CRANberries

Sun, 14 Oct 2018

New package SAVER with initial version 1.1.1
Package: SAVER
Type: Package
Version: 1.1.1
Title: Single-Cell RNA-Seq Gene Expression Recovery
Description: An implementation of a regularized regression prediction and empirical Bayes method to recover the true gene expression profile in noisy and sparse single-cell RNA-seq data. See Huang M, et al (2018) <doi:10.1038/s41592-018-0033-z> for more details.
Authors@R: c( person("Mo", "Huang", email = "mohuangx@gmail.com", role = c("aut", "cre")), person("Nancy", "Zhang", email = "nzh@wharton.upenn.edu", role = "aut"), person("Mingyao", "Li", email = "mingyao@pennmedicine.upenn.edu", role = "aut") )
Maintainer: Mo Huang <mohuangx@gmail.com>
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.1)
Imports: glmnet, foreach, methods, iterators, doParallel, Matrix
RoxygenNote: 6.1.0
URL: https://github.com/mohuangx/SAVER
BugReports: https://github.com/mohuangx/SAVER/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-27 18:16:18 UTC; mohuang
Author: Mo Huang [aut, cre], Nancy Zhang [aut], Mingyao Li [aut]
Repository: CRAN
Date/Publication: 2018-10-14 17:20:10 UTC

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New package rocsvm.path with initial version 0.1.0
Package: rocsvm.path
Type: Package
Title: The Entire Solution Paths for ROC-SVM
Version: 0.1.0
Authors@R: c(person("Seung Jun", "Shin", email = "sjshin@korea.ac.kr", role = c("aut","cre")),person("Do Hyun", "Kim", email = "09dohkim@gmail.com", role = c("aut")))
Description: We develop the entire solution paths for ROC-SVM presented by Rakotomamonjy. The ROC-SVM solution path algorithm greatly facilitates the tuning procedure for regularization parameter, lambda in ROC-SVM by avoiding grid search algorithm which may be computationally too intensive. For more information on the ROC-SVM, see the report in the ROC Analysis in AI workshop(ROCAI-2004) : Hernàndez-Orallo, José, et al. (2004) <doi:10.1145/1046456.1046489>.
Imports: quadprog, svmpath
Depends: R (>= 3.4.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Maintainer: Seung Jun Shin <sjshin@korea.ac.kr>
Packaged: 2018-10-07 00:50:22 UTC; KimDoHyun
Author: Seung Jun Shin [aut, cre], Do Hyun Kim [aut]
Repository: CRAN
Date/Publication: 2018-10-14 17:30:03 UTC

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New package PDFEstimator with initial version 0.1-0
Package: PDFEstimator
Version: 0.1-0
Date: 2018-09-24
Title: Nonparametric Probability Density Estimator
Author: Jenny Farmer <jfarmer6@uncc.edu> and Donald Jacobs <djacobs1@uncc.ecu>
Maintainer: Jenny Farmer <jfarmer6@uncc.edu>
Description: 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: 2018-10-05 15:04:11 UTC; jenny
Repository: CRAN
Date/Publication: 2018-10-14 17:20:15 UTC

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New package nvmix with initial version 0.0-1
Package: nvmix
Version: 0.0-1
Encoding: UTF-8
Title: Multivariate Normal Variance Mixtures (Including Student's t Distribution for Non-Integer Degrees of Freedom)
Description: Functions for working with multivariate normal variance mixture distributions including evaluating their distribution functions, densities and random number generation.
Authors@R: c(person(given = "Marius", family = "Hofert", role = c("aut", "cre"), email = "marius.hofert@uwaterloo.ca"), person(given = "Erik", family = "Hintz", role = "aut", email = "erik.hintz@uwaterloo.ca"), person(given = "Christiane", family = "Lemieux", role = "aut", email = "clemieux@uwaterloo.ca"))
Author: Marius Hofert [aut, cre], Erik Hintz [aut], Christiane Lemieux [aut]
Maintainer: Marius Hofert <marius.hofert@uwaterloo.ca>
Depends: R (>= 3.2.0)
Imports: stats, methods, qrng
Suggests: knitr, RColorBrewer, lattice
Enhances:
License: GPL (>= 3) | file LICENCE
NeedsCompilation: yes
VignetteBuilder: knitr
Repository: CRAN
Date/Publication: 2018-10-14 17:20:03 UTC
Packaged: 2018-10-07 15:58:51 UTC; mhofert

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New package nprotreg with initial version 1.0.0
Package: nprotreg
Title: Nonparametric Rotations for Sphere-Sphere Regression
Version: 1.0.0
Authors@R: c( person(c("Charles","C."), "Taylor", email = "charles@maths.leeds.ac.uk", role = c("aut")), person("Giovanni", "Lafratta", email = "giovanni.lafratta@unich.it", role = c("aut", "cre")), person("Stefania", "Fensore", email = "stefania.fensore@unich.it", role = c("aut")))
Description: Fits sphere-sphere regression models by estimating locally weighted rotations. Simulation of sphere-sphere data according to non-rigid rotation models. Provides methods for bias reduction applying iterative procedures within a Newton-Raphson learning scheme. Cross-validation is exploited to select smoothing parameters. See Marco Di Marzio, Agnese Panzera & Charles C. Taylor (2018) <doi:10.1080/01621459.2017.1421542>.
Depends: R (>= 3.3.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.1
Suggests: testthat
Imports: methods, expm, stats
NeedsCompilation: no
Packaged: 2018-10-05 11:52:07 UTC; giova
Author: Charles C. Taylor [aut], Giovanni Lafratta [aut, cre], Stefania Fensore [aut]
Maintainer: Giovanni Lafratta <giovanni.lafratta@unich.it>
Repository: CRAN
Date/Publication: 2018-10-14 17:20:06 UTC

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New package Immigrate with initial version 0.0.1
Package: Immigrate
Title: Iterative Max-Min Entropy Margin-Maximization with Interaction Terms for Feature Selection
Version: 0.0.1
Author: Ruzhang Zhao, Pengyu Hong, Jun S. Liu
Description: Based on large margin principle, this package performs feature selection methods: "IM4E"(Iterative Margin-Maximization under Max-Min Entropy Algorithm); "imIM4E"(imbalance Iterative Margin-Maximization under Max-Min Entropy Algorithm); "Immigrate"(Iterative Max-Min Entropy Margin-Maximization with Interaction Terms Algorithm); "Simba"(Iterative Search Margin Based Algorithm); "LFE"(Local Feature Extraction Algorithm). This package also performs prediction for the above feature selection methods.
Maintainer: Ruzhang Zhao<zrz6787@gmail.com>
Depends: R (>= 3.0.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0.9000
LinkingTo: Rcpp
Imports: Rcpp, pROC
NeedsCompilation: yes
Packaged: 2018-10-06 13:06:38 UTC; zhaoruzhang
Repository: CRAN
Date/Publication: 2018-10-14 17:20:18 UTC

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New package classyfireR with initial version 0.1.1
Package: classyfireR
Type: Package
Title: R Interface to the ClassyFire RESTful API
Version: 0.1.1
Date: 2018-10-05
Authors@R: c( person("Tom", "Wilson", , "tpw2@aber.ac.uk", c("aut", "cre")))
Description: Access to the ClassyFire RESTful API <http://classyfire.wishartlab.com>. Retrieve existing entity classifications and submit new entities for classification.
Depends: magrittr
Imports: httr, jsonlite, tibble, crayon, clisymbols
Suggests: testthat, covr, dplyr, purrr, tidyr
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
URL: https://github.com/wilsontom/classyfireR
BugReports: https://github.com/wilsontom/classyfireR/issues
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-05 10:03:50 UTC; tom
Author: Tom Wilson [aut, cre]
Maintainer: Tom Wilson <tpw2@aber.ac.uk>
Repository: CRAN
Date/Publication: 2018-10-14 17:10:02 UTC

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New package carbonate with initial version 0.1.0
Package: carbonate
Title: Interact with 'carbon.js'
Version: 0.1.0
Authors@R: person(given = "Jonathan", family = "Sidi", email = "yonicd@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4222-1819"))
Description: Create beautiful images of source code using 'carbon.js'<https://carbon.now.sh/about>.
Depends: R (>= 3.2.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: R6, clipr, magick, wdman, RSelenium, utils, httr, rtweet, yaml
Suggests: testthat, covr, knitr, rmarkdown
URL: https://github.com/yonicd/carbonate
BugReports: https://github.com/yonicd/carbonate/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-05 15:43:20 UTC; yonis
Author: Jonathan Sidi [aut, cre] (<https://orcid.org/0000-0002-4222-1819>)
Maintainer: Jonathan Sidi <yonicd@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-14 17:10:05 UTC

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New package ssdtools with initial version 0.0.2
Package: ssdtools
Version: 0.0.2
Date: 2018-10-04
Title: Species Sensitivity Distributions
Description: Fits and plots species sensitivity distributions using maximum likelihood and information-theoretic-based model averaging.
Authors@R: c( person("Joe", "Thorley", email = "joe@poissonconsulting.ca", role = c("aut", "cre", "ctr"), comment = c(ORCID = "0000-0002-7683-4592")), person("Carl", "Schwarz", role = c("aut", "ctr")), person("Ali", "Azizishirazi", email = "Ali.Azizishirazi@gov.bc.ca", role = "ctb"), person("Angeline", "Tillmanns", role = "ctb"), person("Stephanie", "Hazlitt", role = "ctb"), person("Province of British Columbia", role = "cph") )
License: Apache License (== 2.0) | file LICENSE
URL: https://github.com/bcgov/ssdca
BugReports: https://github.com/bcgov/ssdca/issues
Depends: R (>= 3.4.0), graphics, stats, VGAM, ggplot2, fitdistrplus
Imports: actuar, checkr, dplyr, FAdist, grid, magrittr, plyr, pryr, purrr, tibble, scales
Suggests: covr, knitr, rmarkdown, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-05 02:20:52 UTC; joe
Author: Joe Thorley [aut, cre, ctr] (<https://orcid.org/0000-0002-7683-4592>), Carl Schwarz [aut, ctr], Ali Azizishirazi [ctb], Angeline Tillmanns [ctb], Stephanie Hazlitt [ctb], Province of British Columbia [cph]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>
Repository: CRAN
Date/Publication: 2018-10-14 16:50:03 UTC

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New package scoper with initial version 0.1.0
Package: scoper
Type: Package
Version: 0.1.0
Date: 2018-10-04
Authors@R: c(person("Nima", "Nouri", role=c("aut", "cre"), email="nima.nouri@yale.edu"), person("Jason", "Vander Heiden", role=c("ctb"), email="jason.vanderheiden@yale.edu"), person("Steven", "Kleinstein", role=c("aut", "cph"), email="steven.kleinstein@yale.edu"))
Title: Spectral Clustering-Based Method for Identifying B Cell Clones
Description: Provides a computational framework for unsupervised identification B cell clones from adaptive immune receptor repertoire sequencing (AIRR-Seq) datasets. This method is based on spectral clustering of the junction sequences of B cell receptors (BCRs, also referred to as Immunoglobulins, (Igs)) that share the same V gene, J gene and junction length.
License: CC BY-SA 4.0
URL: https://scoper.readthedocs.io
BugReports: https://bitbucket.org/kleinstein/scoper/issues
LazyData: true
BuildVignettes: true
VignetteBuilder: knitr
Encoding: UTF-8
Depends: R (>= 3.1.2), ggplot2 (>= 2.0.0)
Imports: alakazam (>= 0.2.11), shazam (>= 0.1.10), doParallel, foreach, dplyr (>= 0.7.0), stringi, methods, stats, iterators, lazyeval
Suggests: knitr, rmarkdown, testthat
RoxygenNote: 6.1.0
Collate: 'Data.R' 'Scoper.R' 'Functions.R'
NeedsCompilation: no
Packaged: 2018-10-04 20:58:03 UTC; nima
Author: Nima Nouri [aut, cre], Jason Vander Heiden [ctb], Steven Kleinstein [aut, cph]
Maintainer: Nima Nouri <nima.nouri@yale.edu>
Repository: CRAN
Date/Publication: 2018-10-14 17:00:03 UTC

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New package pubchunks with initial version 0.1.0
Package: pubchunks
Title: Fetch Sections of XML Scholarly Articles
Description: Get chunks of XML scholarly articles without having to know how to work with XML. Custom mappers for each publisher and for each article section pull out the information you want. Works with outputs from package 'fulltext', 'xml2' package documents, and file paths to XML documents.
Version: 0.1.0
License: MIT + file LICENSE
Authors@R: c( person("Scott", "Chamberlain", role = c("aut", "cre"), email = "sckott@protonmail.com", comment = c(ORCID = "0000-0003-1444-9135")) )
URL: https://github.com/ropensci/pubchunks
BugReports: https://github.com/ropensci/pubchunks/issues
Encoding: UTF-8
Language: en-US
Imports: xml2 (>= 1.1.1), data.table
Suggests: fulltext (>= 1.0.1), testthat
RoxygenNote: 6.1.0
X-schema.org-applicationCategory: Literature
X-schema.org-keywords: text-ming, literature, pdf, xml, publications, citations, full-text, TDM
X-schema.org-isPartOf: https://ropensci.org
NeedsCompilation: no
Packaged: 2018-10-04 20:07:53 UTC; sckott
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <sckott@protonmail.com>
Repository: CRAN
Date/Publication: 2018-10-14 16:50:07 UTC

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New package Omisc with initial version 0.1.0
Package: Omisc
Type: Package
Title: Univariate Bootstrapping and Other Things
Version: 0.1.0
Author: Patrick O'Keefe
Maintainer: Patrick O'Keefe <patrick.okeefe@vanderbilt.edu>
Description: Primarily devoted to implementing the Univariate Bootstrap (as well as the Traditional Bootstrap). In addition there are multiple functions for DeFries-Fulker behavioral genetics models. The univariate bootstrapping functions, DeFries-Fulker functions, regression and traditional bootstrapping functions form the original core. Additional features may come online later, however this software is a work in progress. For more information about univariate bootstrapping see: Lee and Rodgers (1998) and Beasley et al (2007) <doi.org/10.1037/1082-989X.12.4.414>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: MASS, base, stats, psych
Suggests: lavaan
NeedsCompilation: no
Packaged: 2018-10-04 14:37:12 UTC; Patrick
Repository: CRAN
Date/Publication: 2018-10-14 16:50:12 UTC

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New package nasapower with initial version 1.0.1
Package: nasapower
Type: Package
Title: 'NASA' 'POWER' 'API' Client
Version: 1.0.1
Authors@R: c( person("Adam H.", "Sparks", role = c("aut", "cre"), email = "adamhsparks@gmail.com", comment = c(ORCID = "0000-0002-0061-8359")), person("Scott", "Chamberlain", role = "rev", email = "myrmecocystus@gmail.com", comment = c(ORCID = "0000-0003-1444-9135")), person("Hazel", "Kavili", role = "rev"), person("Alison", "Boyer", role = "rev"))
URL: https://github.com/ropensci/nasapower
BugReports: https://github.com/ropensci/nasapower/issues
Description: Client for 'NASA' 'POWER' global meteorology, surface solar energy and climatology data 'API'. 'POWER' (Prediction Of Worldwide Energy Resource) data are freely available global meteorology and surface solar energy climatology data for download with a resolution of 0.5 by 0.5 arc degree longitude and latitude and are funded through the 'NASA' Earth Science Directorate Applied Science Program. For more on the data themselves and a web-based data viewer and access, please see <https://power.larc.nasa.gov/>.
Depends: R (>= 3.2.0)
License: MIT + file LICENSE
Imports: APSIM, crul, curl, dplyr, lubridate, jsonlite, readr, tibble, utils
RoxygenNote: 6.1.0
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
LazyData: TRUE
ByteCompile: TRUE
Suggests: covr, ggplot2, knitr, raster, rmarkdown, testthat, vcr
VignetteBuilder: knitr
X-schema.org-applicationCategory: Tools
X-schema.org-keywords: NASA, meteorological-data, weather, global, weather, weather-data, meteorology, NASA-POWER, agroclimatology, earth-science, data-access
X-schema.org-isPartOf: https://ropensci.org
Packaged: 2018-10-04 08:49:44 UTC; adamsparks
Author: Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Scott Chamberlain [rev] (<https://orcid.org/0000-0003-1444-9135>), Hazel Kavili [rev], Alison Boyer [rev]
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>
Date/Publication: 2018-10-14 16:10:03 UTC

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New package jsonify with initial version 0.1.1
Package: jsonify
Type: Package
Title: Converts 'R' Objects to Javascript Object Notation (JSON)
Version: 0.1.1
Date: 2018-10-04
Authors@R: c( person("David", "Cooley", ,"dcooley@symbolix.com.au", role = c("aut", "cre")) )
Description: Converts 'R' objects into Javascript Object Notation (JSON) using the 'rapidjsonr' library <https://CRAN.R-project.org/package=rapidjsonr>.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.18), rapidjsonr
LinkingTo: Rcpp, rapidjsonr
RoxygenNote: 6.1.0
Suggests: microbenchmark, jsonlite, testthat, covr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2018-10-10 08:04:35 UTC; dave
Author: David Cooley [aut, cre]
Maintainer: David Cooley <dcooley@symbolix.com.au>
Repository: CRAN
Date/Publication: 2018-10-14 16:20:03 UTC

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New package jjb with initial version 0.1.0
Package: jjb
Type: Package
Title: Balamuta Miscellaneous
Version: 0.1.0
Authors@R: c( person("James", "Balamuta", email = "balamut2@illinois.edu", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0003-2826-8458")) )
License: GPL (>= 2)
Description: Set of common functions used for manipulating colors, detecting and interacting with 'RStudio', modeling, formatting, determining users' operating system, feature scaling, and more!
RoxygenNote: 6.1.0
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-10-04 04:07:45 UTC; ronin
Author: James Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>)
Maintainer: James Balamuta <balamut2@illinois.edu>
Repository: CRAN
Date/Publication: 2018-10-14 16:30:02 UTC

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New package imputeR with initial version 2.1
Package: imputeR
Title: A General Multivariate Imputation Framework
Version: 2.1
Date: 2018-10-05
Authors@R: c( person("Steffen", "Moritz", email="steffen.moritz10@gmail.com", role=c("aut", "cre"), comment = c(ORCID = "0000-0002-0085-1804")),person("Lingbing", "Feng", role=c("aut")),person("Gen", "Nowak", role=c("ctb")),person("Alan. H.", "Welsh", role=c("ctb")),person("Terry. J.", "O'Neill", role=c("ctb")) )
Author: Steffen Moritz [aut, cre] (<https://orcid.org/0000-0002-0085-1804>), Lingbing Feng [aut], Gen Nowak [ctb], Alan. H. Welsh [ctb], Terry. J. O'Neill [ctb]
Maintainer: Steffen Moritz <steffen.moritz10@gmail.com>
Description: Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.
LazyData: yes
Type: Package
ByteCompile: TRUE
BugReports: https://github.com/SteffenMoritz/imputeR/issues
URL: http://github.com/SteffenMoritz/imputeR
Repository: CRAN
Depends: R (>= 3.1.0),
Imports: stats, utils, graphics, reshape2
Suggests: testthat, rda, caret, glmnet, pls, Cubist, ridge, gbm, mboost, rpart, earth
License: GPL-3
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-10-05 02:53:04 UTC; Steve
Date/Publication: 2018-10-14 16:40:02 UTC

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New package EZtune with initial version 1.0.0
Package: EZtune
Type: Package
Title: Tunes AdaBoost, Support Vector Machines, and Gradient Boosting Machines
Version: 1.0.0
Authors@R: person("Jill", "Lundell", email = "jflundell@gmail.com", role = c("aut", "cre"))
Maintainer: Jill Lundell <jflundell@gmail.com>
Description: Contains two functions that are intended to make tuning supervised learning methods easy. The eztune function uses a genetic algorithm or quasi-Newton-Raphson optimizer to find the best set of tuning parameters. The user can choose the optimizer, the learning method, and if optimization will be based on accuracy obtained through resubstitution or cross-validation. The function eztune.cv will compute a cross-validated error rate. The purpose of eztune.cv is to provide a cross-validated accuracy when resubstitution is used for optimization because resubstitution typically produces an accuracy that is too high.
Depends: R (>= 3.1.0)
Imports: ada, e1071, GA, gbm, mlbench, parallel, doParallel
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-05 07:03:07 UTC; jflun
Author: Jill Lundell [aut, cre]
Repository: CRAN
Date/Publication: 2018-10-14 16:50:17 UTC

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New package trelliscopejs with initial version 0.1.14
Package: trelliscopejs
Title: Create Interactive Trelliscope Displays
Version: 0.1.14
Authors@R: c( person("Ryan", "Hafen", email = "rhafen@gmail.com", role = c("aut", "cre")), person("Barret", "Schloerke", email = "schloerke@gmail.com", role = "aut") )
Description: Trelliscope is a scalable, flexible, interactive approach to visualizing data (Hafen, 2013 <doi:10.1109/LDAV.2013.6675164>). This package provides methods that make it easy to create a Trelliscope display specification for TrelliscopeJS. High-level functions are provided for creating displays from within 'dplyr' or 'ggplot2' workflows. Low-level functions are also provided for creating new interfaces.
Depends: R (>= 3.4.0)
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, purrr, tidyr, grid, htmltools, DistributionUtils, grDevices, gtable, digest, jsonlite, ggplot2 (> 2.1.0), base64enc, htmlwidgets, graphics, progress, utils, knitr, webshot, autocogs, rlang
Suggests: rbokeh, plotly, Cairo, testthat, covr, gapminder, housingData, packagedocs
RoxygenNote: 6.1.0
URL: https://github.com/hafen/trelliscopejs
BugReports: https://github.com/hafen/trelliscopejs/issues
VignetteBuilder: packagedocs
NeedsCompilation: no
Packaged: 2018-10-02 21:06:14 UTC; hafen
Author: Ryan Hafen [aut, cre], Barret Schloerke [aut]
Maintainer: Ryan Hafen <rhafen@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-14 15:30:03 UTC

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New package ppgmmga with initial version 1.0
Package: ppgmmga
Version: 1.0
Date: 2018-10-02
Title: Projection Pursuit Based on Gaussian Mixtures and Evolutionary Algorithms
Description: Projection Pursuit (PP) algorithm for dimension reduction based on Gaussian Mixture Models (GMMs) for density estimation using Genetic Algorithms (GAs) to maximise an approximated negentropy index.
Authors@R: c(person("Alessio", "Serafini", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8579-5695"), email = "srf.alessio@gmail.com"), person("Luca", "Scrucca", role = c("aut"), comment = c(ORCID = "0000-0003-3826-0484"), email = "luca.scrucca@unipg.it"))
Depends: R (>= 3.4)
Imports: Rcpp (>= 0.12.5), mclust (>= 5.0), GA (>= 3.1), ggplot2 (>= 2.2.1), ggthemes (>= 3.4.0), cli, crayon
LinkingTo: Rcpp, RcppArmadillo (>= 0.7)
Suggests: knitr (>= 1.8)
License: GPL (>= 2)
URL: https://github.com/luca-scr/ppgmmga
BugReports: https://github.com/luca-scr/ppgmmga/issues
VignetteBuilder: knitr
ByteCompile: true
Repository: CRAN
NeedsCompilation: yes
LazyLoad: yes
Encoding: UTF-8
Packaged: 2018-10-02 11:15:28 UTC; alessioserafini
Author: Alessio Serafini [aut, cre] (<https://orcid.org/0000-0002-8579-5695>), Luca Scrucca [aut] (<https://orcid.org/0000-0003-3826-0484>)
Maintainer: Alessio Serafini <srf.alessio@gmail.com>
Date/Publication: 2018-10-14 15:30:08 UTC

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New package MLGL with initial version 0.5
Package: MLGL
Type: Package
Title: Multi-Layer Group-Lasso
Version: 0.5
Date: 2018-09-24
Authors@R: c(person("Quentin", "Grimonprez", role = c("aut", "cre"), email = "quentin.grimonprez@inria.fr"), person("Samuel", "Blanck", role = "ctb"), person("Alain", "Celisse", role = "ths"), person("Guillemette", "Marot", role = "ths"), person("Yi","Yang", role = "ctb"), person("Hui","Zou", role = "ctb"))
Copyright: Inria
Description: It implements a new procedure of variable selection in the context of redundancy between explanatory variables, which holds true with high dimensional data (Grimonprez et al. (2018) <https://hal.inria.fr/hal-01857242>).
License: GPL (>= 2)
Imports: gglasso, MASS, Matrix, fastcluster, FactoMineR
RoxygenNote: 6.1.0
Encoding: UTF-8
Author: Quentin Grimonprez [aut, cre], Samuel Blanck [ctb], Alain Celisse [ths], Guillemette Marot [ths], Yi Yang [ctb], Hui Zou [ctb]
Maintainer: Quentin Grimonprez <quentin.grimonprez@inria.fr>
Repository: CRAN
Repository/R-Forge/Project: hcgglasso
Repository/R-Forge/Revision: 33
Repository/R-Forge/DateTimeStamp: 2018-10-03 07:11:50
Date/Publication: 2018-10-14 15:50:04 UTC
NeedsCompilation: no
Packaged: 2018-10-03 07:30:09 UTC; rforge

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New package MachineShop with initial version 0.1-1
Package: MachineShop
Type: Package
Title: Machine Learning Models and Tools
Version: 0.1-1
Date: 2018-10-02
Authors@R: person("Brian J", "Smith", email = "brian-j-smith@uiowa.edu", role = c("aut", "cre"))
Author: Brian J Smith [aut, cre]
Maintainer: Brian J Smith <brian-j-smith@uiowa.edu>
Description: Meta-package for statistical and machine learning with a common interface for model fitting, prediction, performance assessment, and presentation of results. Supports predictive modeling of numerical, categorical, and censored time-to-event outcomes and resample (bootstrap and cross-validation) estimation of model performance.
Imports: abind, foreach, ggplot2, Hmisc, irr, kernlab, magrittr, methods, MLmetrics, ModelMetrics, party, recipes, rsample, survival, survivalROC, utils
Suggests: C50, doParallel, gbm, glmnet, kableExtra, knitr, MASS, nnet, pls, randomForest, rmarkdown, rms, testthat
License: GPL-3
URL: https://github.com/brian-j-smith/MachineShop
BugReports: https://github.com/brian-j-smith/MachineShop/issues
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-02 19:09:28 UTC; bjsmith
Repository: CRAN
Date/Publication: 2018-10-14 15:30:19 UTC

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New package galgo with initial version 1.4
Package: galgo
Version: 1.4
Date: 2018-09-18
Title: Genetic Algorithms for Multivariate Statistical Models from Large-Scale Functional Genomics Data
Authors@R: c(person("Victor", "Trevino", role=c("aut","cre"), email="vtrevino@itesm.mx"), person("Francesco", "Falciani", role=c("aut"), email="F.Falciani@liverpool.ac.uk"), person("Copyright (C) The R Core Team", role=c("cph","ctb")), person("Copyright (C) The R Foundation", role=c("cph","ctb")))
Author: Victor Trevino [aut, cre], Francesco Falciani [aut], Copyright (C) The R Core Team [cph, ctb], Copyright (C) The R Foundation [cph, ctb]
Maintainer: Victor Trevino <vtrevino@itesm.mx>
Description: Build multivariate predictive models from large datasets having far larger number of features than samples such as in functional genomics datasets. Trevino and Falciani (2006) <doi:10.1093/bioinformatics/btl074>.
License: GPL (>= 2)
LazyLoad: no
Depends: R (>= 3.0.0), R.oo
Imports: e1071, rpart, nnet, randomForest, MASS
URL: https://github.com/vtrevino/GALGO
NeedsCompilation: yes
Packaged: 2018-10-02 21:16:04 UTC; victortrevino
Repository: CRAN
Date/Publication: 2018-10-14 15:30:11 UTC

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Fri, 12 Oct 2018

New package ChemoSpecUtils with initial version 0.1.62
Package: ChemoSpecUtils
Type: Package
Title: Functions Supporting Packages ChemoSpec and ChemoSpec2D
Version: 0.1.62
Date: 2018-10-12
Authors@R: c( person("Bryan A.", "Hanson", role = c("aut", "cre"), email = "hanson@depauw.edu", comment = "ORCID 0000-0003-3536-8246"))
Description: Functions supporting the common needs of packages 'ChemoSpec' and 'ChemoSpec2D'.
License: GPL-3
Depends: R (>= 3.1)
Suggests: ChemoSpec (>= 5.0), ChemoSpec2D
Imports: plyr, robustbase, RColorBrewer
URL: https://github.com/bryanhanson/ChemoSpecUtils
ByteCompile: TRUE
BugReports: https://github.com/bryanhanson/ChemoSpecUtils/issues
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-12 13:45:37 UTC; bryanhanson
Author: Bryan A. Hanson [aut, cre] (ORCID 0000-0003-3536-8246)
Maintainer: Bryan A. Hanson <hanson@depauw.edu>
Repository: CRAN
Date/Publication: 2018-10-12 16:50:21 UTC

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New package VFS with initial version 1.0.2
Package: VFS
Title: Vegetated Filter Strip and Erosion Model
Version: 1.0.2
Date: 2018-10-01
Authors@R: c(person("Sarah", "Goslee", role = c("aut", "cre"), email = "Sarah.Goslee@ars.usda.gov"), person("Heather", "Gall", role = "aut"), person("Tamie", "Veith", role = "aut"))
Depends: R (>= 3.4.0)
Imports: stats, graphics, e1071, nleqslv (>= 3.3.0)
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
Description: Empirical models for runoff, erosion, and phosphorus loss across a vegetated filter strip, given slope, soils, climate, and vegetation (Gall et al., 2018) <doi:10.1007/s00477-017-1505-x>. It also includes functions for deriving climate parameters from measured daily weather data, and for simulating rainfall. Models implemented include MUSLE (Williams, 1975) and APLE (Vadas et al., 2009 <doi:10.2134/jeq2008.0337>).
License: GPL-3
BugReports: https://github.com/sgoslee/VFS/issues
LazyData: true
NeedsCompilation: no
Packaged: 2018-10-01 16:20:35 UTC; sarahg
Author: Sarah Goslee [aut, cre], Heather Gall [aut], Tamie Veith [aut]
Maintainer: Sarah Goslee <Sarah.Goslee@ars.usda.gov>
Repository: CRAN
Date/Publication: 2018-10-12 13:20:10 UTC

