Thu, 27 Jul 2017

New package optiSolve with initial version 0.1
Package: optiSolve
Type: Package
Title: Linear, Quadratic, and Rational Optimization
Version: 0.1
Date: 2017-07-27
Author: Robin Wellmann
Maintainer: Robin Wellmann <r.wellmann@uni-hohenheim.de>
Depends: R (>= 3.3.2)
Description: Solver for linear, quadratic, and rational programs with linear, quadratic, and rational constraints. A unified interface to different R packages is provided. Optimization problems are transformed into equivalent formulations and solved by the respective package. For example, quadratic programming problems with linear, quadratic and rational constraints can be solved by augmented Lagrangian minimization using package 'alabama', or by sequential quadratic programming using solver 'slsqp'. Alternatively, they can be reformulated as optimization problems with second order cone constraints and solved with package 'cccp', or transformed into semidefinite programming problems and solved using solver 'csdp'.
License: GPL-2
Imports: Matrix, shapes, Rcsdp, alabama, cccp, nloptr, MASS, methods, plyr, stringr, stats, Rcpp (>= 0.12.4)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-27 08:33:15 UTC; Robin
Repository: CRAN
Date/Publication: 2017-07-27 22:22:13 UTC

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New package CrossValidate with initial version 2.3.0
Package: CrossValidate
Version: 2.3.0
Date: 2017-07-24
Title: Classes and Methods for Cross Validation of "Class Prediction" Algorithms
Author: Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Depends: R (>= 3.0), Modeler
Imports: methods, oompaBase (>= 3.0.1)
Suggests: Biobase
Description: Defines classes and methods to cross-validate various binary classification algorithms used for "class prediction" problems.
License: Apache License (== 2.0)
LazyLoad: yes
biocViews: Microarray, Clustering
URL: http://oompa.r-forge.r-project.org
NeedsCompilation: no
Packaged: 2017-07-27 19:40:54 UTC; coom05
Repository: CRAN
Date/Publication: 2017-07-27 22:23:16 UTC

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New package simsurv with initial version 0.1.0
Package: simsurv
Type: Package
Title: Simulate Survival Data
Version: 0.1.0
Authors@R: c(person("Sam", "Brilleman", email = "sam.brilleman@monash.edu", role = c("cre", "aut", "cph")))
Maintainer: Sam Brilleman <sam.brilleman@monash.edu>
Description: Simulate survival times from standard parametric survival distributions (exponential, Weibull, Gompertz), 2-component mixture distributions, or a user-defined hazard or log hazard function. Baseline covariates can be included under a proportional hazards assumption. Time dependent effects (i.e. non-proportional hazards) can be included by interacting covariates with linear time or some transformation of time. The 2-component mixture distributions can allow for a variety of flexible baseline hazard functions. If the user wishes to provide a user-defined hazard or log hazard function then this is also possible, and the resulting cumulative hazard function does not need to have a closed-form solution. Note that this package is modelled on the 'survsim' package available in the 'Stata' software (see Crowther and Lambert (2012) <http://www.stata-journal.com/sjpdf.html?articlenum=st0275> or Crowther and Lambert (2013) <doi:10.1002/sim.5823>).
License: GPL (>= 3) | file LICENSE
Depends: R (>= 3.3.2)
Imports: methods, stats
Suggests: eha (>= 2.4.5), MASS, survival (>= 2.40.1), testthat (>= 1.0.2)
LazyData: true
BugReports: https://github.com/sambrilleman/simsurv/issues
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-27 04:06:17 UTC; brillems
Author: Sam Brilleman [cre, aut, cph]
Repository: CRAN
Date/Publication: 2017-07-27 11:08:12 UTC

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New package mosaicCalc with initial version 0.5.0
Package: mosaicCalc
Type: Package
Title: Function-Based Numerical and Symbolic Differentiation and Antidifferentiation
Description: Part of the Project MOSAIC (<http://mosaic-web.org/>) suite that provides utility functions for doing calculus (differentiation and integration) in R. The main differentiation and antidifferentiation operators are described using formulas and return functions rather than numerical values. Numerical values can be obtained by evaluating these functions.
Version: 0.5.0
Date: 2017-07-26
Depends: R (>= 3.0.0), mosaicCore
Imports: methods, stats, MASS, mosaic
Suggests: testthat, knitr, rmarkdown
Author: Daniel T. Kaplan <kaplan@macalester.edu>, Randall Pruim <rpruim@calvin.edu>, Nicholas J. Horton <nhorton@amherst.edu>
Maintainer: Randall Pruim <rpruim@calvin.edu>
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
URL: https://github.com/ProjectMOSAIC/mosaicCalc
BugReports: https://github.com/ProjectMOSAIC/mosaicCalc/issues
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-07-27 11:12:00 UTC; rpruim
Repository: CRAN
Date/Publication: 2017-07-27 11:22:02 UTC

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New package recipes with initial version 0.1.0
Package: recipes
Title: Preprocessing Tools to Create Design Matrices
Version: 0.1.0
Authors@R: c( person("Max", "Kuhn", , "max@rstudio.com", c("aut", "cre")), person("Hadley", "Wickham", , "hadley@rstudio.com", "aut"), person("RStudio", role = "cph"))
Description: An extensible framework to create and preprocess design matrices. Recipes consist of one or more data manipulation and analysis "steps". Statistical parameters for the steps can be estimated from an initial data set and then applied to other data sets. The resulting design matrices can then be used as inputs into statistical or machine learning models.
URL: https://github.com/topepo/recipes
BugReports: https://github.com/topepo/recipes/issues
Depends: R (>= 3.2.3), dplyr
Imports: tibble, stats, ipred, dimRed (>= 0.1.0), lubridate, timeDate, ddalpha, purrr, rlang (>= 0.1.1), gower, RcppRoll, tidyselect (>= 0.1.1), magrittr
Suggests: testthat, rpart, kernlab, fastICA, RANN, igraph, knitr, caret, ggplot2, rmarkdown
License: GPL-2
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-27 01:40:39 UTC; max
Author: Max Kuhn [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2017-07-27 10:46:19 UTC

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New package lsplsGlm with initial version 1.0
Package: lsplsGlm
Type: Package
Title: Classification using LS-PLS for Logistic Regression
Version: 1.0
Date: 2017-07-19
Encoding: latin1
Author: Caroline Bazzoli <caroline.bazzoli@univ-grenoble-alpes.fr>, Sophie Lambert-Lacroix <sophie.lambert-lacroix@univ-grenoble-alpes.fr>, Thomas Bouleau <tbouleau@gmail.com>
Depends: R (>= 3.0), methods, stats
Maintainer: Bazzoli Caroline <caroline.bazzoli@univ-grenoble-alpes.fr>
Description: Fit logistic regression models using LS-PLS approaches to analyse both clinical and genomic data. (C. Bazzoli and S. Lambert-Lacroix. (2017) Classification using LS-PLS with logistic regression based on both clinical and gene expression variables <https://hal.archives-ouvertes.fr/hal-01405101>).
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
NeedsCompilation: no
Packaged: 2017-07-27 09:55:55 UTC; tbouleau
Repository: CRAN
Date/Publication: 2017-07-27 10:34:54 UTC

