
Date: 2019-03-25
Author: Kasper Welbers & Wouter van Atteveldt
Maintainer: Kasper Welbers <kasperwelbers@gmail.com>
Description: A collection of tools for measuring the similarity of text messages and tracing the flow of messages over time and across media.
License: MIT + file LICENSE
Depends: R (>= 3.2.0), igraph, tm, Matrix (>= 1.2)
Imports: slam, stringi, scales, wordcloud, data.table, methods, quanteda, Rcpp (>= 0.12.12)
LinkingTo: Rcpp, RcppEigen, RcppProgress
LazyData: true
SystemRequirements: C++11
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-04-01 07:25:31 UTC; kasper
Repository: CRAN
Date/Publication: 2019-04-01 17:40:06 UTC

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New package Umoments with initial version 0.1.0
Package: Umoments
Type: Package
Title: Unbiased Central Moment Estimates
Version: 0.1.0
Author: Inna Gerlovina [aut, cre], Alan E. Hubbard [aut]
Maintainer: Inna Gerlovina <innager@berkeley.edu>
Description: Calculates one-sample unbiased central moment estimates and two-sample pooled estimates up to 6th order, including unbiased estimates of powers and products of central moments. Provides the machinery for obtaining unbiased central moment estimators beyond 6th order.
Depends: R (>= 3.4.0)
Imports: stats, utils
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-29 23:23:31 UTC; innars
Repository: CRAN
Date/Publication: 2019-04-01 16:10:03 UTC

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New package STAT with initial version 0.1.0
Package: STAT
Type: Package
Title: Interactive Document for Working with Basic Statistical Analysis
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive document on the topic of basic statistical analysis using 'rmarkdown' and 'shiny' packages. Runtime examples are provided in the package function as well as at <https://jarvisatharva.shinyapps.io/StatisticsPrimer/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown,psycho,dplyr,corrgram,Hmisc,rpivotTable,psych,datasets
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-04-01 15:30:54 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-04-01 16:40:10 UTC

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New package otsad with initial version 0.1.0
Package: otsad
Type: Package
Title: Online Time Series Anomaly Detectors
Version: 0.1.0
Authors@R: c( person("Alaiñe", "Iturria", email = "aiturria@ikerlan.es", role = c("aut","cre")), person("Jacinto", "Carrasco", email = "jacintocc@decsai.ugr.es", role = c("aut")), person("Francisco", "Herrera", email = "herrera@decsai.ugr.es", role = c("aut")), person("Santiago", "Charramendieta", email = "scharramendieta@ikerlan.es", role = c("aut")), person("Karmele", "Intxausti", email = "kintxausti@ikerlan.es", role = c("aut")))
Description: Implements a set of online fault detectors for time-series, called: PEWMA see M. Carter et al. (2012) <doi:10.1109/SSP.2012.6319708>, SD-EWMA and TSSD-EWMA see H. Raza et al. (2015) <doi:10.1016/j.patcog.2014.07.028>, KNN-CAD see E. Burnaev et al. (2016) <arXiv:1608.04585>, KNN-LDCD see V. Ishimtsev et al. (2017) <arXiv:1706.03412> and CAD-OSE see M. Smirnov (2018) <https://github.com/smirmik/CAD>. The first three algorithms belong to prediction-based techniques and the last three belong to window-based techniques. In addition, the SD-EWMA and PEWMA algorithms are algorithms designed to work in stationary environments, while the other four are algorithms designed to work in non-stationary environments.
Depends: R (>= 3.4.0)
SystemRequirements: Python (>= 3.0.1); bencode-python3 (1.0.2)
License: AGPL (>= 3)
URL: https://github.com/alaineiturria/otsad
BugReports: https://github.com/alaineiturria/otsad/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: testthat, stream, knitr, rmarkdown
Imports: stats, ggplot2, plotly, sigmoid, reticulate
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-04-01 04:52:53 UTC; aiturria
Author: Alaiñe Iturria [aut, cre], Jacinto Carrasco [aut], Francisco Herrera [aut], Santiago Charramendieta [aut], Karmele Intxausti [aut]
Maintainer: Alaiñe Iturria <aiturria@ikerlan.es>
Repository: CRAN
Date/Publication: 2019-04-01 16:40:03 UTC

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New package lisa with initial version 0.1.0
Package: lisa
Title: Color Palettes from Color Lisa
Version: 0.1.0
Authors@R: person(given = "Tyler", family = "Littlefield", role = c("aut", "cre"), email = "tylurp1@gmail.com")
Description: Contains 128 palettes from Color Lisa. All palettes are based on masterpieces from the worlds greatest artists. For more information, see <http://colorlisa.com/>.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
URL: https://github.com/tyluRp/lisa
BugReports: https://github.com/tyluRp/lisa/issues
NeedsCompilation: no
Packaged: 2019-03-31 17:01:52 UTC; tylerlittlefield
Author: Tyler Littlefield [aut, cre]
Maintainer: Tyler Littlefield <tylurp1@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-01 15:40:03 UTC

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New package adoption with initial version 0.6.2
Package: adoption
Version: 0.6.2
Title: Modelling Adoption Process in Marketing
Author: Martin Schlather [aut, cre]
Maintainer: Martin Schlather <schlather@math.uni-mannheim.de>
LinkingTo: RandomFieldsUtils
Depends: R (>= 3.0), RandomFieldsUtils (>= 0.5.3)
Imports: stats, graphics, methods, grDevices, utils, quadprog, tcltk, tkrplot
Description: The classical Bass (1969) <doi:10.1287/mnsc.15.5.215> model and the agent based models, such as that by Goldenberg, Libai and Muller (2010) <doi:10.1016/j.ijresmar.2009.06.006> have been two different approaches to model adoption processes in marketing. These two approaches can be unified by explicitly modelling the utility functions. This package provides a GUI that allows, in a unified way, the modelling of these two processes and other processes.
License: GPL (>= 3) | CC BY 4.0
URL: http://ms.math.uni-mannheim.de/de/publications/software/adoption
NeedsCompilation: yes
Packaged: 2019-03-29 17:06:57 UTC; schlather
Repository: CRAN
Date/Publication: 2019-04-01 15:30:03 UTC

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New package tmt with initial version 0.1.9-3
Package: tmt
Type: Package
Title: Estimation of the Rasch Model for Multistage Tests
Version: 0.1.9-3
Date: 2019-03-31
Authors@R: c( person(given = "Jan", family = "Steinfeld", email = "jan.d.steinfeld@gmail.com", role = c("cre","aut"), comment = c(ORCID = "0000-0001-9853-8260") ), person(given = "Alexander", family = "Robitzsch", email = "robitzsch@ipn.uni-kiel.de", role = c("aut"), comment = c(ORCID = "0000-0002-8226-3132") ) )
Author: Jan Steinfeld [cre, aut] (<https://orcid.org/0000-0001-9853-8260>), Alexander Robitzsch [aut] (<https://orcid.org/0000-0002-8226-3132>)
Maintainer: Jan Steinfeld <jan.d.steinfeld@gmail.com>
URL: https://github.com/jansteinfeld/tmt
BugReports: https://github.com/jansteinfeld/tmt/issues
Description: Provides conditional maximum likelihood (CML) estimation of item parameters in multistage designs (Zwitser & Maris, 2013, <doi:10.1007/s11336-013-9369-6>) and CML estimation for conventional designs. Additional features are the likelihood ratio test (Andersen, 1973, <doi:10.1007/BF02291180>) and simulation of multistage designs.
License: GPL-3
LazyLoad: yes
LazyData: true
VignetteBuilder: knitr
Depends: R (>= 3.0)
Encoding: UTF-8
NeedsCompilation: yes
Suggests: roxygen2, eRm, knitr, prettydoc, psychotools, testthat, rmarkdown, dexterMST
Imports: parallel, ggplot2, Rcpp (>= 0.12.0), stats
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Packaged: 2019-03-31 14:40:57 UTC; jansteinfeld
Repository: CRAN
Date/Publication: 2019-04-01 09:10:03 UTC

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New package foretell with initial version 0.1.0
Package: foretell
Type: Package
Title: Projecting Customer Retention Based on Fader and Hardie Probability Models
Version: 0.1.0
Author: Srihari Jaganathan
Maintainer: Srihari Jaganathan <sriharitn@gmail.com>
Description: Project Customer Retention based on Beta Geometric, Beta Discrete Weibull and Latent Class Discrete Weibull Models This package is based on Fader and Hardie (2007) <doi:10.1002/dir.20074> and Fader and Hardie et al. (2018) <doi:10.1016/j.intmar.2018.01.002> .
Depends: R (>= 3.0.1)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-31 01:38:57 UTC; haria
Repository: CRAN
Date/Publication: 2019-04-01 09:10:06 UTC

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New package shipunov with initial version 1.0
Package: shipunov
Type: Package
Title: Miscellaneous Functions from Alexey Shipunov
Version: 1.0
Date: 2019-03-24
Author: Alexey Shipunov [aut, cre], Karl W Broman [ctb], Paul Murrell [ctb], Marcello D'Orazio [ctb], Stephen Turner [ctb], Eugeny Altshuler [ctb], Roland Rau [ctb], Christoph Heibl [ctb], Marcus W Beck [ctb]
Maintainer: Alexey Shipunov <dactylorhiza@gmail.com>
Description: A collection of functions for data manipulation, plotting and statistical computing, to use separately or with the book "Visual Statistics. Use R!": Shipunov (2019) <http://ashipunov.info/shipunov/software/r/r-en.htm>.
Suggests: PBSmapping, ape, class, cluster, effsize, gpclib, grid, ips, randomForest, nnet, scales, smirnov, vegan, MASS, adabag, e1071, neuralnet, rpart, tree
Imports: methods
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2019-03-29 19:06:41 UTC; alexey
Repository: CRAN
Date/Publication: 2019-04-01 08:20:03 UTC