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New package varbin with initial version 0.2.1
Package: varbin
Type: Package
Title: Optimal Binning of Continuous and Categorical Variables
Version: 0.2.1
Date: 2018-09-21
Author: Daniel Safai
Maintainer: Daniel Safai <danielsafai@gmail.com>
Description: Tool for easy and efficient discretization of continuous and categorical data. The package calculates the most optimal binning of a given explanatory variable with respect to a user-specified target variable. The purpose is to assign a unique Weight-of-Evidence value to each of the calculated binpoints in order to recode the original variable. The package allows users to impose certain restrictions on the functional form on the resulting binning while maximizing the overall information value in the original data. The package is well suited for logistic scoring models where input variables may be subject to restrictions such as linearity by e.g. regulatory authorities. An excellent source describing in detail the development of scorecards, and the role of Weight-of-Evidence coding in credit scoring is (Siddiqi 2006, ISBN: 978–0-471–75451–0). The package utilizes the discrete nature of decision trees and Isotonic Regression to accommodate the trade-off between flexible functional forms and maximum information value.
License: GPL (>= 2)
Imports: rpart
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-02 12:56:54 UTC; danielsafai
Repository: CRAN
Date/Publication: 2018-10-12 13:50:03 UTC

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New package slouch with initial version 2.1.0
Package: slouch
Type: Package
Title: Stochastic Linear Ornstein-Uhlenbeck Comparative Hypotheses
Version: 2.1.0
Date: 2018-10-02
Authors@R: c(person("Bj\u00F8rn Tore", "Kopperud", role =c("aut", "cre"), email = "b.t.kopperud@nhm.uio.no"), person("Jason", "Pienaar", role = c("aut")), person("Kjetil Lysne", "Voje", role = c("aut")), person("Steven Hecht", "Orzack", role = c("aut")), person("Thomas F.", "Hansen", role = c("aut")), person("Mark", "Grabowski", role = c("ctb")))
Description: An implementation of a phylogenetic comparative method. It can fit univariate among-species Ornstein-Uhlenbeck models of phenotypic trait evolution, where the trait evolves towards a primary optimum. The optimum can be modelled as a single parameter, as multiple discrete regimes on the phylogenetic tree, and/or with continuous covariates.
License: GPL-2
LazyData: FALSE
ByteCompile: FALSE
RoxygenNote: 6.1.0
Depends: R (>= 3.0.0), base, stats
Imports: parallel, ape, memoise
Suggests: knitr, rmarkdown, bookdown, testthat
URL: http://github.com/kopperud/slouch
BugReports: http://github.com/kopperud/slouch/issues
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-10-02 15:50:37 UTC; bjorntko
Author: Bjørn Tore Kopperud [aut, cre], Jason Pienaar [aut], Kjetil Lysne Voje [aut], Steven Hecht Orzack [aut], Thomas F. Hansen [aut], Mark Grabowski [ctb]
Maintainer: Bjørn Tore Kopperud <b.t.kopperud@nhm.uio.no>
Repository: CRAN
Date/Publication: 2018-10-12 13:50:06 UTC

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New package RcppNLoptExample with initial version 0.0.1
Package: RcppNLoptExample
Type: Package
Title: 'Rcpp' Package Illustrating Header-Only Access to 'NLopt'
Version: 0.0.1
Date: 2018-10-01
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Description: An example package which shows use of 'NLopt' functionality from C++ via 'Rcpp' without requiring linking, and relying just on 'nloptr' thanks to the exporting API added there by Jelmer Ypma. This package is a fully functioning, updated, and expanded version of the initial example by Julien Chiquet at <https://github.com/jchiquet/RcppArmadilloNLoptExample> also containing a large earlier pull request of mine.
License: GPL (>= 2)
Encoding: UTF-8
LinkingTo: Rcpp, nloptr (>= 1.2.0)
Imports: Rcpp, nloptr (>= 1.2.0)
Depends: R (>= 3.0.2)
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-10-02 02:32:59 UTC; edd
Repository: CRAN
Date/Publication: 2018-10-12 13:40:02 UTC

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New package pmpp with initial version 0.1.0
Package: pmpp
Type: Package
Title: Posterior Mean Panel Predictor
Version: 0.1.0
Date: 2018-09-23
Authors@R: person("Michal", "Oleszak", email = "oleszak.michal@gmail.com", role = c("aut", "cre"))
Description: Dynamic panel modelling framework based on an empirical-Bayes approach. Contains tools for computing point forecasts and bootstrapping prediction intervals. Reference: Liu et al. (2016) <doi:10.2139/ssrn.2889000>.
URL: https://github.com/veneficusnl/pmpp
BugReports: https://github.com/veneficusnl/pmpp/issues
License: GPL (>= 2)
Depends: R (>= 3.4.0)
Imports: plm, pracma, MASS, Matrix, minqa, dplyr, data.table, moments, magrittr, ggplot2, stats, utils, graphics
Suggests: testthat, lintr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-01 21:09:02 UTC; Asus
Author: Michal Oleszak [aut, cre]
Maintainer: Michal Oleszak <oleszak.michal@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-12 13:50:09 UTC

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New package learnPopGen with initial version 0.9.8
Package: learnPopGen
Version: 0.9.8
Date: 2018-10-1
Title: Population Genetic Simulations & Numerical Analysis
Author: Liam J. Revell
Maintainer: Liam J. Revell <liam.revell@umb.edu>
Depends: R (>= 2.6)
Imports: grDevices, graphics, gtools, methods, phytools, stats
Suggests:
ZipData: no
Description: Conducts various numerical analyses and simulations in population genetics and evolutionary theory, primarily for the purpose of teaching (and learning about) key concepts in population & quantitative genetics, and evolutionary theory.
License: GPL (>= 2)
URL: http://github.com/liamrevell/PopGen
Packaged: 2018-10-01 19:51:28 UTC; liamj
Repository: CRAN
Date/Publication: 2018-10-12 13:20:03 UTC
NeedsCompilation: no

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New package ioanalysis with initial version 0.1
Package: ioanalysis
Title: Input Output Analysis
Version: 0.1
Authors@R: c( person("John", "Wade", email = "jjpwade2@illinois.edu", role = c("aut", "cre")), person("Ignacio", "Sarmiento-Barbieri", email = "srmntbr2@illinois.edu", role = c("aut")))
Author: John Wade [aut, cre], Ignacio Sarmiento-Barbieri [aut]
Maintainer: John Wade <jjpwade2@illinois.edu>
Description: Calculates fundamental IO matrices (Leontief, Wassily W. (1951) <doi:10.1038/scientificamerican1051-15>, Ghosh, A. (1958) <doi:10.2307/2550694>); within period analysis via various rankings and coefficients (Sonis and Hewings (2006) <doi:10.1080/09535319200000013>, Blair and Miller (2009) <ISBN:978-0-521-73902-3>, Antras et al (2012) <doi:10.3386/w17819>, Hummels, Ishii, and Yi (2001) <doi:10.1016/S0022-1996(00)00093-3>); across period analysis with impact analysis (Dietzenbacher, van der Linden, and Steenge (2006) <doi:10.1080/09535319300000017>, Sonis, Hewings, and Guo (2006) <doi:10.1080/09535319600000002>); and a variety of table operators.
Depends: R (>= 3.4.0)
License: GPL (>= 2)
URL: http://www.real.illinois.edu
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-10-01 19:14:16 UTC; JJPWade
Repository: CRAN
Date/Publication: 2018-10-12 13:20:06 UTC

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New package HARModel with initial version 0.1
Package: HARModel
Type: Package
Title: Heterogeneous Autoregressive Models
Version: 0.1
Date: 2018-09-26
Author: Emil Sjoerup
Maintainer: Emil Sjoerup <emilsjoerup@live.dk>
Description: Estimation, simulation, and forecasting using the HAR model from Corsi(2009) <DOI:10.1093/jjfinec/nbp001>.
License: GPL-3
Imports: Rcpp (>= 0.12.17) , xts, zoo, sandwich,
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Depends: R (>= 2.10), methods
Packaged: 2018-10-02 06:00:33 UTC; emils
Repository: CRAN
Date/Publication: 2018-10-12 14:00:02 UTC

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New package descstatsr with initial version 0.1.0
Package: descstatsr
Type: Package
Title: Descriptive Univariate Statistics
Version: 0.1.0
Author: Harish Kumar
Maintainer: Harish Kumar <kadamatiharish@gmail.com>
Description: It generates summary statistics on the input dataset using different descriptive univariate statistical measures on entire data or at a group level. Though there are other packages which does similar job but each of these are deficient in one form or other, in the measures generated, in treating numeric, character and date variables alike, no functionality to view these measures on a group level or the way the output is represented. Given the foremost role of the descriptive statistics in any of the exploratory data analysis or solution development, there is a need for a more constructive, structured and refined version over these packages. This is the idea behind the package and it brings together all the required descriptive measures to give an initial understanding of the data quality, distribution in a faster,easier and elaborative way.The function brings an additional capability to be able to generate these statistical measures on the entire dataset or at a group level. It calculates measures of central tendency (mean, median), distribution (count, proportion), dispersion (min, max, quantile, standard deviation, variance) and shape (skewness, kurtosis). Addition to these measures, it provides information on the data type, count on no. of rows, unique entries and percentage of missing entries. More importantly the measures are generated based on the data types as required by them,rather than applying numerical measures on character and data variables and vice versa. Output as a dataframe object gives a very neat representation, which often is useful when working with a large number of columns. It can easily be exported as csv and analyzed further or presented as a summary report for the data.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: datasets,zoo,moments
Suggests: knitr
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-01 18:05:07 UTC; sudo
Repository: CRAN
Date/Publication: 2018-10-12 13:10:03 UTC

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New package balance with initial version 0.1.6
Package: balance
Title: Visualize Balances of Compositional Data
Version: 0.1.6
URL: http://github.com/tpq/balance
BugReports: http://github.com/tpq/balance/issues
Authors@R: c( person("Thomas", "Quinn", email = "contacttomquinn@gmail.com", role = c("aut", "cre")) )
Description: Balances have become a cornerstone of compositional data analysis. However, conceptualizing balances is difficult, especially for high-dimensional data. Most often, investigators visualize balances with "balance dendrograms". However, this visualization tool does not scale well for large data. This package provides an alternative scheme for visualizing balances, described in [Quinn (2018) <DOI:10.12688/f1000research.15858.1>]. This package also provides a method for principal balance analysis.
License: GPL-2
LazyData: TRUE
VignetteBuilder: knitr
RoxygenNote: 6.1.0
Encoding: UTF-8
Imports: methods, ggplot2, grid
Depends: R (>= 3.2.2)
Suggests: ape, ggthemes, knitr, philr, propr, reshape2, rmarkdown, robCompositions, testthat
NeedsCompilation: no
Packaged: 2018-10-02 08:28:52 UTC; thom
Author: Thomas Quinn [aut, cre]
Maintainer: Thomas Quinn <contacttomquinn@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-12 13:30:03 UTC

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New package AlphaSimR with initial version 0.8.1
Package: AlphaSimR
Type: Package
Title: Breeding Program Simulations
Version: 0.8.1
Date: 2018-10-01
Authors@R: c(person("Chris", "Gaynor", email = "gaynor.robert@hotmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0558-6656")), person("Gregor", "Gorjanc", role = "ctb", comment = c(ORCID = "0000-0001-8008-2787")), person("David", "Wilson", role = "ctb"), person("Daniel", "Money", role = "ctb"), person("John", "Hickey", role = "ctb", comment = c(ORCID = "0000-0001-5675-3974")))
Description: The successor to the 'AlphaSim' software for breeding program simulation (Faux et al., 2016, <doi:10.3835/plantgenome2016.02.0013>). Used for stochastic simulations of breeding programs to the level of DNA sequence for every individual. Contained is a wide range of functions for modeling common tasks in a breeding program, such as selection and crossing. These functions allow for constructing simulations of highly complex plant and animal breeding programs via scripting in the R software environment. Such simulations can be used to evaluate overall breeding program performance and conduct research into breeding program design, such as implementation of genomic selection. Included is the 'Markovian Coalescent Simulator' ('MaCS') for fast simulation of biallelic sequences according to a population demographic history (Chen et al., 2009, <doi:10.1101/gr.083634.108>).
License: MIT + file LICENSE
URL: https://alphagenes.roslin.ed.ac.uk/wp/software/alphasimr/, https://bitbucket.org/hickeyjohnteam/alphasimr
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0), methods, R6
Imports: Rcpp (>= 0.12.7)
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.500.0.0), BH
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-10-01 17:43:20 UTC; rgaynor
Author: Chris Gaynor [aut, cre] (<https://orcid.org/0000-0003-0558-6656>), Gregor Gorjanc [ctb] (<https://orcid.org/0000-0001-8008-2787>), David Wilson [ctb], Daniel Money [ctb], John Hickey [ctb] (<https://orcid.org/0000-0001-5675-3974>)
Maintainer: Chris Gaynor <gaynor.robert@hotmail.com>
Repository: CRAN
Date/Publication: 2018-10-12 13:10:06 UTC

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Wed, 10 Oct 2018

New package saemix with initial version 2.2
Package: saemix
Type: Package
Title: Stochastic Approximation Expectation Maximization (SAEM) Algorithm
Version: 2.2
Date: 2018-10-05
Author: Emmanuelle Comets, Audrey Lavenu, Marc Lavielle (2017) <doi:10.18637/jss.v080.i03>
Maintainer: Emmanuelle Comets <emmanuelle.comets@inserm.fr>
Description: The SAEMIX package implements the Stochastic Approximation EM algorithm for parameter estimation in (non)linear mixed effects models. The SAEM algorithm: - computes the maximum likelihood estimator of the population parameters, without any approximation of the model (linearisation, quadrature approximation,...), using the Stochastic Approximation Expectation Maximization (SAEM) algorithm, - provides standard errors for the maximum likelihood estimator - estimates the conditional modes, the conditional means and the conditional standard deviations of the individual parameters, using the Hastings-Metropolis algorithm. Several applications of SAEM in agronomy, animal breeding and PKPD analysis have been published by members of the Monolix group (<http://group.monolix.org/>).
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
Suggests: testthat (>= 0.3)
Imports: graphics, stats, methods
Collate: 'aaa_generics.R' 'SaemixData.R' 'SaemixModel.R' 'SaemixRes.R' 'SaemixObject.R' 'compute_LL.R' 'func_FIM.R' 'func_aux.R' 'func_distcond.R' 'func_plots.R' 'func_simulations.R' 'main.R' 'main_estep.R' 'main_initialiseMainAlgo.R' 'main_mstep.R' 'zzz.R'
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-10 13:09:15 UTC; eco
Repository: CRAN
Date/Publication: 2018-10-10 16:00:03 UTC

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New package revealedPrefs with initial version 0.4
Package: revealedPrefs
Type: Package
Title: Revealed Preferences and Microeconomic Rationality
Version: 0.4
Date: 2018-10-10
Author: Julien Boelaert <jubo.stats@gmail.com>
Maintainer: Julien Boelaert <jubo.stats@gmail.com>
Description: Computation of (direct and indirect) revealed preferences, fast non-parametric tests of rationality axioms (WARP, SARP, GARP), simulation of axiom-consistent data, and detection of axiom-consistent subpopulations. Rationality tests follow Varian (1982) <doi:10.2307/1912771>, axiom-consistent subpopulations follow Crawford and Pendakur (2012) <doi:10.1111/j.1468-0297.2012.02545.x>.
License: GPL (>= 3)
Imports: pso
Depends: Rcpp
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2018-10-10 15:01:42 UTC; bart
Repository: CRAN
Date/Publication: 2018-10-10 16:00:20 UTC

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New package uwIntroStats with initial version 0.0.7
Package: uwIntroStats
Type: Package
Title: Descriptive Statistics, Inference, Regression, and Plotting in an Introductory Statistics Course
Version: 0.0.7
Date: 2018-10-9
Maintainer: Travis Y. Hee Wai <theewai@uw.edu>
Authors@R: c(person(given = "Scott S.", family = "Emerson", role = "aut"), person(given = "Andrew J.", family = "Spieker", role = "aut"), person(given = "Brian D.", family = "Williamson", role= "aut"), person(given = "Travis Y.", family = "Hee Wai", role = c("aut","cre"),email="theewai@uw.edu"), person(given = "Solomon", family = "Lim", role = "aut"), person("R Core Team", role = "ctb"), person(given = "Terry M", family = "Therneu", role = "ctb"), person("Thomas", "Lumley", role = "ctb"))
Description: A set of tools designed to facilitate easy adoption of R for students in introductory classes with little programming experience. Compiles output from existing routines together in an intuitive format, and adds functionality to existing functions. For instance, the regression function can perform linear models, generalized linear models, Cox models, or generalized estimating equations. The user can also specify multiple-partial F-tests to print out with the model coefficients. We also give many routines for descriptive statistics and plotting.
Imports: Exact, geepack, plyr, survival, sandwich
License: GPL-2
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-10 02:27:52 UTC; theewai
Author: Scott S. Emerson [aut], Andrew J. Spieker [aut], Brian D. Williamson [aut], Travis Y. Hee Wai [aut, cre], Solomon Lim [aut], R Core Team [ctb], Terry M Therneu [ctb], Thomas Lumley [ctb]
Repository: CRAN
Date/Publication: 2018-10-10 11:50:02 UTC

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Tue, 09 Oct 2018

New package RGoogleAnalytics with initial version 0.1.6
Package: RGoogleAnalytics
Version: 0.1.6
Date: 2018-10-01
Title: R Wrapper for the Google Analytics API
Author: Michael Pearmain. Contributions from Nick Mihailowski, Vignesh Prajapati, Kushan Shah, Nicolas Remy and Manuel de Francisco Vera person("Manuel", "de Francisco", email = "mdefraver@hotelspecials.nl", role = c("ctb"))
Description: Provides functions for accessing and retrieving data from the Google Analytics API.
Maintainer: Manuel de Francisco Vera <manueldefrancisco@gmail.com>
BugReports: https://github.com/ManuelDeFrancisco/RGoogleAnalytics/issues
Depends: R(>= 3.0.2), lubridate, httr, digest (>= 0.6.8)
Suggests: testthat
License: Apache License 2.0
NeedsCompilation: no
Repository: CRAN
RoxygenNote: 6.0.1
Packaged: 2018-10-09 13:33:54 UTC; mdefraver
Date/Publication: 2018-10-09 15:30:02 UTC

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New package FisherEM with initial version 1.5
Package: FisherEM
Type: Package
Title: The FisherEM Algorithm to Simultaneously Cluster and Visualize High-Dimensional Data
Version: 1.5
Date: 2018-10-1
Author: Charles Bouveyron and Camille Brunet
Maintainer: Charles Bouveyron <charles.bouveyron@gmail.com>
Depends: MASS, elasticnet, parallel
Description: FisherEM is an efficient algorithm for the unsupervised classification of high-dimensional data. FisherEM models and clusters the data in a discriminative and low-dimensional latent subspace. It also provides a low-dimensional representation of the clustered data. A sparse version of Fisher-EM algorithm is also provided.
License: GPL-2
LazyLoad: yes
NeedsCompilation: no
Packaged: 2018-10-09 13:34:33 UTC; bouveyro
Repository: CRAN
Date/Publication: 2018-10-09 15:20:06 UTC

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Mon, 08 Oct 2018

New package vamc with initial version 0.1.0
Package: vamc
Type: Package
Title: A Monte Carlo Valuation Framework for Variable Annuities
Version: 0.1.0
Authors@R: c( person("Hengxin", "Li", email = "h343li@uwaterloo.ca", role = c("aut", "cph")), person("Ben", "Feng", email = "ben.feng@uwaterloo.ca", role = c("aut", "cph", "cre")), person("GuoJun", "Gan", email = "Guojun.Gan@uconn.edu", role = c("ctb")))
Description: Implementation of a Monte Carlo simulation engine for valuing synthetic portfolios of variable annuities, which reflect realistic features of common annuity contracts in practice. It aims to facilitate the development and dissemination of research related to the efficient valuation of a portfolio of large variable annuities. The main valuation methodology was proposed by Gan (2017) <doi:10.1515/demo-2017-0021>.
Depends: R (>= 3.3.0)
License: GPL-2
LazyData: true
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
RoxygenNote: 6.1.0
Imports: stats (>= 3.3.0), utils (>= 3.3.0), Rdpack (>= 0.4)
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2018-10-01 16:23:19 UTC; thecoolestman
Author: Hengxin Li [aut, cph], Ben Feng [aut, cph, cre], GuoJun Gan [ctb]
Maintainer: Ben Feng <ben.feng@uwaterloo.ca>
Repository: CRAN
Date/Publication: 2018-10-08 18:30:03 UTC

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New package TPMplt with initial version 0.1.0
Package: TPMplt
Type: Package
Title: Tool-Kit for Dynamic Materials Model and Thermal Processing Maps
Version: 0.1.0
Date: 2018-09-30
Authors@R: person("ZHANG_Chen", "Developer", email = "447974102@qq.com", role = c("aut", "com", "cre"))
Description: Provides a simple approach for constructing dynamic materials modeling suggested by Prasad and Gegel <doi:10.1007/BF02664902>. It can easily generate various processing-maps based on this model as well. The calculation result in this package contains full materials constants, information about power dissipation efficiency factor, and rheological properties, can be exported completely also, through which further analysis and customized plots will be applicable as well.
License: GPL-3
URL: https://github.com/CubicZebra/TPMplt
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: VBTree, ggplot2, rgl, e1071, qpcR, grDevices, rowr, graphics, stats
Depends: R (>= 2.10)
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-01 15:30:18 UTC; chen_zhang
Author: ZHANG_Chen Developer [aut, com, cre]
Maintainer: ZHANG_Chen Developer <447974102@qq.com>
Repository: CRAN
Date/Publication: 2018-10-08 18:40:03 UTC

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New package nlgeocoder with initial version 0.1.3
Package: nlgeocoder
Title: Geocoding for the Netherlands
Version: 0.1.3
Authors@R: c(person("Willy", "Tadema", role = c("aut")), person("Egge-Jan", "Pollé", role = c("aut")) ,person("Edwin", "de Jonge", email = "edwindjonge@gmail.com", role = c("aut", "cre")) ,person("Juris", "Breidaks", role = c("ctb")))
Description: R interface to the open location server API of 'Publieke Diensten Op de Kaart' (<http://www.pdok.nl>). It offers geocoding, address suggestions and lookup of geographical objects. Included is an utility function for displaying leaflet tiles restricted to the Netherlands.
Depends: R (>= 3.4)
License: GPL-2
BugReports: https://github.com/uRos2018/nlgeocoder/issues
URL: https://github.com/uRos2018/nlgeocoder
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: testthat, knitr, rmarkdown, sf, shiny, leaflet
VignetteBuilder: knitr
Imports: jsonlite
NeedsCompilation: no
Packaged: 2018-10-01 12:37:12 UTC; edwin
Author: Willy Tadema [aut], Egge-Jan Pollé [aut], Edwin de Jonge [aut, cre], Juris Breidaks [ctb]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-08 18:30:06 UTC

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New package IntrinioStockAPI with initial version 0.0.1
Package: IntrinioStockAPI
Title: Wrapper for the 'Intrinio Stock API'
Version: 0.0.1
Maintainer: Kenneth Miller <kmiller@intrinio.com>
Description: Download financial data from the free 'Intrinio Stock API' (<https://intrinio.com/>). 'Intrinio' offers a REST API which provides financial markets data including intra-day stock prices, historical stock prices, technical indicators, company fundamentals, and more. Complete documentation for the 'Intrinio Stock API' is available here: <https://intrinio.com/documentation/api/>. To access the 'Intrinio Stock API', simply create a free account <https://intrinio.com/>.
Author: Intrinio
Depends: R (>= 3.0.1)
Imports: stringr, httr, jsonlite, gtools
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/intrinio/r-sdk
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-01 16:14:15 UTC; kgmiller
Repository: CRAN
Date/Publication: 2018-10-08 18:50:07 UTC

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New package processcheckR with initial version 0.1.0
Package: processcheckR
Type: Package
Title: Rule-Based Conformance Checking of Business Process Event Data
Version: 0.1.0
Date: 2018-10-01
Authors@R: person("Gert","Janssenswillen", email = "gert.janssenswillen@uhasselt.be", role = c("aut","cre"))
Description: Check compliance of event data from (business) processes with respect to specified rules. Rules supported are of three types: frequency (activities that should (not) happen x number of times), order (succession between activities) and exclusiveness (and and exclusive choice between activities).
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, bupaR, rlang, edeaR, stringr, glue
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, eventdataR
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-01 12:55:00 UTC; lucp8407
Author: Gert Janssenswillen [aut, cre]
Maintainer: Gert Janssenswillen <gert.janssenswillen@uhasselt.be>
Repository: CRAN
Date/Publication: 2018-10-08 14:20:03 UTC

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New package epos with initial version 0.1.0
Package: epos
Type: Package
Title: Epilepsy Ontology Similarities
Version: 0.1.0
Author: Bernd Müller
Maintainer: Bernd Mueller <bernd.mueller@zbmed.de>
Depends: R (>= 2.10)
Description: Analysis and visualization of similarities between epilepsy ontologies based on text mining results by comparing ranked lists of co-occurring drug terms in the corpus of LIVIVO. The ranked result lists of neurological drug terms co-occurring with named entities from the epilepsy ontologies EpSO, ESSO, and EPILONT are aggregated in order to generate two different results: an overview table of drugs that are relevant to epilepsy created with the method createNeuroTable, and a plot of tanimoto similarity coefficients between the aggregated list of drug terms against the list of drug terms from each of the ontologies created with the method createTanimotoBaseline(). The alignment of the Top-K Ranked Lists is conducted using the R-package TopKLists <https://cran.r-project.org/package=TopKLists>. The source data to create the ranked lists of drug names is produced using the text mining workflows described in Mueller, Bernd and Hagelstein, Alexandra (2016) <doi:10.4126/FRL01-006408558> and Mueller, Bernd et al. (2017) <doi:10.1007/978-3-319-58694-6_22>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: hashmap, ggplot2, tidyr, dplyr, testthat, gridExtra, TopKLists, stringr, xtable
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2018-10-08 10:27:05 UTC; muellerb
Repository: CRAN
Date/Publication: 2018-10-08 14:20:06 UTC

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New package crossrun with initial version 0.1.0
Package: crossrun
Version: 0.1.0
Title: Joint Distribution of Number of Crossings and Longest Run
Authors@R: c(person("Tore","Wentzel-Larsen",email="tore.wentzellarsen@gmail.com",role=c("aut","cre")), person("Jacob", "Anhøj", email="jacob@anhoej.net", role="aut"))
Description: Joint distribution of number of crossings and the longest run in a series of independent Bernoulli trials. The computations uses an iterative procedure where computations are based on results from shorter series. The procedure conditions on the start value and partitions by further conditioning on the position of the first crossing (or none).
Depends: R (>= 3.5)
License: GPL-3
Encoding: UTF-8
URL: https://github.com/ToreWentzel-Larsen/crossrun
LazyData: true
Imports: Rmpfr (>= 0.7-1)
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-01 09:50:57 UTC; Tore Admin
Author: Tore Wentzel-Larsen [aut, cre], Jacob Anhøj [aut]
Maintainer: Tore Wentzel-Larsen <tore.wentzellarsen@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-08 14:20:10 UTC

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New package OSDR with initial version 1.1
Package: OSDR
Type: Package
Title: Finds an Optimal System of Distinct Representatives
Version: 1.1
Date: 2018-09-19
Authors@R: person("Massimo", "Cannas", role = c("aut", "cre"), email = "massimo.cannas@unica.it")
Author: Massimo Cannas [aut, cre]
Maintainer: Massimo Cannas <massimo.cannas@unica.it>
Description: Provides routines for finding an Optimal System of Distinct Representatives (OSDR), as defined by D.Gale (1968) <doi:10.1016/S0021-9800(68)80039-0>.
Suggests: optrees, optmatch
License: GPL-2
NeedsCompilation: no
Packaged: 2018-09-30 21:59:18 UTC; massimo
Repository: CRAN
Date/Publication: 2018-10-08 12:40:14 UTC

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New package lorentz with initial version 1.0-0
Package: lorentz
Type: Package
Title: The Lorentz Transform in Relativistic Physics
Version: 1.0-0
Author: Robin K. S. Hankin
Depends: magrittr
Suggests: knitr
Imports: emulator
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>
Description: Addition of velocities in special relativity is not straightforward: the parallelogram addition law does not apply because velocity addition is neither commutative nor associative. This package furnishes functionality to work with Lorentz transforms and the gyrogroup structure of three-velocities. For general relativity, see the 'schwarzschild' package.
License: GPL-3
URL: https://github.com/RobinHankin/lorentz.git
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-30 18:51:00 UTC; rhankin
Repository: CRAN
Date/Publication: 2018-10-08 12:40:03 UTC

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New package logisticRR with initial version 0.1.0
Package: logisticRR
Type: Package
Title: Adjusted Relative Risk from Logistic Regression
Version: 0.1.0
Author: Youjin Lee
Maintainer: Youjin Lee <ylee160@jhu.edu>
Imports: stats
Suggests: knitr, testthat
Description: Adjusted odds ratio conditional on potential confounders can be directly obtained from logistic regression. However, those adjusted odds ratios have been widely incorrectly interpreted as a relative risk. As relative risk is often of interest in public health, we provide a simple code to return adjusted relative risks from logistic regression model under potential confounders.
License: GPL (>= 3) | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
URL: https://github.com/youjin1207/logisticRR
NeedsCompilation: no
Packaged: 2018-10-01 02:48:34 UTC; Youjin
Repository: CRAN
Date/Publication: 2018-10-08 12:40:06 UTC