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New package icmm with initial version 1.0
Package: icmm
Type: Package
Title: Empirical Bayes Variable Selection via ICM/M Algorithm
Version: 1.0
Authors@R: c(person("Vitara", "Pungpapong", role = c("aut", "cre"), email = "vitara@cbs.chula.ac.th"), person("Min", "Zhang", role = "aut", email="minzhang@stat.purdue.edu"), person("Dabao", "Zhang", role = "aut", email = "zhangdb@stat.purdue.edu"))
Author: Vitara Pungpapong [aut, cre], Min Zhang [aut], Dabao Zhang [aut]
Maintainer: Vitara Pungpapong <vitara@cbs.chula.ac.th>
Description: Carries out empirical Bayes variable selection via ICM/M algorithm. The basic problem is to fit high-dimensional regression which most coefficients are assumed to be zero. This package allows incorporating the Ising prior to capture structure of predictors in the modeling process. The current version of this package can handle the normal, binary logistic, and Cox's regression (Pungpapong et. al. (2015) <doi:10.1214/15-EJS1034>, Pungpapong et. al. (2017) <arXiv:1707.08298>).
License: GPL (>= 2)
Imports: EbayesThresh
Suggests: MASS, stats
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-07-27 08:17:17 UTC; vpungpap
Repository: CRAN
Date/Publication: 2017-07-27 08:42:29 UTC

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Wed, 26 Jul 2017

New package unrepx with initial version 1.0
Package: unrepx
Type: Package
Title: Analysis and Graphics for Unreplicated Experiments
Version: 1.0
Date: 2017-07-26
Authors@R: c(person("Russell", "Lenth", role = c("aut", "cre", "cph"), email = "russell-lenth@uiowa.edu"))
LazyData: yes
BugReports: https://github.com/rvlenth/unrepx/issues
Description: Provides half-normal plots, reference plots, and Pareto plots of effects from an unreplicated experiment, along with various pseudo-standard-error measures, simulated reference distributions, and other tools. Many of these methods are described in Daniel C. (1959) <doi:10.1080/00401706.1959.10489866> and/or Lenth R.V. (1989) <doi:10.1080/00401706.1989.10488595>, but some new approaches are added and integrated in one package.
Suggests: knitr
VignetteBuilder: knitr
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-07-26 19:57:05 UTC; rlenth
Author: Russell Lenth [aut, cre, cph]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>
Repository: CRAN
Date/Publication: 2017-07-26 21:59:28 UTC

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New package sdm with initial version 1.0-41
Package: sdm
Type: Package
Title: Species Distribution Modelling
Version: 1.0-41
Date: 2017-07-26
Author: Babak Naimi, Miguel B. Araujo
Maintainer: Babak Naimi <naimi.b@gmail.com>
Depends: methods, sp (>= 1.2-0), R (>= 3.0.0)
Imports: raster
Suggests: rgdal (>= 0.9-1), knitr, shinyBS, shiny, dismo, rmarkdown
Description: An extensible framework for developing species distribution models using individual and community-based approaches, generate ensembles of models, evaluate the models, and predict species potential distributions in space and time. For more information, please check the following paper: Naimi, B., Araujo, M.B. (2016) <doi:10.1111/ecog.01881>.
License: GPL (>= 3)
URL: http://biogeoinformatics.org
VignetteBuilder: knitr
Repository: CRAN
Repository/R-Forge/Project: sdm
Repository/R-Forge/Revision: 63
Repository/R-Forge/DateTimeStamp: 2017-07-26 18:33:47
Date/Publication: 2017-07-26 22:13:23 UTC
NeedsCompilation: no
Packaged: 2017-07-26 18:46:15 UTC; rforge

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New package mnreadR with initial version 0.1.0
Package: mnreadR
Type: Package
Title: MNREAD Parameters Estimation
Version: 0.1.0
Authors@R: c( person("Aurelie", "Calabrese", email = "acalabre@umn.edu", role = c("aut", "cre")), person("J. Steve", "Mansfield", email = "steve.mansfield@plattsburgh.edu", role = "aut"), person("Gordon E.", "Legge", email = "legge@umn.edu", role = "aut") )
Description: Allows to analyze MNREAD data. The MNREAD Acuity Charts are continuous text reading acuity charts for normal and low vision. Provides the necessary functions to estimate automatically the four MNREAD parameters: Maximum Reading Speed, Critical Print Size, Reading Acuity and Reading Accessibility Index (Calabrese et al (2016) <doi:10.1001/jamaophthalmol.2015.6097>).
Depends: R (>= 2.10), dplyr
Imports: stats
URL: http://legge.psych.umn.edu/mnread-acuity-charts
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-26 20:21:57 UTC; Aurelie
Author: Aurelie Calabrese [aut, cre], J. Steve Mansfield [aut], Gordon E. Legge [aut]
Maintainer: Aurelie Calabrese <acalabre@umn.edu>
Repository: CRAN
Date/Publication: 2017-07-26 22:06:42 UTC

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New package maxTPR with initial version 0.1.0
Package: maxTPR
Type: Package
Title: Maximizing the TPR for a Specified FPR
Version: 0.1.0
Date: 2017-07-26
Author: Allison Meisner
Maintainer: Allison Meisner <allison.meisner@gmail.com>
Description: Estimates a linear combination of predictors by maximizing a smooth approximation to the estimated true positive rate (TPR; sensitivity) while constraining a smooth approximation to the estimated false positive rate (FPR; 1-specificity) at a user-specified level.
License: GPL-2
LazyData: TRUE
Imports: aucm, Rsolnp
NeedsCompilation: no
Packaged: 2017-07-26 17:53:36 UTC; allison
Repository: CRAN
Date/Publication: 2017-07-26 21:41:21 UTC

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New package loon with initial version 1.1.0
Package: loon
Type: Package
Title: Interactive Statistical Data Visualization
Version: 1.1.0
Date: 2017-07-26
Authors@R: c( person("Adrian", "Waddell", , "adrian@waddell.ch", role = c("aut", "cre")), person("R. Wayne", "Oldford", , "rwoldford@uwaterloo.ca", role = "aut") )
URL: http://waddella.github.io/loon/
Description: An extendable toolkit for interactive data visualization and exploration.
License: GPL-2
Depends: R (>= 3.4.0), methods, tcltk
Imports: tools, graphics, grDevices, utils, stats
Suggests: maps, sp, graph, scagnostics, PairViz, RColorBrewer, RnavGraphImageData, rworldmap, rgl, Rgraphviz, RDRToolbox, kernlab, scales, MASS, dplyr, testthat, knitr, rmarkdown
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-26 19:34:25 UTC; adrian
Author: Adrian Waddell [aut, cre], R. Wayne Oldford [aut]
Maintainer: Adrian Waddell <adrian@waddell.ch>
Repository: CRAN
Date/Publication: 2017-07-26 21:51:02 UTC

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New package blandr with initial version 0.4.3
Package: blandr
Title: Bland-Altman Method Comparison
Version: 0.4.3
Description: Carries out Bland Altman analyses (also known as a Tukey mean-difference plot) as described by JM Bland and DG Altman in 1986 <doi:10.1016/S0140-6736(86)90837-8>. This package was created in 2015 as existing Bland-Altman analysis functions did not calculate confidence intervals. This package was created to rectify this, and create reproducible plots.
Depends: R (>= 3.4.0)
Authors@R: person("Deepankar", "Datta", email = "deepankardatta@nhs.net", role = c("aut", "cre"))
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://github.com/deepankardatta/blandr/
BugReports: https://github.com/deepankardatta/blandr/issues
Imports: ggplot2, knitr
Suggests: rmarkdown
VignetteBuilder: knitr
Collate: 'blandr.basic.plot.r' 'blandr.data.preparation.r' 'blandr.ggplot.r' 'blandr.plot.limits.r' 'blandr.statistics.r' 'blandr.draw.r' 'blandr.display.r' 'blandr.display.and.draw.r' 'blandr.display.and.plot.r' 'blandr.method.comparison.r' 'blandr.plot.r' 'blandr.proportional.bias.r'
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-26 18:28:02 UTC; deepankardatta
Author: Deepankar Datta [aut, cre]
Maintainer: Deepankar Datta <deepankardatta@nhs.net>
Repository: CRAN
Date/Publication: 2017-07-26 21:48:40 UTC