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New package PublicationBias with initial version 1.0.0
Package: PublicationBias
Type: Package
Title: Sensitivity Analysis for Publication Bias in Meta-Analyses
Version: 1.0.0
Author: Maya B. Mathur, Tyler J. VanderWeele
Maintainer: Maya B. Mathur <mmathur@stanford.edu>
Description: Performs sensitivity analysis for publication bias in meta-analyses (per Mathur & VanderWeele, 2019 [<https://osf.io/s9dp6>]). These analyses enable statements such as: "For publication bias to shift the observed point estimate to the null, 'significant' results would need to be at least 30-fold more likely to be published than negative or 'nonsignificant' results." Comparable statements can be made regarding shifting to a chosen non-null value or shifting the confidence interval. Provides a worst-case meta-analytic point estimate under maximal publication bias obtained simply by conducting a standard meta-analysis of only the negative and "nonsignificant" studies.
License: GPL-2
Encoding: UTF-8
Imports: metafor, stats, dplyr, robumeta, ggplot2, Rdpack, MetaUtility
RdMacros: Rdpack
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-29 19:30:10 UTC; mmathur
Repository: CRAN
Date/Publication: 2019-04-01 09:00:03 UTC

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New package MAP with initial version 0.1.3
Package: MAP
Type: Package
Title: Multimodal Automated Phenotyping
Version: 0.1.3
Author: Jiehuan Sun [aut, cre], Katherine P. Liao[aut], Sheng Yu [aut], Tianxi Cai [aut]
Maintainer: Jiehuan Sun <jiehuan.sun@gmail.com>
Description: Electronic health records (EHR) linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently. Towards that end, we developed an automated high-throughput phenotyping method integrating International Classification of Diseases (ICD) codes and narrative data extracted using natural language processing (NLP). Specifically, our proposed method, called MAP (Map Automated Phenotyping algorithm), fits an ensemble of latent mixture models on aggregated ICD and NLP counts along with healthcare utilization. The MAP algorithm yields a predicted probability of phenotype for each patient and a threshold for classifying subjects with phenotype yes/no (See Katherine P. Liao, et al. (2019) <doi:10.1101/587436>.).
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0), flexmix (>= 2.3-14), Matrix(>= 1.2-10)
Suggests: knitr, rmarkdown
NeedsCompilation: no
RoxygenNote: 6.1.1
Packaged: 2019-03-29 19:47:25 UTC; JiehuanSun
Repository: CRAN
Date/Publication: 2019-04-01 08:20:09 UTC

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New package gwer with initial version 1.0
Package: gwer
Type: Package
Title: Geographically Weighted Elliptical Regression
Version: 1.0
Date: 2019-03-29
Author: Yuri A. Araujo, Francisco Jose A. Cysneiros and Audrey H. M. A. Cysneiros
Maintainer: Yuri A. Araujo <yada1@de.ufpe.br>
Description: Computes a elliptical regression model or a geographically weighted regression model with elliptical errors using Fisher's score algorithm. Provides diagnostic measures, residuals and analysis of variance. Cysneiros, F. J. A., Paula, G. A., and Galea, M. (2007) <doi:10.1016/j.spl.2007.01.012>.
Depends: R (>= 2.14), sp (>= 0.8-3), stats
Imports: maptools (>= 0.7-32), Matrix, methods, spData (>= 0.2.6.2), spdep, spgwr, utils, assertthat, glogis, graphics
Suggests: rgdal, parallel
NeedsCompilation: no
License: GPL (>= 2)
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
Packaged: 2019-03-29 23:31:27 UTC; LoD_B
Repository: CRAN
Date/Publication: 2019-04-01 08:30:02 UTC

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New package cheese with initial version 0.0.1
Package: cheese
Version: 0.0.1
Date: 2019-03-12
Title: Tools for Intuitive and Flexible Statistical Analysis Workflows
Authors@R: person(given = "Alex", family = "Zajichek", email = "alexzajichek@gmail.com", role = c("aut", "cre"))
Description: Contains flexible and intuitive functions to assist in carrying out tasks in a statistical analysis and to get from the raw data to presentation-ready results. A user-friendly interface is used in specialized functions that are aimed at common tasks such as building a univariate descriptive table for variables in a dataset. These high-level functions are built on a collection of low(er)-level functions that may be useful for aspects of a custom statistical analysis workflow or for general programming use.
URL: https://github.com/zajichek/cheese
License: MIT + file LICENSE
Depends: R (>= 3.4.0)
Imports: dplyr (>= 0.7.7), forcats (>= 0.3.0), kableExtra (>= 1.0.1), knitr (>= 1.20), magrittr (>= 1.5), methods (>= 3.4.1), purrr (>= 0.2.4), rlang (>= 0.3.0.1), stringr (>= 1.3.1), tibble (>= 1.4.2), tidyr (>= 0.8.1), tidyselect (>= 0.2.4)
Suggests: rmarkdown (>= 1.10), tidyverse (>= 1.2.1)
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2019-03-29 17:07:03 UTC; alexzajichek
Author: Alex Zajichek [aut, cre]
Maintainer: Alex Zajichek <alexzajichek@gmail.com>
Repository: CRAN
Date/Publication: 2019-04-01 08:10:03 UTC

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New package adoptr with initial version 0.1.1
Package: adoptr
Type: Package
Title: Adaptive Optimal Two-Stage Designs in R
Version: 0.1.1
Authors@R: c( person("Kevin", "Kunzmann", role = c("aut", "cre"), email = "kevin.kunzmann@mrc-bsu.cam.ac.uk"), person("Maximilian", "Pilz", role = c("aut"), email = "pilz@imbi.uni-heidelberg.de") )
Description: Optimize one or two-arm, two-stage designs for clinical trials with respect to several pre-implemented objective criteria or implement custom objectives. Optimization under uncertainty and conditional (given stage-one outcome) constraints are supported.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat, covr, rpact, vdiffr
Imports: nloptr, methods
VignetteBuilder: knitr
Collate: adoptr.R util.R DataDistribution.R Prior.R PointMassPrior.R ContinuousPrior.R TwoStageDesign.R GroupSequentialDesign.R OneStageDesign.R Scores.R AffineScoreFunction.R constraints.R minimize.R ConditionalPower.R ConditionalSampleSize.R regularization.R boundary_designs.R
RoxygenNote: 6.1.1
BugReports: https://github.com/kkmann/adoptr/issues
URL: https://github.com/kkmann/adoptr
NeedsCompilation: no
Packaged: 2019-03-30 00:13:32 UTC; kevin
Author: Kevin Kunzmann [aut, cre], Maximilian Pilz [aut]
Maintainer: Kevin Kunzmann <kevin.kunzmann@mrc-bsu.cam.ac.uk>
Repository: CRAN
Date/Publication: 2019-04-01 08:30:06 UTC

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New package robustSingleCell with initial version 0.1.0
Package: robustSingleCell
Type: Package
Title: Robust Clustering of Single Cell RNA-Seq Data
Version: 0.1.0
Authors@R: c( person("Assaf", "Magen", email = "assaf.magen@nih.gov", role = "aut"), person("Meng", "Wang", email = "szmamie@live.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3453-7805")), person("Hao", "Chen", role = "ctb") )
Description: Robust single cell clustering and comparison of population compositions across tissues and experimental models via similarity analysis from Magen 2019 <doi:10.1101/543199>.
Depends: R (>= 3.2.0)
Imports: utils, grDevices, graphics, Matrix, limma, biomaRt, dplyr, ggplot2, reshape2, GGally, ggrepel, RColorBrewer, gplots, ggpubr, cccd, rslurm, Rtsne, igraph, scales, RANN, Rcpp
LinkingTo: Rcpp
License: Artistic-2.0
URL: https://github.com/asmagen/robustSingleCell
BugReports: https://github.com/asmagen/robustSingleCell/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Suggests: GEOquery, knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2019-03-28 20:55:08 UTC; szmamie
Author: Assaf Magen [aut], Meng Wang [aut, cre] (<https://orcid.org/0000-0002-3453-7805>), Hao Chen [ctb]
Maintainer: Meng Wang <szmamie@live.com>
Repository: CRAN
Date/Publication: 2019-04-01 07:30:03 UTC

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Sun, 31 Mar 2019

New package otpr with initial version 0.1.0
Package: otpr
Title: An R Wrapper for the 'OpenTripPlanner' REST API
Version: 0.1.0
Authors@R: c( person("Marcus", "Young", email = "M.A.Young@soton.ac.uk", role = c("aut", "cre")) )
Description: A wrapper for the 'OpenTripPlanner' <http://www.opentripplanner.org/> REST API. Queries are submitted to the relevant 'OpenTripPlanner' API resource, the response is parsed and useful R objects are returned.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: checkmate, httr, curl, jsonlite
RoxygenNote: 6.1.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2019-03-31 10:38:07 UTC; marcu
Author: Marcus Young [aut, cre]
Maintainer: Marcus Young <M.A.Young@soton.ac.uk>
Repository: CRAN
Date/Publication: 2019-03-31 15:10:03 UTC