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New package HCR with initial version 0.1.0
Package: HCR
Type: Package
Title: Causal Discovery on Discrete Data using Hidden Compact Representation
Version: 0.1.0
Authors@R: c(person("Jie","Qiao",email="qiaojie.chn@gmail.com",role=c("aut","cre")), person("Ruichu","Cai",email="cairuichu@gmail.com",role=c("ths","aut")), person("Kun","Zhang",email="kunz1@andrew.cmu.edu",role=c("ths","aut")), person("Zhenjie","Zhang",email="zhenjie.zhang@yitu-inc.com",role=c("ths","aut")), person("Zhifeng","Hao",email="zfhao@gdut.edu.cn",role=c("ths","aut")) )
Author: Jie Qiao [aut, cre], Ruichu Cai [ths, aut], Kun Zhang [ths, aut], Zhenjie Zhang [ths, aut], Zhifeng Hao [ths, aut]
Maintainer: Jie Qiao <qiaojie.chn@gmail.com>
Description: This code provides a method to fit the hidden compact representation model as well as to identify the causal direction on discrete data. We implement an effective solution to recover the above hidden compact representation under the likelihood framework. Please see the Causal Discovery on Discrete Data using Hidden Compact Representation from NIPS 2018 by Ruichu Cai, Jie Qiao, Kun Zhang, Zhenjie Zhang and Zhifeng Hao (2018) <https://nips.cc/Conferences/2018/Schedule?showEvent=11274> for a description of some of our methods.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: data.table (>= 1.10.4), methods
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-08 11:49:22 UTC; qj
Repository: CRAN
Date/Publication: 2018-10-08 12:30:03 UTC

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New package divDyn with initial version 0.6.1
Package: divDyn
Type: Package
Title: Diversity Dynamics using Fossil Sampling Data
Version: 0.6.1
Author: Adam T. Kocsis, John Alroy, Carl J. Reddin, Wolfgang Kiessling
Maintainer: Adam T. Kocsis <adam.kocsis@outlook.com>
Description: Functions to describe sampling and diversity dynamics of fossil occurrence datasets (e.g. from the Paleobiology Database). The package includes methods to calculate range- and occurrence-based metrics of taxonomic richness, extinction and origination rates, along with traditional sampling measures. A powerful subsampling tool is also included that implements frequently used sampling standardization methods in a multiple bin-framework. The plotting of time series and the occurrence data can be simplified by the functions incorporated in the package, as well other calculations, such as environmental affinities and extinction selectivity testing. Details can be found in: Kocsis, A.T.; Reddin, C.J.; Alroy, J. and Kiessling, W. (2018) <doi:10.1101/423780>.
License: CC BY 4.0
Date: 2018-10-01
Encoding: UTF-8
LazyData: false
Depends: R (>= 3.3.0)
Imports: Rcpp, stats, graphics, grDevices
NeedsCompilation: yes
RoxygenNote: 6.0.1
LinkingTo: Rcpp
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
Packaged: 2018-10-01 07:53:22 UTC; kocsis
Repository: CRAN
Date/Publication: 2018-10-08 12:40:09 UTC

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New package TSEntropies with initial version 0.9
Package: TSEntropies
Title: Time Series Entropies
Version: 0.9
Authors@R: person("Jiri", "Tomcala", email = "jiri.tomcala@vsb.cz", role = c("aut", "cre"))
Description: Computes various entropies of given time series. This is the initial version that includes ApEn() and SampEn() functions for calculating approximate entropy and sample entropy. Approximate entropy was proposed by S.M. Pincus in "Approximate entropy as a measure of system complexity", Proceedings of the National Academy of Sciences of the United States of America, 88, 2297-2301 (March 1991). Sample entropy was proposed by J. S. Richman and J. R. Moorman in "Physiological time-series analysis using approximate entropy and sample entropy", American Journal of Physiology, Heart and Circulatory Physiology, 278, 2039-2049 (June 2000). This package also contains FastApEn() and FastSampEn() functions for calculating fast approximate entropy and fast sample entropy. These are newly designed very fast algorithms, resulting from the modification of the original algorithms. The calculated values of these entropies are not the same as the original ones, but the entropy trend of the analyzed time series determines equally reliably. Their main advantage is their speed, which is up to a thousand times higher. A scientific article describing their properties has been submitted to The Journal of Supercomputing and in present time it is waiting for the acceptance.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
RoxygenNote: 6.1.0.9000
Author: Jiri Tomcala [aut, cre]
Maintainer: Jiri Tomcala <jiri.tomcala@vsb.cz>
Packaged: 2018-10-01 08:36:54 UTC; jirka
Repository: CRAN
Date/Publication: 2018-10-08 11:00:07 UTC

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New package stationery with initial version 0.98.5.5
Package: stationery
Type: Package
Title: Working Examples for Reproducible Research Documents
Version: 0.98.5.5
Date: 2018-09-12
Authors@R: c(person("Paul", "Johnson", role = c("aut", "cre"), email = "pauljohn@ku.edu"), person("Brent", "Kaplan", role = c("ctb"), email = "bkaplan4@ku.edu"), person("Meghan", "Sullivan", role = c("ctb"), email = "meg.sullivan@ku.edu"), person("Charles", "Redmon", role = "ctb", email = "redmon@ku.edu"), person("Zack", "Roman", role = "ctb", email = "zroman@ku.edu"), person("Chong", "Xing", role = "ctb", email = "cxing@ku.edu"))
Maintainer: Paul Johnson <pauljohn@ku.edu>
Description: Templates, guides, and scripts for writing documents in 'LaTeX' and 'R markdown' to produce guides, slides, and reports. Special care is taken to illustrate use of templates and customization opportunities. Challenges and opportunities of 'HTML' output from 'R markdown' receive special attention. Includes several vignettes to assist new users of literate programming.
License: CC BY-SA 4.0
Imports: kutils, rmarkdown, knitr
Suggests: rockchalk, xtable, lavaan, utils, psych, pander
LazyData: TRUE
RoxygenNote: 6.0.1
VignetteBuilder: knitr, utils
NeedsCompilation: no
Packaged: 2018-09-12 21:32:08 UTC; pauljohn
Author: Paul Johnson [aut, cre], Brent Kaplan [ctb], Meghan Sullivan [ctb], Charles Redmon [ctb], Zack Roman [ctb], Chong Xing [ctb]
Repository: CRAN
Date/Publication: 2018-10-08 10:30:03 UTC

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New package SMUT with initial version 1.0
Package: SMUT
Type: Package
Title: Multi-SNP Mediation Intersection-Union Test
Version: 1.0
Author: Wujuan Zhong
Maintainer: Wujuan Zhong <zhongwujuan@gmail.com>
Description: Testing the mediation effect of multiple SNPs on an outcome through a gene.
LazyData: true
License: GPL (>= 2)
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.12.14), SKAT, MASS
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2018-09-30 18:06:15 UTC; Fox
Repository: CRAN
Date/Publication: 2018-10-08 10:30:09 UTC

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New package SCINA with initial version 1.0.0
Package: SCINA
Type: Package
Title: A Semi-Supervised Category Identification and Assignment Tool
Version: 1.0.0
Date: 2018-09-18
Author: Ze Zhang
Maintainer: Ze Zhang <Ze.Zhang@utsouthwestern.edu>
Depends: R (>= 2.15.0), MASS, gplots
Description: An automatic cell type detection and assignment algorithm for single cell RNA-Seq and Cytof/FACS data. 'SCINA' is capable of assigning cell type identities to a pool of cells profiled by scRNA-Seq or Cytof/FACS data with prior knowledge of markers, such as genes and protein symbols that are highly or lowly expressed in each category.
URL: http://lce.biohpc.swmed.edu/scina/ https://github.com/jcao89757/SCINA
License: GPL-2
NeedsCompilation: no
RoxygenNote: 6.1.0
Packaged: 2018-09-30 19:14:31 UTC; s421955
Repository: CRAN
Date/Publication: 2018-10-08 11:00:10 UTC

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New package rIP with initial version 0.1.0
Package: rIP
Type: Package
Title: Passes an Array of IP Addresses to Iphub.info and Returns a Dataframe with Details of IP
Version: 0.1.0
Authors@R: c(person("Ryan", "Kennedy", role = c("aut", "cre"), email = "rkennedy@uh.edu"), person("Philip", "Waggoner", role = "aut", email = "pdwaggoner@wm.edu"), person("Scott", "Clifford", role = "ctb"))
Maintainer: Ryan Kennedy <rkennedy@uh.edu>
Description: Takes as its input an array of IPs and the user's X-Key, passes these to <https://iphub.info/>, and returns a dataframe with the ip (used for merging), country code, country name, asn, isp, block, and hostname. Especially important in this is the variable "block", which gives a score indicating whether the IP address is likely from a server farm and should be excluded from the data. It is codes 0 if the IP is residential/unclassified (i.e. safe IP), 1 if the IP is non-residential IP (hostping provider, proxy, etc. -- should likely be excluded), and 2 for non-residential and residential IPs (more stringent, may flag innocent respondents). The recommendation from <https://iphub.info/> is to block or exclude those who score block = 1.
Imports: httr, utils
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-30 15:00:28 UTC; bpwaggo
Author: Ryan Kennedy [aut, cre], Philip Waggoner [aut], Scott Clifford [ctb]
Repository: CRAN
Date/Publication: 2018-10-08 10:40:06 UTC

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New package rgsp with initial version 0.1.0
Package: rgsp
Type: Package
Title: Repetitive Group Sampling Plan Based on Cpk
Version: 0.1.0
Authors@R: c( person(c("Muhammad", "Yaseen"), email = "myaseen208@gmail.com", role = c("aut", "cre")) , person(c("Muhammad", "Aslam"), email = "aslam_ravian@hotmail.com", role = c("aut", "ctb")) , person(c("Sami", "Ullah"), email = "samiullahuos@gmail.com", role = c("aut", "ctb")) , person(c("Muhammad", "Kashif"), email = "mkashif@uaf.edu.pk", role = c("aut", "ctb")) )
Author: Muhammad Yaseen [aut, cre], Muhammad Aslam [aut, ctb], Sami Ullah [aut, ctb], Muhammad Kashif [aut, ctb]
Maintainer: Muhammad Yaseen <myaseen208@gmail.com>
Description: Functions to calculate Sample Number and Average Sample Number for Repetitive Group Sampling Plan Based on Cpk as given in Aslam et al. (2013) (<DOI:10.1080/00949655.2012.663374>).
Depends: R (>= 3.1)
Imports: dplyr, magrittr, tibble
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Note: Department of Mathematics and Statistics, University of Agriculture Faisalabad, Faisalabad-Pakistan.
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-09-30 17:00:37 UTC; myaseen
Repository: CRAN
Date/Publication: 2018-10-08 10:40:03 UTC

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New package parmsurvfit with initial version 0.0.1
Package: parmsurvfit
Title: Parametric Survival Functions
Version: 0.0.1
Authors@R: c(person("Ashley", "Jacobson", email = "ashleypjacobson@gmail.com", role = c("aut", "cre")), person("Victor", "Wilson", email = "victorjw26@yahoo.com", role = c("aut")), person("Shannon", "Pileggi", email = "skmcclintock@gmail.com", role = c("aut")))
Description: Executes parametric survival analysis techniques similar to those in 'Minitab'. Fits right censored data to a given parametric distribution, produces summary statistics of the fitted distribution, and plots parametric survival, hazard, and cumulative hazard plots. Produces Anderson-Darling test statistic and probability plots to assess goodness of fit of right censored data to a distribution.
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: fitdistrplus, flexsurv, ggplot2, stats, graphics
Suggests: survival, utils, knitr, rmarkdown
VignetteBuilder: utils, knitr
NeedsCompilation: no
Packaged: 2018-10-06 22:08:14 UTC; ashle
Author: Ashley Jacobson [aut, cre], Victor Wilson [aut], Shannon Pileggi [aut]
Maintainer: Ashley Jacobson <ashleypjacobson@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-08 10:10:06 UTC

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New package MCSim with initial version 1.0
Package: MCSim
Type: Package
Title: Determine the Optimal Number of Clusters
Version: 1.0
Date: 2018-09-30
Author: Ahmed N. Albatineh, Meredith L. Wilcox, Bashar Zogheib, Magdalena Niewiadomska-Bugaj
Maintainer: Ahmed N. Albatineh <aalbatineh@hsc.edu.kw>
Description: Identifies the optimal number of clusters by calculating the similarity between two clustering methods at the same number of clusters using the corrected indices of Rand and Jaccard as described in Albatineh and Niewiadomska-Bugaj (2011). The number of clusters at which the index attain its maximum more frequently is a candidate for being the optimal number of clusters.
Depends: R (>= 3.1.0)
Imports: MASS,CircStats,stats,graphics
License: GPL-2
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-10-08 10:37:50 UTC; aalbatineh
Repository: CRAN
Date/Publication: 2018-10-08 11:00:17 UTC

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New package FourgameteP with initial version 0.1.0
Package: FourgameteP
Type: Package
Title: FourGamete Test
Version: 0.1.0
Author: Milton T Drott
Maintainer: Milton T Drott <mtd66@cornell.edu>
Description: The four-gamete test is based on the infinite-sites model which assumes that the probability of the same mutation occurring twice (recurrent or parallel mutations) and the probability of a mutation back to the original state (reverse mutations) are close to zero. Without these types of mutations, the only explanation for observing the four dilocus genotypes (example below) is recombination (Hudson and Kaplan 1985, Genetics 111:147-164). Thus, the presence of all four gametes is also called phylogenetic incompatibility.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-30 18:55:13 UTC; mtd
Repository: CRAN
Date/Publication: 2018-10-08 10:50:03 UTC

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New package ectotemp with initial version 0.1.1
Package: ectotemp
Title: Quantitative Estimates of Small Ectotherm Temperature Regulation Effectiveness
Version: 0.1.1
Author: Wouter Beukema <wouter.beukema@gmail.com>
Maintainer: Wouter Beukema <wouter.beukema@gmail.com>
Description: Easy and rapid quantitative estimation of small terrestrial ectotherm temperature regulation effectiveness in R. 'ectotemp' is built on classical formulas that evaluate temperature regulation by means of various indices, inaugurated by Hertz et al. (1993) <doi: 10.1086/285573>. Options for bootstrapping and permutation testing are included to test hypotheses about divergence between organisms, species or populations.
Depends: R (>= 3.5.0)
Imports: dplyr, psych, stats, graphics
URL: https://github.com/wouterbeukema/ectotemp
BugReports: https://github.com/wouterbeukema/ectotemp/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-30 10:35:18 UTC; beukepap
Repository: CRAN
Date/Publication: 2018-10-08 10:20:03 UTC

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New package BayesMallows with initial version 0.1.0
Package: BayesMallows
Type: Package
Title: Bayesian Preference Learning with the Mallows Rank Model
Version: 0.1.0
Author: Oystein Sorensen, Valeria Vitelli, Marta Crispino, Qingua Liu
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>
Description: An implementation of the Bayesian version of the Mallows rank model (Vitelli et al., Journal of Machine Learning Research, 2018 <http://jmlr.org/papers/v18/15-481.html>). Both Cayley, footrule, Kendall, and Spearman distances are supported in the models. The rank data to be analyzed can be the form of complete rankings, top-k rankings, partially missing rankings, as well as consistent pairwise preferences. Several functions for plotting and studying the posterior distributions of parameters are provided. The package also provides functions for estimating the partition function (normalizing constant) of the Mallows rank model, both with the importance sampling algorithm of Vitelli et al. and asymptotic approximation with the IPFP algorithm (Mukherjee, Annals of Statistics, 2016 <doi:10.1214/15-AOS1389>).
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Depends: R (>= 2.10)
Imports: Rcpp (>= 0.12.17), ggplot2 (>= 2.2.1), Rdpack (>= 0.8), stats (>= 3.5.0), igraph (>= 1.2.2), dplyr (>= 0.7.6), sets (>= 1.0-18), relations (>= 0.6-8), tidyr (>= 0.8.1), purrr (>= 0.2.5), rlang (>= 0.2.1), HDInterval (>= 0.2.0), cowplot (>= 0.9.3)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, gtools (>= 3.8.1), knitr, PerMallows (>= 1.13), rmarkdown, Rankcluster (>= 0.94)
VignetteBuilder: knitr
RdMacros: Rdpack
NeedsCompilation: yes
Packaged: 2018-09-30 15:55:00 UTC; oyss
Repository: CRAN
Date/Publication: 2018-10-08 10:50:25 UTC

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New package jipApprox with initial version 0.1.1
Package: jipApprox
Title: Approximate Inclusion Probabilities for Survey Sampling
Version: 0.1.1
Date: 2018-09-20
Authors@R: person("Roberto", "Sichera", email = "roberto.sichera@unipa.it", role = c("aut", "cre"))
Description: Approximate joint-inclusion probabilities in Unequal Probability Sampling, or compute Monte Carlo approximations of the first and second-order inclusion probabilities of a general sampling design as in Fattorini (2006) <doi:10.1093/biomet/93.2.269>.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/rhobis/jipApprox/issues
RoxygenNote: 6.1.0
Imports: sampling
NeedsCompilation: no
Packaged: 2018-09-20 07:27:37 UTC; roberto
Author: Roberto Sichera [aut, cre]
Maintainer: Roberto Sichera <roberto.sichera@unipa.it>
Repository: CRAN
Date/Publication: 2018-10-08 10:00:03 UTC

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New package COMBIA with initial version 1.0.6
Encoding: UTF-8
Package: COMBIA
Type: Package
Title: Synergy/Antagonism Analyses of Drug Combinations
Version: 1.0.6
Date: 2018-10-07
Author: Muhammad Kashif
Maintainer: Muhammad Kashif <Muhammad.Kashif@medsci.uu.se>
Description: A comprehensive synergy/antagonism analyses of drug combinations with quality graphics and data. The analyses can be performed by Bliss independence and Loewe additivity models. 'COMBIA' provides improved statistical analysis and makes only very weak assumption of data variability while calculating bootstrap intervals (BIs). It is based on heteroscedasticity controlled resampling (bootstrapping) and includes a global (omnibus) test. Finally, package shows analyzed data, 2D and 3D plots ready to use in research publications. 'COMBIA' does not require manual data entry. Data can be directly input from wet lab experimental platforms for example fluostar, automated robots etc. One only needs to call a single function, analyzeCOMBO(), to perform all analysis (examples are provided with sample data).
URL: <http://www.impactjournals.com/oncotarget/index.php?journal=oncotarget&page=article&op=view&path%5B%5D=21895&path%5B%5D=69432>.
Depends: hash, lattice, latticeExtra, oro.nifti
Imports: gdata, grDevices, stats, utils
License: GPL (>= 2)
SystemRequirements: perl (>= 5.10.0)
LazyLoad: yes
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-10-08 09:23:20 UTC; muhkas
Repository: CRAN
Date/Publication: 2018-10-08 09:50:26 UTC

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Sun, 07 Oct 2018

New package UPSvarApprox with initial version 0.1.1
Package: UPSvarApprox
Type: Package
Title: Approximate the Variance of the Horvitz-Thompson Total Estimator
Version: 0.1.1
Date: 2018-09-20
Authors@R: person("Roberto", "Sichera", email = "roberto.sichera@unipa.it", role = c("aut", "cre") )
Description: Variance approximations for the Horvitz-Thompson total estimator in Unequal Probability Sampling using only first-order inclusion probabilities. See Matei and Tillé (2005) and Haziza, Mecatti and Rao (2008) for details.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
BugReports: https://github.com/rhobis/UPSvarApprox/issues
NeedsCompilation: no
Packaged: 2018-10-07 17:40:05 UTC; roberto
Author: Roberto Sichera [aut, cre]
Maintainer: Roberto Sichera <roberto.sichera@unipa.it>
Repository: CRAN
Date/Publication: 2018-10-07 18:32:17 UTC

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New package Temporal with initial version 0.1.1
Package: Temporal
Title: Parametric Time to Event Analysis
Version: 0.1.1
Authors@R: person("Zachary", "McCaw", email = "zmccaw@g.harvard.edu", role = c("aut", "cre"))
Description: Performs likelihood-based estimation and inference on time to event data, possibly subject to non-informative right censoring. fitParaSurv() provides maximum likelihood estimates of model parameters and distributional characteristics. compParaSurv() compares the mean and median survival experiences of two treatment arms. Candidate distributions currently include the exponential, gamma, generalized gamma, log-logistic, log-normal, and Weibull.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, RcppEigen
Imports: expint, methods, numDeriv, plyr, Rcpp, stats
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-10-06 23:17:04 UTC; zmccaw
Author: Zachary McCaw [aut, cre]
Maintainer: Zachary McCaw <zmccaw@g.harvard.edu>
Repository: CRAN
Date/Publication: 2018-10-07 18:32:20 UTC

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New package directotree with initial version 1.0.0
Package: directotree
Type: Package
Title: Creates an Interactive Tree Structure of a Directory
Version: 1.0.0
Authors@R: person("Louis", "Sirugue", email = "lsirugue@protonmail.com", role = c("aut", "cre"))
Description: Represents the content of a directory as an interactive collapsible tree. Offers the possibility to assign a text (e.g., a 'Readme.txt') to each folder (represented as a clickable node), so that when the user hovers the pointer over a node, the corresponding text is displayed as a tooltip.
Depends: R (>= 3.0.0)
License: GPL (>= 3)
Encoding: UTF-8
Imports: collapsibleTree (>= 0.1.6), data.tree (>= 0.7.6)
LazyData: true
NeedsCompilation: no
Packaged: 2018-10-06 22:54:44 UTC; Louis
Author: Louis Sirugue [aut, cre]
Maintainer: Louis Sirugue <lsirugue@protonmail.com>
Repository: CRAN
Date/Publication: 2018-10-07 18:32:12 UTC

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New package coxrt with initial version 1.0.0
Package: coxrt
Type: Package
Title: Cox Proportional Hazards Regression for Right Truncated Data
Version: 1.0.0
Author: Bella Vakulenko-Lagun, Micha Mandel, Rebecca A. Betensky
Maintainer: Bella Vakulenko-Lagun <bella.vakulenko-lagun@mail.huji.ac.il>
Description: Fits Cox regression based on retrospectively ascertained times-to-event. The method uses Inverse-Probability-Weighting estimating equations.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: survival, BB, inline, gss, ggplot2
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Bella2001/coxrt
BugReports: https://github.com/Bella2001/coxrt/issues
NeedsCompilation: yes
Packaged: 2018-10-07 02:08:13 UTC; bev271
Repository: CRAN
Date/Publication: 2018-10-07 19:00:02 UTC

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New package radiant with initial version 0.9.7
Package: radiant
Type: Package
Title: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: A platform-independent browser-based interface for business analytics in R, based on the shiny package. The application combines the functionality of radiant.data, radiant.design, radiant.basics, radiant.model, and radiant.multivariate.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7), radiant.design (>= 0.9.7), radiant.basics (>= 0.9.7), radiant.model (>= 0.9.7), radiant.multivariate (>= 0.9.7)
Imports: shiny (>= 1.1.0), import (>= 1.1.0)
Suggests: testthat (>= 2.0.0), knitr, rmarkdown
URL: https://github.com/radiant-rstats/radiant
BugReports: https://github.com/radiant-rstats/radiant/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-10-06 22:03:03 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-07 17:30:03 UTC

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New package lolog with initial version 1.0
Package: lolog
Maintainer: Ian E. Fellows <ian@fellstat.com>
License: MIT + file LICENSE
Title: Latent Order Logistic Graph Models
LinkingTo: Rcpp, BH
Type: Package
LazyLoad: yes
Author: c(person(c("Ian","E."),"Fellows", role=c("aut","cre"), email="ian@fellstat.com"), person(c("Mark","S."),"Handcock", role="ctb"))
Description: Estimation of Latent Order Logistic (LOLOG) Models for Networks. LOLOGs are a flexible and fully general class of statistical graph models. This package provides functions for performing MOM, GMM and variational inference. Visual diagnostics and goodness of fit metrics are provided. See Fellows (2018) <arXiv:1804.04583> for a detailed description of the methods.
Version: 1.0
Depends: R (>= 3.0.0), methods, Rcpp (>= 0.9.4)
Imports: network, parallel, ggplot2, reshape2, intergraph
Suggests: testthat, inline, knitr, rmarkdown, ergm, BH, igraph
URL: https://github.com/statnet/lolog
RcppModules: lolog
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-10-05 17:43:48 UTC; ianfellows
Repository: CRAN
Date/Publication: 2018-10-07 17:30:08 UTC

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Sat, 06 Oct 2018

New package tls with initial version 0.1.0
Package: tls
Title: Tools of Total Least Squares in Error-in-Variables Models
Version: 0.1.0
Date: 2018-09-28
Authors@R: c( person(given = "Yan", family = "Li", email = "yan.4.li@uconn.edu", role = c("aut", "cre")), person(given = "Kun", family = "Chen", role = "aut"), person(given = "Jun", family = "Yan", role = "aut"))
Description: Functions for point and interval estimation in error-in-variables models via total least squares or generalized total least squares method. See Golub and Van Loan (1980) <doi:10.1137/0717073>, Gleser (1981) <https://www.jstor.org/stable/2240867>, Ivan Markovsky and Huffel (2007) <doi:10.1016/j.sigpro.2007.04.004> for more information.
Depends: R (>= 3.2.3)
Imports: stats, utils
License: GPL (>= 3)
URL: https://github.com/LiYanStat/tls
BugReports: https://github.com/LiYanStat/tls/issues
Repository: CRAN
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-28 23:29:10 UTC; YLi
Author: Yan Li [aut, cre], Kun Chen [aut], Jun Yan [aut]
Maintainer: Yan Li <yan.4.li@uconn.edu>
Date/Publication: 2018-10-06 23:00:03 UTC

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New package lamme with initial version 0.0.1
Package: lamme
Title: Log-Analytic Methods for Multiplicative Effects
Version: 0.0.1
Authors@R: person("Qimin", "Liu", email = "qliu6@nd.edu", role = c("aut", "cre"))
Description: Log-analytic methods intended for testing multiplicative effects.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0.9000
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-29 05:13:02 UTC; qliu6
Author: Qimin Liu [aut, cre]
Maintainer: Qimin Liu <qliu6@nd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 23:00:06 UTC

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New package CoRpower with initial version 1.0.0
Package: CoRpower
Title: Power Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials
Version: 1.0.0
BugReports: https://github.com/mjuraska/CoRpower/issues
Authors@R: c(person("Peter", "Gilbert", email = "pgilbert@scharp.org", role = "aut"), person("Stephanie", "Wu", email = "swu18@uw.edu", role = "aut"), person("Michal", "Juraska", email = "mjuraska@fredhutch.org", role = c("aut", "cre")), person("Yunda", "Huang", email = "yunda@scharp.org", role = "aut"))
Description: Calculates power for assessment of intermediate biomarker responses as correlates of risk in the active treatment group in clinical efficacy trials, as described in Gilbert, Janes, and Huang, Power/Sample Size Calculations for Assessing Correlates of Risk in Clinical Efficacy Trials (2016, Statistics in Medicine). The methods differ from past approaches by accounting for the level of clinical treatment efficacy overall and in biomarker response subgroups, which enables the correlates of risk results to be interpreted in terms of potential correlates of efficacy/protection. The methods also account for inter-individual variability of the observed biomarker response that is not biologically relevant (e.g., due to technical measurement error of the laboratory assay used to measure the biomarker response), which is important because power to detect a specified correlate of risk effect size is heavily affected by the biomarker's measurement error. The methods can be used for a general binary clinical endpoint model with a univariate dichotomous, trichotomous, or continuous biomarker response measured in active treatment recipients at a fixed timepoint after randomization, with either case-cohort Bernoulli sampling or case-control without-replacement sampling of the biomarker (a baseline biomarker is handled as a trivial special case). In a specified two-group trial design, the computeN() function can initially be used for calculating additional requisite design parameters pertaining to the target population of active treatment recipients observed to be at risk at the biomarker sampling timepoint. Subsequently, the power calculation employs an inverse probability weighted logistic regression model fitted by the tps() function in the 'osDesign' package. Power results as well as the relationship between the correlate of risk effect size and treatment efficacy can be visualized using various plotting functions.
URL: https://github.com/mjuraska/CoRpower
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
Imports: survival, osDesign
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-28 21:34:45 UTC; mjuraska
Author: Peter Gilbert [aut], Stephanie Wu [aut], Michal Juraska [aut, cre], Yunda Huang [aut]
Maintainer: Michal Juraska <mjuraska@fredhutch.org>
Repository: CRAN
Date/Publication: 2018-10-06 23:00:09 UTC

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New package QDComparison with initial version 1.0
Package: QDComparison
Type: Package
Title: Modern Nonparametric Tools for Two-Sample Quantile and Distribution Comparisons
Version: 1.0
Date: 2018-09-25
Author: David Jungreis, Subhadeep Mukhopadhyay
Maintainer: David Jungreis <dbjungreis@gmail.com>
Description: Allows practitioners to determine (i) if two univariate distributions (which can be continuous, discrete, or even mixed) are equal, (ii) how two distributions differ (shape differences, e.g., location, scale, etc.), and (iii) where two distributions differ (at which quantiles), all using nonparametric LP statistics. The primary reference is Jungreis, D. and Mukhopadhyay, S. (2018, Technical Report).
License: GPL-2
NeedsCompilation: no
Packaged: 2018-09-28 17:18:00 UTC; Dave
Repository: CRAN
Date/Publication: 2018-10-06 21:20:11 UTC

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New package PredictionR with initial version 1.0-11
Package: PredictionR
Title: Prediction for Future Data from any Continuous Distribution
Version: 1.0-11
Authors@R: c(person("H. ", "M. Barakat", role = c("aut"), email = "hbarakat2@hotmail.com"), person("O. ", "M. Khaled", role = c("aut"), email = "osam87@yahoo.com"), person("Hadeer ", "A. Ghonem", role = c("aut", "cre"), email = "hadeer_ghonem15@yahoo.com"))
Author: H. M. Barakat [aut], O. M. Khaled [aut], Hadeer A. Ghonem [aut, cre]
Maintainer: Hadeer A. Ghonem <hadeer_ghonem15@yahoo.com>
Description: Functions to get prediction intervals and prediction points of future observations from any continuous distribution.
License: GPL (>= 2)
LazyData: TRUE
Imports: stats, fitdistrplus
Suggests: actuar
NeedsCompilation: no
Packaged: 2018-09-28 15:25:40 UTC; USER
Repository: CRAN
Date/Publication: 2018-10-06 21:30:14 UTC