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New package metaBMA with initial version 0.3.8
Package: metaBMA
Type: Package
Date: 2017-07-26
Title: Bayesian Model Averaging for Random and Fixed Effects Meta-Analysis
Version: 0.3.8
Authors@R: c(person("Daniel W.","Heck",email="heck@uni-mannheim.de",role=c("aut","cre")), person("Quentin F.", "Gronau", email="quentingronau@web.de", role = c("ctb")), person("Eric-Jan", "Wagenmakers", email="ej.wagenmakers@gmail.com", role = c("ctb")))
Maintainer: Daniel W. Heck <heck@uni-mannheim.de>
Description: Computes the posterior model probabilities for four meta-analysis models (null model vs. alternative model assuming either fixed- or random-effects, respectively). These posterior probabilities are used to estimate the overall mean effect size as the weighted average of the mean effect size estimates of the random- and fixed-effect model as proposed by Gronau, Van Erp, Heck, Cesario, Jonas, & Wagenmakers (2017, <doi:10.1080/23743603.2017.1326760>). The user can define a wide range of noninformative or informative priors for the mean effect size and the heterogeneity coefficient. Funding for this research was provided by the Berkeley Initiative for Transparency in the Social Sciences, a program of the Center for Effective Global Action (CEGA), with support from the Laura and John Arnold Foundation.
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.0)
Imports: mvtnorm, logspline, coda, runjags, LaplacesDemon
Suggests: testthat, knitr
VignetteBuilder: knitr
SystemRequirements: JAGS (http://mcmc-jags.sourceforge.net)
URL: https://github.com/danheck/metaBMA
License: GPL-3
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-26 16:44:33 UTC; Daniel
Author: Daniel W. Heck [aut, cre], Quentin F. Gronau [ctb], Eric-Jan Wagenmakers [ctb]
Repository: CRAN
Date/Publication: 2017-07-26 17:43:28 UTC

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New package iRF with initial version 2.0.0
Package: iRF
Title: iterative Random Forests
Version: 2.0.0
Date: 2017-07-25
Depends: R (>= 3.1.2),
Imports: AUC, Matrix, data.table, dplyr, Rcpp, methods, foreach, doParallel, RColorBrewer
Suggests: MASS, rgl
LinkingTo: Rcpp
SystemRequirements: C++11
Author: Sumanta Basu and Karl Kumbier (based on source codes from the R packages FSInteract by Hyun Jik Kim and Rajen D. Shah, randomForest by Andy Liaw and Matthew Wiener, and the original Fortran codes by Leo Breiman and Adele Cutler)
Description: Iteratively grows feature weighted random forests and finds high-order feature interactions in a stable fashion.
Maintainer: Karl Kumbier <kkumbier@berkeley.edu>
URL: https://arxiv.org/abs/1706.08457
License: GPL-2
NeedsCompilation: yes
Packaged: 2017-07-25 22:55:38 UTC; karl
Repository: CRAN
Date/Publication: 2017-07-26 04:57:45 UTC

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Tue, 25 Jul 2017

New package concaveman with initial version 1.0.0
Package: concaveman
Type: Package
Title: A Very Fast 2D Concave Hull Algorithm
Version: 1.0.0
Authors@R: c( person("Joël", "Gombin", email="joel.gombin@gmail.com", role = c("cre", "aut")), person("Ramnath", "Vaidyanathan", role = "aut"), person("Vladimir", "Agafonkin", role = "aut"), person("Mapbox", role = "cph") )
Description: The concaveman function ports the 'concaveman' (<https://github.com/mapbox/concaveman>) library from 'mapbox'. It computes the concave polygon(s) for one or several set of points.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: V8, sf, magrittr, jsonlite, methods, dplyr
RoxygenNote: 6.0.1
Suggests: testthat, sp
URL: http://www.github.com/joelgombin/concaveman
BugReports: http://www.github.com/joelgombin/concaveman/issues
SystemRequirements: GDAL (>= 2.0.0), GEOS (>= 3.3.0), PROJ.4 (>= 4.8.0)
NeedsCompilation: no
Packaged: 2017-07-25 21:57:11 UTC; joel
Author: Joël Gombin [cre, aut], Ramnath Vaidyanathan [aut], Vladimir Agafonkin [aut], Mapbox [cph]
Maintainer: Joël Gombin <joel.gombin@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-25 22:37:09 UTC

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New package timetk with initial version 0.1.0
Package: timetk
Type: Package
Title: A Tool Kit for Working with Time Series in R
Version: 0.1.0
Date: 2017-07-25
Authors@R: c( person("Matt", "Dancho", email = "mdancho@business-science.io", role = c("aut", "cre")), person("Davis", "Vaughan", email = "dvaughan@business-science.io", role = c("aut")) )
Description: Get the time series index, signature, and summary from time series objects and time-based tibbles. Create future time series based on properties of existing time series index. Coerce between time-based tibbles ('tbl') and 'xts', 'zoo', and 'ts'.
URL: https://github.com/business-science/timetk
BugReports: https://github.com/business-science/timetk/issues
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.3.0)
Imports: devtools (>= 1.12.0), dplyr (>= 0.7.0), forecast (>= 0.8.0), lazyeval (>= 0.2.0), lubridate (>= 1.6.0), padr (>= 0.3.0), purrr (>= 0.2.2), readr (>= 1.0.0), stringi (>= 1.1.5), tibble (>= 1.2), tidyr (>= 0.6.1), xts (>= 0.9-7), zoo (>= 1.7-14)
Suggests: broom, forcats, knitr, rmarkdown, robets, scales, stringr, testthat, tidyverse, tidyquant
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-25 16:53:08 UTC; mdancho
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>
Repository: CRAN
Date/Publication: 2017-07-25 21:43:26 UTC

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New package MiRKAT with initial version 1.0
Package: MiRKAT
Version: 1.0
Date: 2017-07-25
Title: Microbiome Regression-Based Kernel Association Test
Authors@R: c(person("Haotian", "Zheng", role = c("aut"), email = "ht-zh14@mails.tsighua.edu.cn"), person("Xiang", "Zhan", role = "aut"), person("Anna", "Plantinga", role = "aut"), person("Michael", "Wu", role = "aut"), person("Ni", "Zhao", role = c("aut", "cre"), email = "nzhao10@jhu.edu"))
Author: Haotian Zheng [aut], Xiang Zhan [aut], Anna Plantinga [aut], Michael Wu [aut], Ni Zhao [aut, cre]
Maintainer: Ni Zhao <nzhao10@jhu.edu>
Depends: R (>= 2.13.0), survival, PearsonDS, GUniFrac, MASS
Description: Test for overall association between microbiome composition data with a continuous or dichotomous outcome via phylogenetic kernels. The phenotype can be univariate continuous or binary phenotypes (Zhao et al. (2015) <doi:10.1016/j.ajhg.2015.04.003>), survival outcomes (Plantinga et al. (2017) <doi:10.1186/s40168-017-0239-9>), multivariate (Zhan et al. (2017) <doi:10.1002/gepi.22030>) and structured phenotypes (Zhan et al. (2017) <doi:10.1111/biom.12684>). For all these effect, the microbiome community effect was modeled nonparametrically through a kernel function, which can incorporate the phylogenetic tree information.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2017-07-25 20:54:07 UTC; dell
Repository: CRAN
Date/Publication: 2017-07-25 21:52:56 UTC