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New package buildmer with initial version 1.0
Package: buildmer
Title: Stepwise Elimination and Term Reordering for Mixed-Effects Regression
Version: 1.0
Authors@R: person("Cesko", "Voeten", email = "c.c.voeten@hum.leidenuniv.nl", role = c("aut", "cre"))
Description: Finds the largest possible regression model that will still converge for various types of regression analyses (including mixed models and generalized additive models) and then optionally performs stepwise elimination similar to the forward and backward effect selection methods in SAS, based on the change in log-likelihood, Akaike's Information Criterion, or the Bayesian Information Criterion.
Depends: R (>= 3.2)
Imports: methods, mgcv, lme4, plyr, stats, utils
Suggests: JuliaCall, MASS, gamm4, glmmTMB, knitr, lmerTest, nlme, nnet, parallel, pbkrtest
License: FreeBSD
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
BugReports: https://github.com/cvoeten/buildmer/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-31 08:28:31 UTC; cesko
Author: Cesko Voeten [aut, cre]
Maintainer: Cesko Voeten <c.c.voeten@hum.leidenuniv.nl>
Repository: CRAN
Date/Publication: 2019-03-31 14:50:02 UTC

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New package AzureGraph with initial version 1.0.0
Package: AzureGraph
Title: Simple Interface to 'Microsoft Graph'
Version: 1.0.0
Authors@R: c( person("Hong", "Ooi", , "hongooi@microsoft.com", role = c("aut", "cre")), person("Microsoft", role="cph") )
Description: A simple interface to the 'Microsoft Graph' API <https://docs.microsoft.com/en-us/graph/overview>. 'Graph' is a comprehensive framework for accessing data in various online Microsoft services. Currently, this package aims to provide an R interface only to the 'Azure Active Directory' part, with a view to supporting interoperability of R and 'Azure': users, groups, registered apps and service principals. However it can be easily extended to cover other services.
URL: https://github.com/cloudyr/AzureGraph
BugReports: https://github.com/cloudyr/AzureGraph/issues
License: MIT + file LICENSE
VignetteBuilder: knitr
Depends: R (>= 3.3)
Imports: AzureAuth, utils, httr (>= 1.3), jsonlite, openssl, R6
Suggests: AzureRMR, knitr, testthat
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-25 19:47:48 UTC; hongo
Author: Hong Ooi [aut, cre], Microsoft [cph]
Maintainer: Hong Ooi <hongooi@microsoft.com>
Repository: CRAN
Date/Publication: 2019-03-31 14:30:02 UTC

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New package priceR with initial version 0.1.0
Package: priceR
Type: Package
Title: Regular Expressions for Prices and Currencies
Version: 0.1.0
Author: Steve Condylios [aut, cre] (<https://orcid.org/0000-0003-0599-844X>)
Maintainer: Steve Condylios <steve.condylios@gmail.com>
Description: Functions to aid in the analysis of price and currency data by expediting data preprocessing. This includes extraction of relevant data (e.g. from text fields), conversion into numeric class, cleaning, and standardisation as appropriate.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: dplyr, gsubfn, stringr
NeedsCompilation: no
Packaged: 2019-03-29 15:02:00 UTC; st
Repository: CRAN
Date/Publication: 2019-03-31 13:20:03 UTC

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New package nhds with initial version 1.0.3
Package: nhds
Title: National Hospital Discharge Survey 2010 Data
Version: 1.0.3
Authors@R: person(given = "Jack", family = "Wasey", role = c("aut", "cre"), email = "jack@jackwasey.com")
Description: The National Hospital Discharge Survey (2010) summarizes the state of patients at the end of their hospital admissions. The US CDC publishes the data in the public domain, and describes it as follows: The National Hospital Discharge Survey (NHDS) is a continuing nationwide sample survey of short-stay hospitals in the United States. The scope of NHDS encompasses patients discharged from noninstitutional hospitals, exclusive of military and Department of Veterans Affairs hospitals, located in the 50 States and the District of Columbia. Only hospitals having six or more beds for in-patient use are included in the survey. See <https://www.cdc.gov/nchs/nhds> for more information.
License: GPL-3
URL: https://github.com/jackwasey/nhds
BugReports: https://github.com/jackwasey/nhds/issues
Depends: R (>= 2.10)
Suggests: icd, knitr, readr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-28 16:16:21 UTC; waseyj
Author: Jack Wasey [aut, cre]
Maintainer: Jack Wasey <jack@jackwasey.com>
Repository: CRAN
Date/Publication: 2019-03-31 13:30:03 UTC

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New package jrc with initial version 0.1.1
Package: jrc
Type: Package
Title: Exchange Commands Between R and 'JavaScript'
Version: 0.1.1
Date: 2019-02-26
Authors@R: c( person("Svetlana", "Ovchinnikova", role = c("aut", "cre"), email = "s.ovchinnikova@zmbh.uni-heidelberg.de"), person("Simon", "Anders", role = c("aut"), email = "sanders@fs.tum.de") )
Description: An 'httpuv' based bridge between R and 'JavaScript'. Provides an easy way to exchange commands and data between a web page and a currently running R session.
License: GPL-3
Imports: httpuv, jsonlite, utils, stringr
RoxygenNote: 6.1.1
URL: https://github.com/anders-biostat/jrc
BugReports: https://github.com/anders-biostat/jrc/issues
NeedsCompilation: no
Packaged: 2019-03-29 11:36:50 UTC; tyranchik
Author: Svetlana Ovchinnikova [aut, cre], Simon Anders [aut]
Maintainer: Svetlana Ovchinnikova <s.ovchinnikova@zmbh.uni-heidelberg.de>
Repository: CRAN
Date/Publication: 2019-03-31 14:00:03 UTC

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New package bysykkel with initial version 0.1.1.0
Package: bysykkel
Type: Package
Title: Get, Download, and Read City Bike Data from Norway
Description: Functions to get, download, and read open data from each City Bike website, and each City Bike API, in Norway that is made available under the NLOD 2.0 <https://data.norge.no/nlod/en/2.0>. These functions speed up the process of reading city bike data directly to R, and to download the data to disk, so that the user can focus on data analysis. The data is retrieved from the "developer" or "open data" pages of Oslo City Bike <https://developer.oslobysykkel.no/>, Oslo Winter Bike <https://oslovintersykkel.no/en/open-data>, Bergen City Bike <https://bergenbysykkel.no/en/open-data>, and Trondheim City Bike <https://trondheimbysykkel.no/en/open-data>.
Version: 0.1.1.0
Authors@R: person("Iman", "Ghayoornia", email = "ghayoornia.iman@gmail.com", role = c("aut", "cre"))
URL: http://github.com/PersianCatsLikeToMeow/bysykkel
BugReports: http://github.com/PersianCatsLikeToMeow/bysykkel/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: data.table, glue (>= 1.3.0), httr, jsonlite, magrittr, tibble
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-27 22:00:18 UTC; Iman Ghayoornia
Author: Iman Ghayoornia [aut, cre]
Maintainer: Iman Ghayoornia <ghayoornia.iman@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-31 12:00:03 UTC

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New package BDEsize with initial version 1.1
Package: BDEsize
Type: Package
Title: Efficient Determination of Sample Size in Balanced Design of Experiments
Version: 1.1
Date: 2019-03-27
Author: Jong Hee Chung, Yong Bin Lim
Maintainer: Jong Hee Chung <jochung947@gmail.com>
Description: Provides the sample size in balanced design of experiments and three graphs ; detectable standardized effect size vs power, sample size vs detectable standardized effect size, and sample size vs power. Sample size is computed in order to detect a certain standardized effect size with power at the significance level. Three graphs show the mutual relationship between the sample size, power and the detectable standardized effect size. By investigating those graphs, it can be checked that which effects are sensitive to the efficient sample size determination. Lenth,R.V.(2006-9) <http://www.stat.uiowa.edu/~rlenth/Power> Lim, Yong Bin (1998) Marvin, A., Kastenbaum, A. and Hoel, D.G. (1970) <doi:10.2307/2334851> Montgomery, Douglas C. (2013, ISBN: 0849323312).
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 6.1.1
NeedsCompilation: no
Repository: CRAN
Imports: fpow, shiny, shinyalert, ggplot2
Packaged: 2019-03-27 17:29:04 UTC; jonghee
Date/Publication: 2019-03-31 12:00:06 UTC

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New package waterYearType with initial version 1.0.0
Package: waterYearType
Type: Package
Title: Sacramento and San Joaquin Valley Water Year Types
Version: 1.0.0
Authors@R: person("Sadie", "Gill", email = "sgill@flowwest.com", role = c("cre", "aut"))
Description: Provides Water Year Hydrologic Classification Indices based on measured unimpaired runoff (in million acre-feet). Data is provided by California Department of Water Resources and subject to revision.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-03-27 16:39:29 UTC; sadie
Author: Sadie Gill [cre, aut]
Maintainer: Sadie Gill <sgill@flowwest.com>
Repository: CRAN
Date/Publication: 2019-03-31 10:50:03 UTC

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New package ggroups with initial version 1.1.4
Package: ggroups
Title: Pedigree and Genetic Groups
Version: 1.1.4
Date: 2019-03-25
Authors@R: person("Mohammad Ali", "Nilforooshan", email="m.a.nilforooshan@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0339-5442"))
Description: Calculates additive genetic relationship matrix and its inverse, in matrix and tabular-sparse formats. It includes functions for checking and processing pedigree, as well as functions to calculate the matrix of genetic group contributions (Q), and adding those contributions to the genetic merit of animals (Quaas (1988) <doi:10.3168/jds.S0022-0302(88)79691-5>). Calculation of Q is computationally extensive. There are computationally optimized functions to calculate Q.
License: GPL-3
LazyData: true
Suggests: doParallel (>= 1.0.14), foreach (>= 1.4.4)
RoxygenNote: 6.1.1
Encoding: UTF-8
Repository: CRAN
NeedsCompilation: no
Packaged: 2019-03-27 05:55:30 UTC; mnil
Author: Mohammad Ali Nilforooshan [aut, cre] (<https://orcid.org/0000-0003-0339-5442>)
Maintainer: Mohammad Ali Nilforooshan <m.a.nilforooshan@gmail.com>
Date/Publication: 2019-03-31 11:00:03 UTC