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New package outcomerate with initial version 1.0.1
Package: outcomerate
Version: 1.0.1
Title: AAPOR Survey Outcome Rates
Description: Standardized survey outcome rate functions, including the response rate, contact rate, cooperation rate, and refusal rate. These outcome rates allow survey researchers to measure the quality of survey data using definitions published by the American Association of Public Opinion Research (AAPOR). For details on these standards, see AAPOR (2016) <https://www.aapor.org/Standards-Ethics/Standard-Definitions-(1).aspx>.
Authors@R: c( person(given = "Rafael", family = "Pilliard Hellwig", email = "rafael.taph@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-3092-3493")), person(given = "Carl", family = "Ganz", role = "rev"), person(given = "Neal", family = "Richardson", role = "rev") )
License: CC0
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
Depends: R (>= 2.10)
Suggests: dplyr, forcats, ggplot2, knitr, testthat, tidyr, covr, rmarkdown, spelling, stringr
Imports: Rdpack (>= 0.7), stats
RdMacros: Rdpack
Language: en-US
URL: https://github.com/ropensci/outcomerate
BugReports: https://github.com/ropensci/outcomerate/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-27 21:13:18 UTC; rtaph
Author: Rafael Pilliard Hellwig [aut, cre] (<https://orcid.org/0000-0002-3092-3493>), Carl Ganz [rev], Neal Richardson [rev]
Maintainer: Rafael Pilliard Hellwig <rafael.taph@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-06 21:20:03 UTC

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New package mlflow with initial version 0.7.0
Package: mlflow
Type: Package
Title: Interface to 'MLflow'
Version: 0.7.0
Authors@R: c( person("Matei", "Zaharia", email = "matei@databricks.com", role = c("aut", "cre")), person("Javier", "Luraschi", email = "javier@rstudio.com", role = c("aut")), person("Kevin", "Kuo", role = c("aut"), email = "kevin.kuo@rstudio.com", comment = c(ORCID = "0000-0001-7803-7901")), person(family = "RStudio", role = c("cph")) )
Maintainer: Matei Zaharia <matei@databricks.com>
Description: R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
License: Apache License 2.0
URL: https://github.com/mlflow/mlflow
BugReports: https://github.com/mlflow/mlflow/issues
SystemRequirements: MLflow (https://www.mlflow.org/)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.1.2)
Imports: aws.s3, forge, fs, git2r, httpuv, httr, jsonlite, openssl, processx, reticulate, packrat, purrr, swagger, withr, xml2, yaml, pryr, rlang (>= 0.2.0)
RoxygenNote: 6.1.0
Suggests: covr, keras, lintr, testthat
NeedsCompilation: no
Packaged: 2018-09-28 19:17:25 UTC; tomas
Author: Matei Zaharia [aut, cre], Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Repository: CRAN
Date/Publication: 2018-10-06 21:30:03 UTC

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New package metamedian with initial version 0.1.0
Package: metamedian
Type: Package
Title: Meta-Analysis of Medians
Version: 0.1.0
Authors@R: c(person("Sean", "McGrath", role = c("aut", "cre"), email = "sean.mcgrath@mail.mcgill.ca"), person("XiaoFei", "Zhao", role = c("aut"), email = "xiaofei.zhao@mail.mcgill.ca"), person("Russell", "Steele", role = c("aut"), email = "russell.steele@mcgill.ca"), person("Andrea", "Benedetti", role = c("aut"), email = "andrea.benedetti@mcgill.ca"))
Author: Sean McGrath [aut, cre], XiaoFei Zhao [aut], Russell Steele [aut], Andrea Benedetti [aut]
Maintainer: Sean McGrath <sean.mcgrath@mail.mcgill.ca>
Description: Implements several methods to meta-analyze one-group or two-group studies that report the median of the outcome. These methods estimate the pooled median in the one-group context and the pooled raw difference of medians across groups in the two-group context.
Imports: stats, metafor, Hmisc
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-28 18:13:28 UTC; Sean
Repository: CRAN
Date/Publication: 2018-10-06 21:30:07 UTC

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New package airportr with initial version 0.1.2
Package: airportr
Type: Package
Title: Convenience Tools for Working with Airport Data
Version: 0.1.2
Author: Dmitry Shkolnik
Maintainer: Dmitry Shkolnik <shkolnikd@gmail.com>
Description: Retrieves open source airport data and provides tools to look up information, translate names into codes and vice-verse, as well as some basic calculation functions for measuring distances.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr
Depends: R(>= 2.10.0)
URL: https://github.com/dshkol/airportr
BugReports: https://github.com/dshkol/airportr/issues
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-27 15:37:44 UTC; dshkol
Repository: CRAN
Date/Publication: 2018-10-06 21:20:07 UTC

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New package radiant.multivariate with initial version 0.9.7
Package: radiant.multivariate
Type: Package
Title: Multivariate Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Multivariate menu includes interfaces for perceptual mapping, factor analysis, cluster analysis, and conjoint analysis. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7)
Imports: radiant.model (>= 0.9.7), shiny (>= 1.1.0), dplyr (>= 0.7.5), rlang (>= 0.2.0), ggplot2 (>= 2.2.1), gridExtra (>= 2.0.0), scales (>= 0.4.0), magrittr (>= 1.5), psych (>= 1.8.4), GPArotation (>= 2014.11-1), car (>= 2.1.1), MASS (>= 7.3), import (>= 1.1.0), Gmedian (>= 1.2.3), ggrepel (>= 0.8)
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.multivariate, https://radiant-rstats.github.io/radiant.multivariate, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.multivariate/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 16:59:48 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 21:00:07 UTC

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New package radiant.model with initial version 0.9.7
Package: radiant.model
Type: Package
Title: Model Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Model menu includes interfaces for linear and logistic regression, naive Bayes, neural networks, classification and regression trees, model evaluation, collaborative filtering, decision analysis, and simulation. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7)
Imports: radiant.basics (>= 0.9.7), shiny (>= 1.1.0), nnet (>= 7.3.12), NeuralNetTools (>= 1.5.1), sandwich (>= 2.3.4), car (>= 2.1.3), ggplot2 (>= 2.2.1), gridExtra (>= 2.0.0), data.tree (>= 0.7.4), stringr (>= 1.1.0), lubridate (>= 1.7.2), tidyr (>= 0.8.0), dplyr (>= 0.7.6), rlang (>= 0.2.2), magrittr (>= 1.5), DiagrammeR (>= 1.0.0), import (>= 1.1.0), psych (>= 1.8.4), e1071 (>= 1.6.8), rpart (>= 4.1.11), yaml
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.model, https://radiant-rstats.github.io/radiant.model, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.model/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 15:25:47 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 16:00:03 UTC

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New package VICmodel with initial version 0.1.1
Package: VICmodel
Type: Package
Title: The Variable Infiltration Capacity (VIC) Model
Version: 0.1.1
Authors@R: c(person("Ruida", "Zhong", email = "zrd2017@163.com", role = c("aut", "cre")), person("Xiaohong", "Chen", email = "eescxh@mail.sysu.edu.cn", role = c("aut", "ctb")), person("Zhaoli", "Wang", email = "wangzhl@scut.edu.cn", role = c("aut", "ctb")), person("Chengguang", "Lai", email = "laichg@scut.edu.cn", role = c("aut", "ctb")), person("Joseph J", "Hamman", role = c("ctb"), comment = "Contributor and maintainer of VIC source code"), person("Keith", "Cherkauer", role = c("ctb")) )
Description: The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally. If you make use of this model, please acknowledge the appropriate references listed in the help page of this package or on the references page <http://vic.readthedocs.io/en/master/Documentation/References/> of the VIC official documentation website. These should include Liang et al. (1994) plus any references relevant to the features you are using Reference: Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, <doi:10.1029/94JD00483>. Hamman et al. (2018) about VIC 5.0.1 also can be considered: Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, <doi:10.5194/gmd-11-3481-2018>.
License: GPL-3
Copyright: file inst/COPYRIGHTS
URL: https://github.com/Sibada/VICmodel
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: stats, utils, Rcpp (>= 0.12.0), foreach
Suggests: doParallel
LinkingTo: Rcpp
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2018-10-06 03:00:18 UTC; vicerTi
Author: Ruida Zhong [aut, cre], Xiaohong Chen [aut, ctb], Zhaoli Wang [aut, ctb], Chengguang Lai [aut, ctb], Joseph J Hamman [ctb] (Contributor and maintainer of VIC source code), Keith Cherkauer [ctb]
Maintainer: Ruida Zhong <zrd2017@163.com>
Repository: CRAN
Date/Publication: 2018-10-06 06:50:20 UTC

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New package radiant.design with initial version 0.9.7
Package: radiant.design
Type: Package
Title: Design Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Design menu includes interfaces for design of experiments, sampling, and sample size calculation. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7), mvtnorm
Imports: dplyr (>= 0.7.6), shiny (>= 1.1.0), AlgDesign (>= 1.1.7.3), import (>= 1.1.0), polycor
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.design, https://radiant-rstats.github.io/radiant.design, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.design/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 03:42:51 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 06:50:04 UTC

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New package radiant.basics with initial version 0.9.7
Package: radiant.basics
Type: Package
Title: Basics Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-5
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Basics menu includes interfaces for probability calculation, central limit theorem simulation, comparing means and proportions, goodness-of-fit testing, cross-tabs, and correlation. The application extends the functionality in radiant.data.
Depends: R (>= 3.4.0), radiant.data (>= 0.9.7)
Imports: ggplot2 (>= 2.2.1), gridExtra (>= 2.0.0), scales (>= 0.4.0), dplyr (>= 0.7.6), tidyr (>= 0.8.0), magrittr (>= 1.5), shiny (>= 1.1.0), psych (>= 1.8.3.3), import (>= 1.1.0)
Suggests: testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.basics, https://radiant-rstats.github.io/radiant.basics, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.basics/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-06 03:47:04 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-06 06:50:09 UTC

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Fri, 05 Oct 2018

New package radiant.data with initial version 0.9.7
Package: radiant.data
Title: Data Menu for Radiant: Business Analytics using R and Shiny
Version: 0.9.7
Date: 2018-10-4
Authors@R: person("Vincent", "Nijs", , "radiant@rady.ucsd.edu", c("aut", "cre"))
Description: The Radiant Data menu includes interfaces for loading, saving, viewing, visualizing, summarizing, transforming, and combining data. It also contains functionality to generate reproducible reports of the analyses conducted in the application.
Depends: R (>= 3.4.0), magrittr (>= 1.5), ggplot2 (>= 2.2.1), lubridate (>= 1.7.4), tidyr (>= 0.8.0), dplyr (>= 0.7.6)
Imports: tibble (>= 1.4.2), rlang (>= 0.2.2), broom (>= 0.4.3), car (>= 3.0-0), grid (>= 3.3.1), gridExtra (>= 2.0.0), knitr (>= 1.20), markdown (>= 0.8), rmarkdown(>= 1.9), shiny (>= 1.1.0), jsonlite (>= 1.0), shinyAce (>= 0.3.1), psych (>= 1.8.4), DT (>= 0.4), readr (>= 1.1.1), readxl (>= 1.0.0), writexl (>= 0.2), scales (>= 0.4.0), curl (>= 2.5), rstudioapi (>= 0.7), import (>= 1.1.0), plotly (>= 4.7.1), glue (>= 1.3.0), shinyFiles (>= 0.7.1), summarytools (>= 0.8.7), base64enc
Suggests: svglite (>= 1.2.1), DBI (>= 0.7), RSQLite (>= 2.0), odbc (>= 1.1.4), webshot (>= 0.5.0), testthat (>= 2.0.0), pkgdown (>= 1.1.0)
URL: https://github.com/radiant-rstats/radiant.data, https://radiant-rstats.github.io/radiant.data, https://radiant-rstats.github.io/docs
BugReports: https://github.com/radiant-rstats/radiant.data/issues
License: AGPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-05 01:42:11 UTC; vnijs
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>
Repository: CRAN
Date/Publication: 2018-10-05 10:30:03 UTC

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Thu, 04 Oct 2018

New package simode with initial version 1.1.0
Package: simode
Type: Package
Title: Statistical Inference for Systems of Ordinary Differential Equations using Separable Integral-Matching
Version: 1.1.0
Authors@R: c( person("Itai", "Dattner", email = "idattner@stat.haifa.ac.il", role = "aut"), person("Rami", "Yaari", email = "ramiyaari@gmail.com", role = c("aut", "cre")))
Description: Implements statistical inference for systems of ordinary differential equations, that uses the integral-matching criterion and takes advantage of the separability of parameters, in order to obtain initial parameter estimates for nonlinear least squares optimization. Dattner & Yaari (2018) <arXiv:1807.04202>. Dattner et al. (2017) <doi:10.1098/rsif.2016.0525>. Dattner & Klaassen (2015) <doi:10.1214/15-EJS1053>.
Depends: R (>= 3.4.0)
Imports: deSolve, pracma, quadprog
Suggests: parallel, Rcgmin, Rvmmin, R.rsp
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2018-10-04 12:28:02 UTC; ramiy
Author: Itai Dattner [aut], Rami Yaari [aut, cre]
Maintainer: Rami Yaari <ramiyaari@gmail.com>
Repository: CRAN
Date/Publication: 2018-10-04 22:50:02 UTC

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Wed, 03 Oct 2018

New package RcmdrPlugin.RiskDemo with initial version 2.0
Package: RcmdrPlugin.RiskDemo
Type: Package
Title: R Commander Plug-in for Risk Demonstration
Version: 2.0
Date: 2018-10-3
Author: Arto Luoma
Maintainer: Arto Luoma <arto.luoma@wippies.com>
Description: R Commander plug-in to demonstrate various actuarial and financial risks. It includes valuation of bonds and stocks, portfolio optimization, classical ruin theory and demography.
Depends: R (>= 2.10), rgl, demography
Imports: Rcmdr, ftsa
Suggests: tkrplot
License: GPL-2
LazyData: no
LazyLoad: yes
NeedsCompilation: no
Packaged: 2018-10-03 14:07:37 UTC; arto
Repository: CRAN
Date/Publication: 2018-10-03 21:52:23 UTC

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New package Gifi with initial version 0.3-8
Package: Gifi
Type: Package
Title: Multivariate Analysis with Optimal Scaling
Version: 0.3-8
Date: 2018-10-02
Authors@R: c(person("Patrick", "Mair", role = c("aut", "cre"), email = "mair@fas.harvard.edu"), person("Jan", "De Leeuw", role = "aut"), person("Patrick J. F.", "Groenen", role = "ctb"))
Description: Implements categorical principal component analysis ('PRINCALS'), multiple correspondence analysis ('HOMALS'). It replaces the 'homals' package.
URL: http://r-forge.r-project.org/projects/psychor/
Imports: graphics, stats, colorspace
Depends: R (>= 3.1.0)
License: GPL-3
Suggests: knitr, psych
LazyData: yes
LazyLoad: yes
ByteCompile: yes
NeedsCompilation: yes
Packaged: 2018-10-03 12:38:22 UTC; root
Author: Patrick Mair [aut, cre], Jan De Leeuw [aut], Patrick J. F. Groenen [ctb]
Maintainer: Patrick Mair <mair@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2018-10-03 15:27:18 UTC

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Tue, 02 Oct 2018

New package tensorBF with initial version 1.0.2
Package: tensorBF
Type: Package
Title: Bayesian Tensor Factorization
Version: 1.0.2
Date: 2018-10-01
Authors@R: c(person("Suleiman A", "Khan", role = c("aut","cre"), email = "khan.suleiman@gmail.com"), person("Muhammad", "Ammad-ud-din", role = "aut", email = "muhammad.ammad-ud-din@aalto.fi"))
Author: Suleiman A Khan [aut, cre], Muhammad Ammad-ud-din [aut]
Maintainer: Suleiman A Khan <khan.suleiman@gmail.com>
Description: Bayesian Tensor Factorization for decomposition of tensor data sets using the trilinear CANDECOMP/PARAFAC (CP) factorization, with automatic component selection. The complete data analysis pipeline is provided, including functions and recommendations for data normalization and model definition, as well as missing value prediction and model visualization. The method performs factorization for three-way tensor datasets and the inference is implemented with Gibbs sampling.
License: MIT + file LICENSE
Imports: tensor, methods
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-02 07:20:14 UTC; skhan
Repository: CRAN
Date/Publication: 2018-10-02 18:10:03 UTC

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New package synoptReg with initial version 0.1.0
Package: synoptReg
Type: Package
Title: Synoptic Climate Classification and Spatial Regionalization of Environmental Data
Version: 0.1.0
Depends: R (>= 2.10)
Author: Marc Lemus-Canovas
Maintainer: Marc Lemus-Canovas <mlemus@ub.edu>
Description: Computes a synoptic climate classification through daily reanalysis data and creates a climate or environmental regionalization.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: ncdf4, zoo, fields, raster, maps
NeedsCompilation: no
RoxygenNote: 6.1.0
Packaged: 2018-09-28 12:01:52 UTC; Marc
Repository: CRAN
Date/Publication: 2018-10-02 18:00:02 UTC

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Mon, 01 Oct 2018

New package IMmailgun with initial version 0.1.2
Package: IMmailgun
Type: Package
Title: Send Emails using 'Mailgun'
Version: 0.1.2
Author: Ignacio Martinez
Maintainer: Ignacio Martinez <ignacio@protonmail.com>
Description: Send emails using the 'mailgun' api. To use this package you will need an account from <https://www.mailgun.com> .
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: httr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-27 17:10:00 UTC; rstudio
Repository: CRAN
Date/Publication: 2018-10-01 22:40:03 UTC

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New package EncDNA with initial version 1.0.1
Package: EncDNA
Type: Package
Title: Encoding of Nucleotide Sequences into Numeric Feature Vectors
Version: 1.0.1
Date: 2018-09-17
Author: Prabina Kumar Meher
Maintainer: Prabina Kumar Meher <meherprabin@yahoo.com>
Depends: R(>= 3.3.0)
Imports: Biostrings
LazyData: TRUE
Description: We describe fifteen different splice site sequence encoding schemes that have been used in earlier studies for mapping of splice site sequences into numeric feature vectors. These encoding schemes will also be helpful for transforming other nucleotide sequences into numeric forms, provided they are of equal length. These encoding schemes will help the computational biologist working in the field of classification (binary or multiclass) or prediction involving nucleic acid sequences of equal length.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-28 07:52:38 UTC; USER
Repository: CRAN
Date/Publication: 2018-10-01 22:30:03 UTC

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New package WeightedROC with initial version 2018.10.1
Package: WeightedROC
Maintainer: Toby Dylan Hocking <toby.hocking@r-project.org>
Author: Toby Dylan Hocking
Version: 2018.10.1
License: GPL-3
Title: Fast, Weighted ROC Curves
Description: Fast computation of Receiver Operating Characteristic (ROC) curves and Area Under the Curve (AUC) for weighted binary classification problems (weights are example-specific cost values).
Suggests: ROCR, pROC, PRROC, microbenchmark, glmnet, ElemStatLearn, testthat, ggplot2, GsymPoint, geometry
NeedsCompilation: no
Packaged: 2018-10-01 20:17:48 UTC; tdhock
Repository: CRAN
Date/Publication: 2018-10-01 21:50:06 UTC

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New package hrIPW with initial version 0.1.2
Package: hrIPW
Title: Hazard Ratio Estimation using Cox Model Weighted by the Estimated Propensity Score
Version: 0.1.2
Authors@R: person("David", "Hajage", email = "david.hajage@aphp.fr", role = c("aut", "cre"))
Description: Estimates the log hazard ratio associated with a binary exposure using a Cox PH model weighted by the propensity score. Propensity model is estimated using a simple logistic regression. Variance estimation takes into account the propensity score estimation step with the method proposed by Hajage et al. (2018) <doi:10.1002/bimj.201700330>. Both the average treatment effect on the overall (ATE) or the treated (ATT) population can be estimated. For the ATE estimation, both unstabilized and stabilized weights can be used.
Depends: R (>= 3.3)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: survival
Suggests: IPWsurvival, boot
NeedsCompilation: no
Packaged: 2018-09-27 07:51:27 UTC; 3121805
Author: David Hajage [aut, cre]
Maintainer: David Hajage <david.hajage@aphp.fr>
Repository: CRAN
Date/Publication: 2018-10-01 21:50:02 UTC

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New package AMR with initial version 0.4.0
Package: AMR
Version: 0.4.0
Date: 2018-10-01
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 = c("aut", "rev"), 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 = "ths", comment = c(ORCID = "0000-0003-1241-1328")), person( given = c("Alex", "W."), family = "Friedrich", email = "alex.friedrich@umcg.nl", role = "ths", comment = c(ORCID = "0000-0003-4881-038X")), person( given = "Bhanu", family = "Sinha", email = "b.sinha@umcg.nl", role = "ths", comment = c(ORCID = "0000-0003-1634-0010")))
Description: Functions to simplify the analysis of Antimicrobial Resistance (AMR) of microbial isolates, by using new S3 classes and applying EUCAST expert rules on antibiograms according to Leclercq (2013) <doi:10.1111/j.1469-0691.2011.03703.x>.
Depends: R (>= 3.1.0)
Imports: backports, curl, data.table (>= 1.9.0), dplyr (>= 0.7.0), hms, knitr (>= 1.0.0), rlang (>= 0.2.0), rvest (>= 0.3.2), xml2 (>= 1.0.0)
Suggests: covr (>= 3.0.1), ggplot2, rmarkdown, rstudioapi, testthat (>= 1.0.2), tidyr
VignetteBuilder: knitr
URL: https://github.com/msberends/AMR
BugReports: https://github.com/msberends/AMR/issues
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-10-01 14:46:30 UTC; uscloud
Author: Matthijs S. Berends [aut, cre] (<https://orcid.org/0000-0001-7620-1800>), Christian F. Luz [aut, rev] (<https://orcid.org/0000-0001-5809-5995>), Erwin E.A. Hassing [ctb], Corinna Glasner [ths] (<https://orcid.org/0000-0003-1241-1328>), Alex W. Friedrich [ths] (<https://orcid.org/0000-0003-4881-038X>), Bhanu Sinha [ths] (<https://orcid.org/0000-0003-1634-0010>)
Maintainer: Matthijs S. Berends <m.s.berends@umcg.nl>
Repository: CRAN
Date/Publication: 2018-10-01 17:30:11 UTC

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New package cosinor2 with initial version 0.2.0
Package: cosinor2
Title: Extended Tools for Cosinor Analysis of Rhythms
Description: Statistical procedures for calculating population–mean cosinor, non–stationary cosinor, estimation of best–fitting period, tests of population rhythm differences and more. See Cornélissen, G. (2014). <doi:10.1186/1742-4682-11-16>.
Version: 0.2.0
Author: Augustin Mutak <mutak94@gmail.com>
Maintainer: Augustin Mutak <mutak94@gmail.com>
Depends: R (>= 2.10), cosinor (>= 1.1)
Imports: cowplot (>= 0.9.3), scales (>= 1.0.0), magrittr (>= 1.5), stringr (>= 1.3.1), purrr(>= 0.2.5), ggplot2 (>= 3.0.0), matrixStats (>= 0.52.2), Hmisc (>= 4.0-3)
License: GPL-3
Encoding: UTF-8
RoxygenNote: 6.1.0
LazyData: True
URL: https://github.com/amutak/cosinor2
BugReports: https://github.com/amutak/cosinor2/issues
NeedsCompilation: no
Repository: CRAN
Date: 2018-10-01
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2018-09-30 23:32:52 UTC; Augustin
Date/Publication: 2018-10-01 06:10:03 UTC

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Sun, 30 Sep 2018

New package SpNMF with initial version 0.1.0
Package: SpNMF
Type: Package
Title: Supervised NMF
Version: 0.1.0
Authors@R: person("Yun", "Cai", email = "Yun.Cai@dal.ca", role = c("aut", "cre"))
Description: Non-negative Matrix Factorization(NMF) is a powerful tool for identifying the key features of microbial communities and a dimension-reduction method. When we are interested in the differences between the structures of two groups of communities, supervised NMF(Yun Cai, Hong Gu and Tobby Kenney (2017),<doi:10.1186/s40168-017-0323-1>) provides a better way to do this, while retaining all the advantages of NMF -- such as interpretability, and being based on a simple biological intuition.
Depends: R (>= 3.2.3),
Imports: NMF, stats
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-26 10:10:18 UTC; caiyu
Author: Yun Cai [aut, cre]
Maintainer: Yun Cai <Yun.Cai@dal.ca>
Repository: CRAN
Date/Publication: 2018-09-30 22:30:02 UTC

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New package cap with initial version 1.0
Package: cap
Type: Package
Title: Covariate Assisted Principal (CAP) Regression for Covariance Matrix Outcomes
Version: 1.0
Date: 2018-09-07
Author: Yi Zhao <zhaoyi1026@gmail.com>, Bingkai Wang <bwang51@jhmi.edu>, Stewart Mostofsky <mostofsky@kennedykrieger.org>, Brian Caffo <bcaffo@gmail.com>, Xi Luo <xi.rossi.luo@gmail.com>
Maintainer: Yi Zhao <zhaoyi1026@gmail.com>
Description: Performs Covariate Assisted Principal (CAP) Regression for covariance matrix outcomes. The method identifies the optimal projection direction which maximizes the log-likelihood function of the log-linear heteroscedastic regression model in the projection space. See Zhao et al. (2018), Covariate Assisted Principal Regression for Covariance Matrix Outcomes, <doi:10.1101/425033> for details.
Depends: MASS, multigroup
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-26 18:36:36 UTC; yizhao
Repository: CRAN
Date/Publication: 2018-09-30 23:00:03 UTC

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New package RBitmoji with initial version 0.0.2
Package: RBitmoji
Type: Package
Title: An R Wrapper to the Overly Complicated 'Bitmoji' API
Version: 0.0.2
Authors@R: person("Brandon", "Greenwell", email = "greenwell.brandon@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8120-0084"))
Description: An R wrapper to the overly complicated 'Bitmoji' API allowing users to access and plot various comic strips using their personalized 'Bitstrips' avatar (<https://www.bitmoji.com/>).
License: GPL (>= 2)
URL: https://github.com/bgreenwell/RBitmoji
BugReports: https://github.com/bgreenwell/RBitmoji/issues
Depends: R (>= 2.10)
Imports: getPass, graphics, grDevices, httr, jsonlite, png, RCurl
Suggests: knitr, rmarkdown
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-30 15:59:13 UTC; b780620
Author: Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>)
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-30 16:40:02 UTC

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New package quantities with initial version 0.1.1
Package: quantities
Type: Package
Title: Quantity Calculus for R Vectors
Version: 0.1.1
Authors@R: c( person("Iñaki", "Ucar", email="iucar@fedoraproject.org", role=c("aut", "cph", "cre"), comment=c(ORCID="0000-0001-6403-5550")))
Description: Integration of the 'units' and 'errors' packages for a complete quantity calculus system for R vectors, matrices and arrays, with automatic propagation, conversion, derivation and simplification of magnitudes and uncertainties.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/r-quantities/quantities
BugReports: https://github.com/r-quantities/quantities/issues
Depends: R (>= 3.1.0), units (>= 0.6-1), errors (>= 0.3.0)
Imports: Rcpp, utils
Suggests: tibble, pillar, dplyr, tidyr, testthat, knitr, rmarkdown
LinkingTo: Rcpp (>= 0.12.10)
ByteCompile: yes
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-09-30 16:12:33 UTC; inaki
Author: Iñaki Ucar [aut, cph, cre] (<https://orcid.org/0000-0001-6403-5550>)
Maintainer: Iñaki Ucar <iucar@fedoraproject.org>
Repository: CRAN
Date/Publication: 2018-09-30 16:30:07 UTC

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New package Opt5PL with initial version 0.1.0
Package: Opt5PL
Type: Package
Title: Optimal Designs for the 5-Parameter Logistic Model
Version: 0.1.0
Author: Seung Won Hyun, Weng Kee Wong, and Yarong Yang
Maintainer: Seung Won Hyun <yellowatom09@gmail.com>
Description: Obtain and evaluate various optimal designs for the 3, 4, and 5-parameter logistic models. The optimal designs are obtained based on the numerical algorithm in Hyun, Wong, Yang (2018) <doi:10.18637/jss.v083.i05>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.12.18), matrixcalc
LinkingTo: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-09-30 16:00:42 UTC; raina
Repository: CRAN
Date/Publication: 2018-09-30 16:40:06 UTC

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New package impimp with initial version 0.2.0
Package: impimp
Type: Package
Title: Imprecise Imputation for Statistical Matching
Version: 0.2.0
Date: 2018-09-25
Authors@R: c(person("Paul", "Fink", email = "paul.fink@stat.uni-muenchen.de", role = c("aut", "cre")), person("Eva", "Endres", email = "eva.endres@stat.uni-muenchen.de", role = c("aut")), person("Melissa", "Schmoll", email = "", role = c("ctb")))
Description: Imputing blockwise missing data by imprecise imputation, featuring a domain-based, variable-wise, and case-wise strategy. Furthermore, the estimation of lower and upper bounds for unconditional and conditional probabilities based on the obtained imprecise data is implemented. Additionally, two utility functions are supplied: one to check whether variables in a data set contain set-valued observations; and another to merge two already imprecisely imputed data.
License: GPL-2 | GPL-3
LazyData: TRUE
Encoding: UTF-8
Imports: stats
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-25 10:02:05 UTC; finkpa
Author: Paul Fink [aut, cre], Eva Endres [aut], Melissa Schmoll [ctb]
Maintainer: Paul Fink <paul.fink@stat.uni-muenchen.de>
Repository: CRAN
Date/Publication: 2018-09-30 16:50:03 UTC

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New package ggwordcloud with initial version 0.1.0
Type: Package
Package: ggwordcloud
Title: A Wordcloud Geom for 'ggplot2'
Version: 0.1.0
Authors@R: c(person(given = "Erwan", family = "Le Pennec", role = c("aut", "cre"), email = "lepennec@gmail.com"), person(given = "Kamil", family = "Slowikowski", role = "aut", email = "kslowikowski@gmail.com"))
Maintainer: Erwan Le Pennec <lepennec@gmail.com>
Description: Provides a wordcloud text geom for 'ggplot2'. Texts are placed so that they do not overlap as in 'ggrepel'. The algorithm used is a variation around the one of 'wordcloud2.js'.
License: GPL-3
Depends: ggplot2 (>= 3.0.0)
Imports: Cairo (>= 1.5.9), grid, Rcpp, scales (>= 1.0.0)
Suggests: testthat (>= 2.0.0), knitr, rmarkdown, ggrepel
LinkingTo: Rcpp
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
URL: https://github.com/lepennec/ggwordcloud
BugReports: https://github.com/lepennec/ggwordcloud/issues
NeedsCompilation: yes
Packaged: 2018-09-24 20:23:14 UTC; lepennec
Author: Erwan Le Pennec [aut, cre], Kamil Slowikowski [aut]
Repository: CRAN
Date/Publication: 2018-09-30 16:20:08 UTC