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New package bayeslongitudinal with initial version 0.1.0
Package: bayeslongitudinal
Type: Package
Title: Adjust Longitudinal Regression Models Using Bayesian Methodology
Version: 0.1.0
Date: 2017-07-18
Author: Edwin Javier Castillo Carreño, Edilberto Cepeda Cuervo
Maintainer: Edwin Javier Castillo Carreño <edjcastilloca@unal.edu.co>
Description: Adjusts longitudinal regression models using Bayesian methodology for covariance structures of composite symmetry (SC), autoregressive ones of order 1 AR (1) and autoregressive moving average of order (1,1) ARMA (1,1).
License: GPL (>= 2)
Depends: R(>= 3.1.0), LearnBayes, mvtnorm, MASS
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-18 21:21:17 UTC; edwin
Repository: CRAN
Date/Publication: 2017-07-25 21:13:13 UTC

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New package qqplotr with initial version 0.0.1
Package: qqplotr
Type: Package
Version: 0.0.1
Title: Quantile-Quantile Plot Extensions for 'ggplot2'
Description: Extensions of 'ggplot2' Q-Q plot functionalities.
Authors@R: c(person("Alexandre", "Almeida", email = "almeida.xan@gmail.com", role = c("aut", "cre")), person("Adam", "Loy", email = "loyad01@gmail.com", role = c("aut")), person("Heike", "Hofmann", role = "aut"))
URL: https://github.com/aloy/qqplotr
BugReports: https://github.com/aloy/qqplotr/issues
License: GPL-3 | file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Collate: 'stat_qq_point.R' 'stat_qq_line.R' 'stat_qq_band.R'
Depends: ggplot2
Imports: dplyr, robustbase, stats4
NeedsCompilation: no
Packaged: 2017-07-22 19:46:03 UTC; almeida
Author: Alexandre Almeida [aut, cre], Adam Loy [aut], Heike Hofmann [aut]
Maintainer: Alexandre Almeida <almeida.xan@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-25 17:34:47 UTC

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New package MRTSampleSize with initial version 0.1.0
Package: MRTSampleSize
Type: Package
Title: A Sample Size Calculator for Micro-Randomized Trials
Version: 0.1.0
Authors@R: c( person("Liying","Huang", email = "lxh37@psu.edu", role = c("aut","cre")), person("Nicholas J.","Seewald", email = "nseewald@umich.edu", role = "aut"), person("Peng","Liao", email = "pengliao@umich.edu", role ="aut"), person("Ji","Sun", email = "sunji@umich.edu", role ="aut"))
Depends: R (>= 2.15.0)
Copyright: The Pennsylvania State University
Description: Provide a sample size calculator for micro-randomized trials (MRTs) based on methodology developed in Sample Size Calculations for Micro-randomized Trials in mHealth by Liao et al. (2016) <DOI:10.1002/sim.6847>.
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-07-21 13:15:14 UTC; admin_lxh37
Author: Liying Huang [aut, cre], Nicholas J. Seewald [aut], Peng Liao [aut], Ji Sun [aut]
Maintainer: Liying Huang <lxh37@psu.edu>
Repository: CRAN
Date/Publication: 2017-07-25 11:06:21 UTC

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New package treeDA with initial version 0.0.2
Package: treeDA
Title: Tree-Based Discriminant Analysis
Version: 0.0.2
Authors@R: person("Julia", "Fukuyama", email = "julia.fukuyama@gmail.com", role = c("aut", "cre"))
Description: Performs sparse discriminant analysis on a combination of node and leaf predictors when the predictor variables are structured according to a tree.
Depends: R (>= 3.4.1)
Imports: sparseLDA (>= 0.1.9), Matrix (>= 1.2.10), mvtnorm (>= 1.0.6), reshape2 (>= 1.4.2), gtable (>= 0.2.0), grid (>= 3.4.1), phyloseq (>= 1.20.0), ggplot2 (>= 2.2.1), stats (>= 3.4.1)
Suggests: adaptiveGPCA (>= 0.1), knitr (>= 1.16)
VignetteBuilder: knitr
License: GPL-2
URL: https://github.com/jfukuyama/treeda
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-24 21:59:20 UTC; juliefukuyama
Author: Julia Fukuyama [aut, cre]
Maintainer: Julia Fukuyama <julia.fukuyama@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-25 08:30:30 UTC

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New package pulver with initial version 0.1.0
Package: pulver
Title: Parallel Ultra-Rapid p-Value Computation for Linear Regression Interaction Terms
Version: 0.1.0
Authors@R: person("Sophie", "Molnos", email = "somolnos@gmail.com", role = c("aut", "cre"))
Maintainer: Sophie Molnos <somolnos@gmail.com>
Description: Computes p-values for the interaction term in a very large number of linear regression models.
Depends: R (>= 3.3.0)
License: GPL (>= 2)
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp, DatABEL, parallel, methods
Suggests: testthat, knitr, rmarkdown, devtools
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2017-07-25 07:37:16 UTC; sophie.molnos
Author: Sophie Molnos [aut, cre]
Repository: CRAN
Date/Publication: 2017-07-25 08:26:31 UTC

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New package PSIMEX with initial version 1.0
Package: PSIMEX
Type: Package
Title: SIMEX Algorithm on Pedigree Structures
Version: 1.0
Depends: MCMCglmm, plotrix, pedigree, knitr
VignetteBuilder: knitr
Date: 2017-07-23
Author: Erica Ponzi
Maintainer: Erica Ponzi <erica.ponzi@uzh.ch>
Description: Generalization of the SIMEX algorithm from Cook & Stefanski (1994) <doi:10.2307/2290994> for the calculation of inbreeding depression or heritability on pedigree structures affected by missing or misassigned paternities. It simulates errors and tracks the behavior of the estimate as a function of the error proportion. It extrapolates back a true value corresponding to the null error rate.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-07-25 07:13:48 UTC; ericapo
Repository: CRAN
Date/Publication: 2017-07-25 08:23:59 UTC

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New package curstatCI with initial version 0.1.0
Package: curstatCI
Type: Package
Title: Confidence Intervals for the Current Status Model
Version: 0.1.0
Authors@R: c( person("Piet", "Groeneboom", email = "P.Groeneboom@tudelft.nl",role = "aut"), person("Kim", "Hendrickx", email = "kim.hendrickx@uhasselt.be",role = "cre"))
Description: Computes the maximum likelihood estimator, the smoothed maximum likelihood estimator and pointwise bootstrap confidence intervals for the distribution function under current status data. Groeneboom and Hendrickx (2017) <arXiv:1701.07359>.
License: GPL-3
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Imports: Rcpp
Depends: R (>= 2.10)
RoxygenNote: 6.0.1
URL: https://github.com/kimhendrickx/curstatCI
BugReports: https://github.com/kimhendrickx/curstatCI/issues
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2017-07-25 08:41:11 UTC; lucp8442
Author: Piet Groeneboom [aut], Kim Hendrickx [cre]
Maintainer: Kim Hendrickx <kim.hendrickx@uhasselt.be>
Repository: CRAN
Date/Publication: 2017-07-25 08:50:19 UTC

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Mon, 24 Jul 2017

New package ThermIndex with initial version 0.1.0
Package: ThermIndex
Type: Package
Title: Calculate Thermal Indexes
Version: 0.1.0
Author: Francisco Jablinski Castelhano/Laboclima - Universidade Federal do Paraná
Maintainer: Francisco Jablinski Castelhano <fjcastelhano@gmail.com>
Description: Calculates several thermal comfort indexes using temperature, wind speed and relative humidity values, calculating indexes such as Humidex, windchill, Discomfort Index and others.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-24 19:49:49 UTC; Chico
Repository: CRAN
Date/Publication: 2017-07-24 22:08:45 UTC