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Sat, 30 Mar 2019

New package clustringr with initial version 1.0
Package: clustringr
Type: Package
Title: Cluster Strings by Edit-Distance
Version: 1.0
Author: Dan S. Reznik
Maintainer: Dan S. Reznik <dreznik@gmail.com>
Description: Returns an edit-distance based clusterization of an input vector of strings. Each cluster will contain a set of strings w/ small mutual edit-distance (e.g., Levenshtein, optimum-sequence-alignment, Damerau-Levenshtein), as computed by stringdist::stringdist(). The set of all mutual edit-distances is then used by graph algorithms (from package 'igraph') to single out subsets of high connectivity.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: magrittr, dplyr, stringi, stringr, stringdist, igraph, assertthat, forcats, rlang, tidygraph, ggraph, ggplot2
Depends: R (>= 3.1)
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-26 18:10:58 UTC; dreznik
Repository: CRAN
Date/Publication: 2019-03-30 16:10:03 UTC

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New package NDP with initial version 0.1.0
Package: NDP
Type: Package
Title: Interactive Presentation for Working with Normal Distribution
Version: 0.1.0
Author: Kartikeya Bolar
Maintainer: Kartikeya Bolar <kartikeya.bolar@tapmi.edu.in>
Description: An interactive presentation on the topic of normal distribution using 'rmarkdown' and 'shiny' packages. It is helpful to those who want to learn normal distribution quickly and get a hands on experience. The presentation has a template for solving problems on normal distribution. Runtime examples are provided in the package function as well as at <https://kartikeyastat.shinyapps.io/NormalDistribution/>.
License: GPL-2
Encoding: UTF-8
LazyData: TRUE
Depends: R (>= 3.0.3)
Imports: shiny,rmarkdown
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2019-03-26 03:30:02 UTC; KARTIKEYA
Repository: CRAN
Date/Publication: 2019-03-30 15:00:02 UTC

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New package adeptdata with initial version 1.0.1
Package: adeptdata
Type: Package
Title: Accelerometry Data Sets
Version: 1.0.1
Authors@R: c( person("Marta", "Karas", email = "marta.karass@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5889-3970")), person("Jacek", "Urbanek", role = c("aut"), comment = c(ORCID = "0000-0002-1890-8899")), person("Jaroslaw", "Harezlak", role = c("aut"), comment = c(ORCID = "0000-0002-3070-7686")), person("William", "Fadel", role = c("aut"), comment = c(ORCID = "0000-0002-0292-6734")) )
Description: Created to host raw accelerometry data sets and their derivatives which are used in the corresponding 'adept' package.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Depends: R (>= 2.10)
Suggests: spelling
Language: en-US
NeedsCompilation: no
Packaged: 2019-03-25 16:29:12 UTC; martakaras
Author: Marta Karas [aut, cre] (<https://orcid.org/0000-0001-5889-3970>), Jacek Urbanek [aut] (<https://orcid.org/0000-0002-1890-8899>), Jaroslaw Harezlak [aut] (<https://orcid.org/0000-0002-3070-7686>), William Fadel [aut] (<https://orcid.org/0000-0002-0292-6734>)
Maintainer: Marta Karas <marta.karass@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-30 12:50:03 UTC

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Fri, 29 Mar 2019

New package steps with initial version 0.2.0
Package: steps
Type: Package
Title: Spatially- and Temporally-Explicit Population Simulator
Version: 0.2.0
Date: 2019-03-27
Authors@R: c( person("Casey", "Visintin", email = "casey.visintin@unimelb.edu.au", role=c("aut", "cre")), person("Nick", "Golding", email = "nick.golding.research@gmail.com", role = "ctb"), person("Skipton", "Woolley", email = "skip.woolley@csiro.au", role = "ctb"), person("John", "Baumgartner", email = "john.baumgartner@mq.edu.au", role = "ctb") )
Maintainer: Casey Visintin <casey.visintin@unimelb.edu.au>
Description: Software to simulate population dynamics across space and time.
Depends: R (>= 3.2.2)
License: GPL (>= 2)
Imports: Rcpp, magrittr, RColorBrewer, plyr, raster, rgdal, sp, methods, igraph, scales, future, future.apply, rasterVis, viridisLite, memuse
LinkingTo: Rcpp
RoxygenNote: 6.1.1
Suggests: testthat, fields, knitr, rmarkdown, foreach
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Packaged: 2019-03-29 03:26:37 UTC; casey
Author: Casey Visintin [aut, cre], Nick Golding [ctb], Skipton Woolley [ctb], John Baumgartner [ctb]
Repository: CRAN
Date/Publication: 2019-03-29 22:10:03 UTC

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New package unine with initial version 0.1.0
Package: unine
Type: Package
Title: Unine Light Stemmer
Version: 0.1.0
Authors@R: c(person("Michaël", "Benesty", role = c("aut", "cre", "cph"), email = "michael@benesty.fr"), person("Jacques Savoy", role = c("cph"), email = "Jacques.Savoy@unine.ch"))
Maintainer: Michaël Benesty <michael@benesty.fr>
Description: Implementation of "light" stemmers for French, German, Italian, Spanish, Portuguese, Finnish, Swedish. They are based on the same work as the "light" stemmers found in 'SolR' <https://lucene.apache.org/solr/> or 'ElasticSearch' <https://www.elastic.co/fr/products/elasticsearch>. A "light" stemmer consists in removing inflections only for noun and adjectives. Indexing verbs for these languages is not of primary importance compared to nouns and adjectives. The stemming procedure for French is described in (Savoy, 1999) <doi:10.1002/(SICI)1097-4571(1999)50:10%3C944::AID-ASI9%3E3.3.CO;2-H>.
URL: https://github.com/pommedeterresautee/unine, https://pommedeterresautee.github.io/unine/, http://members.unine.ch/jacques.savoy/clef/
BugReports: https://github.com/pommedeterresautee/unine/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp (>= 1.0.0), methods
SystemRequirements: C++11
RoxygenNote: 6.1.1
NeedsCompilation: yes
Suggests: testthat, covr, stringi
Packaged: 2019-03-26 21:42:58 UTC; geantvert
Author: Michaël Benesty [aut, cre, cph], Jacques Savoy [cph]
Repository: CRAN
Date/Publication: 2019-03-29 17:50:02 UTC

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New package PRSim with initial version 1.0
Package: PRSim
Type: Package
Title: Stochastic Simulation of Streamflow Time Series using Phase Randomization
Version: 1.0
Date: 2019-03-10
Authors@R: c(person("Manuela", "Brunner", role = c("aut", "cre"), email = "manuela.brunner@wsl.ch", comment = c(ORCID = "0000-0001-8824-877X")), person("Reinhard", "Furrer", role = c("aut"), email = "reinhard.furrer@math.uzh.ch", comment = c(ORCID = "0000-0002-6319-2332")))
Author: Manuela Brunner [aut, cre] (<https://orcid.org/0000-0001-8824-877X>), Reinhard Furrer [aut] (<https://orcid.org/0000-0002-6319-2332>)
Maintainer: Manuela Brunner <manuela.brunner@wsl.ch>
Description: Provides a simulation framework to simulate streamflow time series with similar main characteristics as observed data. These characteristics include the distribution of daily streamflow values and their temporal correlation as expressed by short- and long-range dependence. The approach is based on the randomization of the phases of the Fourier transform. We further use the flexible four-parameter Kappa distribution, which allows for the extrapolation to yet unobserved low and high flows.
URL: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel
BugReports: https://git.math.uzh.ch/reinhard.furrer/PRSim-devel
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: homtest
Suggests: lattice
Imports: stats
NeedsCompilation: no
Packaged: 2019-03-25 07:34:20 UTC; furrer
Repository: CRAN
Date/Publication: 2019-03-29 17:10:03 UTC

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New package pct with initial version 0.1.1
Package: pct
Type: Package
Title: Propensity to Cycle Tool
Version: 0.1.1
Authors@R: c( person("Robin", "Lovelace", email = "rob00x@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-5679-6536")), person("Layik", "Hama", email = "layik.hama@gmail.com", role = c("aut"), comment = c(ORCID = "0000-0003-1912-4890")) )
Description: Functions and example data to teach and increase the reproducibility of the methods and code underlying the Propensity to Cycle Tool (PCT), a research project and web application hosted at <https://www.pct.bike/>. For an academic paper on the methods, see Lovelace et al (2017) <doi:10.5198/jtlu.2016.862>.
Depends: R (>= 3.5.0)
License: GPL-3
URL: http://www.pct.bike/, https://itsleeds.github.io/pct/
BugReports: https://github.com/ITSLeeds/pct/issues
Encoding: UTF-8
LazyData: true
Imports: boot, stplanr (>= 0.2.8), readr, sf
Suggests: testthat, knitr, curl, covr, pbapply, ggplot2, remotes, rmarkdown, leaflet
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Language: en-GB
NeedsCompilation: no
Packaged: 2019-03-25 17:09:03 UTC; robin
Author: Robin Lovelace [aut, cre] (<https://orcid.org/0000-0001-5679-6536>), Layik Hama [aut] (<https://orcid.org/0000-0003-1912-4890>)
Maintainer: Robin Lovelace <rob00x@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-29 17:30:03 UTC