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New package codified with initial version 0.2.0
Package: codified
Title: Produce Standard/Formalized Demographics Tables
Description: Augment clinical data with metadata to create output used in conventional publications and reports.
Version: 0.2.0
Date: 2018-09-06
Authors@R: c(person("Will", "Beasley", role = c("aut", "cre"), email = "wibeasley@hotmail.com", comment = c(ORCID = "0000-0002-5613-5006")), person("Peter", "Higgins", role = "ctb"))
URL: https://ouhscbbmc.github.io/codified/, https://github.com/OuhscBbmc/codified, https://github.com/higgi13425/nih_enrollment_table
BugReports: https://github.com/OuhscBbmc/codified/issues
Depends: R(>= 3.0.0), stats
Imports: checkmate (>= 1.8.4), dplyr (>= 0.7.0), kableExtra, knitr (>= 1.18.0), magrittr, methods, readr (>= 1.1.0), rlang, tibble (>= 1.4.0), tidyr (>= 0.7.0)
Suggests: devtools, REDCapR, rmarkdown, testthat (>= 2.0)
License: MIT + file LICENSE
LazyData: TRUE
VignetteBuilder: knitr
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-12 14:54:18 UTC; wibeasley
Author: Will Beasley [aut, cre] (<https://orcid.org/0000-0002-5613-5006>), Peter Higgins [ctb]
Maintainer: Will Beasley <wibeasley@hotmail.com>
Repository: CRAN
Date/Publication: 2018-09-30 16:10:02 UTC

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New package sym.arma with initial version 1.0
Package: sym.arma
Type: Package
Title: Autoregressive and Moving Average Symmetric Models
Version: 1.0
Date: 2018-09-23
Author: Vinicius Quintas Souto Maior [aut,cre,cph] and Francisco Jose A Cysneiros [aut]
Maintainer: Vinicius Quintas Souto Maior <vinicius@de.ufpe.br>
Description: Functions for fitting the Autoregressive and Moving Average Symmetric Model for univariate time series introduced by Maior and Cysneiros (2018), <doi:10.1007/s00362-016-0753-z>. Fitting method: conditional maximum likelihood estimation. For details see: Wei (2006), Time Series Analysis: Univariate and Multivariate Methods, Section 7.2.
License: GPL-2
NeedsCompilation: no
Packaged: 2018-09-23 14:24:51 UTC; vinicius
Repository: CRAN
Date/Publication: 2018-09-30 15:40:03 UTC

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New package SpatialVS with initial version 1.0
Package: SpatialVS
Title: Spatial Variable Selection
Version: 1.0
Author: Yili Hong, Li Xu, Yimeng Xie, and Zhongnan Jin
Maintainer: Yili Hong <yilihong@vt.edu>
Description: Perform variable selection for the spatial Poisson regression model under the adaptive elastic net penalty. Spatial count data with covariates is the input. We use a spatial Poisson regression model to link the spatial counts and covariates. For maximization of the likelihood under adaptive elastic net penalty, we implemented the penalized quasi-likelihood (PQL) and the approximate penalized loglikelihood (APL) methods. The proposed methods can automatically select important covariates, while adjusting for possible spatial correlations among the responses. More details are available in Xie et al. (2018, <arXiv:1809.06418>). The package also contains the Lyme disease dataset, which consists of the disease case data from 2006 to 2011, and demographic data and land cover data in Virginia. The Lyme disease case data were collected by the Virginia Department of Health. The demographic data (e.g., population density, median income, and average age) are from the 2010 census. Land cover data were obtained from the Multi-Resolution Land Cover Consortium for 2006.
Depends: R (>= 3.3.0)
License: GPL-2
Imports: MASS,nlme, fields
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-09-26 01:14:12 UTC; yilihong
Repository: CRAN
Date/Publication: 2018-09-30 15:30:07 UTC

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New package sazedR with initial version 1.0.0
Package: sazedR
Type: Package
Title: Parameter-Free Domain-Agnostic Season Length Detection in Time Series
Version: 1.0.0
Authors@R: c( person("Maximilian", "Toller", , "maximilian.toller@student.tugraz.at", c("aut")), person("Tiago", "Santos", , "teixeiradossantos@tugraz.at", c("aut", "cre")), person("Roman", "Kern", , "rkern@know-center.at", c("aut")) )
Description: Spectral and Average Autocorrelation Zero Distance Density ('sazed') is a method for estimating the season length of a seasonal time series. 'sazed' is aimed at practitioners, as it employs only domain-agnostic preprocessing and does not depend on parameter tuning or empirical constants. The computation of 'sazed' relies on the efficient autocorrelation computation methods suggested by Thibauld Nion (2012, URL: <http://www.tibonihoo.net/literate_musing/autocorrelations.html>) and by Bob Carpenter (2012, URL: <https://lingpipe-blog.com/2012/06/08/autocorrelation-fft-kiss-eigen/>).
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: bspec (>= 1.5), fftwtools (>= 0.9.8), forecast (>= 8.4), pracma (>= 2.1.4), signal (>= 0.7.6), zoo (>= 1.8-3)
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-22 12:25:08 UTC; rstudio
Author: Maximilian Toller [aut], Tiago Santos [aut, cre], Roman Kern [aut]
Maintainer: Tiago Santos <teixeiradossantos@tugraz.at>
Repository: CRAN
Date/Publication: 2018-09-30 15:10:03 UTC

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New package portsort with initial version 0.1.0
Package: portsort
Type: Package
Date: 2018-09-12
Title: Factor-Based Portfolio Sorts
Version: 0.1.0
Author: Alex Dickerson [aut,cre], Jonathan Spohnholtz [aut,cre]
Maintainer: Alex Dickerson <a.dickerson@warwick.ac.uk>
Description: Designed to aid both academic researchers and asset managers in conducting factor based portfolio sorts. Provides functionality to sort assets into portfolios for up to three factors via a conditional or unconditional sorting procedure.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Depends: xts, zoo, R (>= 2.10)
Suggests: PortfolioAnalytics, PerformanceAnalytics, knitr
VignetteBuilder: knitr
Imports: stats
NeedsCompilation: no
Packaged: 2018-09-24 08:27:39 UTC; Alexander
Repository: CRAN
Date/Publication: 2018-09-30 15:50:03 UTC

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New package piggyback with initial version 0.0.7
Package: piggyback
Version: 0.0.7
Title: Managing Larger Data on a GitHub Repository
Description: Because larger (> 50 MB) data files cannot easily be committed to git, a different approach is required to manage data associated with an analysis in a GitHub repository. This package provides a simple work-around by allowing larger (up to 2 GB) data files to piggyback on a repository as assets attached to individual GitHub releases. These files are not handled by git in any way, but instead are uploaded, downloaded, or edited directly by calls through the GitHub API. These data files can be versioned manually by creating different releases. This approach works equally well with public or private repositories. Data can be uploaded and downloaded programmatically from scripts. No authentication is required to download data from public repositories.
Authors@R: c(person("Carl", "Boettiger", email = "cboettig@gmail.com", role = c("aut", "cre", "cph"), comment = c(ORCID = "0000-0002-1642-628X")), person("Mark", "Padgham", role = c("ctb"), comment = c(ORCID = "0000-0003-2172-5265")))
URL: https://github.com/ropensci/piggyback
BugReports: https://github.com/ropensci/piggyback/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
Imports: gh, httr, jsonlite, git2r, fs, usethis, crayon, clisymbols, magrittr, lubridate, memoise
Suggests: spelling, readr, covr, testthat, datasets, knitr, rmarkdown
VignetteBuilder: knitr
RoxygenNote: 6.1.0
Language: en-US
NeedsCompilation: no
Packaged: 2018-09-22 05:59:49 UTC; cboettig
Author: Carl Boettiger [aut, cre, cph] (<https://orcid.org/0000-0002-1642-628X>), Mark Padgham [ctb] (<https://orcid.org/0000-0003-2172-5265>)
Maintainer: Carl Boettiger <cboettig@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-30 15:10:06 UTC

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New package linguisticsdown with initial version 1.0.1
Package: linguisticsdown
Title: Easy Linguistics Document Writing with R Markdown
Version: 1.0.1
Authors@R: person("Yongfu", "Liao", , "liao961120@gmail.com", c("aut", "cre", "cph"))
Description: Provides 'Shiny gadgets' to search, type, and insert IPA symbols into documents or scripts, requiring only knowledge about phonetics or 'X-SAMPA'. Also provides functions to facilitate the rendering of IPA symbols in 'LaTeX' and PDF format, making IPA symbols properly rendered in all output formats. A minimal R Markdown template for authoring Linguistics related documents is also bundled with the package.
URL: https://liao961120.github.io/linguisticsdown/
BugReports: https://github.com/liao961120/linguisticsdown/issues
Depends: R (>= 3.4.0)
License: MIT + file LICENCE
Encoding: UTF-8
LazyData: true
Imports: dplyr, stringr, tidyr, shiny, magrittr, miniUI, knitr, rstudioapi, DT
RoxygenNote: 6.1.0
Suggests: pkgdown, rmarkdown, testthat
NeedsCompilation: no
Packaged: 2018-09-30 13:57:32 UTC; liao
Author: Yongfu Liao [aut, cre, cph]
Maintainer: Yongfu Liao <liao961120@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-30 15:20:03 UTC

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New package lineqGPR with initial version 0.0.3
Package: lineqGPR
Type: Package
Title: Gaussian Process Regression Models with Linear Inequality Constraints
Version: 0.0.3
Date: 2018-09-26
Author: Andres Felipe LOPEZ-LOPERA
Maintainer: Andres Felipe LOPEZ-LOPERA <andres-felipe.lopez@emse.fr>
Description: Gaussian processes regression models with linear inequality constraints (Lopez-Lopera et al., 2017) <arXiv:1710.07453>.
Note: internal package of the Chair OQUAIDO.
License: GPL-3
Depends: stats, nloptr, broom, tmg, mvtnorm
Imports: MASS, quadprog, Matrix, restrictedMVN, TruncatedNormal, graphics, grDevices, ggplot2
Suggests: Rcpp (>= 0.10.5), testthat, DiceDesign, doMC, viridis, tikzDevice
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-26 07:09:08 UTC; andres-felipe.lopez
Repository: CRAN
Date/Publication: 2018-09-30 15:30:03 UTC

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New package colourvalues with initial version 0.1.1
Package: colourvalues
Type: Package
Title: Assigns Colours to Values
Version: 0.1.1
Date: 2018-09-30
Authors@R: c( person("David", "Cooley", ,"dcooley@symbolix.com.au", role = c("aut", "cre")) )
Description: Maps one of the viridis colour palettes, or a user-specified palette to values. Viridis colour maps are created by Stéfan van der Walt and Nathaniel Smith. They were set as the default palette for the 'Python' 'Matplotlib' library, introduced at SciPy 2015 conference <http://scipy2015.scipy.org/ehome/index.php?eventid=115969&>.
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp, BH
Imports: Rcpp
RoxygenNote: 6.0.1
Suggests: covr, microbenchmark, ggplot2, scales, testthat, viridisLite
NeedsCompilation: yes
Packaged: 2018-09-29 20:46:16 UTC; dave
Author: David Cooley [aut, cre]
Maintainer: David Cooley <dcooley@symbolix.com.au>
Repository: CRAN
Date/Publication: 2018-09-30 15:50:09 UTC

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New package roptim with initial version 0.1.0
Package: roptim
Type: Package
Title: General Purpose Optimization in R using C++
Version: 0.1.0
Author: Yi Pan [aut, cre]
Maintainer: Yi Pan <ypan1988@gmail.com>
Description: Perform general purpose optimizations in R using C++. A unified wrapper interface is provided to call C functions of the five optimization algorithms ('Nelder-Mead', 'BFGS', 'CG', 'L-BFGS-B' and 'SANN') underlying optim().
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
SystemRequirements: C++11
Imports: Rcpp (>= 0.12.14)
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
URL: https://github.com/ypan1988/roptim/
BugReports: https://github.com/ypan1988/roptim/issues
NeedsCompilation: yes
Packaged: 2018-09-21 18:46:52 UTC; pany
Repository: CRAN
Date/Publication: 2018-09-30 14:50:02 UTC

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New package DCEM with initial version 0.0.1
Package: DCEM
Type: Package
Title: Clustering for Multivariate and Univariate Data Using Expectation Maximization Algorithm
Version: 0.0.1
Authors@R: c( person("Sharma", "Parichit", email = "parishar@iu.edu", role = c("aut","cre", "ctb")), person("Kurban", "Hasan", role = c("aut","ctb")), person("Jenne", "Mark", role = c("aut","ctb")), person("Dalkilic", "Mehmet", role = "aut"))
Maintainer: Sharma Parichit <parishar@iu.edu>
Description: Implements the Expectation Maximisation (EM) algorithm for clustering finite gaussian mixture models for both multivariate and univariate datasets. The initialization is done by randomly selecting the samples from the dataset as the mean of the Gaussian(s). Future versions will improve the parameter initialization and execution on big datasets. The algorithm returns a set of Gaussian parameters-posterior probabilities, mean, co-variance matrices (multivariate data)/standard-deviation (for univariate datasets) and priors. Reference: Hasan Kurban, Mark Jenne, Mehmet M. Dalkilic (2016) <doi:10.1007/s41060-017-0062-1>. This work is partially supported by NCI Grant 1R01CA213466-01.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: mvtnorm (>= 1.0.7), matrixcalc (>= 1.0.3), MASS (>= 7.3.49)
RoxygenNote: 6.1.0
Depends: R(>= 3.4.0)
URL: https://github.iu.edu/parishar/DCEM
BugReports: https://github.iu.edu/parishar/DCEM/issues
NeedsCompilation: no
Packaged: 2018-09-20 22:37:43 UTC; schmuck
Author: Sharma Parichit [aut, cre, ctb], Kurban Hasan [aut, ctb], Jenne Mark [aut, ctb], Dalkilic Mehmet [aut]
Repository: CRAN
Date/Publication: 2018-09-30 14:40:03 UTC

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New package ctrlGene with initial version 1.0.0
Package: ctrlGene
Title: Assess the Stability of Candidate Housekeeping Genes
Version: 1.0.0
Authors@R: person("Shangliang","Zhong",email="slzhong@foxmail.com",role=c("aut","cre"))
Description: A simple way to assess the stability of candidate housekeeping genes is implemented in this package.
Depends: R (>= 3.2.3)
Imports: psych,stats,graphics
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.1.0
URL: http://www.bioinf.com.cn/
NeedsCompilation: no
Packaged: 2018-09-21 23:59:01 UTC; admin
Author: Shangliang Zhong [aut, cre]
Maintainer: Shangliang Zhong <slzhong@foxmail.com>
Repository: CRAN
Date/Publication: 2018-09-30 15:00:07 UTC

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New package av with initial version 0.2
Package: av
Type: Package
Title: Working with Audio and Video
Version: 0.2
Authors@R: person("Jeroen", "Ooms", role = c("aut", "cre"), email = "jeroen@berkeley.edu", comment = c(ORCID = "0000-0002-4035-0289"))
Description: Bindings to 'FFmpeg' <http://www.ffmpeg.org/> AV library for working with audio and video in R. Generate high quality videos files by capturing images from the R graphics device combined with custom audio stream. This package interfaces directly to the C API and does not require any command line utilities.
License: MIT + file LICENSE
URL: https://github.com/ropensci/av (devel) http://www.ffmpeg.org/ (upstream)
BugReports: https://github.com/ropensci/av/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
SystemRequirements: FFmpeg >= 3.2: libavfilter-dev (deb), ffmpeg-devel(rpm)
Suggests: testthat, ps, ggplot2, gapminder
NeedsCompilation: yes
Packaged: 2018-09-21 23:24:52 UTC; jeroen
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>
Repository: CRAN
Date/Publication: 2018-09-30 15:00:10 UTC

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New package tdsc with initial version 1.0.0.1
Package: tdsc
Title: Time Domain Signal Coding
Version: 1.0.0.1
Authors@R: person("Ed", "Baker", email = "ed@ebaker.me.uk", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5887-9543"))
Description: Functions for performing time domain signal coding as used in Chesmore (2001) <doi:10.1016/S0003-682X(01)00009-3>, and related tasks. This package creates the standard S-matrix and A-matrix (with variable lag), has tools to convert coding matrices into distributed matrices, provides published codebooks and allows for extraction of code sequences.
Depends: R (>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0.9000
Imports: data.table, methods
Suggests: tuneR, alluvial
NeedsCompilation: no
Packaged: 2018-09-20 11:36:56 UTC; ed
Author: Ed Baker [aut, cre] (<https://orcid.org/0000-0002-5887-9543>)
Maintainer: Ed Baker <ed@ebaker.me.uk>
Repository: CRAN
Date/Publication: 2018-09-30 14:00:02 UTC

More information about tdsc at CRAN
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New package Rfolding with initial version 1.0
Package: Rfolding
Type: Package
Title: The Folding Test of Unimodality
Version: 1.0
Authors@R: c( person("Alban", "Siffer", email="alban.siffer@irisa.fr", role= c("aut","cre")), person("Amossys", email="contact@amossys.fr", role = c("cph", "fnd")))
Description: The basic algorithm to perform the folding test of unimodality. Given a dataset X (d dimensional, n samples), the test checks whether the distribution of the data are rather unimodal or rather multimodal. This package stems from the following research publication: Siffer Alban, Pierre-Alain Fouque, Alexandre Termier, and Christine Largouët. "Are your data gathered?" In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery Data Mining, pp. 2210-2218. ACM, 2018. <doi:10.1145/3219819.3219994>.
Encoding: UTF-8
License: GPL-3
LazyData: true
RoxygenNote: 6.1.0
Suggests: testthat,MASS,knitr,rmarkdown
Imports: stats
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-19 07:23:46 UTC; asr
Author: Alban Siffer [aut, cre], Amossys [cph, fnd]
Maintainer: Alban Siffer <alban.siffer@irisa.fr>
Repository: CRAN
Date/Publication: 2018-09-30 13:10:12 UTC

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New package colorfindr with initial version 0.1.0
Package: colorfindr
Type: Package
Title: Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format Images
Version: 0.1.0
Authors@R: person("David", "Zumbach", role = c("aut", "cre"), email = "david.zumbach@gfzb.ch")
Description: Extracts colors from various image types, returns customized reports and plots treemaps of image compositions. Selected colors and color ranges can be excluded from the analysis.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/zumbov2/colorfindr/issues
RoxygenNote: 6.1.0
Imports: purrr, stringr, pixmap, tibble, treemap, rsvg, png, jpeg, tiff, bmp
Suggests: dplyr
NeedsCompilation: no
Packaged: 2018-09-20 00:17:22 UTC; David Zumbach
Author: David Zumbach [aut, cre]
Maintainer: David Zumbach <david.zumbach@gfzb.ch>
Repository: CRAN
Date/Publication: 2018-09-30 13:50:10 UTC

More information about colorfindr at CRAN
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New package BRETIGEA with initial version 1.0.0
Package: BRETIGEA
Title: Brain Cell Type Specific Gene Expression Analysis
Version: 1.0.0
Author: Andrew McKenzie [aut, cre], Minghui Wang [aut], Bin Zhang [aut]
Maintainer: Andrew McKenzie <amckenz@gmail.com>
Description: Analysis of relative cell type proportions in bulk gene expression data. Provides a well-validated set of brain cell type-specific marker genes derived from multiple types of experiments, as described in McKenzie (2018) <doi:10.1038/s41598-018-27293-5>. For brain tissue data sets, there are marker genes available for astrocytes, endothelial cells, microglia, neurons, oligodendrocytes, and oligodendrocyte precursor cells, derived from each of human, mice, and combination human/mouse data sets. However, if you have access to your own marker genes, the functions can be applied to bulk gene expression data from any tissue. Also implements multiple options for relative cell type proportion estimation using these marker genes, adapting and expanding on approaches from the 'CellCODE' R package described in Chikina (2015) <doi:10.1093/bioinformatics/btv015>. The number of cell type marker genes used in a given analysis can be increased or decreased based on your preferences and the data set. Finally, provides functions to use the estimates to adjust for variability in the relative proportion of cell types across samples prior to downstream analyses.
Depends: R (>= 3.0.0)
Suggests: testthat, stats, utils, knitr
VignetteBuilder: knitr
RoxygenNote: 6.1.0
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-19 03:31:15 UTC; mckena01
Repository: CRAN
Date/Publication: 2018-09-30 13:50:12 UTC

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New package MetaStan with initial version 0.0.1
Package: MetaStan
Version: 0.0.1
Title: Bayesian Meta-Analysis via 'Stan'
Description: Performs Bayesian meta-analysis using 'Stan'. Includes binomial-normal hierarchical models and option to use weakly informative priors for the heterogeneity parameter and the treatment effect parameter which are described in Guenhan, Roever, and Friede (2018) <arXiv:1809.04407>.
Authors@R: c(person("Burak Kuersad", "Guenhan", email="burak.gunhan@med.uni-goettingen.de", role=c("aut", "cre")), person("Trustees of", "Columbia University", role="cph", comment="src/init.cpp, tools/make_cpp.R, R/stanmodels.R"))
License: GPL (>= 3)
Encoding: UTF-8
Date: 2018-08-23
LazyData: true
ByteCompile: true
Depends: R (>= 3.4.0), Rcpp (>= 0.12.17), methods
Imports: rstan (>= 2.17.3), rstantools (>= 1.5.0)
Suggests: testthat, knitr, rmarkdown, ggplot2
LinkingTo: StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>= 1.66.0-1), Rcpp (>= 0.12.17), RcppEigen (>= 0.3.3.4.0)
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 6.1.0
URL: http://github.com/gunhanb/MetaStan
BugReports: http://github.com/gunhanb/MetaStan/issues
VignetteBuilder: knitr
Packaged: 2018-09-18 07:36:01 UTC; burakgunhan
Author: Burak Kuersad Guenhan [aut, cre], Trustees of Columbia University [cph] (src/init.cpp, tools/make_cpp.R, R/stanmodels.R)
Maintainer: Burak Kuersad Guenhan <burak.gunhan@med.uni-goettingen.de>
Repository: CRAN
Date/Publication: 2018-09-30 12:50:03 UTC

More information about MetaStan at CRAN
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New package ggparliament with initial version 2.0.0
Package: ggparliament
Type: Package
Title: Parliament Plots
Description: Simple parliament plots using 'ggplot2'. Visualize election results as points in the architectural layout of the legislative chamber.
Depends: R (>= 2.10)
License: MIT + file LICENSE
Version: 2.0.0
Date: 2018-09-14
Authors@R: c(person("Robert", "Hickman", role = c("aut","cre"), email = "robwhickman@gmail.com"), person("Zoe", "Meers", role = c("aut"), email = "zoe.meers@gmail.com"), person("Thomas J.", "Leeper",role = c("aut"), email = "thosjleeper@gmail.com", comment = c(ORCID = "0000-0003-4097-6326")))
URL: https://github.com/robwhickman/ggparliament
BugReports: https://github.com/robwhickman/ggparliament/issues
LazyData: true
Imports: ggplot2, dplyr, rlang
Suggests: tidyr, magrittr, knitr, testthat, rmarkdown, purrr, ggrepel, scales
VignetteBuilder: knitr
RoxygenNote: 6.1.0.9000
Encoding: UTF-8
Collate: 'ggparliament_package.R' 'data.R' 'draw_majoritythreshold.R' 'helper_funcs.R' 'parliament_data.R' 'draw_partylabels.R' 'draw_totalseats.R' 'geom_parliament_seats.R' 'geom_emphasize_parliamentarians.R' 'geom_parliament_bar.R' 'geom_highlight_government.R' 'geom_overhang_seats.R' 'theme_ggparliament.R'
NeedsCompilation: no
Packaged: 2018-09-19 00:43:56 UTC; Robert
Author: Robert Hickman [aut, cre], Zoe Meers [aut], Thomas J. Leeper [aut] (<https://orcid.org/0000-0003-4097-6326>)
Maintainer: Robert Hickman <robwhickman@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-30 13:00:03 UTC

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Sat, 29 Sep 2018

New package Ryacas with initial version 0.3-4
Package: Ryacas
Version: 0.3-4
Title: R Interface to the Yacas Computer Algebra System
Author: Rob Goedman <goedman@mac.com>, Gabor Grothendieck <ggrothendieck@gmail.com>, Søren Højsgaard <sorenh@math.aau.dk>, Ayal Pinkus <apinkus@xs4all.nl>, Grzegorz Mazur <teoretyk@gmail.com>, Mikkel Meyer Andersen <mikl@math.aau.dk>
Maintainer: Mikkel Meyer Andersen <mikl@math.aau.dk>
Encoding: UTF-8
Description: An interface to the yacas computer algebra system.
Depends: R (>= 3.3.0)
Imports: Rcpp (>= 0.12.0), xml2, stats
LinkingTo: Rcpp
Suggests: testthat (>= 0.9.0), devtools (>= 1.11.0)
License: GPL-2
URL: https://github.com//mikldk/ryacas, http://www.yacas.org
BugReports: https://github.com/mikldk/ryacas/issues
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-09-29 07:29:48 UTC; mikl
Repository: CRAN
Date/Publication: 2018-09-29 15:40:03 UTC

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Fri, 28 Sep 2018

New package rmytarget with initial version 1.1
Package: rmytarget
Type: Package
Title: Load Data from 'MyTarget API'
Version: 1.1
Date: 2018-09-12
Author: Alexey Seleznev
Maintainer: Alexey Seleznev <selesnow@gmail.com>
Description: Allows work with 'MyTarget API' <https://target.my.com/adv/api-marketing/> and load data by ads, campaigns and statistic from your ads account.
URL: http://selesnow.github.io/rmytarget
Imports: httr, jsonlite, dplyr, lubridate, stringr
Depends: R (>= 3.5.0)
License: GPL-2
Encoding: UTF-8
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-09-18 06:10:55 UTC; Alsey
Repository: CRAN
Date/Publication: 2018-09-28 21:30:06 UTC

More information about rmytarget at CRAN
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New package pzfx with initial version 0.1.0
Package: pzfx
Type: Package
Title: Read 'GraphPad Prism' Files
Version: 0.1.0
Authors@R: c( person("Yue", "Jiang", role = c("aut", "cre"), email = "rivehill@gmail.com", comment = c(ORCID = "0000-0002-9798-5517")) )
Description: Read 'GraphPad Prism' '.pzfx' files into R.
URL: https://github.com/Yue-Jiang/pzfx
BugReports: https://github.com/Yue-Jiang/pzfx/issues
Imports: xml2 (>= 1.2.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-18 04:42:57 UTC; yuejiang
Author: Yue Jiang [aut, cre] (<https://orcid.org/0000-0002-9798-5517>)
Maintainer: Yue Jiang <rivehill@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-28 21:30:09 UTC

More information about pzfx at CRAN
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New package esquisse with initial version 0.1.5
Package: esquisse
Type: Package
Title: Explore and Visualize Your Data Interactively
Version: 0.1.5
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")))
Description: A 'shiny' gadget to create 'ggplot2' charts interactively with drag-and-drop to map your variables. You can quickly visualize your data accordingly to their type, export to 'PNG' or 'PowerPoint', and retrieve the code to reproduce the chart.
URL: https://github.com/dreamRs/esquisse
BugReports: https://github.com/dreamRs/esquisse/issues
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: miniUI, rstudioapi, shiny, htmltools, jsonlite, shinyWidgets, ggplot2, ggthemes, RColorBrewer, scales, stringi
Suggests: officer, rvg, DT, testthat
NeedsCompilation: no
Packaged: 2018-09-18 15:05:13 UTC; perri
Author: Fanny Meyer [aut], Victor Perrier [aut, cre]
Maintainer: Victor Perrier <victor.perrier@dreamrs.fr>
Repository: CRAN
Date/Publication: 2018-09-28 22:00:03 UTC

More information about esquisse at CRAN
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New package deflateBR with initial version 1.1.2