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New package cordillera with initial version 0.7-0
Package: cordillera
Title: Calculation of the OPTICS Cordillera
Version: 0.7-0
Date: 2017-07-24
Authors@R: c(person(given="Thomas", family="Rusch", email="thomas.rusch@wu.ac.at", role = c("aut","cre")), person(given="Patrick",family="Mair", role = "ctb"),person(given="Kurt",family="Hornik", role = "ctb"))
Author: Thomas Rusch [aut, cre], Patrick Mair [ctb], Kurt Hornik [ctb]
Maintainer: Thomas Rusch <thomas.rusch@wu.ac.at>
Description: Functions for calculating the OPTICS Cordillera. The OPTICS Cordillera measures the amount of 'clusteredness' in a numeric data matrix within a distance-density based framework for a given minimum number of points comprising a cluster, as described in Rusch, Hornik, Mair (2017) <doi:10.1080/10618600.2017.1349664>. There is an R native version and a version that uses 'ELKI', with methods for printing, summarizing, and plotting the result. There also is an interface to the reference implementation of OPTICS in 'ELKI'.
Depends: R (>= 3.1.2),
SystemRequirements: ELKI (>=0.6.0 if used)
Imports: dbscan, yesno
Suggests: cluster, scatterplot3d, MASS
License: GPL-2 | GPL-3
LazyData: true
URL: http://r-forge.r-project.org/projects/stops/
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-24 20:27:45 UTC; root
Repository: CRAN
Date/Publication: 2017-07-24 22:07:51 UTC

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New package pcensmix with initial version 1.2-1
Package: pcensmix
Type: Package
Title: Model Fitting to Progressively Censored Mixture Data
Version: 1.2-1
Authors@R: c(person("Lida", "Fallah", role = c("aut", "cre"), email = "l.fallah22@gmail.com"), person("John", "Hinde", role = "aut"))
Depends: R (>= 3.3.3), stats
Imports: utils
Description: Functions for generating progressively Type-II censored data in a mixture structure and fitting models using a constrained EM algorithm. It can also create a progressive Type-II censored version of a given real dataset to be considered for model fitting.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-24 17:18:11 UTC; LidaFallah
Author: Lida Fallah [aut, cre], John Hinde [aut]
Maintainer: Lida Fallah <l.fallah22@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-24 19:01:10 UTC

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New package GGEBiplots with initial version 0.1.1
Package: GGEBiplots
Title: GGE Biplots with 'ggplot2'
Version: 0.1.1
Authors@R: c(person("Sam", "Dumble", email = "s.dumble@stats4sd.org", role = c("aut", "cre")),person("Elisa", "Frutos Bernal", email = "efb@usal.es", role = c("ctb")),person("Purificacion", "Galindo Villardon", email = "pgalindo@usal.es", role = c("ctb")))
Description: Genotype plus genotype-by-environment (GGE) biplots rendered using 'ggplot2'. Provides a command line interface to all of the functionality contained within 'GGEBiplotGUI'.
Depends: R (>= 3.3.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2 (>= 2.2.0), ggforce (>= 0.1.1), scales (>= 0.4.1), grDevices (>= 3.3.1), stats (>= 3.3.1), GGEBiplotGUI (>= 1.0-9), grid (>= 3.3.1), utils (>= 3.3.1), gge (>= 1.2)
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-07-24 16:12:42 UTC; sdumb
Author: Sam Dumble [aut, cre], Elisa Frutos Bernal [ctb], Purificacion Galindo Villardon [ctb]
Maintainer: Sam Dumble <s.dumble@stats4sd.org>
Repository: CRAN
Date/Publication: 2017-07-24 18:38:35 UTC

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New package mosaicCore with initial version 0.2.0
Package: mosaicCore
Type: Package
Title: Common Utilities for Other MOSAIC-Family Packages
Version: 0.2.0
Date: 2017-07-24
Depends: R (>= 3.0.0),
Imports: stats, dplyr, lazyeval, rlang, tidyr
Suggests: mosaicData, mosaic, ggformula
Author: Randall Pruim <rpruim@calvin.edu>, Daniel T. Kaplan <kaplan@macalester.edu>, Nicholas J. Horton <nhorton@amherst.edu>
Maintainer: Randall Pruim <rpruim@calvin.edu>
Description: Common utilities used in other MOSAIC-family packages are collected here.
License: GPL (>= 2)
LazyLoad: yes
LazyData: yes
URL: https://github.com/ProjectMOSAIC/mosaicCore
BugReports: https://github.com/ProjectMOSAIC/mosaicCore/issues
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-07-24 14:09:04 UTC; rpruim
Repository: CRAN
Date/Publication: 2017-07-24 15:46:38 UTC

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New package tidyselect with initial version 0.1.1
Package: tidyselect
Title: Select from a Set of Strings
Version: 0.1.1
Authors@R: c( person("Lionel", "Henry", ,"lionel@rstudio.com", c("aut", "cre")), person("Hadley", "Wickham", ,"hadley@rstudio.com", "aut"), person("RStudio", role = "cph") )
Description: A backend for the selecting functions of the 'tidyverse'. It makes it easy to implement select-like functions in your own packages in a way that is consistent with other 'tidyverse' interfaces for selection.
Depends: R (>= 3.1.0)
Imports: glue, rlang (>= 0.1), Rcpp (>= 0.12.0)
Suggests: testthat
LinkingTo: Rcpp (>= 0.12.0),
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-07-24 09:12:34 UTC; lionel
Author: Lionel Henry [aut, cre], Hadley Wickham [aut], RStudio [cph]
Maintainer: Lionel Henry <lionel@rstudio.com>
Repository: CRAN
Date/Publication: 2017-07-24 10:39:37 UTC

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New package estprod with initial version 0.0.1
Package: estprod
Title: Estimation of Production Functions
Version: 0.0.1
Date: 2017-07-23
Authors@R: c( person("Rodrigo", "R Remédio", , email = "rremedio@hotmail.com", role = c("aut", "cre")), person("Paul", "Schrimpf",,, role = "ctb", comment = "panel_lag function") )
Description: Estimation of production functions by the Olley-Pakes and Levinsohn-Petrin methodologies. The package aims to reproduce the results obtained with the Stata's user written opreg <http://www.stata-journal.com/article.html?article=st0145> and levpet <http://www.stata-journal.com/article.html?article=st0060> commands. The first was originally proposed by Olley, G.S. and Pakes, A. (1996) <doi:10.2307/2171831>. And the second by Levinsohn, J. and Petrin, A. (2003) <doi:10.1111/1467-937X.00246>.
Depends: R (>= 3.4.1)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: lazyeval, boot, minpack.lm, Formula
NeedsCompilation: no
Packaged: 2017-07-23 22:20:16 UTC; Rodrigo
Author: Rodrigo R Remédio [aut, cre], Paul Schrimpf [ctb] (panel_lag function)
Maintainer: Rodrigo R Remédio <rremedio@hotmail.com>
Repository: CRAN
Date/Publication: 2017-07-24 09:04:19 UTC

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Sun, 23 Jul 2017

New package hIRT with initial version 0.1.0
Package: hIRT
Type: Package
Title: Hierarchical Item Response Theory Models
Version: 0.1.0
Authors@R: person("Xiang", "Zhou", email = "xiang_zhou@fas.harvard.edu", role = c("aut", "cre"))
Description: Implementation of a class of hierarchical item response theory (IRT) models where both the mean and the variance of latent preferences (ability parameters) can depend on observed covariates. The current implementation includes both the two-parameter latent trait model and the graded response model for ordinal data. Both are fitted via the Expectation-Maximization (EM) algorithm. Asymptotic standard errors are derived from the observed information matrix.
Depends: R (>= 3.3.2), stats
Imports: pryr (>= 0.1.2), rms (>= 5.1-1)
Suggests: ggplot2 (>= 2.2.1)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
URL: http://github.com/xiangzhou09/hIRT
BugReports: http://github.com/xiangzhou09/hIRT
NeedsCompilation: no
Packaged: 2017-07-23 11:04:00 UTC; Xiang
Author: Xiang Zhou [aut, cre]
Maintainer: Xiang Zhou <xiang_zhou@fas.harvard.edu>
Repository: CRAN
Date/Publication: 2017-07-23 20:06:29 UTC