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New package intensity.analysis with initial version 0.1.6
Package: intensity.analysis
Type: Package
Title: Intensity of Change for Comparing Categorical Maps from Sequential Intervals
Version: 0.1.6
Author: Robert Gilmore Pontius Jr. <rpontius@clarku.edu>, Sam Khallaghi <SKhallaghi@clarku.edu>
Maintainer: Sam Khallaghi <SKhallaghi@clarku.edu>
Description: Calculate metrics of change intensity for category, transition and interval levels in categorical maps from sequential intervals. For more information please consult: Aldwaik,Safaa Zakaria and Robert Gilmore Pontius Jr. (2012). "Intensity analysis to unify measurements of size and stationarity of land changes by interval, category, and transition". Landscape and Urban Planning. 106, 103-114. <doi:10.1016/j.landurbplan.2012.02.010>.
License: GPL (>= 2)
Depends: R (>= 3.3.0), rgdal
Imports: diffeR, raster, ggplot2, reshape2, graphics, grDevices, stats, utils
Encoding: UTF-8
NeedsCompilation: no
LazyData: true
RoxygenNote: 6.1.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2019-03-25 18:50:58 UTC; samkh
Repository: CRAN
Date/Publication: 2019-03-29 17:40:02 UTC

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New package IndexConstruction with initial version 0.1-1
Package: IndexConstruction
Type: Package
Title: Index Construction for Time Series Data
Version: 0.1-1
Date: 2019-03-25
Author: Simon Trimborn <simon.trimborn@nus.edu.sg>
Maintainer: Simon Trimborn <simon.trimborn@nus.edu.sg>
LazyLoad: yes
LazyData: true
Depends: R (>= 2.10)
Imports: KernSmooth, fGarch, lubridate, xts, RcppBDT, zoo
Description: Derivation of indexes for benchmarking purposes. The methodology of the CRyptocurrency IndeX (CRIX) family with flexible number of constituents is implemented. Also functions for market capitalization and volume weighted indexes with fixed number of constituents are available. The methodology behind the functions provided gets introduced in Trimborn and Haerdle (2018) <doi:10.1016/j.jempfin.2018.08.004>.
License: GPL (>= 3)
NeedsCompilation: no
Packaged: 2019-03-25 02:08:44 UTC; matsim
Repository: CRAN
Date/Publication: 2019-03-29 16:50:03 UTC

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New package IMWatson with initial version 0.5.0
Package: IMWatson
Type: Package
Title: Chat with Watson's Assistant API
Version: 0.5.0
Author: Ignacio Martinez
Maintainer: Ignacio Martinez <ignacio@protonmail.com>
Description: Chat with a chatbot created with the 'IBM Watson Assistant' <https://www.ibm.com/cloud/watson-assistant/>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: httr, jsonlite, R6, assertive, magrittr, shiny, V8, shinyjs, glue, shinydashboard
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-24 19:50:48 UTC; rstudio
Repository: CRAN
Date/Publication: 2019-03-29 16:40:03 UTC

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New package BNPmix with initial version 0.1.1
Package: BNPmix
Type: Package
Title: Algorithms for Pitman-Yor Process Mixtures
Version: 0.1.1
Date: 2019-03-14
Author: Riccardo Corradin
Maintainer: Riccardo Corradin <riccardo.corradin@gmail.com>
Description: Contains different algorithms to both univariate and multivariate Pitman-Yor process mixture models, and Griffiths-Milne Dependent Dirichlet process mixture models. Pitman-Yor process mixture models are flexible Bayesian nonparametric models to deal with density estimation. Estimation could be done via importance conditional sampler, or via slice sampler, as done by Walker (2007) <doi:10.1080/03610910601096262>, or using a marginal sampler, as in Escobar and West (1995) <doi:10.2307/2291069> and extensions. The package contains also the procedures to estimate via importance conditional sampler a GM-Dependent Dirichlet process mixture model.
License: LGPL-3 | file LICENSE
NeedsCompilation: yes
Imports: methods, ggplot2
Depends: R (>= 3.3.0)
LinkingTo: RcppArmadillo, Rcpp(>= 0.12.13)
RoxygenNote: 6.1.1
Encoding: UTF-8
Packaged: 2019-03-24 15:06:11 UTC; Riccardo
Repository: CRAN
Date/Publication: 2019-03-29 16:30:03 UTC

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New package tapkee with initial version 1.0
Package: tapkee
Type: Package
Title: Wrapper for 'tapkee' Dimension Reduction Library
Version: 1.0
Date: 2019-03-22
Author: Alexey Shipunov
Maintainer: Alexey Shipunov <dactylorhiza@gmail.com>
Description: Wrapper for using 'tapkee' command line utility, it allows to run it from inside R and catch the results for further analysis and plotting. 'Tapkee' is a program for fast dimension reduction (see <http://tapkee.lisitsyn.me/> for more details).
SystemRequirements: 'tapkee' (http://tapkee.lisitsyn.me/)
Suggests: scatterplot3d, rgl
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: no
Packaged: 2019-03-22 18:39:12 UTC; alexey
Repository: CRAN
Date/Publication: 2019-03-29 15:30:03 UTC

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New package sapfluxnetr with initial version 0.0.6
Package: sapfluxnetr
Title: Working with 'Sapfluxnet' Project Data
Version: 0.0.6
Authors@R: c( person("Victor", "Granda", email = "victorgrandagarcia@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0469-1991")), person("Rafael", "Poyatos", email = "r.poyatos@creaf.uab.cat", role = "aut", comment = c(ORCID = "0000-0003-0521-2523")), person("Victor", "Flo", email = "v.flo@creaf.uab.cat", role = "aut", comment = c(ORCID = "0000-0003-1908-4577")), person("Jacob", "Nelson", email = "", role = 'ctb', comment = c(ORCID = "0000-0002-4663-2420")), person("Sapfluxnet Core Team", email = "sapfluxnet@creaf.uab.cat", role = 'cph') )
Description: Access, modify, aggregate and plot data from the 'Sapfluxnet' project (<http:sapfluxnet.creaf.cat>), the first global database of sap flow measurements.
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, furrr, ggplot2, glue, lubridate, magrittr, methods, purrr, rlang, stats, stringr, tibble, tibbletime, tidyr, utils
RoxygenNote: 6.1.1
Collate: 'data.R' 'getters.R' 'helpers.R' 'imports.R' 'metrics.R' 'sfn_data_classes.R' 'sfn_data_generics.R' 'sfn_data_methods.R' 'sfn_dplyr.R' 'visualizations.R'
Suggests: future, knitr, remotes, rmarkdown, testthat, tidyverse, xtable
VignetteBuilder: knitr
URL: https://github.com/sapfluxnet/sapfluxnetr
BugReports: https://github.com/sapfluxnet/sapfluxnetr/issues
NeedsCompilation: no
Packaged: 2019-03-13 19:08:25 UTC; malditobarbudo
Author: Victor Granda [aut, cre] (<https://orcid.org/0000-0002-0469-1991>), Rafael Poyatos [aut] (<https://orcid.org/0000-0003-0521-2523>), Victor Flo [aut] (<https://orcid.org/0000-0003-1908-4577>), Jacob Nelson [ctb] (<https://orcid.org/0000-0002-4663-2420>), Sapfluxnet Core Team [cph]
Maintainer: Victor Granda <victorgrandagarcia@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-29 15:10:03 UTC

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New package Rxnat with initial version 1.0.4
Package: Rxnat
Type: Package
Version: 1.0.4
Title: Queries and Extracts Images from Extensible Neuroimaging Archive Toolkit Public/Private Datasets
Description: Allows communication with Extensible Neuroimaging Archive Toolkit <https://www.xnat.org>. 'Rxnat' is using the 'XNAT' REST API to perform data queries and download images.
Authors@R: person("Adi", "Gherman", ,"adig@jhu.edu", c("aut", "cre"))
Maintainer: Adi Gherman <adig@jhu.edu>
Imports: RCurl, httr, utils
Suggests: testthat, knitr, rmarkdown, covr
License: GPL-2
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
BugReports: https://github.com/adigherman/Rxnat/issues
NeedsCompilation: no
Packaged: 2019-03-22 20:02:24 UTC; adi
Author: Adi Gherman [aut, cre]
Repository: CRAN
Date/Publication: 2019-03-29 15:30:06 UTC

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New package rapidxmlr with initial version 0.1.0
Package: rapidxmlr
Type: Package
Title: 'Rapidxml' C++ Header Files
Date: 2019-03-13
Version: 0.1.0
Authors@R: c( person("David", "Cooley", ,"david.cooley.au@gmail.com", role = c("aut", "cre")), person("Marcin", "Kalicinski", , role = "ctb", comment = "Author of c++ rapidxml library") )
Description: Provides XML parsing capability through the 'Rapidxml' 'C++' header-only library.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-14 07:39:26 UTC; dave
Author: David Cooley [aut, cre], Marcin Kalicinski [ctb] (Author of c++ rapidxml library)
Maintainer: David Cooley <david.cooley.au@gmail.com>
Repository: CRAN
Date/Publication: 2019-03-29 15:10:09 UTC

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New package EWOC2 with initial version 1.0
Package: EWOC2
Type: Package
Title: Escalation with Overdose Control using 2 Drug Combinations
Version: 1.0
Date: 2019-03-15
Author: Quanlin Li and Mourad Tighiouart
Maintainer: Quanlin Li <choplum@gmail.com>
Description: Implements escalation with overdose control (EWOC) trial designs using two drug combinations described by Tighiouart, Li and Rogatko (2017) <doi:10.1002/sim.6961>. It calculates the recommended dose for next cohorts and perform simulations to obtain operating characteristics.
License: GPL (>= 2)
Depends: rjags
Imports: MASS
NeedsCompilation: no
Packaged: 2019-03-20 02:25:01 UTC; liq
Repository: CRAN
Date/Publication: 2019-03-29 15:20:03 UTC