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New package ddiv with initial version 0.1.0
Package: ddiv
Type: Package
Title: Data Driven I-v Feature Extraction
Description: The Data Driven I-V Feature Extraction is used to extract Current-Voltage (I-V) features from I-V curves. I-V curves indicate the relationship between current and voltage for a solar cell or Photovoltaic (PV) modules. The I-V features such as maximum power point (Pmp), shunt resistance (Rsh), series resistance (Rs),short circuit current (Isc), open circuit voltage (Voc), fill factor (FF), current at maximum power (Imp) and voltage at maximum power(Vmp) contain important information of the performance for PV modules. The traditional method uses the single diode model to model I-V curves and extract I-V features. This package does not use the diode model, but uses data-driven a method which select different linear parts of the I-V curves to extract I-V features. This method also uses a sampling method to calculate uncertainties when extracting I-V features. Also, because of the partially shaded array, "steps" occurs in I-V curves. The "Segmented Regression" method is used to identify steps in I-V curves. This material is based upon work supported by the U.S. Department of Energy’s Office of Energy Efficiency and Renewable Energy (EERE) under Solar Energy Technologies Office (SETO) Agreement Number DE-EE0007140.
Version: 0.1.0
Authors@R: c(person("Wei-Heng", "Huang", email="wxh272@case.edu", role=c("aut"), comment = c(ORCID = "0000-0002-6609-4981")), person("Xuan", "Ma", email="xxm115@case.edu", role=c("aut","cre"), comment = c(ORCID = "0000-0003-2361-2846")), person("Jiqi", "Liu", email="jxl1763@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0003-2016-4160")), person("Menghong", "Wang", email="mxw477@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0001-7349-699X")), person("Alan J.", "Curran", email="ajc269@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-4505-8359")), person("Justin S.", "Fada", email="jsf77@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-0029-5051")), person("Jean-Nicolas", "Jaubert", email="jn.jaubert@canadiansolar.com", role=c("ctb"), comment = c(ORCID = "0000-0002-9663-6999")), person("Jing", "Sun", email="J.Sun@canadiansolar.com", role=c("ctb"), comment = c(ORCID = "0000-0002-4313-2316")), person("Jennifer L.", "Braid", email="jlb269@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0002-0677-7756")), person("Jenny", "Brynjarsdottir", email="jxb628@case.edu", role=c("ctb"), comment = c(ORCID = "0000-0003-1859-4962")), person("Roger H.", "French", email="rxf131@case.edu", role=c("aut","cph"), comment = c(ORCID = "0000-0002-6162-0532")) )
Depends: R (>= 3.4.0)
Imports: MASS (>= 0.5-3.0), segmented (>= 0.5-3.0)
Suggests: rmarkdown, testthat, knitr
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-18 18:30:20 UTC; xuanma
Author: Wei-Heng Huang [aut] (<https://orcid.org/0000-0002-6609-4981>), Xuan Ma [aut, cre] (<https://orcid.org/0000-0003-2361-2846>), Jiqi Liu [ctb] (<https://orcid.org/0000-0003-2016-4160>), Menghong Wang [ctb] (<https://orcid.org/0000-0001-7349-699X>), Alan J. Curran [ctb] (<https://orcid.org/0000-0002-4505-8359>), Justin S. Fada [ctb] (<https://orcid.org/0000-0002-0029-5051>), Jean-Nicolas Jaubert [ctb] (<https://orcid.org/0000-0002-9663-6999>), Jing Sun [ctb] (<https://orcid.org/0000-0002-4313-2316>), Jennifer L. Braid [ctb] (<https://orcid.org/0000-0002-0677-7756>), Jenny Brynjarsdottir [ctb] (<https://orcid.org/0000-0003-1859-4962>), Roger H. French [aut, cph] (<https://orcid.org/0000-0002-6162-0532>)
Maintainer: Xuan Ma <xxm115@case.edu>
Repository: CRAN
Date/Publication: 2018-09-28 21:50:10 UTC

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New package titeIR with initial version 0.1.0
Package: titeIR
Type: Package
Title: Isotonic Designs for Phase 1 Trials with Late-Onset Toxicities
Version: 0.1.0
Authors@R: c(person("Lee", "McDaniel", role = c("aut", "cre"),email = "lmcda4@lsuhsc.edu"))
Maintainer: Lee McDaniel <lmcda4@lsuhsc.edu>
Date: 2018-09-17
Description: Functions to design phase 1 trials using an isotonic regression based design incorporating time-to-event information. Simulation and design functions are available, which incorporate information about followup and DLTs, and apply isotonic regression to devise estimates of DLT probability.
License: GPL-3
Imports: Iso
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-17 21:29:14 UTC; lmcda4
Author: Lee McDaniel [aut, cre]
Repository: CRAN
Date/Publication: 2018-09-28 18:10:03 UTC

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New package HDcpDetect with initial version 0.1.0
Package: HDcpDetect
Type: Package
Title: Detect Change Points in Means of High Dimensional Data
Version: 0.1.0
Author: Jeffrey Okamoto [aut], Natasha Stewart [aut], Dr. Jun Li [aut]
Maintainer: Natasha Stewart <natashastewart@utexas.edu>
Description: Objective: Implement new methods for detecting change points in high-dimensional time series data. These new methods can be applied to non-Gaussian data, account for spatial and temporal dependence, and detect a wide variety of change-point configurations, including changes near the boundary and changes in close proximity. Additionally, this package helps address the “small n, large p” problem, which occurs in many research contexts. This problem arises when a dataset contains changes that are visually evident but do not rise to the level of statistical significance due to the small number of observations and large number of parameters. The problem is overcome by treating the dimensions as a whole and scaling the test statistics only by its standard deviation, rather than scaling each dimension individually. Due to the computational complexity of the functions, the package runs best on datasets with a relatively large number of attributes but no more than a few hundred observations.
License: GPL-3
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-09-27 12:18:17 UTC; natas
Repository: CRAN
Date/Publication: 2018-09-28 18:20:03 UTC

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New package crfsuite with initial version 0.1
Package: crfsuite
Type: Package
Title: Conditional Random Fields for Labelling Sequential Data in Natural Language Processing
Version: 0.1
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jwijffels@bnosac.be', comment = "R wrapper"), person('BNOSAC', role = 'cph', comment = "R wrapper"), person("Naoaki", "Okazaki", role = c('aut', 'ctb', 'cph'), comment = "CRFsuite library (BSD licensed), libLBFGS library (MIT licensed), Constant Quark Database software (BSD licensed)"), person("Bob", "Jenkins", role = c('aut', 'ctb'), comment = "File src/cqdb/src/lookup3.c (Public Domain)"), person("Jorge", "Nocedal", role = c('aut', 'ctb', 'cph'), comment = "libLBFGS library (MIT licensed)"), person("Jesse", "Long", role = c('aut', 'ctb', 'cph'), comment = "RumAVL library (MIT licensed)"))
Description: Wraps the 'CRFsuite' library <https://github.com/chokkan/crfsuite> allowing users to fit a Conditional Random Field model and to apply it on existing data. The focus of the implementation is in the area of Natural Language Processing where this R package allows you to easily build and apply models for named entity recognition, text chunking, part of speech tagging, intent recognition or classification of any category you have in mind. Next to training, a small web application is included in the package to allow you to easily construct training data.
License: BSD_3_clause + file LICENSE
Depends: R (>= 2.10)
Imports: Rcpp, data.table (>= 1.9.6), utils, tools
Suggests: udpipe, knitr
LinkingTo: Rcpp
RoxygenNote: 6.0.1
SystemRequirements: GNU make
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-09-17 21:16:34 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Naoaki Okazaki [aut, ctb, cph] (CRFsuite library (BSD licensed), libLBFGS library (MIT licensed), Constant Quark Database software (BSD licensed)), Bob Jenkins [aut, ctb] (File src/cqdb/src/lookup3.c (Public Domain)), Jorge Nocedal [aut, ctb, cph] (libLBFGS library (MIT licensed)), Jesse Long [aut, ctb, cph] (RumAVL library (MIT licensed))
Repository: CRAN
Date/Publication: 2018-09-28 18:10:10 UTC

More information about crfsuite at CRAN
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New package airGR with initial version 1.0.14.1
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.0.14.1
Date: 2018-09-28
Authors@R: c( person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")), person("Charles", "Perrin", role = c("aut", "ths"), comment = c(ORCID = "0000-0001-8552-1881")), person("Olivier", "Delaigue", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-7668-8468"), email = "airGR@irstea.fr"), person("Guillaume", "Thirel", role = c("aut"), comment = c(ORCID = "0000-0002-1444-1830")), person("Claude", "Michel", role = c("aut", "ths")), person("Vazken", "Andréassian", role = c("ctb", "ths"), comment = c(ORCID = "0000-0001-7124-9303")), person("François", "Bourgin", role = c("ctb"), comment = c(ORCID = "0000-0002-2820-7260", vignette = "'Parameter estimation' vignettes")), person("Pierre", "Brigode", role = c("ctb"), comment = c(ORCID = "0000-0001-8257-0741")), person("Nicolas", "Le Moine", role = c("ctb")), person("Thibaut", "Mathevet", role = c("ctb")), person("Safouane", "Mouelhi", role = c("ctb")), person("Ludovic", "Oudin", role = c("ctb")), person("Raji", "Pushpalatha", role = c("ctb")), person("Audrey", "Valéry", role = c("ctb")) )
Depends: R (>= 3.0.1)
Suggests: knitr, rmarkdown, coda, DEoptim, dplyr, FME, ggmcmc, hydroPSO, Rmalschains
Description: Hydrological modelling tools developed at Irstea-Antony (HYCAR Research Unit, France). The package includes several conceptual rainfall-runoff models (GR4H, GR4J, GR5J, GR6J, GR2M, GR1A), a snow accumulation and melt model (CemaNeige) and the associated functions for their calibration and evaluation. Use help(airGR) for package description and references.
License: GPL-2
URL: https://webgr.irstea.fr/en/airGR/
NeedsCompilation: yes
Encoding: UTF-8
VignetteBuilder: knitr
Packaged: 2018-09-28 07:20:22 UTC; olivier.delaigue
Author: Laurent Coron [aut, trl] (<https://orcid.org/0000-0002-1503-6204>), Charles Perrin [aut, ths] (<https://orcid.org/0000-0001-8552-1881>), Olivier Delaigue [aut, cre] (<https://orcid.org/0000-0002-7668-8468>), Guillaume Thirel [aut] (<https://orcid.org/0000-0002-1444-1830>), Claude Michel [aut, ths], Vazken Andréassian [ctb, ths] (<https://orcid.org/0000-0001-7124-9303>), François Bourgin [ctb] (<https://orcid.org/0000-0002-2820-7260>, 'Parameter estimation' vignettes), Pierre Brigode [ctb] (<https://orcid.org/0000-0001-8257-0741>), Nicolas Le Moine [ctb], Thibaut Mathevet [ctb], Safouane Mouelhi [ctb], Ludovic Oudin [ctb], Raji Pushpalatha [ctb], Audrey Valéry [ctb]
Maintainer: Olivier Delaigue <airGR@irstea.fr>
Repository: CRAN
Date/Publication: 2018-09-28 08:50:07 UTC

More information about airGR at CRAN
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Wed, 26 Sep 2018

New package LncPath with initial version 1.1
Package: LncPath
Type: Package
Title: Identifying the Pathways Regulated by LncRNA Sets of Interest
Version: 1.1
Date: 2018-09-26
Author: Junwei Han, Zeguo Sun
Maintainer: Junwei Han <hanjunwei1981@163.com>
Description: Identifies pathways synergisticly regulated by the interested lncRNA(long non-coding RNA) sets based on a lncRNA-mRNA(messenger RNA) interaction network. 1) The lncRNA-mRNA interaction network was built from the protein-protein interactions and the lncRNA-mRNA co-expression relationships in 28 RNA-Seq data sets. 2) The interested lncRNAs can be mapped into networks as seed nodes and a random walk strategy will be performed to evaluate the rate of each coding genes influenced by the seed lncRNAs. 3) Pathways regulated by the lncRNA set will be evaluated by a weighted Kolmogorov-Smirnov statistic as an ES Score. 4) The p value and false discovery rate value will also be calculated through a permutation analysis. 5) The running score of each pathway can be plotted and the heat map of each pathway can also be plotted if an expression profile is provided. 6) The rank and scores of the gene list of each pathway can be printed.
Imports: stats, graphics, utils, grDevices
Depends: R (>= 3.2.1), igraph
Suggests: Matrix,graph
License: GPL (>= 2)
LazyData: Yes
NeedsCompilation: no
Packaged: 2018-09-26 06:47:17 UTC; liu
Repository: CRAN
Date/Publication: 2018-09-26 14:20:06 UTC

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Mon, 24 Sep 2018

New package thriftr with initial version 1.0.3
Package: thriftr
Type: Package
Title: Apache Thrift Client Server
Version: 1.0.3
Date: 2018-09-16
Authors@R: c(person("Marek", "Jagielski", role = c("aut", "cre", "cph"), email = "marek.jagielski@gmail.com"), person("Lixin", "Yu", role = c("aut", "cph")))
Author: Marek Jagielski [aut, cre, cph], Lixin Yu [aut, cph]
Maintainer: Marek Jagielski <marek.jagielski@gmail.com>
Description: Pure R implementation of Apache Thrift. This library doesn't require any code generation. To learn more about Thrift go to <https://thrift.apache.org>.
License: MIT + file LICENSE
URL: https://github.com/systemincloud/thriftr
BugReports: https://github.com/systemincloud/thriftr/issues
Suggests: testthat
Encoding: UTF-8
Imports: R6, rly, stringi
RoxygenNote: 6.0.1
Collate: 'thrift.R' 'transport.R' 'rpc.R' 'parser.R' 'protocol_binary.R' 'server.R' 'transport_buffered.R' 'transport_memory.R' 'transport_socket.R' 'utils.R'
NeedsCompilation: no
Packaged: 2018-09-16 20:36:48 UTC; lupus
Repository: CRAN
Date/Publication: 2018-09-24 23:10:03 UTC

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New package splinetree with initial version 0.1.0
Package: splinetree
Title: Longitudinal Regression Trees and Forests
Version: 0.1.0
Authors@R: c(person("Anna", "Neufeld", email = "aneufeld@uw.edu", role = c("aut", "cre")), person("Brianna", "Heggeseth", email = "bheggese@macalester.edu", role = c("aut","ths")))
Description: Builds regression trees and random forests for longitudinal or functional data using a spline projection method. Implements and extends the work of Yu and Lambert (1999) <doi:10.1080/10618600.1999.10474847>. This method allows trees and forests to be built while considering either level and shape or only shape of response trajectories.
Depends: R (>= 3.5.0), rpart, nlme, splines
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: mosaic, ggplot2, treeClust, mclust
RoxygenNote: 6.1.0
Suggests: R.rsp, knitr, rmarkdown, testthat
VignetteBuilder: R.rsp
BugReports: https://github.com/anna-neufeld/splinetree/issues
URL: https://github.com/anna-neufeld/splinetree
NeedsCompilation: no
Packaged: 2018-09-16 22:02:03 UTC; annaneufeld
Author: Anna Neufeld [aut, cre], Brianna Heggeseth [aut, ths]
Maintainer: Anna Neufeld <aneufeld@uw.edu>
Repository: CRAN
Date/Publication: 2018-09-24 23:30:03 UTC

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New package PBRF with initial version 1.0.0
Package: PBRF
Type: Package
Title: The Probability of Being in Response Function and Its Variance Estimates
Version: 1.0.0
Date: 2018-09-22
Maintainer: Xiaodong Luo <xiaodong.luo@sanofi.com>
Description: Provides three ways to estimate the probability of being in response function (PBRF) The estimates are presented in Tsai, Luo and Crowley (2017) <doi: 10.1007/978-981-10-0126-0_10>.
Authors@R: c( person(given="Xiaodong", family="Luo", email = "xiaodong.luo@sanofi.com", role =c("aut", "cre")), person("Sanofi", role = "cph"))
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 5.0.1
LazyData: true
NeedsCompilation: yes
Packaged: 2018-09-22 13:15:48 UTC; Administrator
Author: Xiaodong Luo [aut, cre], Sanofi [cph]
Repository: CRAN
Date/Publication: 2018-09-24 23:20:02 UTC

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New package hgutils with initial version 0.2.3
Package: hgutils
Version: 0.2.3
Date: 2018-09-16
Title: Collection of Utility Functions
Authors@R: person("H.G.", "van den Boorn", email = "hvdboorn@gmail.com", role = c("aut", "cre"))
Description: A handy collection of utility functions designed to aid in package development, plotting and scientific research. Package development functionalities includes among others tools such as cross-referencing package imports with the description file, analysis of redundant package imports, editing of the description file and the creation of package badges for GitHub. Some of the other functionalities include automatic package installation and loading, plotting points without overlap, creating nice breaks for plots, overview tables and many more handy utility functions.
Depends: R (>= 3.1)
Imports: crayon, grDevices, limSolve, magrittr, stringr, utils, XML
Suggests: methods, testthat
License: GPL-3
URL: https://github.com/hvdboorn/hgutils
BugReports: https://github.com/hvdboorn/hgutils/issues
Encoding: UTF-8
LazyData: true
Language: en-GB
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-16 19:21:39 UTC; H.G. van den Boorn
Author: H.G. van den Boorn [aut, cre]
Maintainer: H.G. van den Boorn <hvdboorn@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-24 23:10:06 UTC

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New package GNAR with initial version 0.2.7
Package: GNAR
Type: Package
Title: Methods for Fitting Network Time Series Models
Version: 0.2.7
Date: 2018-09-16
Author: Kathryn Leeming [aut], Guy Nason [aut], Matt Nunes [aut, cre], Marina Knight [ctb]
Authors@R: c(person("Kathryn", "Leeming", role="aut"), person("Guy","Nason",role="aut"), person("Matt", "Nunes", role=c("aut","cre"),email="nunesrpackages@gmail.com"), person("Marina","Knight",role="ctb"))
Maintainer: Matt Nunes <nunesrpackages@gmail.com>
Description: Simulation of, and fitting models for, Generalised Network Autoregressive (GNAR) time series models which take account of network structure. Such models are described in Knight et al. (2016), see <arXiv:1603.03221>.
Depends: igraph
License: GPL-2
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-16 10:19:53 UTC; matt
Repository: CRAN
Date/Publication: 2018-09-24 23:10:20 UTC

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New package behaviorchange with initial version 0.0.2
Package: behaviorchange
Type: Package
Title: Tools for Behavior Change Researchers and Professionals
Version: 0.0.2
Date: 2018-09-25
Authors@R: c(person("Gjalt-Jorn", "Peters", email = "gjalt-jorn@a-bc.eu", role = c("aut", "cre", "ctb")))
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@a-bc.eu>
License: GPL (>= 3)
Description: Contains specialised analyses and visualisation tools for behavior change science. These facilitate conducting determinant studies (for example, using confidence interval-based estimation of relevance, CIBER, or CIBERlite plots) and systematically developing, reporting, and analysing interventions (for example, using acyclic behavior change diagrams). This package is especially useful for researchers in the field of behavior change or health psychology and to behavior change professionals such as intervention developers and prevention workers.
URL: https://a-bc.eu
BugReports: https://github.com/academy-of-behavior-change/behaviorchange/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Depends: R (>= 3.0.0)
Imports: data.tree (>= 0.7.5), DiagrammeR (>= 1.0.0), ggplot2 (>= 2.2.1), googlesheets (>= 0.3.0), gridExtra (>= 2.3), gtable (>= 0.2.0), magrittr (>= 0.1.5), ufs (>= 0.0.1), userfriendlyscience (>= 0.7.1), viridis (>= 0.5.1)
NeedsCompilation: no
Packaged: 2018-09-24 18:33:00 UTC; micro
Author: Gjalt-Jorn Peters [aut, cre, ctb]
Repository: CRAN
Date/Publication: 2018-09-24 23:10:16 UTC

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New package userfriendlyscience with initial version 0.7.2
Package: userfriendlyscience
Type: Package
Title: Quantitative Analysis Made Accessible
Version: 0.7.2
Date: 2018-09-25
Authors@R: c(person("Gjalt-Jorn", "Peters", email = "gjalt-jorn@userfriendlyscience.com", role = c("aut", "cre", "ctb")), person("Peter", "Verboon", role = c("ctb")), person("James", "Green", role = c("ctb")))
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@userfriendlyscience.com>
License: GPL (>= 3)
Description: Contains a number of functions that serve two goals. First, to make R more accessible to people migrating from SPSS by adding a number of functions that behave roughly like their SPSS equivalents (also see <https://rosettastats.com>). Second, to make a number of slightly more advanced functions more user friendly to relatively novice users. The package also conveniently houses a number of additional functions that are intended to increase the quality of methodology and statistics in psychology, not by offering technical solutions, but by shifting perspectives, for example towards reasoning based on sampling distributions as opposed to on point estimates.
URL: http://userfriendlyscience.com
BugReports: https://github.com/matherion/userfriendlyscience/issues
LazyData: true
Imports: BiasedUrn, car, data.tree, DiagrammeR, diptest, digest, GGally, ggplot2, ggrepel, ggridges, gridExtra, GPArotation, gtable, knitr, lavaan, lme4, MASS, MBESS, minpack.lm, pander, plyr, psych, pwr, RColorBrewer, rio, scales, SCRT, SuppDists, ufs (>= 0.0.1), viridis, XML, xtable
Suggests: multcompView
NeedsCompilation: no
Packaged: 2018-09-24 16:50:22 UTC; micro
Author: Gjalt-Jorn Peters [aut, cre, ctb], Peter Verboon [ctb], James Green [ctb]
Repository: CRAN
Date/Publication: 2018-09-24 18:30:03 UTC

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Sun, 23 Sep 2018

New package DescribeDisplay with initial version 0.2.7
Package: DescribeDisplay
Version: 0.2.7
Date: 2018-09-23
Title: An Interface to the 'DescribeDisplay' 'GGobi' Plugin
Description: Produce publication quality graphics from output of 'GGobi' describe display plugin.
Authors@R: c( person("Di", "Cook", , "dicook@monash.edu" , c("aut", "cre")), person("Hadley", "Wickham", , "h.wickham@gmail.com" , c("aut")), person("Andreas", "Buja", , "buja@wharton.upenn.edu", c("aut")), person("Barret", "Schloerke", , "schloerke@gmail.com" , c("aut")) )
License: MIT + file LICENSE
URL: https://github.com/ggobi/DescribeDisplay
BugReports: https://github.com/ggobi/DescribeDisplay/issues
Imports: reshape2, ggplot2 (>= 3.0.0), plyr, scales, grid, GGally (>= 1.4.0)
Suggests: roxygen2 (>= 6.0.1), testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-23 21:30:35 UTC; dicook
Author: Di Cook [aut, cre], Hadley Wickham [aut], Andreas Buja [aut], Barret Schloerke [aut]
Maintainer: Di Cook <dicook@monash.edu>
Repository: CRAN
Date/Publication: 2018-09-23 22:20:12 UTC

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New package mFilter with initial version 0.1-4
Package: mFilter
Title: Miscellaneous Time Series Filters
Date: 2018-09-22
Version: 0.1-4
Author: Mehmet Balcilar <mehmet@mbalcilar.net>
Depends: R (>= 2.2.0), stats
Suggests: tseries, pastecs, locfit, tseriesChaos, tsDyn, forecast
Description: The mFilter package implements several time series filters useful for smoothing and extracting trend and cyclical components of a time series. The routines are commonly used in economics and finance, however they should also be interest to other areas. Currently, Christiano-Fitzgerald, Baxter-King, Hodrick-Prescott, Butterworth, and trigonometric regression filters are included in the package.
Maintainer: Mehmet Balcilar <mehmet@mbalcilar.net>
License: GPL (>= 2)
URL: http://www.mbalcilar.net
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-22 21:15:45 UTC; mbalcilar
Repository: CRAN
Date/Publication: 2018-09-23 13:50:03 UTC

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Fri, 21 Sep 2018

New package zeroEQpart with initial version 0.1.0
Package: zeroEQpart
Type: Package
Title: Zero Order vs (Semi) Partial Correlation Test and CI
Version: 0.1.0
Imports: ppcor, stats, utils, MASS
Authors@R: c( person("Dan", "Richard", email = "djrichar@ualberta.ca", role = c("aut", "cre")), person("Karen", "Buro", email = "BuroK@macewan.ca", role = "ctb"), person("Wanhua", "Su", email = "SuW3@macewan.ca", role = "ctb") )
Description: Uses bootstrap to test zero order correlation being equal to a partial or semi-partial correlation (one or two tailed). Confidence intervals for the parameter (zero order minus partial) can also be determined. Implements the bias-corrected and accelerated bootstrap method as described in "An Introduction to the Bootstrap" Efron (1983) <0-412-04231-2>.
URL: https://github.com/djrichar92/zeroEQpart
BugReports: https://github.com/djrichar92/zeroEQpart/issues
License: GPL-2
Encoding: UTF-8
LazyData: FALSE
Date: 2018-09-13
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-13 17:35:56 UTC; djric
Author: Dan Richard [aut, cre], Karen Buro [ctb], Wanhua Su [ctb]
Maintainer: Dan Richard <djrichar@ualberta.ca>
Repository: CRAN
Date/Publication: 2018-09-21 22:30:03 UTC

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New package trigpoints with initial version 1.0.0
Package: trigpoints
Title: Data Set of Trig Points in Great Britain in British National Grid Coordinates
Version: 1.0.0
Authors@R: person(given = "Phil Mike", family = "Jones", role = c("aut", "cre"), email = "philmikejones@gmail.com", comment = c(ORCID = "0000-0001-5173-3245"))
Description: A complete data set of historic GB trig points in British National Grid (OSGB36) coordinate reference system. Trig points (aka triangulation stations) are fixed survey points used to improve the accuracy of map making in Great Britain during the 20th Century. Trig points are typically located on hilltops so still serve as a useful navigational aid for walkers and hikers today.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Depends: R (>= 2.10)
Imports: sf, tibble
BugReports: https://github.com/philmikejones/trigpoints/issues
URL: https://philmikejones.github.io/trigpoints/
NeedsCompilation: no
Packaged: 2018-09-15 09:13:12 UTC; lw1pj
Author: Phil Mike Jones [aut, cre] (<https://orcid.org/0000-0001-5173-3245>)
Maintainer: Phil Mike Jones <philmikejones@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-21 22:40:03 UTC

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New package powdR with initial version 0.1.0
Package: powdR
Type: Package
Title: Full Pattern Summation of X-Ray Powder Diffraction Data
Version: 0.1.0
Date: 2018-09-13
Authors@R: c( person("Benjamin", "Butler", email = "benjamin.butler@hutton.ac.uk", role = c("aut", "cre")), person("Stephen", "Hillier", email = "stephen.hillier@hutton.ac.uk", role = "ctb"))
Maintainer: Benjamin Butler <benjamin.butler@hutton.ac.uk>
Description: Full pattern summation of X-ray powder diffraction data as described in Chipera and Bish (2002) <doi:10.1107/S0021889802017405>. Derives quantitative estimates of crystalline and amorphous phase concentrations in complex mixtures.
License: GPL-2 | file LICENSE
URL: http://github.com/benmbutler/powdR
BugReports: http://github.com/benmbutler/powdR/issues
Depends: R (>= 3.2.0)
Encoding: UTF-8
LazyData: true
Imports: reshape (>= 0.8.6), plotly (>= 4.7.1), ggplot2 (>= 2.2.1), stats (>= 3.4.3), ggpubr(>= 0.1.7), shiny (>= 1.0.5)
Suggests: knitr, rmarkdown
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-13 18:23:14 UTC; bb42885
Author: Benjamin Butler [aut, cre], Stephen Hillier [ctb]
Repository: CRAN
Date/Publication: 2018-09-21 22:30:06 UTC

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New package optweight with initial version 0.1.0
Package: optweight
Type: Package
Title: Targeted Stable Balancing Weights Using Optimization
Version: 0.1.0
Author: Noah Greifer [aut, cre]
Maintainer: Noah Greifer <noah.greifer@gmail.com>
Description: Use optimization to estimate weights that balance covariates for binary, multinomial, continuous, and longitudinal treatments in the spirit of Zubizarreta (2015) <doi:10.1080/01621459.2015.1023805>. The degree of balance can be specified for each covariate.
Depends: R (>= 3.4.0)
Imports: rosqp (>= 0.1.0), Matrix (>= 1.2-13), ggplot2 (>= 3.0.0)
Suggests: cobalt (>= 3.4.1), twang (>= 1.5)
License: GPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-15 18:42:33 UTC; NoahGreifer
Repository: CRAN
Date/Publication: 2018-09-21 22:40:07 UTC

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New package LocalControlStrategy with initial version 1.3
Package: LocalControlStrategy
Title: Local Control Strategy for Analysis of Cross-Sectional Data
Version: 1.3
Date: 2018-09-15
Author: Bob Obenchain
Maintainer: Bob Obenchain <wizbob@att.net>
Depends: cluster, lattice
Description: Especially when cross-sectional data are observational, effects of treatment selection bias and confounding are revealed by using the unsupervised, nonparametric preprocessing methods central to Local Control (LC) strategy. The LC objective is to estimate the "effect-size distribution" that best quantifies a potentially causal relationship between a continuous y-Outcome variable and a t-Treatment variable. This t-variable may be either binary {1 = "new" vs 0 = "control"} or a numeric measure of Exposure level. LC Strategy starts by CLUSTERING experimental units (patients) on baseline x-Covariates, forming mutually exclusive and exhaustive BLOCKS of relatively well-matched units. The implicit statistical model for LC is thus simple one-way ANOVA. The Within-Block measures of effect-size are Local Rank Correlations (LRCs) when Exposure is numeric with more than two levels. Otherwise, Treatment choice is Nested within BLOCKS, and effect-sizes are Local Treatment Differences (LTDs) between within-cluster y-Outcome Means ["new" minus "control"]. An Instrumental Variable (IV) method is also provided so that Local Average y-Outcomes (LAOs) within BLOCKS may also contribute information for effect-size inferences ...assuming that x-Covariates influence only Treatment choice or Exposure level and otherwise have no direct effects on y-Outcome.
License: GPL
URL: https://www.R-project.org, http://localcontrolstatistics.org
NeedsCompilation: no
Packaged: 2018-09-14 17:24:52 UTC; wiz
Repository: CRAN
Date/Publication: 2018-09-21 22:30:18 UTC

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New package BootstrapQTL with initial version 1.0.2
Package: BootstrapQTL
Type: Package
Title: Bootstrap cis-QTL Method that Corrects for the Winner's Curse
Version: 1.0.2
Author: Qin Qin Huang [aut], Scott Ritchie [aut, cre]
Maintainer: Scott Ritchie <sritchie73@gmail.com>
BugReports: https://github.com/InouyeLab/bootstrapQTL/issues
Description: Identifies genome-related molecular traits with significant evidence of genetic regulation and performs a bootstrap procedure to correct estimated effect sizes for over-estimation present in cis-QTL mapping studies (The "Winner's Curse"), described in Huang QQ *et al.* 2018 <doi: 10.1093/nar/gky780>.
Depends: MatrixEQTL
Imports: foreach, data.table
Suggests: doMC, doParallel, qvalue, testthat
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-14 16:24:35 UTC; sritchie
Repository: CRAN
Date/Publication: 2018-09-21 22:30:22 UTC

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New package blockingChallenge with initial version 1.0
Package: blockingChallenge
Type: Package
Title: Create Blocks or Strata which are Similar Within
Version: 1.0
Date: 2018-09-10
Author: Bikram Karmakar
Maintainer: Bikram Karmakar <bikramk@wharton.upenn.edu>
Description: Implements a heuristic algorithm to build blocks of a given size aiming to maximize similarity within strata across multiple covariates. The blocking structure can be used for causal inference and for sensitivity analysis to unmeasured confounding. A stratified structure gives more flexibility for using multiple instrumental variables and direct treatment vs. control analysis as evidence factors. Karmakar, B., Small, D. S., and Rosenbaum, P. R. (2018). Rosenbaum, P. R. (2010)<ISBN:978-1-4419-1213-8>.
Enhances: optmatch
Suggests: MASS
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2018-09-14 17:23:35 UTC; bikra
Repository: CRAN
Date/Publication: 2018-09-21 22:50:08 UTC