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New package spData with initial version 0.2.2
Package: spData
Title: Datasets for Spatial Analysis
Version: 0.2.2
Authors@R: c(person("Roger", "Bivand", role = "aut", email="Roger.Bivand@nhh.no"), person("Jakub", "Nowosad", role = c("aut", "cre"), email="nowosad.jakub@gmail.com"), person("Robin", "Lovelace", role = "aut") )
Description: Diverse spatial datasets for demonstrating, benchmarking and teaching spatial data analysis. It includes R data of class sf (defined by the package 'sf'). Unlike other spatial data packages such as 'rnaturalearth' and 'maps', it also contains data stored in a range of file formats including GeoJSON, ESRI Shapefile and GeoPackage. Some of the datasets are designed to illustrate specific analysis techniques. cycle_hire_osm, for example, is designed to illustrate point pattern analysis techniques.
Depends: R (>= 3.3.0)
Suggests: sf
License: CC0
RoxygenNote: 6.0.1
LazyData: true
URL: https://github.com/Nowosad/spData
BugReports: https://github.com/Nowosad/spData/issues
NeedsCompilation: no
Packaged: 2017-07-23 16:21:53 UTC; jn
Author: Roger Bivand [aut], Jakub Nowosad [aut, cre], Robin Lovelace [aut]
Maintainer: Jakub Nowosad <nowosad.jakub@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-23 17:37:41 UTC

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New package ProjectionBasedClustering with initial version 1.0.0
Package: ProjectionBasedClustering
Type: Package
Title: Projection Based Clustering
Version: 1.0.0
Authors@R: c(person("Michael", "Thrun", email= "m.thrun@gmx.net",role=c("aut","cre")),person("Florian", "Lerch",role="aut"),person("Felix", "Pape",role="aut"),person("Nybo", "Nybo",role="cph"),person("Jarkko", "Venna",role="cph"))
Date: 2017-07-21
Description: A clustering approach for every projection method based on the generalized U*-matrix visualization of a topographic map is made available here. The number of clusters and the cluster structure can be estimated by counting the valleys in a topographic map. If the number of clusters and the clustering method are chosen correctly, then the clusters will be well separated by mountains in the visualization. Most projection methods are wrappers for already available methods in R. However, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' software package and the Curvilinear Component Analysis (CCA) is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R.
License: GPL-3
Imports: Rcpp, ggplot2, stats, graphics, vegan, deldir, geometry, GeneralizedUmatrix
Suggests: fastICA, tsne, FastKNN, MASS, pcaPP, spdep, methods, pracma, grid, mgcv
LinkingTo: Rcpp
LazyData: TRUE
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2017-07-23 06:13:40 UTC; MT
Author: Michael Thrun [aut, cre], Florian Lerch [aut], Felix Pape [aut], Nybo Nybo [cph], Jarkko Venna [cph]
Maintainer: Michael Thrun <m.thrun@gmx.net>
Repository: CRAN
Date/Publication: 2017-07-23 17:50:38 UTC

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New package nofrills with initial version 0.1.0
Package: nofrills
Type: Package
Title: Low-Cost Anonymous Functions
Version: 0.1.0
Authors@R: person("Eugene", "Ha", , "eha@posteo.de", c("aut", "cre"))
Description: Provides a compact variation of the usual syntax of function declaration, in order to support Tidyverse-style quasiquotation of a function's arguments and body.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
ByteCompile: true
Depends: R (>= 3.1.0)
Imports: rlang (>= 0.1.1)
Suggests: testthat
URL: https://github.com/egnha/nofrills
BugReports: https://github.com/egnha/nofrills/issues
Collate: 'nofrills.R' 'fn.R' 'as-fn.R'
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-22 21:58:19 UTC; eha
Author: Eugene Ha [aut, cre]
Maintainer: Eugene Ha <eha@posteo.de>
Repository: CRAN
Date/Publication: 2017-07-23 17:39:03 UTC

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New package jpndistrict with initial version 0.2.0
Package: jpndistrict
Type: Package
Title: Create Japanese Administration Area and Office Maps
Version: 0.2.0
Authors@R: c(person(given = "Shinya", family = "Uryu", email = "suika1127@gmail.com", role = c("aut", "cre")))
Maintainer: Shinya Uryu <suika1127@gmail.com>
Description: Utilizing the data that Japanese administration area provided by the National Land Numerical Information download service (<http://nlftp.mlit.go.jp/ksj/index.html>).
Depends: R (>= 3.1.0)
Imports: dplyr, leaflet, magrittr, miniUI, readr, sf, shiny (>= 0.13), stringi, tibble
Suggests: devtools, ggplot2, kokudosuuchi, jpmesh, knitr, plotly, purrr, rmarkdown, rvest, testthat, tidyr
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
URL: https://github.com/uribo/jpndistrict
BugReports: https://github.com/uribo/jpndistrict/issues
NeedsCompilation: no
Packaged: 2017-07-23 13:52:57 UTC; uri
Author: Shinya Uryu [aut, cre]
Repository: CRAN
Date/Publication: 2017-07-23 17:50:34 UTC

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New package c2c with initial version 0.1.0
Package: c2c
Type: Package
Title: Compare Two Classifications or Clustering Solutions of Varying Structure
Version: 0.1.0
Authors@R: person("Mitchell", "Lyons", email = "mitchell.lyons@gmail.com", role = c("aut", "cre"))
Maintainer: Mitchell Lyons <mitchell.lyons@gmail.com>
Description: Compare two classifications or clustering solutions that may or may not have the same number of classes, and that might have hard or soft (fuzzy, probabilistic) membership. Calculate various metrics to assess how the clusters compare to each other. The calculations are simple, but provide a handy tool for users unfamiliar with matrix multiplication. This package is not geared towards traditional accuracy assessment for classification/ mapping applications - the motivating use case is for comparing a probabilistic clustering solution to a set of reference or existing class labels that could have any number of classes (that is, without having to degrade the probabilistic clustering to hard classes).
Depends: R (>= 3.1.0)
URL: https://github.com/mitchest/c2c/
BugReports: https://github.com/mitchest/c2c/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat, knitr, rmarkdown, e1071
RoxygenNote: 6.0.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-23 02:57:48 UTC; mitchell
Author: Mitchell Lyons [aut, cre]
Repository: CRAN
Date/Publication: 2017-07-23 17:50:40 UTC

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New package tfruns with initial version 0.9
Package: tfruns
Type: Package
Title: Training Run Directories for 'TensorFlow'
Version: 0.9
Authors@R: c( person("JJ", "Allaire", role = c("aut", "cre"), email = "jj@rstudio.com"), person(family = "RStudio", role = c("cph", "fnd")) )
Description: Create and manage unique directories for each 'TensorFlow' training run. Provides a unique, timestamped directory for each run along with functions to retrieve the directory of the latest run or latest several runs.
License: Apache License 2.0
URL: https://github.com/rstudio/tfruns
BugReports: https://github.com/rstudio/tfruns/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-23 00:53:32 UTC; jjallaire
Author: JJ Allaire [aut, cre], RStudio [cph, fnd]
Maintainer: JJ Allaire <jj@rstudio.com>
Repository: CRAN
Date/Publication: 2017-07-23 08:54:19 UTC