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New package dotdot with initial version 0.1.0
Package: dotdot
Type: Package
Title: Enhanced Assignment Operator to Overwrite or Grow Objects
Version: 0.1.0
Author: Antoine Fabri
Maintainer: Antoine Fabri <antoine.fabri@gmail.com>
Description: Use '..' on the right hand side of the ':=' operator as a shorthand for the left hand side, so that 'var := f(..) + ..' is equivalent to 'var <- f(var) + var'. This permits the user to be explicit about growing an object or overwriting it using its previous value, avoids repeating a variable name, and saves keystrokes, time, visual space and cognitive load.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, htmltools
NeedsCompilation: no
Packaged: 2019-03-23 22:56:57 UTC; Antoine
Repository: CRAN
Date/Publication: 2019-03-29 15:50:02 UTC

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New package clusternor with initial version 0.0-3
Package: clusternor
Version: 0.0-3
Date: 2019-03-28
Title: A Parallel Clustering Non-Uniform Memory Access ('NUMA') Optimized Package
Authors@R: c(person("Disa", "Mhembere", role = c("aut", "cre"), email = "disa@cs.jhu.edu"), person("Neurodata (https://neurodata.io)", role="cph"))
Description: The clustering 'NUMA' Optimized Routines package or 'clusternor' is a highly optimized package for performing clustering in parallel with accelerations specifically targeting multi-core Non-Uniform Memory Access ('NUMA') hardware architectures. Disa Mhembere, Da Zheng, Carey E. Priebe, Joshua T. Vogelstein, Randal Burns (2019) <arXiv:1902.09527>.
LinkingTo: Rcpp
Depends: R (>= 3.0), Rcpp (>= 0.12.8)
License: Apache License 2.0
URL: https://github.com/neurodata/knorR
SystemRequirements: GNU make C++11, pthreads
BugReports: https://github.com/flashxio/knor/issues
RoxygenNote: 6.1.1
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
Suggests: testthat
Packaged: 2019-03-29 05:47:47 UTC; disa
Author: Disa Mhembere [aut, cre], Neurodata (https://neurodata.io) [cph]
Maintainer: Disa Mhembere <disa@cs.jhu.edu>
Repository: CRAN
Date/Publication: 2019-03-29 15:40:03 UTC

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New package funcy with initial version 1.0.1
Package: funcy
Type: Package
Title: Functional Clustering Algorithms
Version: 1.0.1
Date: 2019-03-04
Authors@R: c( person(given="Christina", family="Yassouridis", email="chris.yassou@gmail.com", role=c("aut", "cre")), person(given="Dominik", family="Ernst", role="ctb"), person(given="Madison", family="Giacofci", role="ctb"), person(given="Sophie", family="Lambert-Lacroix", role="ctb"), person(given="Guillemette", family="Marot", role="ctb"), person(given="Franck", family="Picard", role="ctb"), person(given="Nicoleta", family="Serban", role="ctb"), person(given="Huijing", family="Jiang", role="ctb"), person(given="Gareth", family="James", role="ctb"), person(given="Catherine", family="Sugar", role="ctb"), person(given="Hans-Georg", family="Mueller", role="ctb"), person(given="Jie", family="Peng", role="ctb"), person(given="Chiou", family="Jeng-Min", role="ctb"), person(given="Pai-Ling", family="Li", role="ctb") )
Description: Unified framework to cluster functional data according to one of seven models. All models are based on the projection of the curves onto a basis. The main function funcit() calls wrapper functions for the existing algorithms, so that input parameters are the same. A list is returned with each entry representing the same or extended output for the corresponding method. Method specific as well as general visualization tools are available.
License: GPL-2
Depends: flexclust, splines
Imports: MASS, Matrix, fda, methods, wavethresh, kernlab, parallel, car, fields, calibrate, cluster, sm, plyr
Suggests: scatterplot3d, funHDDC, testthat
LazyLoad: yes
Encoding: UTF-8
NeedsCompilation: yes
RoxygenNote: 6.1.1
Author: Christina Yassouridis [aut, cre], Dominik Ernst [ctb], Madison Giacofci [ctb], Sophie Lambert-Lacroix [ctb], Guillemette Marot [ctb], Franck Picard [ctb], Nicoleta Serban [ctb], Huijing Jiang [ctb], Gareth James [ctb], Catherine Sugar [ctb], Hans-Georg Mueller [ctb], Jie Peng [ctb], Chiou Jeng-Min [ctb], Pai-Ling Li [ctb]
Maintainer: Christina Yassouridis <chris.yassou@gmail.com>
Repository: CRAN
Packaged: 2019-03-29 12:38:49 UTC; chris
Date/Publication: 2019-03-29 14:50:03 UTC

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New package AMR with initial version 0.6.1
Package: AMR
Version: 0.6.1
Date: 2019-03-28
Title: Antimicrobial Resistance Analysis
Authors@R: c( person( given = c("Matthijs", "S."), family = "Berends", email = "m.s.berends@umcg.nl", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-7620-1800")), person( given = c("Christian", "F."), family = "Luz", email = "c.f.luz@umcg.nl", role = "aut", comment = c(ORCID = "0000-0001-5809-5995")), person( given = c("Erwin", "E.", "A."), family = "Hassing", email = "e.hassing@certe.nl", role = "ctb"), person( given = "Corinna", family = "Glasner", email = "c.glasner@umcg.nl", role = c("aut", "ths"), comment = c(ORCID = "0000-0003-1241-1328")), person( given = c("Alex", "W."), family = "Friedrich", email = "alex.friedrich@umcg.nl", role = c("aut", "ths"), comment = c(ORCID = "0000-0003-4881-038X")), person( given = c("Bhanu", "N.", "M."), family = "Sinha", email = "b.sinha@umcg.nl", role = c("aut", "ths"), comment = c(ORCID = "0000-0003-1634-0010")))
Description: Functions to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and to work with microbial and antimicrobial properties by using evidence-based methods.
Depends: R (>= 3.1.0)
Imports: backports, crayon (>= 1.3.0), data.table (>= 1.9.0), dplyr (>= 0.7.0), ggplot2, hms, knitr (>= 1.0.0), microbenchmark, rlang (>= 0.3.1), tidyr (>= 0.7.0)
Suggests: covr (>= 3.0.1), curl, readxl, rmarkdown, rstudioapi, rvest (>= 0.3.2), testthat (>= 1.0.2), xml2 (>= 1.0.0)
VignetteBuilder: knitr
URL: https://msberends.gitlab.io/AMR, https://gitlab.com/msberends/AMR
BugReports: https://gitlab.com/msberends/AMR/issues
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-28 21:26:56 UTC; uscloud
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut] (<https://orcid.org/0000-0001-5809-5995>), Erwin E. A. Hassing [ctb], Corinna Glasner [aut, ths] (<https://orcid.org/0000-0003-1241-1328>), Alex W. Friedrich [aut, ths] (<https://orcid.org/0000-0003-4881-038X>), Bhanu N. M. Sinha [aut, ths] (<https://orcid.org/0000-0003-1634-0010>)
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>
Repository: CRAN
Date/Publication: 2019-03-29 12:00:03 UTC

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Thu, 28 Mar 2019

New package MLCM with initial version 0.4.2
Package: MLCM
Type: Package
Title: Maximum Likelihood Conjoint Measurement
Version: 0.4.2
Date: 2019-02-25
Authors@R: c(person("Ken", "Knoblauch", role = "aut", email = "ken.knoblauch@inserm.fr"), person(c("Laurence", "T."), "Maloney", role = "aut"), person("Guillermo", "Aguilar", role=c("aut", "cre"), email="guillermo.aguilar@mail.tu-berlin.de"))
Depends: R (>= 3.0), graphics, stats, utils, base
Description: Conjoint measurement is a psychophysical procedure in which stimulus pairs are presented that vary along 2 or more dimensions and the observer is required to compare the stimuli along one of them. This package contains functions to estimate the contribution of the n scales to the judgment by a maximum likelihood method under several hypotheses of how the perceptual dimensions interact. Reference: Knoblauch & Maloney (2012) "Modeling Psychophysical Data in R". <doi:10.1007/978-1-4614-4475-6>.
License: GPL (>= 2)
LazyData: yes
Packaged: 2019-03-28 16:20:47 UTC; guille
Author: Ken Knoblauch [aut], Laurence T. Maloney [aut], Guillermo Aguilar [aut, cre]
Maintainer: Guillermo Aguilar <guillermo.aguilar@mail.tu-berlin.de>
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2019-03-28 23:30:03 UTC

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Wed, 27 Mar 2019

New package RWsearch with initial version 4.5
Package: RWsearch
Title: Lazy Search in R Packages, Task Views, CRAN, the Web. All-in-One Download
Description: Search by keywords in R packages, task views, CRAN, the web and display the results in console, txt, html or pdf pages. Within a single instruction, download the whole documentation (html index, pdf manual, vignettes, source code, etc), either in a flat format or in subdirectories defined by the keywords. Several functions for task view maintenance. Quick links to more than 60 web search engines. Lazy evaluation of non-standard content is available throughout the package and eases the use of many functions.
Version: 4.5
Date: 2019-03-27
Depends: R (>= 3.4.0)
Imports: brew, latexpdf, sig, sos
Suggests: ctv, cranly, findR, foghorn, knitr, pacman, pkgnet, rmarkdown
License: GPL-2
Maintainer: Patrice Kiener <fattailsr@inmodelia.com>
Author: Patrice Kiener [aut, cre] (<https://orcid.org/0000-0002-0505-9920>)
Encoding: UTF-8
NeedsCompilation: no
LazyData: false
Language: en-GB
VignetteBuilder: knitr
RoxygenNote: 6.1.1
Packaged: 2019-03-27 08:41:55 UTC; patrice
Repository: CRAN
Date/Publication: 2019-03-27 09:40:03 UTC