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New package blin with initial version 0.0.1
Package: blin
Title: Bipartite Longitudinal Influence Network (BLIN) Estimation
Version: 0.0.1
Authors@R: c(person("Frank W. Marrs", email="frank.marrs@colostate.edu", role=c("aut", "cre")), person("Benjamin W. Campbell", role=c("aut")), person("Bailey K. Fosdick", role=c("aut")), person("Skyler J. Cranmer", role=c("aut")), person("Tobias B{\"o}hmelt", role=c("aut")))
Description: Estimate influence networks from longitudinal bipartite relational data, where the longitudinal relations are continuous. The outputs are estimates of weighted influence networks among each actor type in the data set. The generative model is the Bipartite Longitudinal Influence Network (BLIN) model, a linear autoregressive model for these type of data. The supporting paper is ``Inferring Influence Networks from Longitudinal Bipartite Relational Data'', which is in preparation by the same authors. The model may be estimated using maximum likelihood methods and Bayesian methods. For more detail on methods, see Marrs et. al. <arXiv:1809.03439>.
Depends: R (>= 3.3.0)
Imports: glmnet, stats, Matrix, MASS, abind, graphics, mvtnorm
VignetteBuilder: knitr
Suggests: knitr, knitcitations
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-14 17:33:42 UTC; fmarrs3
Author: Frank W. Marrs [aut, cre], Benjamin W. Campbell [aut], Bailey K. Fosdick [aut], Skyler J. Cranmer [aut], Tobias B{"o}hmelt [aut]
Maintainer: Frank W. Marrs <frank.marrs@colostate.edu>
Repository: CRAN
Date/Publication: 2018-09-21 22:30:10 UTC

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New package autocogs with initial version 0.1.1
Package: autocogs
Title: Automatic Cognostic Summaries
Version: 0.1.1
Authors@R: c( person("Barret", "Schloerke", email = "schloerke@gmail.com", role = c("aut")), person("Ryan", "Hafen", email = "rhafen@gmail.com", role = c("ths", "cre")) )
Description: Automatically calculates cognostic groups for plot objects and list column plot objects. Results are returned in a nested data frame.
Depends: R (>= 3.4.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: dplyr, checkmate, MASS, broom, moments, diptest, mclust, ggplot2, tibble, utils, hexbin, progress
RoxygenNote: 6.1.0
Collate: 'autocog.R' 'known_cog_groups.R' 'add_cog_group.R' 'field_info.R' 'add_cog_group_.R' 'known_layer_cogs.R' 'add_layer_cogs.R' 'add_layer_cogs_.R' 'cog_desc.R' 'cog_spec.R' 'layer_count.R' 'layer_info.R' 'of_type.R' 'plot_class.R' 'plot_cogs.R'
Suggests: testthat, covr
URL: https://github.com/schloerke/autocogs
BugReports: https://github.com/schloerke/autocogs/issues
NeedsCompilation: no
Packaged: 2018-09-13 17:32:16 UTC; hafen
Author: Barret Schloerke [aut], Ryan Hafen [ths, cre]
Maintainer: Ryan Hafen <rhafen@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-21 22:30:13 UTC

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Thu, 20 Sep 2018

New package metadynminer with initial version 0.1.2
Package: metadynminer
Type: Package
Title: Tools to Read, Analyze and Visualize Metadynamics HILLS Files from 'Plumed'
Version: 0.1.2
Date: 2018-08-24
Authors@R: person("Vojtech", "Spiwok", email = "spiwokv@vscht.cz", role = c("aut", "cre"), comment = c(ORCID = "0000-0001-8108-2033"))
Depends: R (>= 3.3.0)
LinkingTo: Rcpp
Description: Metadynamics is a state of the art biomolecular simulation technique. 'Plumed' Tribello, G.A. et al. (2014) <doi:10.1016/j.cpc.2013.09.018> program makes it possible to perform metadynamics using various simulation codes. The results of metadynamics done in 'Plumed' can be analyzed by 'metadynminer'. The package 'metadynminer' reads 1D and 2D metadynamics hills files from 'Plumed' package. It uses a fast algorithm by Hosek, P. and Spiwok, V. (2016) <doi:10.1016/j.cpc.2015.08.037> to calculate a free energy surface from hills. Minima can be located and plotted on the free energy surface. Transition states can be analyzed by Nudged Elastic Band method by Henkelman, G. and Jonsson, H. (2000) <doi:10.1063/1.1323224>. Free energy surfaces, minima and transition paths can be plotted to produce publication quality images.
LazyData: true
License: GPL-3
RoxygenNote: 6.1.0
Imports: Rcpp
URL: http://www.metadynamics.cz/metadynminer
NeedsCompilation: yes
Packaged: 2018-09-14 07:26:56 UTC; spiwokv
Author: Vojtech Spiwok [aut, cre] (<https://orcid.org/0000-0001-8108-2033>)
Maintainer: Vojtech Spiwok <spiwokv@vscht.cz>
Repository: CRAN
Date/Publication: 2018-09-20 18:20:03 UTC

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New package DIconvex with initial version 1.0.0
Package: DIconvex
Type: Package
Title: Finding Patterns of Monotonicity and Convexity in Data
Version: 1.0.0
Author: Paul Schneider [aut, ths], Liudmila Karagyaur [aut]
Maintainer: Liudmila Karagyaur <liudmila.karagyaur@usi.ch>
Description: Given an initial set of points, this package minimizes the number of elements to discard from this set such that there exists at least one monotonic and convex mapping within pre-specified upper and lower bounds.
Depends: lpSolveAPI
License: GPL-2
NeedsCompilation: no
Packaged: 2018-09-14 14:17:08 UTC; paultschi
Repository: CRAN
Date/Publication: 2018-09-20 18:00:15 UTC

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New package CutpointsOEHR with initial version 0.1.0
Package: CutpointsOEHR
Type: Package
Title: Optimal Equal-HR Method to Find Two Cutpoints for U-Shaped Relationships in Cox Model
Version: 0.1.0
Author: Yimin Chen, Zhang Jinxin
Maintainer: Yimin Chen <chenyimin0226@126.com>
Description: Use optimal equal-HR method to determine two optimal cutpoints of a continuous predictor that has a U-shaped relationship with survival outcomes based on Cox regression model. The optimal equal-HR method estimates two optimal cut-points that have approximately the same log hazard value based on Cox regression model and divides individuals into different groups according to their HR values.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: survival
NeedsCompilation: no
RoxygenNote: 6.1.0.9000
Packaged: 2018-09-14 00:39:58 UTC; ad
Repository: CRAN
Date/Publication: 2018-09-20 18:00:19 UTC

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New package broom.mixed with initial version 0.2.2
Package: broom.mixed
Type: Package
Title: Tidying Methods for Mixed Models
Version: 0.2.2
Authors@R: c( person("Ben", "Bolker", email = "bolker@mcmaster.ca", role = c("aut", "cre")), person("David", "Robinson", email = "admiral.david@gmail.com", role = "aut"), person("Dieter", "Menne", role = "ctb"), person("Jonah", "Gabry", role = "ctb"), person("Paul", "Buerkner", role = "ctb"), person("Christopher", "Hua", role = "ctb"), person("Will", "Petry", role = "ctb"), person("Josh", "Wiley", role = "ctb"), person("Patrick", "Kennedy", role = "ctb") )
Maintainer: Ben Bolker <bolker@mcmaster.ca>
Description: Convert fitted objects from various R mixed-model packages into tidy data frames along the lines of the 'broom' package. The package provides three S3 generics for each model: tidy(), which summarizes a model's statistical findings such as coefficients of a regression; augment(), which adds columns to the original data such as predictions, residuals and cluster assignments; and glance(), which provides a one-row summary of model-level statistics.
Depends: R (>= 3.5.0)
Imports: broom, dplyr, tidyr, plyr, purrr, tibble, reshape2, nlme, methods, stringr, coda, glmmTMB, TMB
Suggests: knitr, testthat, ggplot2, Matrix, MCMCglmm, lme4, rstan, rstanarm, brms, mgcv, gamlss, lmerTest, glmmADMB
URL: http://github.com/bbolker/broom.mixed
BugReports: http://github.com/bbolker/broom.mixed/issues
License: GPL-3
RoxygenNote: 6.1.0
Encoding: UTF-8
Additional_repositories: http://bbolker.github.io/drat
NeedsCompilation: no
Packaged: 2018-09-14 14:43:38 UTC; bolker
Author: Ben Bolker [aut, cre], David Robinson [aut], Dieter Menne [ctb], Jonah Gabry [ctb], Paul Buerkner [ctb], Christopher Hua [ctb], Will Petry [ctb], Josh Wiley [ctb], Patrick Kennedy [ctb]
Repository: CRAN
Date/Publication: 2018-09-20 18:00:10 UTC

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Wed, 19 Sep 2018

New package binb with initial version 0.0.1
Package: binb
Type: Package
Title: 'binb' is not 'Beamer'
Version: 0.0.1
Date: 2018-09-19
Author: Dirk Eddelbuettel and Ista Zahn
Maintainer: Dirk Eddelbuettel <edd@debian.org>
Description: A collection of 'LaTeX' styles using 'Beamer' customization for pdf-based presentation slides in 'RMarkdown'. At present it contains 'RMarkdown' adaptations of the LaTeX themes 'Metropolis' (formerly 'mtheme') theme by Matthias Vogelgesang and others (now included in 'TeXLive'), and the 'IQSS' by Ista Zahn (which is included here). Additional (free) fonts may be needed: 'Metropolis' prefers 'Fira', and 'IQSS' requires 'Libertinus'.
URL: https://github.com/eddelbuettel/binb
BugReports: https://github.com/eddelbuettel/binb/issues
Imports: rmarkdown, knitr
VignetteBuilder: knitr
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-19 12:26:29.858568 UTC; edd
Repository: CRAN
Date/Publication: 2018-09-19 22:30:03 UTC

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New package bcf with initial version 1.2.1
Package: bcf
Type: Package
Title: Causal Inference for a Binary Treatment and Continuous Outcome using Bayesian Causal Forests
Version: 1.2.1
Date: 2018-09-19
Author: P. Richard Hahn, Jared S. Murray, and Carlos Carvalho
Maintainer: Jared S. Murray <jared.murray@mccombs.utexas.edu>
Description: Causal inference for a binary treatment and continuous outcome using Bayesian Causal Forests. See Hahn, Murray and Carvalho (2017) <arXiv:1706.09523> for additional information. This implementation relies on code originally accompanying Pratola et. al. (2013) <arXiv:1309.1906>.
License: GPL-3
Depends: Rcpp (>= 0.10.4)
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2018-09-19 21:17:11 UTC; jared
Repository: CRAN
Date/Publication: 2018-09-19 22:20:02 UTC

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New package taipan with initial version 0.1.1
Package: taipan
Version: 0.1.1
Title: Tool for Annotating Images in Preparation for Analysis
Authors@R: c(person("Stephanie", "Kobakian", email = "stephanie.kobakian@gmail.com", role = c("aut", "cre")), person("Mitchell", "O'Hara-Wild", email = "mail@mitchelloharawild.com", role = c("aut")))
Description: A tool to help create shiny apps for selecting and annotating elements of images. Users must supply images, questions, and answer choices. The user interface is a dynamic shiny app, that displays the images and questions and answer choices. The data generated can be saved to a file that can be used for subsequent analysis. The original purpose was to annotate still images from tennis video for face recognition and emotion detection purposes.
Depends: R (>= 3.2.0)
Imports: shiny, utils
Suggests: testthat, knitr, rmarkdown, tidyverse
URL: https://github.com/srkob1/taipan
BugReports: https://github.com/srkob1/taipan/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-12 03:11:56 UTC; steff
Author: Stephanie Kobakian [aut, cre], Mitchell O'Hara-Wild [aut]
Maintainer: Stephanie Kobakian <stephanie.kobakian@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-19 15:10:03 UTC

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New package distdichoR with initial version 0.1-0
Package: distdichoR
Type: Package
Title: Distributional Method for the Dichotomisation of Continuous Outcomes
Version: 0.1-0
Author: Odile Sauzet
Maintainer: Odile Sauzet <odile.sauzet@uni-bielefeld.de>
Description: Contains a range of functions covering the present development of the distributional method for the dichotomisation of continuous outcomes. The method provides estimates with standard error of a comparison of proportions (difference, odds ratio and risk ratio) derived, with similar precision, from a comparison of means. See the URL below or <arXiv:1809.03279> for more information.
URL: https://arxiv.org/abs/1809.03279
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: boot, sn, lsmeans, stats, nlme
Suggests: knitr, rmarkdown
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-13 16:07:40 UTC; janne
Repository: CRAN
Date/Publication: 2018-09-19 15:20:06 UTC

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New package ddsPLS with initial version 1.0.0
Package: ddsPLS
Version: 1.0.0
Title: Multi-Data-Driven Sparse PLS Robust to Missing Samples
Description: Allows to build Multi-Data-Driven Sparse PLS models. Multi-blocks with high-dimensional settings are particularly sensible to this.
Authors@R: person("Hadrien","Lorenzo", role = c("aut", "cre"), email = "hadrien.lorenzo.2015@gmail.com")
Maintainer: Hadrien Lorenzo <hadrien.lorenzo.2015@gmail.com>
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.1.0
Imports: RColorBrewer,MASS,graphics,stats,utils,Rdpack,doParallel,foreach,parallel,iterators
RdMacros: Rdpack
Suggests: knitr,rmarkdown
Depends: R (>= 2.10)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-12 15:34:16 UTC; hl1
Author: Hadrien Lorenzo [aut, cre]
Repository: CRAN
Date/Publication: 2018-09-19 15:10:06 UTC

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New package SplitSoftening with initial version 1.0-0
Package: SplitSoftening
Version: 1.0-0
Title: Softening Splits in Decision Trees
Author: Jakub Dvorak
Maintainer: Jakub Dvorak <JakubDvorak@email.cz>
Depends: R (>= 3.0.0)
Enhances: tree
Suggests: gsl
Description: Allows to produce and use classification trees with probability (soft) splits.
License: GPL (>= 2)
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2018-09-12 09:48:49 UTC; jdv01
Repository: CRAN
Date/Publication: 2018-09-19 10:00:06 UTC

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New package bayesdfa with initial version 0.1.0
Package: bayesdfa
Type: Package
Title: Bayesian Dynamic Factor Analysis (DFA) with 'Stan'
Version: 0.1.0
Authors@R: c( person(c("Eric", "J."), "Ward", role = c("aut", "cre"), email = "eric.ward@noaa.gov"), person(c("Sean", "C."), "Anderson", role = "aut"), person(c("Luis", "A."), "Damiano", role = "aut"), person(c("Mary", "E."), "Hunsicker,", role = "ctb"), person(c("Mike", "A."), "Litzow", role = "ctb"), person("Trustees of", "Columbia University", role = "cph"))
Description: Implements Bayesian dynamic factor analysis with 'Stan'. Dynamic factor analysis is a dimension reduction tool for multivariate time series. 'bayesdfa' extends conventional dynamic factor models in several ways. First, extreme events may be estimated in the latent trend by modeling process error with a student-t distribution. Second, autoregressive and moving average components can be optionally included. Third, the estimated dynamic factors can be analyzed with hidden Markov models to evaluate support for latent regimes.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.4.0), Rcpp (>= 0.12.0)
Imports: rstan (>= 2.16.0), ggplot2 (>= 2.2.0), loo, dplyr (>= 0.7.0), methods, rlang, reshape2
LinkingTo: StanHeaders (>= 2.16.0), rstan (>= 2.16.0), BH (>= 1.62.0), Rcpp (>= 0.12.0), RcppEigen
Suggests: testthat, parallel, knitr, rmarkdown, MARSS
URL: https://github.com/fate-ewi/bayesdfa
BugReports: https://github.com/fate-ewi/bayesdfa/issues
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2018-09-10 12:15:54 UTC; eric.ward
Author: Eric J. Ward [aut, cre], Sean C. Anderson [aut], Luis A. Damiano [aut], Mary E. Hunsicker, [ctb], Mike A. Litzow [ctb], Trustees of Columbia University [cph]
Maintainer: Eric J. Ward <eric.ward@noaa.gov>
Repository: CRAN
Date/Publication: 2018-09-19 10:00:02 UTC

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Tue, 18 Sep 2018

New package rmetalog with initial version 1.0.0
Package: rmetalog
Type: Package
Title: R Implementation of the Metalog Distribution
Version: 1.0.0
Authors@R: c( person("Isaac", "Faber", email = "isaacfab@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4478-9598")), person("Jongbin", "Jung", email = "me@jongbin.com", role = c("aut")))
Description: Implementation of the metalog distribution in R. The metalog distribution is a modern, highly flexible, data-driven distribution. Metalogs are developed by Keelin (2016) <doi:10.1287/deca.2016.0338>. This package provides functions to build these distributions from raw data. Resulting metalog objects are then useful for exploratory and probabilistic analysis.
Imports: lpSolve, ggplot2
Suggests: devtools, knitr, rmarkdown
Depends: R (>= 3.1.0)
BugReports: https://github.com/isaacfab/rmetalog/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-17 18:16:02 UTC; isaacfaber
Author: Isaac Faber [aut, cre] (<https://orcid.org/0000-0002-4478-9598>), Jongbin Jung [aut]
Maintainer: Isaac Faber <isaacfab@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-18 23:00:03 UTC

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New package eivtools with initial version 0.1-8
Package: eivtools
Type: Package
Title: Measurement Error Modeling Tools
Version: 0.1-8
Date: 2018-09-16
Depends: R (>= 3.4.0), stats, grDevices, graphics, utils, R2jags
Author: J.R. Lockwood
Maintainer: J.R. Lockwood <jrlockwood@ets.org>
Description: This includes functions for analysis with error-prone covariates, including deconvolution, latent regression and errors-in-variables regression. It implements methods by Rabe-Hesketh et al. (2003) <doi:10.1191/1471082x03st056oa>, Lockwood and McCaffrey (2014) <doi:10.3102/1076998613509405>, and Lockwood and McCaffrey (2017) <doi:10.1007/s11336-017-9556-y>, among others.
License: GPL (>= 2) | file LICENSE
LazyData: true
NeedsCompilation: no
Packaged: 2018-09-17 14:52:19 UTC; jlock
Repository: CRAN
Date/Publication: 2018-09-18 22:30:08 UTC

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New package conStruct with initial version 1.0.0
Package: conStruct
Version: 1.0.0
Title: Models Spatially Continuous and Discrete Population Genetic Structure
Description: A method for modeling genetic data as a combination of discrete layers, within each of which relatedness may decay continuously with geographic distance. This package contains code for running analyses (which are implemented in the modeling language 'rstan') and visualizing and interpreting output. See the paper for more details on the model and its utility.
Authors@R: person("Gideon", "Bradburd", email = "bradburd@msu.edu", role = c("aut", "cre"))
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.4.0), Rcpp (>= 0.12.18), methods
Imports: rstan (>= 2.17.3), rstantools (>= 1.5.0), caroline, gtools, foreach, parallel, doParallel
LinkingTo: StanHeaders (>= 2.17.2), rstan (>= 2.17.3), BH (>= 1.66.0-1), Rcpp (>= 0.12.18), RcppEigen (>= 0.3.3.4.0)
SystemRequirements: GNU make
NeedsCompilation: yes
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, maps
VignetteBuilder: knitr
Packaged: 2018-09-17 14:08:03 UTC; bradburd
Author: Gideon Bradburd [aut, cre]
Maintainer: Gideon Bradburd <bradburd@msu.edu>
Repository: CRAN
Date/Publication: 2018-09-18 22:40:03 UTC

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New package mhurdle with initial version 1.1-8
Package: mhurdle
Version: 1.1-8
Date: 2018-09-17
Title: Multiple Hurdle Tobit Models
Authors@R: c(person("Yves", "Croissant", role = c("aut", "cre"), email = "yves.croissant@univ-reunion.fr"), person("Fabrizio", "Carlevaro", role = "aut", email = "fabrizio.carlevaro@unige.ch"), person("Stephane", "Hoareau", role = "aut", email = "sjlhoaro@univ-reunion.fr"))
Depends: R (>= 2.10), methods, Formula, truncreg, maxLik, survival, texreg
Description: Estimation of models with zero left-censored variables. Null values may be caused by a selection process (Cragg (1971) <doi:10.2307/1909582>), insufficient resources (Tobin (1958) <doi:10.2307/1907382>) or infrequency of purchase (Deaton and Irish (1984) <doi:10.1016/0047-2727(84)90067-7>).
License: GPL (>= 2)
URL: https://www.R-project.org
Author: Yves Croissant [aut, cre], Fabrizio Carlevaro [aut], Stephane Hoareau [aut]
Maintainer: Yves Croissant <yves.croissant@univ-reunion.fr>
Repository: CRAN
Repository/R-Forge/Project: mhurdle
Repository/R-Forge/Revision: 75
Repository/R-Forge/DateTimeStamp: 2018-09-18 13:53:04
Date/Publication: 2018-09-18 17:00:07 UTC
NeedsCompilation: yes
Packaged: 2018-09-18 14:10:42 UTC; rforge

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New package shiny.router with initial version 0.1.1
Package: shiny.router
Type: Package
Title: Basic Routing for Shiny Web Applications
Version: 0.1.1
Author: Filip Stachura <filip@appsilon.com>
Maintainer: Dominik Krzemiński <dominik@appsilon.com>
Description: The minimal router for your Shiny apps. It allows you to create dynamic web applications with real-time user interface and easily share URLs to pages within your Shiny apps.
Encoding: UTF-8
LazyData: true
License: MIT + file LICENSE
Imports: magrittr, shiny
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2018-09-17 08:17:25 UTC; dominik
Repository: CRAN
Date/Publication: 2018-09-18 08:50:07 UTC

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New package RSelenium with initial version 1.7.4
Package: RSelenium
Type: Package
Title: R Bindings for 'Selenium WebDriver'
Version: 1.7.4
Authors@R: c( person("John", "Harrison", , "johndharrison0@gmail.com", role = "aut", comment = "original author"), person("Ju Yeong", "Kim", , "jkim2345@fredhutch.org", role = "cre", comment = "rOpenSci maintainer"))
Description: Provides a set of R bindings for the 'Selenium 2.0 WebDriver' (see <https://seleniumhq.github.io/docs/wd.html> for more information) using the 'JsonWireProtocol' (see <https://github.com/SeleniumHQ/selenium/wiki/JsonWireProtocol> for more information). 'Selenium 2.0 WebDriver' allows driving a web browser natively as a user would either locally or on a remote machine using the Selenium server it marks a leap forward in terms of web browser automation. Selenium automates web browsers (commonly referred to as browsers). Using RSelenium you can automate browsers locally or remotely.
License: AGPL-3
URL: http://ropensci.github.io/RSelenium
BugReports: http://github.com/ropensci/RSelenium/issues
Additional_repositories: http://www.omegahat.net/R
Depends: R (>= 3.0.0)
Imports: XML, methods, caTools, tools, utils, openssl, httr, wdman(>= 0.2.2), binman
Suggests: testthat, knitr, Rcompression, covr, rmarkdown
VignetteBuilder: knitr
LazyData: true
Collate: 'RSelenium.R' 'errorHandler.R' 'remoteDriver.R' 'rsDriver.R' 'selKeys-data.R' 'util.R' 'webElement.R' 'zzz.R'
Encoding: UTF-8
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-17 18:43:13 UTC; jkim2345
Author: John Harrison [aut] (original author), Ju Yeong Kim [cre] (rOpenSci maintainer)
Maintainer: Ju Yeong Kim <jkim2345@fredhutch.org>
Repository: CRAN
Date/Publication: 2018-09-18 08:30:12 UTC

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New package ccfa with initial version 1.1.0
Package: ccfa
Type: Package
Title: Continuous Counterfactual Analysis
Version: 1.1.0
Authors@R: c(person("Weige", "Huang", role=c("aut","cre"), email="weige.huang@temple.edu"), person("Brantly", "Callaway", role="aut", email="brantly.callaway@temple.edu"))
Description: Contains methods for computing counterfactuals with a continuous treatment variable as in Callaway and Huang (2017) <https://ssrn.com/abstract=3078187>. In particular, the package can be used to calculate the expected value, the variance, the interquantile range, the fraction of observations below or above a particular cutoff, or other user-supplied functions of an outcome of interest conditional on a continuous treatment. The package can also be used for computing these same functionals after adjusting for differences in covariates at different values of the treatment. Further, one can use the package to conduct uniform inference for each parameter of interest across all values of the treatment, uniformly test whether adjusting for covariates makes a difference at any value of the treatment, and test whether a parameter of interest is different from its average value at an value of the treatment.
Depends: R (>= 2.1.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Imports: quantreg, stats, pbapply, BMisc, tidyr, ggplot2, TempleMetrics, doParallel, foreach, formula.tools
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-17 20:25:10 UTC; weigehuang
Author: Weige Huang [aut, cre], Brantly Callaway [aut]
Maintainer: Weige Huang <weige.huang@temple.edu>
Repository: CRAN
Date/Publication: 2018-09-18 08:20:08 UTC

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Mon, 17 Sep 2018

New package echarts4r with initial version 0.1.1
Package: echarts4r
Title: Create Interactive Graphs with 'Echarts JavaScript' Version 4
Date: 2018-09-12
Version: 0.1.1
Authors@R: person("John", "Coene", email = "jcoenep@gmail.com", role = c("aut", "cre"))
Description: Easily create interactive charts by leveraging the 'Echarts Javascript' library which includes 33 chart types, themes, 'Shiny' proxies and animations.
License: Apache License (>= 2.0)
Encoding: UTF-8
LazyData: true
Imports: htmlwidgets, magrittr, dplyr, purrr, data.tree, crosstalk, base64enc, countrycode, d3r, broom
RoxygenNote: 6.1.0
Suggests: jsonlite, shiny, quantmod, png, tibble, htmltools
URL: http://echarts4r.john-coene.com/
BugReports: https://github.com/JohnCoene/echarts4r/issues
NeedsCompilation: no
Packaged: 2018-09-12 12:06:38 UTC; JCOE
Author: John Coene [aut, cre]
Maintainer: John Coene <jcoenep@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-17 16:40:03 UTC

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New package UKgrid with initial version 0.1.0
Package: UKgrid
Type: Package
Title: The UK National Electricity Transmission System Dataset
Version: 0.1.0
Author: Rami Krispin
Maintainer: Rami Krispin <rami.krispin@gmail.com>
Description: A time series of the national grid demand (high-voltage electric power transmission network) in the UK since 2011.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.2)
Imports: data.table(>= 1.11.2), dplyr(>= 0.7.5), lubridate (>= 1.6.0), magrittr (>= 1.5), rlang (>= 0.2.1), xts (>= 0.10-1), zoo (>= 1.8-0)
Suggests: knitr, rmarkdown, devtools, TSstudio
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-11 05:23:33 UTC; rami
Repository: CRAN
Date/Publication: 2018-09-17 15:10:07 UTC

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New package stuart with initial version 0.7.3
Package: stuart
Type: Package
Title: Subtests Using Algorithmic Rummaging Techniques
Version: 0.7.3
Date: 2018-09-11
Authors@R: person("Martin", "Schultze", email="martin.schultze@fu-berlin.de", role=c('aut','cre'))
Description: Construct subtests from a pool of items by using ant-colony-optimization, genetic algorithms, brute force, or random sampling. Schultze (2017) <doi:10.17169/refubium-622>.
License: GPL-3
Depends: R (>= 3.5.0)
Imports: stats, utils
Suggests: parallel, lavaan (>= 0.5.18), MplusAutomation (>= 0.7-2), graphics
RoxygenNote: 6.0.1
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-11 20:00:37 UTC; martin
Author: Martin Schultze [aut, cre]
Maintainer: Martin Schultze <martin.schultze@fu-berlin.de>
Repository: CRAN
Date/Publication: 2018-09-17 15:30:03 UTC

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New package rlmDataDriven with initial version 0.1.0
Package: rlmDataDriven
Type: Package
Title: Robust Regression with Data Driven Tuning Parameter
Version: 0.1.0
Author: You-Gan Wang
Maintainer: The package maintainer <you-gan.wang@qut.edu.au>
Imports: stats, MASS
Description: Data driven approach for robust regression estimation. See Wang et al. (2007), <doi:10.1198/106186007X180156>.
License: GPL (>= 2.0)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-08-10 04:37:08 UTC; wangy
Repository: CRAN
Date/Publication: 2018-09-17 15:10:03 UTC

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New package radix with initial version 0.5
Type: Package
Package: radix
Title: 'R Markdown' Format for Scientific and Technical Writing
Version: 0.5
Authors@R: c( person("JJ", "Allaire", role = c("aut", "cre"), email = "jj@rstudio.com"), person("Rich", "Iannone", role = c("aut")), person("Yihui", "Xie", role = c("aut")), person(family = "RStudio, Inc.", role = "cph"), person(family = "Google LLC", role = c("ctb", "cph"), comment = "https://distill.pub/guide/"), person("Nick", "Williams", role = c("ctb", "cph"), comment = "https://wicky.nillia.ms/headroom.js/"), person("Denis", "Demchenko", role = c("ctb", "cph"), comment = "https://github.com/lancedikson/bowser"), person(family = "The Polymer Authors", role = c("ctb", "cph"), comment = "https://www.webcomponents.org/polyfills/"), person("Gábor", "Csárdi", role = c("ctb", "cph"), comment = "whoami") )
Description: Scientific and technical article format for the web. 'Radix' articles feature attractive, reader-friendly typography, flexible layout options for visualizations, and full support for footnotes and citations.
License: Apache License 2.0
URL: https://github.com/rstudio/radix
BugReports: https://github.com/rstudio/radix/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: utils, stats, tools, rmarkdown (>= 1.10), htmltools, jsonlite (>= 1.3), lubridate, png, mime, rstudioapi, rprojroot, xml2, base64enc, whisker, downloader, progress, stringr, knitr (>= 1.15.6), digest, yaml
Suggests: htmlwidgets, r2d3, DiagrammeR, shiny, rsconnect, testthat
Language: en-US
NeedsCompilation: no
Packaged: 2018-09-17 13:54:10 UTC; jjallaire
Author: JJ Allaire [aut, cre], Rich Iannone [aut], Yihui Xie [aut], RStudio, Inc. [cph], Google LLC [ctb, cph] (https://distill.pub/guide/), Nick Williams [ctb, cph] (https://wicky.nillia.ms/headroom.js/), Denis Demchenko [ctb, cph] (https://github.com/lancedikson/bowser), The Polymer Authors [ctb, cph] (https://www.webcomponents.org/polyfills/), Gábor Csárdi [ctb, cph] (whoami)
Maintainer: JJ Allaire <jj@rstudio.com>
Repository: CRAN
Date/Publication: 2018-09-17 15:40:02 UTC