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Sat, 22 Jul 2017

New package SMM with initial version 1.0
Package: SMM
Type: Package
Title: Simulation and Estimation of Multi-State Discrete-Time Semi-Markov and Markov Models
Version: 1.0
Date: 2017-07-14
Depends: seqinr, DiscreteWeibull
Author: Vlad Stefan Barbu, Caroline Berard, Dominique Cellier, Mathilde Sautreuil and Nicolas Vergne
Maintainer: Nicolas Vergne <nicolas.vergne@univ-rouen.fr>
Description: Performs parametric and non-parametric estimation and simulation for multi-state discrete-time semi-Markov processes. For the parametric estimation, several discrete distributions are considered for the sojourn times: Uniform, Geometric, Poisson, Discrete Weibull and Negative Binomial. The non-parametric estimation concerns the sojourn time distributions, where no assumptions are done on the shape of distributions. Moreover, the estimation can be done on the basis of one or several sample paths, with or without censoring at the beginning or/and at the end of the sample paths. The implemented methods are described in Barbu, V.S., Limnios, N. (2008) <doi:10.1007/978-0-387-73173-5>, Barbu, V.S., Limnios, N. (2008) <doi:10.1080/10485250701261913> and Trevezas, S., Limnios, N. (2011) <doi:10.1080/10485252.2011.555543>. Estimation and simulation of discrete-time k-th order Markov chains are also considered.
License: GPL
VignetteBuilder: utils
Suggests: utils
NeedsCompilation: no
Packaged: 2017-07-22 14:00:15 UTC; msautreuil
Repository: CRAN
Date/Publication: 2017-07-22 20:28:47 UTC

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New package vcov with initial version 0.0.1
Package: vcov
Version: 0.0.1
Title: Variance-Covariance Matrices and Standard Errors
Author: Michael Chirico
Maintainer: Michael Chirico <MichaelChirico4@gmail.com>
Depends: R (>= 3.4.0)
Description: Methods for faster extraction (about 5x faster in a few test cases) of variance-covariance matrices and standard errors from models. Methods in the 'stats' package tend to rely on the summary method, which may waste time computing other summary statistics which are summarily ignored.
License: GPL (>= 2) | file LICENSE
URL: https://github.com/MichaelChirico/vcov
NeedsCompilation: no
Packaged: 2017-07-21 16:00:28 UTC; michael
Repository: CRAN
Date/Publication: 2017-07-22 16:09:54 UTC

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New package prisonbrief with initial version 0.1.0
Package: prisonbrief
Type: Package
Title: Downloads and Parses World Prison Brief Data
Version: 0.1.0
Authors@R: c( person("Danilo", "Freire", , "danilofreire@gmail.com", c("aut", "cre")), person("Robert", "McDonnell", , "mcdonnell.robert5@gmail.com", c("aut")) )
URL: http://danilofreire.com/prisonbrief
Description: Download, parses and tidies information from the World Prison Brief project <http://www.prisonstudies.org/>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: yes
Depends: R (>= 3.0)
Imports: httr (>= 1.2.1), tibble (>= 1.3.3), dplyr (>= 0.5.0), data.table(>= 1.10.4), magrittr (>= 1.5), rvest (>= 0.3.2), xml2 (>= 1.1.1), tidyr (>= 0.6.3), rlang (>= 0.1.1), passport (>= 0.1.1), rnaturalearth (>= 0.1.0), rnaturalearthdata (>= 0.1.0), stringr(>= 1.2.0)
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-07-22 15:15:06 UTC; sussa
Author: Danilo Freire [aut, cre], Robert McDonnell [aut]
Maintainer: Danilo Freire <danilofreire@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-22 16:34:51 UTC

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Thu, 20 Jul 2017

New package incR with initial version 0.3.1
Package: incR
Type: Package
Title: Analysis of Incubation Data
Version: 0.3.1
Date: 2017-07-20
Authors@R: person ("Pablo", "Capilla-Lasheras", email="pacapilla@gmail.com", role=c("aut", "cre"))
Author: Pablo Capilla-Lasheras [aut, cre]
Maintainer: Pablo Capilla-Lasheras <pacapilla@gmail.com>
Description: Suite of functions to study animal incubation. At the core of incR lays an algorithm that allows for the scoring of incubation behaviour. Additionally, several functions extract biologically relevant metrics of incubation such as off-bout number and off-bout duration - for a review of avian incubation studies, see Nests, Eggs, and Incubation: New ideas about avian reproduction (2015) edited by D. Charles Deeming and S. James Reynolds <doi:10.1093/acprof:oso/9780198718666.001.0001>.
License: GPL-3
Depends: R (>= 3.4.0), base, stats
Imports: dplyr, maptools, lubridate, rgeos, utils
Suggests: codetools, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-20 15:09:43 UTC; pc395
Repository: CRAN
Date/Publication: 2017-07-20 15:16:35 UTC

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New package subgroup.discovery with initial version 0.1.3
Package: subgroup.discovery
Type: Package
Title: Subgroup Discovery and Bump Hunting
Version: 0.1.3
Authors@R: c( person(given = "Jurian", family = "Baas", email = "jurian@jurianbaas.nl", role = c("aut", "cre", "cph")), person(given = "Ad", family ="Feelders", email = "A.J.Feelders@uu.nl", role = c("ctb")))
Description: Developed to assist in discovering interesting subgroups in high-dimensional data. The PRIM implementation is based on the 1998 paper "Bump hunting in high-dimensional data" by Jerome H. Friedman and Nicholas I. Fisher. <doi:10.1023/A:1008894516817> PRIM involves finding a set of "rules" which combined imply unusually large (or small) values of some other target variable. Specifically one tries to find a set of sub regions in which the target variable is substantially larger than overall mean. The objective of bump hunting in general is to find regions in the input (attribute/feature) space with relatively high (low) values for the target variable. The regions are described by simple rules of the type if: condition-1 and ... and condition-n then: estimated target value. Given the data (or a subset of the data), the goal is to produce a box B within which the target mean is as large as possible. There are many problems where finding such regions is of considerable practical interest. Often these are problems where a decision maker can in a sense choose or select the values of the input variables so as to optimize the value of the target variable. In bump hunting it is customary to follow a so-called covering strategy. This means that the same box construction (rule induction) algorithm is applied sequentially to subsets of the data.
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
URL: https://github.com/Jurian/subgroup.discovery
BugReports: https://github.com/Jurian/subgroup.discovery/issues
Date: 2017-07-15
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-07-20 11:08:36 UTC; juria
Author: Jurian Baas [aut, cre, cph], Ad Feelders [ctb]
Maintainer: Jurian Baas <jurian@jurianbaas.nl>
Repository: CRAN
Date/Publication: 2017-07-20 12:31:59 UTC

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New package ASIP with initial version 0.3
Package: ASIP
Type: Package
Date: 2017-07-11
Title: Automated Satellite Image Processing
Version: 0.3
Author: M J Riyas [aut, cre], T H Syed [aut]
Maintainer: M J Riyas <riyasmjgeo@gmail.com>
Description: Perform complex satellite image processes automatically and efficiently. Package currently supports satellite images from most widely used Landsat 4,5,7 and 8 and ASTER L1T data. The primary uses of this package is given below. 1. Conversion of optical bands to top of atmosphere reflectance. 2. Conversion of thermal bands to corresponding temperature images. 3. Derive application oriented products directly from source satellite image bands. 4. Compute user defined equation and produce corresponding image product. 5. Other basic tools for satellite image processing. References. i. Chander and Markham (2003) <doi:10.1109/TGRS.2003.818464>. ii. Roy et.al, (2014) <doi:10.1016/j.rse.2014.02.001>. iii. Abrams (2000) <doi:10.1080/014311600210326>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.4.1)
Imports: raster (>= 2.5-8), utils, gdalUtils (>= 2.0.1.7), rgdal (>= 1.2-8)
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-20 11:54:10 UTC; xplorer
Repository: CRAN
Date/Publication: 2017-07-20 12:21:29 UTC