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Tue, 26 Mar 2019

New package SemNetDictionaries with initial version 0.1.1
Package: SemNetDictionaries
Title: Dictionaries for the 'SemNetCleaner' Package
Version: 0.1.1
Date: 2019-03-26
Author: Alexander P. Christensen
Maintainer: Alexander P. Christensen <alexpaulchristensen@gmail.com>
Description: Implements dictionaries that can be used in the 'SemNetCleaner' package. Also includes several functions aimed at facilitating the text cleaning analysis in the 'SemNetCleaner' package. This package is designed to integrate and update word lists and dictionaries based on each user's individual needs by allowing users to store and save their own dictionaries. Dictionaries can be added to the 'SemNetDictionaries' package by submitting user-defined dictionaries to <https://github.com/AlexChristensen/SemNetDictionaries>.
Depends: R (>= 3.3.0)
License: GPL (>= 3.0)
URL: https://github.com/AlexChristensen/SemNetDictionaries
BugReports: https://github.com/AlexChristensen/SemNetDictionaries/issues
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
Imports: tcltk
RoxygenNote: 6.1.1
Packaged: 2019-03-26 17:00:14 UTC; APCHRIST
Repository: CRAN
Date/Publication: 2019-03-26 17:23:21 UTC

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New package geneHummus with initial version 1.0.1
Package: geneHummus
Title: A Pipeline to Define Gene Families in Legumes and Beyond
Version: 1.0.1
Authors@R: c( person("Jose V.", "Die", email = "jose.die@uco.es", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7506-8590")), person("Moamen M.", "Elmassry", email = "moamen.elmassry@ttu.edu", role = c("aut")), person("Kimberly H.", "LeBlanc", email = "kimberly.leblanc@nih.gov", role = c("aut")), person("Olaitan I.", "Awe", email = "laitanawe@gmail.com", role = c("aut")), person("Allissa","Dillman", email = "Allissa.Dillman@nih.gov", role = c("aut")), person("Ben", "Busby", email = "Ben.Busby@nih.gov", role = c("aut")))
Description: A pipeline with high specificity and sensitivity in extracting proteins from the RefSeq database (National Center for Biotechnology Information). Manual identification of gene families is highly time-consuming and laborious, requiring an iterative process of manual and computational analysis to identify members of a given family. The pipelines implements an automatic approach for the identification of gene families based on the conserved domains that specifically define that family. See Die et al. (2017) <doi:10.1101/436659> for more information and examples.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: rentrez (>= 1.2.1), stringr (>= 1.4.0), dplyr (>= 0.8.0.1), httr (>= 1.4.0), utils, curl (>= 3.3)
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.1
URL: https://github.com/NCBI-Hackathons/GeneHummus
BugReports: https://github.com/NCBI-Hackathons/GeneHummus/issues
NeedsCompilation: no
Packaged: 2019-03-26 13:22:47 UTC; josedie
Author: Jose V. Die [aut, cre] (<https://orcid.org/0000-0002-7506-8590>), Moamen M. Elmassry [aut], Kimberly H. LeBlanc [aut], Olaitan I. Awe [aut], Allissa Dillman [aut], Ben Busby [aut]
Maintainer: Jose V. Die <jose.die@uco.es>
Repository: CRAN
Date/Publication: 2019-03-26 15:20:03 UTC

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Mon, 25 Mar 2019

New package dfConn with initial version 0.1.1
Package: dfConn
Type: Package
Title: Dynamic Functional Connectivity Analysis
Version: 0.1.1
Authors@R: c(person("Zikai", "Lin", email = "ziklin@iu.edu", role = c("aut", "cre")), person("Maria", "Kudela", email = "maria.kudela@gmail.com", role = c("aut")), person("Jaroslaw","Harezlak",email = "harezlak@iu.edu", role = c("aut")), person("Mario","Dzemidzic", email = "mdzemidz@iupui.edu", role = c("aut")))
Maintainer: Zikai Lin <ziklin@iu.edu>
Description: An implementation of multivariate linear process bootstrap (MLPB) method and sliding window technique to assess the dynamic functional connectivity (dFC) estimate by providing its confidence bands, based on Maria Kudela (2017) <doi: 10.1016/j.neuroimage.2017.01.056>. It also integrates features to visualize non-zero coverage for selected a-priori regions of interest estimated by the dynamic functional connectivity model (dFCM) and dynamic functional connectivity (dFC) curves for reward-related a-priori regions of interest where the activation-based analysis reported.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Suggests: iterators, testthat, itertools, mgcv, latex2exp
Imports: doParallel, nlme, parallel, foreach, ggplot2, fields, gplots, splines, stats, stringr, graphics, data.table, gtools, Rcpp (>= 0.12.18)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-03-25 19:38:03 UTC; ziklin
Author: Zikai Lin [aut, cre], Maria Kudela [aut], Jaroslaw Harezlak [aut], Mario Dzemidzic [aut]
Repository: CRAN
Date/Publication: 2019-03-25 22:33:20 UTC

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New package lgr with initial version 0.2.1
Type: Package
Package: lgr
Title: A Fully Featured Logging Framework
Version: 0.2.1
Authors@R: person(given = "Stefan", family = "Fleck", role = c("aut", "cre"), email = "stefan.b.fleck@gmail.com", comment = c(ORCID = "0000-0003-3344-9851"))
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>
Description: A flexible, feature-rich yet light-weight logging framework based on 'R6' classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, 'JSON', memory buffers, and databases, as well as email and push notifications. For a full list of features with examples please refer to the package vignette.
License: MIT + file LICENSE
URL: https://github.com/s-fleck/lgr
BugReports: https://github.com/s-fleck/lgr/issues
Imports: R6 (>= 2.4.0)
Suggests: covr, crayon, data.table, DBI, desc, future, future.apply, glue, gmailr, jsonlite, knitr, rmarkdown, sendmailR, RSQLite, RMariaDB, RPostgres, RMySQL, RPostgreSQL, rprojroot, testthat, tibble, tools, utils, whoami, yaml
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Collate: 'Filterable.R' 'utils-sfmisc.R' 'utils.R' 'Appender.R' 'Filter.R' 'log_levels.R' 'print_LogEvent.R' 'Layout.R' 'LogEvent.R' 'Logger.R' 'default_functions.R' 'get_logger.R' 'lgr-package.R' 'logger_config.R' 'print_Logger.R' 'read_json_log.R' 'simple_logging.R' 'test.R' 'use_logger.R' 'utils-formatting.R' 'utils-logging.R' 'utils-rd.R'
NeedsCompilation: no
Packaged: 2019-03-25 11:46:20 UTC; fleck
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Repository: CRAN
Date/Publication: 2019-03-25 15:40:03 UTC

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New package dydea with initial version 0.1.0
Package: dydea
Type: Package
Title: Detection of Chaotic and Regular Intervals in the Data
Version: 0.1.0
Authors@R: person("Radek", "Halfar", email = "radek.halfar@vsb.cz", role = c("aut", "cre"))
Description: Finds regular and chaotic intervals in the data using the 0-1 test for chaos proposed by Gottwald and Melbourne (2004) <DOI:10.1137/080718851>.
Depends: R (>= 3.5.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Imports: Chaos01
RoxygenNote: 6.1.1
Packaged: 2019-03-22 12:14:11 UTC; radek
Author: Radek Halfar [aut, cre]
Maintainer: Radek Halfar <radek.halfar@vsb.cz>
Repository: CRAN
Date/Publication: 2019-03-25 11:00:03 UTC

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New package latte with initial version 0.2.1
Package: latte
Type: Package
Title: Interface to 'LattE' and '4ti2'
Version: 0.2.1
Authors@R: c(person("David", "Kahle", email = "david@kahle.io", role = c("aut", "cph", "cre"), comment = c(ORCID = "0000-0002-9999-1558")), person("Luis", "Garcia",email = "lgarcia@shsu.edu", role = c("aut", "cph")), person("Ruriko", "Yoshida", email = "ryoshida@nps.edu", role = c("aut", "cph")))
Maintainer: David Kahle <david@kahle.io>
Description: Back-end connections to 'LattE' (<https://www.math.ucdavis.edu/~latte>) for counting lattice points and integration inside convex polytopes and '4ti2' (<http://www.4ti2.de/>) for algebraic, geometric, and combinatorial problems on linear spaces and front-end tools facilitating their use in the 'R' ecosystem.
License: GPL-2
URL: https://github.com/dkahle/latte
BugReports: https://github.com/dkahle/latte/issues
LazyData: TRUE
SystemRequirements: LattE <https://www.math.ucdavis.edu/~latte/>, 4ti2 <http://www.4ti2.de/>
Imports: magrittr, stringr, mpoly, ggplot2, memoise, dplyr, usethis, glue
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2019-03-22 00:34:52 UTC; david_kahle
Author: David Kahle [aut, cph, cre] (<https://orcid.org/0000-0002-9999-1558>), Luis Garcia [aut, cph], Ruriko Yoshida [aut, cph]
Repository: CRAN
Date/Publication: 2019-03-25 10:50:03 UTC

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New package quiddich with initial version 1.0.0
Package: quiddich
Type: Package
Title: QUick IDentification of DIagnostic CHaracters
Version: 1.0.0
Date: 2019-03-21
Author: A. Luise Kuehn
Maintainer: A. Luise Kuehn <luise.kuehn@uni-greifswald.de>
Description: Provides tools for an automated identification of diagnostic molecular characters, i.e. such columns in a given nucleotide or amino acid alignment that allow to distinguish taxa from each other. These characters can then be used to complement the formal descriptions of the taxa, which are often based on morphological and anatomical features. Especially for morphologically cryptic species, this will be helpful. QUIDDICH distinguishes between four different types of diagnostic characters. For more information, see "Kuehn, A.L., Haase, M. 2019. QUIDDICH: QUick IDentification of DIagnostic CHaracters."
Depends: ape(>= 5.2), R(>= 0.12.0)
Suggests: spider, adegenet
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-21 10:19:35 UTC; Luise
Repository: CRAN
Date/Publication: 2019-03-25 09:30:03 UTC