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New package HMMextra0s with initial version 1.0.0
Package: HMMextra0s
Type: Package
Title: Hidden Markov Models with Extra Zeros
Version: 1.0.0
Imports: mvtnorm, ellipse
Suggests: HiddenMarkov
Depends: methods
Date: 2018-09-12
Author: Ting Wang - I am grateful to Jiancang Zhuang for some helpful suggestions and contributions
Maintainer: Ting Wang <ting.wang@otago.ac.nz>
Description: Contains functions for hidden Markov models with observations having extra zeros as defined in the following two publications, Wang, T., Zhuang, J., Obara, K. and Tsuruoka, H. (2016) <doi:10.1111/rssc.12194>; Wang, T., Zhuang, J., Buckby, J., Obara, K. and Tsuruoka, H. (2018) <doi:10.1029/2017JB015360>. The observed response variable is either univariate or bivariate Gaussian conditioning on presence of events, and extra zeros mean that the response variable takes on the value zero if nothing is happening. Hence the response is modelled as a mixture distribution of a Bernoulli variable and a continuous variable. That is, if the Bernoulli variable takes on the value 1, then the response variable is Gaussian, and if the Bernoulli variable takes on the value 0, then the response is zero too. This package includes functions for simulation, parameter estimation, goodness-of-fit, the Viterbi algorithm, and plotting the classified 2-D data. Some of the functions in the package are based on those of the R package 'HiddenMarkov' by David Harte.
License: GPL (>= 2)
URL: http://www.stats.otago.ac.nz/?people=ting_wang
Packaged: 2018-09-11 20:49:19 UTC; twang
NeedsCompilation: yes
Repository: CRAN
Date/Publication: 2018-09-17 15:30:07 UTC

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New package farver with initial version 1.0
Package: farver
Type: Package
Title: Vectorised Colour Conversion and Comparison
Version: 1.0
Date: 2018-09-17
Authors@R: c(person(given = "Thomas Lin", family = "Pedersen", role = c("cre", "aut"), email = "thomasp85@gmail.com"), person(given = "Berendea", family = "Nicolae", role = "aut", comment = "Author of the ColorSpace C++ library"), person(given = "Romain", family = "François", role = "aut", email = "romain@purrple.cat", comment = c(ORCID = "0000-0002-2444-4226")) )
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>
Description: The encoding of colour can be handled in many different ways, using different colour spaces. As different colour spaces have different uses, efficient conversion between these representations are important. The 'farver' package provides a set of functions that gives access to very fast colour space conversion and comparisons implemented in C++, and offers 100-fold speed improvements over the 'convertColor' function in the 'grDevices' package.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: C++11
Imports: Rcpp (>= 0.12.15)
LinkingTo: Rcpp
RoxygenNote: 6.1.0
URL: https://github.com/thomasp85/farver
BugReports: https://github.com/thomasp85/farver/issues
Suggests: testthat, covr
NeedsCompilation: yes
Packaged: 2018-09-17 09:12:47 UTC; thomas
Author: Thomas Lin Pedersen [cre, aut], Berendea Nicolae [aut] (Author of the ColorSpace C++ library), Romain François [aut] (<https://orcid.org/0000-0002-2444-4226>)
Repository: CRAN
Date/Publication: 2018-09-17 15:20:02 UTC

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New package VICmodel with initial version 0.1.0
Package: VICmodel
Type: Package
Title: The Variable Infiltration Capacity (VIC) Model
Version: 0.1.0
Authors@R: c(person("Ruida", "Zhong", email = "zrd2017@163.com", role = c("aut", "cre")), person("Xiaohong", "Chen", role = c("aut", "ctb")), person("Joseph J", "Hamman", role = c("ctb"), comment = "Contributor and maintainer of VIC source code"), person("Keith", "Cherkauer", role = c("ctb"), comment = "Contributer of codes of src/vic/vic_run/src/write_vegvar.c and src/vic/drivers/shared_all/src/cmd_proc.c") )
Description: The Variable Infiltration Capacity (VIC) model is a macroscale hydrologic model that solves full water and energy balances, originally developed by Xu Liang at the University of Washington (UW). The version of VIC source code used is of 5.0.1 on <https://github.com/UW-Hydro/VIC/>, see Hamman et al. (2018). Development and maintenance of the current official version of the VIC model at present is led by the UW Hydro (Computational Hydrology group) in the Department of Civil and Environmental Engineering at UW. VIC is a research model and in its various forms it has been applied to most of the major river basins around the world, as well as globally. If you make use of this model, please acknowledge the appropriate references listed in the help page of this package or on the references page <http://vic.readthedocs.io/en/master/Documentation/References/> of the VIC official documentation website. These should include Liang et al. (1994) plus any references relevant to the features you are using Reference: Liang, X., D. P. Lettenmaier, E. F. Wood, and S. J. Burges (1994), A simple hydrologically based model of land surface water and energy fluxes for general circulation models, J. Geophys. Res., 99(D7), 14415-14428, <doi:10.1029/94JD00483>. Hamman et al. (2018) about VIC 5.0.1 also can be considered: Hamman, J. J., Nijssen, B., Bohn, T. J., Gergel, D. R., and Mao, Y. (2018), The Variable Infiltration Capacity model version 5 (VIC-5): infrastructure improvements for new applications and reproducibility, Geosci. Model Dev., 11, 3481-3496, <doi:10.5194/gmd-11-3481-2018>.
License: GPL-3
Copyright: file inst/COPYRIGHTS
URL: https://github.com/Sibada/VICmodel
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: stats, utils, Rcpp (>= 0.12.0), foreach
Suggests: doParallel
LinkingTo: Rcpp
RoxygenNote: 5.0.1
NeedsCompilation: yes
Packaged: 2018-09-11 05:22:49 UTC; Da
Author: Ruida Zhong [aut, cre], Xiaohong Chen [aut, ctb], Joseph J Hamman [ctb] (Contributor and maintainer of VIC source code), Keith Cherkauer [ctb] (Contributer of codes of src/vic/vic_run/src/write_vegvar.c and src/vic/drivers/shared_all/src/cmd_proc.c)
Maintainer: Ruida Zhong <zrd2017@163.com>
Repository: CRAN
Date/Publication: 2018-09-17 14:20:06 UTC

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New package MSPRT with initial version 1.0
Package: MSPRT
Type: Package
Title: Modified Sequential Probability Ratio Test (MSPRT)
Version: 1.0
Date: 2018-09-11
Authors@R: c(person("Sandipan", "Pramanik", email = "sandy@stat.tamu.edu", role = c("aut", "cre")), person("Valen E.", "Johnson", role = "aut"), person("Anirban", "Bhattacharya", role = "aut") )
Author: Sandipan Pramanik [aut, cre], Valen E. Johnson [aut], Anirban Bhattacharya [aut]
Maintainer: Sandipan Pramanik <sandy@stat.tamu.edu>
Description: A modified SPRT (MSPRT) can be designed and implemented with the help of this package. In a MSPRT design, the maximum sample size of an experiment is fixed prior to the start of an experiment, the alternative hypothesis used to define the rejection region of the test is derived from the size of the test (Type I error), the maximum available sample size (N), and the targeted Type 2 error (equal to 1 minus the power) is also prespecified. Given these values, the MSPRT is defined in a manner very similar to Wald's initial proposal. This test can reduce the average sample size required to perform statistical hypothesis tests at the specified levels of significance and power. This package facilitates the carrying out of one sample Z tests, T Tests and tests of binomial success probabilities. A user guidance for this software package is provided here and also in the supplemental information.
Imports: nleqslv, ggplot2, foreach, iterators, parallel, doParallel, datasets, graphics, grDevices, methods, stats, utils
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-11 16:56:52 UTC; sandipanpramanik
Repository: CRAN
Date/Publication: 2018-09-17 14:50:03 UTC

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New package emhawkes with initial version 0.9.0
Package: emhawkes
Title: Exponential Multivariate Hawkes Model
Version: 0.9.0
Authors@R: person("Kyungsub", "Lee", email = "kyungsub@gmail.com", role = c("aut", "cre"))
Maintainer: Kyungsub Lee <kyungsub@gmail.com>
Description: Simulate and fitting exponential multivariate Hawkes model. This package simulates a multivariate Hawkes model, introduced by Hawkes (1971) <doi:10.1093/biomet/58.1.83>, with an exponential kernel and fits the parameters from the data. Models with the constant parameters, as well as complex dependent structures, can also be simulated and estimated. The estimation is based on the maximum likelihood method, introduced by introduced by Ozaki (1979) <doi:10.1007/BF02480272>, with 'maxLik' package.
Depends: R (>= 3.4.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: maxLik, methods
Collate: 'harrival.R' 'hspec.R' 'hmoment.R' 'hllf.R' 'hfit.R' 'utilities.R' 'hreal.R' 'hsim.R' 'script.R'
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-03 01:25:13 UTC; user
Author: Kyungsub Lee [aut, cre]
Repository: CRAN
Date/Publication: 2018-09-17 14:20:02 UTC

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New package xopen with initial version 1.0.0
Package: xopen
Title: Open System Files, 'URLs', Anything
Version: 1.0.0
Authors@R: c( person("Gábor", "Csárdi",, "csardi.gabor@gmail.com", c("aut", "cre")), person("Fathi", "Boudra", role = "aut"), person("Rex", "Dieter", role = "aut"), person("Kevin", "Krammer", role = "aut"), person("Jeremy", "White", role = "aut"))
Description: Cross platform solution to open files, directories or 'URLs' with their associated programs.
License: MIT + file LICENSE
LazyData: true
URL: https://github.com/r-lib/xopen#readme
BugReports: https://github.com/r-lib/xopen/issues
RoxygenNote: 6.1.0
Imports: processx
Suggests: ps, testthat
Encoding: UTF-8
Depends: R (>= 3.1)
NeedsCompilation: no
Packaged: 2018-09-10 20:47:53 UTC; gaborcsardi
Author: Gábor Csárdi [aut, cre], Fathi Boudra [aut], Rex Dieter [aut], Kevin Krammer [aut], Jeremy White [aut]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-17 13:10:03 UTC

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New package ipc with initial version 0.1.0
Package: ipc
Type: Package
Title: Tools for Message Passing Between Processes
Version: 0.1.0
Author: Ian E. Fellows
Maintainer: Ian E. Fellows <ian@fellstat.com>
Description: Provides tools for passing messages between R processes. Shiny Examples are provided showing how to perform useful tasks such as: updating reactive values from within a future, progress bars for long running async tasks, and interrupting async tasks based on user input.
Imports: R6, shiny, txtq, redux
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, future, promises
VignetteBuilder: knitr
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-11 00:29:27 UTC; ianfellows
Repository: CRAN
Date/Publication: 2018-09-17 13:20:03 UTC

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New package empirical with initial version 0.1.0
Package: empirical
Title: Empirical Probability Density Functions and Empirical Cumulative Distribution Functions
Version: 0.1.0
Date: 2018-09-11
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>
Description: Implements empirical probability density functions (continuous functions) and empirical cumulative distribution functions (step functions or continuous). Currently, univariate only.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-11 01:13:54 UTC; Student9
Repository: CRAN
Date/Publication: 2018-09-17 13:20:06 UTC

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New package CorDiff with initial version 1.0
Package: CorDiff
Type: Package
Imports: mcc
Title: Set-Based Differential Covariance Testing for Genomics
Version: 1.0
Date: 2018-09-05
Author: Yi-Hui Zhou
Maintainer: Yi-Hui Zhou <yihui_zhou@ncsu.edu>
Description: We describe four different summary statistics, to ensure power and flexibility under various settings, including a new connectivity statistic that is sensitive to changes in overall covariance magnitude.
License: GPL-2
LazyLoad: yes
NeedsCompilation: no
Packaged: 2018-09-05 14:16:01 UTC; yzhou19
Repository: CRAN
Date/Publication: 2018-09-17 13:10:10 UTC

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New package salty with initial version 0.1.0
Type: Package
Package: salty
Title: Turn Clean Data into Messy Data
Version: 0.1.0
Authors@R: c( person("Matthew Lincoln", email = "matthew.d.lincoln@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4387-3384")))
Description: Take real or simulated data and salt it with errors commonly found in the wild, such as pseudo-OCR errors, Unicode problems, numeric fields with nonsensical punctuation, bad dates, etc.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: assertthat, purrr, stringr
Suggests: charlatan, testthat (>= 2.0.0), tibble, covr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
URL: https://github.com/mdlincoln/salty
BugReports: https://github.com/mdlincoln/salty/issues
NeedsCompilation: no
Packaged: 2018-09-10 11:49:31 UTC; mlincoln
Author: Matthew Lincoln [aut, cre] (<https://orcid.org/0000-0002-4387-3384>)
Maintainer: Matthew Lincoln <matthew.d.lincoln@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-17 11:40:03 UTC

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New package EloOptimized with initial version 0.3.0
Package: EloOptimized
Title: Optimized Elo Rating Method for Obtaining Dominance Ranks
Version: 0.3.0
Date: 2018-09-05
Authors@R: c( person("Joseph", "Feldblum", email = "feldblum@umich.edu", role = c("aut", "cre")), person("Steffen", "Foerster", email = "sf2041@gmail.com", role = c("aut")), person("Mathias", "Franz", email = "m.franz@izw-berlin.de", role = c("aut")))
Description: Provides an implementation of the maximum likelihood methods for deriving Elo scores as published in Foerster, Franz et al. (2016) <DOI:10.1038/srep35404>.
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: dplyr, reshape2, BAMMtools, tcltk, rlist, magrittr, lubridate, rlang
URL: https://github.com/jtfeld/EloOptimized
BugReports: https://github.com/jtfeld/EloOptimized/issues
NeedsCompilation: no
Packaged: 2018-09-10 21:35:33 UTC; Joseph Feldblum
Author: Joseph Feldblum [aut, cre], Steffen Foerster [aut], Mathias Franz [aut]
Maintainer: Joseph Feldblum <feldblum@umich.edu>
Repository: CRAN
Date/Publication: 2018-09-17 11:50:08 UTC

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New package CA3variants with initial version 1.0
Package: CA3variants
Type: Package
Title: Three-Way Correspondence Analysis Variants
Version: 1.0
Date: 2018-08-20
Author: Rosaria Lombardo and Eric J Beh
Maintainer: Rosaria Lombardo <rosaria.lombardo@unicampania.it>
Description: Provides three variants of three-way correspondence analysis (ca) three-way symmetrical ca, three-way non-symmetrical ca, three-way ordered symmetrical ca.
Depends: R (> 3.0.1), methods, tools, ggplot2, gridExtra, ggrepel
LazyData: true
License: GPL (> 2)
URL: https://www.R-project.org
NeedsCompilation: no
Packaged: 2018-09-10 16:57:56 UTC; Amministratore
Repository: CRAN
Date/Publication: 2018-09-17 09:00:13 UTC

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Sun, 16 Sep 2018

New package VBTree with initial version 0.1.0
Package: VBTree
Type: Package
Title: Vector Binary Tree to Make Your Data Management More Efficient
Version: 0.1.0
Date: 2018-09-05
Author: ZHANG Chen
Maintainer: ZHANG Chen <447974102@qq.com>
Description: Provides a new data structure, vector binary tree, to make your data visiting and management more efficient. if your data has very structurized column names with specific connecting pattern, it can read, split, and factorize these names, then build the mapping from all string objects to an array or tensor, through vector binary tree, by which the batched data processing can be implemented easily. The methods of array and tensor are also applicable.
Imports: tensorA
Depends: R (>= 2.10)
License: GPL-3
URL: https://github.com/CubicZebra/VBTree
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 12:06:20 UTC; chen_zhang
Repository: CRAN
Date/Publication: 2018-09-16 18:10:09 UTC

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New package taxotools with initial version 0.0.3
Package: taxotools
Type: Package
Title: Tools to Handle Taxonomic Lists
Version: 0.0.3
Date: 2018-09-10
Authors@R: c( person("Vijay", "Barve", ,"vijay.barve@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4852-2567")))
Maintainer: Vijay Barve <vijay.barve@gmail.com>
Description: Some tools to work with taxonomic name lists.
License: CC0
Imports: taxize, wikitaxa
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
BugReports: https://github.com/vijaybarve/taxotools/issues
NeedsCompilation: no
Packaged: 2018-09-10 14:44:36 UTC; vijaybarve
Author: Vijay Barve [aut, cre] (<https://orcid.org/0000-0002-4852-2567>)
Repository: CRAN
Date/Publication: 2018-09-16 18:20:03 UTC

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New package stylest with initial version 0.1.0
Package: stylest
Version: 0.1.0
Title: Estimating Speaker Style Distinctiveness
Authors@R: c( person("Leslie", "Huang", role = c("aut", "cph", "cre"), email = "lesliehuang@nyu.edu"), person(c("Patrick", "O."), "Perry", role = c("aut", "cph")), person("Arthur", "Spirling", role = c("aut", "cph")))
Depends: R (>= 2.10)
Imports: corpus, Matrix, stats
Suggests: knitr, rmarkdown, testthat, kableExtra
Description: Estimates distinctiveness in speakers' (authors') style. Fits models that can be used for predicting speakers of new texts. Methods developed in Spirling et al (2018) <doi:10.2139/ssrn.3235506> (working paper).
License: GPL-3
URL: https://github.com/leslie-huang/stylest
BugReports: https://github.com/leslie-huang/stylest/issues
LazyData: true
Encoding: UTF-8
VignetteBuilder: knitr, rmarkdown
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2018-09-10 12:50:57 UTC; lesliehuang
Author: Leslie Huang [aut, cph, cre], Patrick O. Perry [aut, cph], Arthur Spirling [aut, cph]
Maintainer: Leslie Huang <lesliehuang@nyu.edu>
Repository: CRAN
Date/Publication: 2018-09-16 18:10:03 UTC

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New package roundhouse with initial version 0.0.1
Package: roundhouse
Type: Package
Title: An R Wrapper to the 'ICNDb' API
Version: 0.0.1
Authors@R: person("Brandon", "Greenwell", email = "greenwell.brandon@gmail.com", role = c("aut", "cre"))
Description: An R wrapper to the 'Internet Chuck Norris database' ('ICNDb') API for generating random Chuck Norris facts.
License: GPL (>= 2)
URL: ttps://github.com/bgreenwell/roundhouse
BugReports: https://github.com/bgreenwell/roundhouse/issues
Imports: httr, jsonlite
Suggests: covr, magick, testthat
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-16 18:02:59 UTC; bgreenwell
Author: Brandon Greenwell [aut, cre]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-16 18:30:02 UTC

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New package ojUtils with initial version 0.1.0
Package: ojUtils
Type: Package
Title: A Collection of Utility Functions
Version: 0.1.0
Date: 2018-08-27
Author: Owe Jessen
Maintainer: Owe Jessen <post@owejessen.de>
Description: This is a collection of utility functions. Currently, it provides alternatives to base ifelse() and base combn() functions utilizing 'Rcpp', and providing a significant speedup compared to base.
License: GPL-3
Imports: Rcpp (>= 0.11.0), testthat
LinkingTo: Rcpp
RoxygenNote: 6.1.0
NeedsCompilation: yes
Packaged: 2018-09-10 19:04:44 UTC; Owe
Repository: CRAN
Date/Publication: 2018-09-16 18:30:06 UTC

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New package NTsets with initial version 1.0
Package: NTsets
Type: Package
Title: Normality Test Sets Integrated Function and Figure Methods for Continuous Variables
Version: 1.0
Date: 2018-08-25
Author: Wenlong Ren,Jing Xiao,Yawen Zhang and Zhikai Liang
Maintainer: Wenlong Ren<wenlongren@ntu.edu.cn>
Description: Conduct normality test with nine different function methods and three different figure methods for continuous variables with a friendly GUI. For different data types, provide a more comprehensive means of judgement.
Depends: gWidgets,gWidgetsRGtk2,RGtk2Extras
Imports: RGtk2,methods,nortest,tseries,fBasics
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2018-09-02 13:01:57 UTC; 78165
Repository: CRAN
Date/Publication: 2018-09-16 18:20:06 UTC

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New package MPN with initial version 0.1.0
Package: MPN
Title: Most Probable Number for Serial Dilutions
Version: 0.1.0
Authors@R: c( person("Martine", "Ferguson", email = "Martine.Ferguson@fda.hhs.gov", role = "aut", comment = "original R code"), person("John", "Ihrie", email = "John.Ihrie@fda.hhs.gov", role = c("cre", "aut")))
Maintainer: John Ihrie <John.Ihrie@fda.hhs.gov>
Description: Calculates the Most Probable Number for serial dilutions to quantify the concentration (density) of microbes in a laboratory sample. Currently implements the confidence interval approach described in Jarvis (2010) <doi:10.1111/j.1365-2672.2010.04792.x>.
Depends: R (>= 3.4.0)
License: Unlimited
URL: https://mpncalc.galaxytrakr.org/
LazyData: TRUE
RoxygenNote: 6.1.0
Imports: stats (>= 3.4.0)
Suggests: knitr (>= 1.20), rmarkdown (>= 1.10), testthat (>= 2.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-04 13:54:02 UTC; John.Ihrie
Author: Martine Ferguson [aut] (original R code), John Ihrie [cre, aut]
Repository: CRAN
Date/Publication: 2018-09-16 18:20:09 UTC

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New package caMST with initial version 0.1.0
Package: caMST
Type: Package
Title: Mixed Computerized Adaptive Multistage Testing
Version: 0.1.0
Date: 2018-08-22
Authors@R: person("Anthony", "Raborn", email = "anthony.w.raborn@gmail.com", role = c("aut","cre"))
Description: Provides functions to more easily analyze computerized adaptive tests. Currently, functions for computerized adaptive tests (CAT), computer adaptive multistage tests (CMT), and mixed computer adaptive multistage tests (McaMST) utilizing CAT item-level adaptation for the initial stage and traditional MST module-level adaptation for the subsequent stages have been created, and a variation of Hybrid computer adaptive MST is planned as well. For an in-depth look at CAT and MST, see Weiss & Kingsbury (1984) <doi:10.1111/j.1745-3984.1984.tb01040.x> and Luecht & Nungester (2000) <doi:10.1007/0-306-47531-6_6> respectively.
License: LGPL (>= 2.0, < 3) | Mozilla Public License
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.3)
Imports: catR, mstR
Suggests: testthat, knitr, rmarkdown
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2018-09-10 14:45:18 UTC; chika
Author: Anthony Raborn [aut, cre]
Maintainer: Anthony Raborn <anthony.w.raborn@gmail.com>
Repository: CRAN
Date/Publication: 2018-09-16 18:10:06 UTC

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New package ahpsurvey with initial version 0.2.1
Package: ahpsurvey
Type: Package
Title: Analytic Hierarchy Process for Survey Data
Version: 0.2.1
Authors@R: person("Frankie", "Cho", email = "htcho@connect.hku.hk", role = c("aut", "cre"))
Description: The Analytic Hierarchy Process is a versatile multi-criteria decision-making tool introduced by Saaty (1987) <doi:10.1016/0270-0255(87)90473-8> that allows decision-makers to weigh attributes and evaluate alternatives presented to them. This package provides a consistent methodology for researchers to reformat data and run analytic hierarchy process in R on data that are formatted using the survey data entry mode. It is optimized for performing the analytic hierarchy process with many decision-makers, and provides tools and options for researchers to aggregate individual preferences and test multiple options. It also allows researchers to quantify, visualize and correct for inconsistency in the decision-maker's comparisons.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.1.0
Imports: Rdpack, stats, magrittr, knitr, tidyr, dplyr
Suggests: ggplot2, tidyverse, scales
RdMacros: Rdpack
Collate: 'ahp_mat.R' 'ahp_aggjudge.R' 'ahp_aggpref.R' 'ahp_bweight.R' 'ahp_cr.R' 'ahp_indpref.R' 'ahp_error.R' 'ahp_harker.R' 'ahp_missing.R' 'ahp_pwerror.R' 'ahpsurvey.R' 'data.R'
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 16:24:00 UTC; chohinting
Author: Frankie Cho [aut, cre]
Maintainer: Frankie Cho <htcho@connect.hku.hk>
Repository: CRAN
Date/Publication: 2018-09-16 18:40:03 UTC

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New package duawranglr with initial version 0.6.3
Package: duawranglr
Title: Securely Wrangle Dataset According to Data Usage Agreement
Version: 0.6.3
Authors@R: person("Benjamin", "Skinner", email = "btskinner@virginia.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-7415"))
URL: https://github.com/btskinner/duawranglr
BugReports: https://github.com/btskinner/duawranglr/issues
Description: Create shareable data sets from raw data files that contain protected elements. Relying on master crosswalk files that list restricted variables, package functions warn users about possible violations of data usage agreement and prevent writing protected elements.
Depends: R (>= 3.1.2)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: haven, readxl, readr, digest, dplyr
RoxygenNote: 6.1.0
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2018-09-10 13:05:52 UTC; bts4h
Author: Benjamin Skinner [aut, cre] (<https://orcid.org/0000-0002-0337-7415>)
Maintainer: Benjamin Skinner <btskinner@virginia.edu>
Repository: CRAN
Date/Publication: 2018-09-16 18:00:02 UTC

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Sat, 15 Sep 2018

New package BLPestimatoR with initial version 0.2.5
Package: BLPestimatoR
Type: Package
Title: Performs a BLP Demand Estimation
Version: 0.2.5
Author: Daniel Brunner (aut), Constantin Weiser (ctr), Andre Romahn (ctr)
Maintainer: Daniel Brunner <daniel.brunner@hhu.de>
Description: Provides the estimation algorithm to perform the demand estimation described in Berry, Levinsohn and Pakes (1995) <DOI:10.2307/2171802> . The routine uses analytic gradients and offers a large number of implemented integration methods and optimization routines.
License: GPL-3
LazyData: TRUE
Imports: Rcpp (>= 0.11.0), mvQuad, numDeriv, randtoolbox, Formula, stats
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.1.0
NeedsCompilation: yes
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2018-09-14 17:43:13 UTC; brubu
Repository: CRAN
Date/Publication: 2018-09-15 07:20:16 UTC

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Fri, 14 Sep 2018

New package rym with initial version 0.4.0
Package: rym
Type: Package
Title: R Interface to Yandex Metrika API
Version: 0.4.0
Date: 2018-09-03
Author: Alexey Seleznev <selesnow@gmail.com>
Maintainer: Alexey Seleznev <selesnow@gmail.com>
Description: Allows work with 'Management API' for load counters, segments, filters, user permissions and goals list from Yandex Metrika, 'Reporting API' allows you to get information about the statistics of site visits and other data without using the web interface, 'Logs API' allows to receive non-aggregated data and 'Compatible with Google Analytics Core Reporting API v3' allows receive information about site traffic and other data using field names from Google Analytics Core API. For more information see official documents <https://tech.yandex.ru/metrika/doc/api2/concept/about-docpage/>.
Depends: R (>= 3.5.0)
BugReports: https://github.com/selesnow/rym/issues
License: GPL-2
Imports: httr, stringr, utils
URL: http://selesnow.github.io/
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2018-09-10 12:29:06 UTC; Alsey
Repository: CRAN
Date/Publication: 2018-09-14 23:00:02 UTC

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New package episcan with initial version 0.0.1
Package: episcan
Title: Scan Pairwise Epistasis
Version: 0.0.1
Author: Beibei Jiang <beibei_jiang@psych.mpg.de> and Benno Pütz <puetz@psych.mpg.de>
Maintainer: Beibei Jiang <beibei_jiang@psych.mpg.de>
Description: Searching genomic interactions with linear/logistic regression in a high-dimensional dataset is a time-consuming task. This package provides some efficient ways to scan epistasis in genome-wide interaction studies (GWIS). Both case-control status (binary outcome) and quantitative phenotype (continuous outcome) are supported (the main references: 1. Kam-Thong, T., D. Czamara, K. Tsuda, K. Borgwardt, C. M. Lewis, A. Erhardt-Lehmann, B. Hemmer, et al. (2011). <doi:10.1038/ejhg.2010.196>. 2. Kam-Thong, T., B. Pütz, N. Karbalai, B. Müller-Myhsok, and K. Borgwardt. (2011). <doi:10.1093/bioinformatics/btr218>.)
Depends: R (>= 3.5.0)
License: GPL (>= 2)
Encoding: UTF-8
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.1.0
NeedsCompilation: no
Packaged: 2018-09-10 12:13:44 UTC; beibei_jiang
Repository: CRAN
Date/Publication: 2018-09-14 23:02:19 UTC

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New package embed with initial version 0.0.1
Package: embed
Version: 0.0.1
Title: Extra Recipes for Encoding Categorical Predictors
Description: Factor predictors can be converted to one or more numeric representations using simple generalized linear models <arXiv:1611.09477> or nonlinear models <arXiv:1604.06737>. All encoding methods are supervised.
Authors@R: c( person("Max", "Kuhn", , "max@rstudio.com", c("aut", "cre")), person("RStudio", role = "cph"))
Depends: R (>= 3.1), recipes (>= 0.1.3)
Imports: rstanarm, keras, stats, dplyr, purrr, rlang, utils, broom, tidyr, tibble, lme4, tensorflow
Suggests: testthat, knitr, rmarkdown, covr
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
ByteCompile: true
URL: https://tidymodels.github.io/embed
BugReports: https://github.com/tidymodels/embed/issues
NeedsCompilation: no
Packaged: 2018-09-06 01:25:20 UTC; max
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2018-09-14 23:12:24 UTC

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