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New package geneHummus with initial version 1.0.0
Package: geneHummus
Title: A Pipeline to Define Gene Families in Legumes and Beyond
Version: 1.0.0
Authors@R: c( person("Jose V.", "Die", email = "jose.die@uco.es", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7506-8590")), person("Moamen M.", "Elmassry", email = "moamen.elmassry@ttu.edu", role = c("aut")), person("Kimberly H.", "LeBlanc", email = "kimberly.leblanc@nih.gov", role = c("aut")), person("Olaitan I.", "Awe", email = "laitanawe@gmail.com", role = c("aut")), person("Allissa","Dillman", email = "Allissa.Dillman@nih.gov", role = c("aut")), person("Ben", "Busby", email = "Ben.Busby@nih.gov", role = c("aut")))
Description: A pipeline with high specificity and sensitivity in extracting proteins from the RefSeq database (National Center for Biotechnology Information). Manual identification of gene families is highly time-consuming and laborious, requiring an iterative process of manual and computational analysis to identify members of a given family. The pipelines implements an automatic approach for the identification of gene families based on the conserved domains that specifically define that family. See Die et al. (2017) <doi:10.1101/436659> for more information and examples.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: rentrez, stringr, dplyr, httr, utils
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.1
URL: https://github.com/NCBI-Hackathons/GeneHummus
NeedsCompilation: no
Packaged: 2019-03-20 17:41:05 UTC; josedie
Author: Jose V. Die [aut, cre] (<https://orcid.org/0000-0002-7506-8590>), Moamen M. Elmassry [aut], Kimberly H. LeBlanc [aut], Olaitan I. Awe [aut], Allissa Dillman [aut], Ben Busby [aut]
Maintainer: Jose V. Die <jose.die@uco.es>
Repository: CRAN
Date/Publication: 2019-03-25 09:10:07 UTC

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New package encryptr with initial version 0.1.2
Package: encryptr
Type: Package
Title: Easily Encrypt and Decrypt Data Frame or Tibble Columns using RSA Public/Private Keys
Version: 0.1.2
Authors@R: c( person(given = "Cameron", family = "Fairfield", role = c("aut"), email = "cameron.fairfield@ed.ac.uk"), person(given = "Riinu", family = "Ots", role = c("aut")), person(given = "Stephen", family = "Knight", role = c("aut")), person(given = "Tom", family = "Drake", role = c("aut")), person(given = "Ewen", family = "Harrison", role = c("aut", "cre"), email = "ewen.harrison@ed.ac.uk") )
Maintainer: Ewen Harrison <ewen.harrison@ed.ac.uk>
Description: It is important to ensure that sensitive data is protected. This straightforward package is aimed at the end-user. Strong RSA encryption using a public/private key pair is used to encrypt data frame or tibble columns. A public key can be shared to allow others to encrypt data to be sent to you. This is particularly aimed a healthcare settings so patient data can be pseudonymised.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/SurgicalInformatics/encryptr/issues
URL: https://github.com/SurgicalInformatics/encryptr
Imports: dplyr, knitr, openssl, purrr, readr, rlang
RoxygenNote: 6.1.0
Suggests: testthat, withr
NeedsCompilation: no
Packaged: 2019-03-21 10:20:41 UTC; eharrison
Author: Cameron Fairfield [aut], Riinu Ots [aut], Stephen Knight [aut], Tom Drake [aut], Ewen Harrison [aut, cre]
Repository: CRAN
Date/Publication: 2019-03-25 09:40:03 UTC

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New package clustcurv with initial version 1.0.0
Package: clustcurv
Type: Package
Title: Determining Groups in Multiples Curves
URL: https://github.com/noramvillanueva/clustcurv
BugReports: http://github.com/noramvillanueva/clustcurv/issues
Version: 1.0.0
Date: 2019-03-15
Maintainer: Nora M. Villanueva <nmvillanueva@uvigo.es>
Authors@R: c(person("Nora", "M. Villanueva",email= "nmvillanueva@uvigo.es", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8085-2745")), person("Marta", "Sestelo",email= "sestelo@uvigo.es", role = "aut"))
Description: A method for determining groups in multiple survival curves with an automatic selection of their number based on k-means or k-medians algorithms. The selection of the optimal number is provided by bootstrap methods. Implemented methods are: Grouping multiple survival curves described by Villanueva et al. (2018) <doi:10.1002/sim.8016>.
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: doParallel, foreach, ggplot2, ggfortify, doRNG, Gmedian, survival, wesanderson
Suggests: testthat, usethis, condSURV
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-20 18:34:47 UTC; nora
Author: Nora M. Villanueva [aut, cre] (<https://orcid.org/0000-0001-8085-2745>), Marta Sestelo [aut]
Repository: CRAN
Date/Publication: 2019-03-25 09:23:23 UTC

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Sun, 24 Mar 2019

New package rocTree with initial version 1.0.0
Package: rocTree
Title: Receiver Operating Characteristic (ROC)-Guided Classification and Survival Tree
Version: 1.0.0
Authors@R: c(person("Yifei", "Sun", email = "ys3072@cumc.columbia.edu", role = "aut"), person("Mei-Cheng", "Wang", email = "mcwang@jhu.edu", role = "aut"), person("Sy Han", "Chiou", email = "schiou@utdallas.edu", role = c("aut", "cre")))
Description: Receiver Operating Characteristic (ROC)-guided survival trees and forests algorithms are implemented, providing a unified framework for tree-structured analysis with censored survival outcomes. A time-invariant partition scheme on the survivor population was considered to incorporate time-dependent covariates. Motivated by ideas of randomized tests, generalized time-dependent ROC curves were used to evaluate the performance of survival trees and establish the optimality of the target hazard function. The optimality of the target hazard function motivates us to use a weighted average of the time-dependent area under the curve (AUC) on a set of time points to evaluate the prediction performance of survival trees and to guide splitting and pruning. A detailed description of the implemented methods can be found in Sun et al. (2019) <arXiv:1809.05627>.
Depends: R (>= 3.4.0)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: DiagrammeR (>= 1.0.0), parallel, data.tree (>= 0.7.5), graphics, stats, survival (>= 2.38), methods, tibble, dplyr, ggplot2, MASS, flexsurv
URL: http://github.com/stc04003/rocTree
BugReports: http://github.com/stc04003/rocTree/issues
NeedsCompilation: yes
Packaged: 2019-03-20 16:21:55 UTC; schiou
Author: Yifei Sun [aut], Mei-Cheng Wang [aut], Sy Han Chiou [aut, cre]
Maintainer: Sy Han Chiou <schiou@utdallas.edu>
Repository: CRAN
Date/Publication: 2019-03-24 19:50:02 UTC

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New package legocolors with initial version 0.1.2
Package: legocolors
Title: Official Lego Color Palettes
Version: 0.1.2
Authors@R: person(given = "Matthew", family = "Leonawicz", role = c("aut", "cre"), email = "matt_leonawicz@esource.com")
Description: Provides a dataset containing several color naming conventions established by multiple sources, along with associated color metadata. The package also provides related helper functions for mapping among the different Lego color naming conventions and between Lego colors, hex colors, and 'R' color names. The functions include nearest color matching based on Euclidean distance in RGB space. Naming conventions for color mapping include those from 'BrickLink' (<https://www.bricklink.com>), 'The Lego Group' (<https://www.lego.com>), 'LDraw' (<https://www.ldraw.org/>), and 'Peeron' (<http://www.peeron.com/>).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/leonawicz/legocolors
BugReports: https://github.com/leonawicz/legocolors/issues
Depends: R (>= 2.10)
Suggests: testthat, covr
Language: en-US
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-03-20 14:20:53 UTC; Matt
Author: Matthew Leonawicz [aut, cre]
Maintainer: Matthew Leonawicz <matt_leonawicz@esource.com>
Repository: CRAN
Date/Publication: 2019-03-24 19:10:03 UTC

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New package ideamdb with initial version 0.0.9
Package: ideamdb
Type: Package
Title: Easy Manipulation of IDEAM's Climatological Data
Version: 0.0.9
Authors@R: c( person("Luz Maria", "Morales", email = "lummoralesgo@unal.edu.co", role = c("aut", "cre")), person("Edwin", "Echeverri", email = "eecheverris@unal.edu.co", role = "aut"), person("Kenneth Roy", "Cabrera", email = "krcabrer@unal.edu.co", role = "aut"))
Description: Time series plain text conversion and data visualization. It allows to transform IDEAM (Instituto de Hidrologia, Meteorologia y Estudios Ambientales) daily series from plain text to CSV files or data frames in R. Additionally, it is possible to obtain exploratory graphs from times series. IDEAM’s data is freely delivered under formal request through the official web page <http://www.ideam.gov.co/solicitud-de-informacion>.
License: GPL (>= 2)
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.1
Imports: stringr, tidyr, dplyr, ggplot2, utils, graphics
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2019-03-20 04:29:06 UTC; ees_o
Author: Luz Maria Morales [aut, cre], Edwin Echeverri [aut], Kenneth Roy Cabrera [aut]
Maintainer: Luz Maria Morales <lummoralesgo@unal.edu.co>
Repository: CRAN
Date/Publication: 2019-03-24 19:10:06 UTC

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