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Wed, 19 Jul 2017

New package OBRE with initial version 0.1-0
Package: OBRE
Title: Optimal B-Robust Estimator Tools
Date: 2017-06-13
Version: 0.1-0
Authors@R: c( person("Andrea", "Riboldi", email = "andreariboldi.ar@gmail.com", role = c("aut", "cre")), person("Ivan Luciano", "Danesi", email = "ivanluciano.danesi@unicredit.eu", role = c("aut")), person("Fabio", "Piacenza", email = "fabio.piacenza@unicredit.eu", role = c("aut")), person("Ruben", "Ciaponi", role = c("ctb")), person("Stephen", "Allen", role = c("ctb")), person("Novella", "Saccenti", role = c("ctb")), person("Annarita", "Filippi", role = c("ctb")))
Author: Andrea Riboldi [aut, cre], Ivan Luciano Danesi [aut], Fabio Piacenza [aut], Ruben Ciaponi [ctb], Stephen Allen [ctb], Novella Saccenti [ctb], Annarita Filippi [ctb]
Maintainer: Andrea Riboldi <andreariboldi.ar@gmail.com>
Description: An implementation for computing Optimal B-Robust Estimators (OBRE) of two parameters distributions. The procedure is composed by some equations that are evaluated alternatively until the solution is reached. Some tools for analyzing the estimates are included. The most relevant is OBRE covariance matrix computation using a closed formula.
Depends: R (>= 2.11.1), pracma(>= 1.7.3)
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-07-19 18:22:20 UTC; Admin
Repository: CRAN
Date/Publication: 2017-07-19 21:55:05 UTC

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New package ivregEX with initial version 1.0
Package: ivregEX
Type: Package
Title: Create Independent Evidence in IV Analyses and Do Sensitivity Analysis in Regression and IV Analysis
Version: 1.0
Date: 2017-07-18
Author: Bikram Karmakar
Maintainer: Bikram Karmakar <bikramk@wharton.upenn.edu>
Imports: AER,Formula
Depends: lmtest,sandwich
Description: Allows you to create an evidence factor (EX analysis) in an instrumental variables regression model. Additionally, performs Sensitivity analysis for OLS analysis, 2SLS analysis and EX analysis with interpretable plotting and printing features.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-07-19 19:00:10 UTC; bikra
Repository: CRAN
Date/Publication: 2017-07-19 21:46:49 UTC

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New package BiDAG with initial version 1.0.0
Package: BiDAG
Type: Package
Title: Bayesian Inference for Directed Acyclic Graphs (BiDAG): Software for the Efficient Inference and Sampling of Bayesian Networks
Version: 1.0.0
Date: 2017-07-17
Author: Polina Minkina [aut, cre], Jack Kuipers [aut]
Maintainer: Polina Minkina <polina.minkina@bsse.ethz.ch>
Description: Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data.
Acknowledgments: We would like to thank Giusi Moffa for discussion and comments on the package and its manual.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.7), pcalg, methods, stats, utils
LinkingTo: Rcpp
RoxygenNote: 6.0.1
LazyData: TRUE
NeedsCompilation: yes
Packaged: 2017-07-19 20:02:39 UTC; me664
Repository: CRAN
Date/Publication: 2017-07-19 21:44:55 UTC

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New package atus with initial version 0.1
Package: atus
Type: Package
Title: American Time Use Survey Data
Version: 0.1
Date: 2017-07-19
Author: Paul Gramieri and Xiaofei Wang
Maintainer: Xiaofei Wang <xiaofei.wang@yale.edu>
Description: Abridged data from the American Time Use Survey (ATUS) for years 2003-2016. The ATUS is an annual survey conducted on a sample of individuals across the United States studying how individuals spent their time over the course of a day. Individual respondents were interviewed about what activities they did, during what times (rounded to 15 minute increments), at what locations, and in the presence of which individuals. The activities are subsequently encoded based on 3 separate tier codes for classification. This package includes data from the multi-year ATUS Activities, ATUS-CPS, and ATUS Respondents files were included. Columns were selected based on completeness of data as well as presence on the Frequently Used Variables list provided by the ATUS website. All activity codes (other than code '50' for 'Unable to Code') were included. Permission was obtained from the Bureau of Labor Statistics for inclusion in this package. The full data can be obtained from <http://www.bls.gov/tus/>.
License: GPL (>= 2)
LazyData: TRUE
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-07-19 17:58:07 UTC; eastie
Depends: R (>= 2.10)
Repository: CRAN
Date/Publication: 2017-07-19 21:43:33 UTC

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New package adiv with initial version 1.0
Package: adiv
Type: Package
Title: Analysis of Diversity
Version: 1.0
Date: 2017-07-19
Author: Sandrine Pavoine
Maintainer: Sandrine Pavoine <sandrine.pavoine@mnhn.fr>
Description: Includes functions, data sets and examples for the calculation of various indices of biodiversity including species, functional and phylogenetic diversity. Part of the indices are expressed in terms of equivalent numbers of species. It also provides ways to partition biodiversity across spatial or temporal scales (alpha, beta, gamma diversities). In addition to the quantification of biodiversity, ordination approaches are available which rely on diversity indices and allow the detailed identification of species, functional or phylogenetic differences between communities.
Depends: R (>= 3.4.1), ade4, adephylo, ape, cluster, methods, phylobase
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-07-19 18:48:23 UTC; Sandrine
Repository: CRAN
Date/Publication: 2017-07-19 21:38:24 UTC

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New package harmonicmeanp with initial version 1.0
Package: harmonicmeanp
Type: Package
Title: Harmonic Mean p-Values and Model Averaging by Mean Maximum Likelihood
Version: 1.0
Date: 2017-07-19
Author: Daniel J. Wilson
Maintainer: Daniel Wilson <hmp.R.package@gmail.com>
Depends: FMStable
Description: The harmonic mean p-value (HMP) test simply and instantly combines p-values and corrects for multiple testing while controlling the family-wise error rate in a way that is more powerful than common alternatives including Bonferroni and Simes procedures, more stringent than controlling the false discovery rate, and is robust to positive correlations between tests and unequal weights. It is a multi-level test in the sense that a superset of one or more significant tests is almost certain to be significant and conversely when the superset is non-significant, the constituent tests are almost certain to be non-significant. It is based on MAMML (model averaging by mean maximum likelihood), a frequentist analogue to Bayesian model averaging, and is theoretically grounded in generalized central limit theorem.
License: Unlimited
NeedsCompilation: no
Packaged: 2017-07-19 15:59:53 UTC; wilson
Repository: CRAN
Date/Publication: 2017-07-19 16:45:06 UTC

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New package dicecrawler with initial version 0.1.0
Package: dicecrawler
Type: Package
Title: Downloads Job Descriptions from Dice.com
Version: 0.1.0
Authors@R: person("Vlad", "Krotov", email = "vkrotov@murraystate.edu", role = c("aut", "cre", "cph"))
Description: A Web crawler for <http://www.dice.com>. The function getjobs() automatically crawls Dice.com and downloads job descriptions based on the supplied parameters. The job data is returned via a data frame. JobSearch API supplied by Dice.com is used for retrieving job data.
Depends: jsonlite, rvest, curl, xml2
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-19 16:06:15 UTC; vkrotov
Author: Vlad Krotov [aut, cre, cph]
Maintainer: Vlad Krotov <vkrotov@murraystate.edu>
Repository: CRAN
Date/Publication: 2017-07-19 16:55:26 UTC

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New package subscreen with initial version 0.2.2
Package: subscreen
Type: Package
Title: Systematic Screening of Study Data for Subgroup Effects
Version: 0.2.2
Author: Hermann Kulmann, Bodo Kirsch, Susanne Lippert, Thomas Schmelter
Maintainer: Bodo Kirsch <bodo.kirsch@bayer.com>
Description: Systematically screens study data for subgroup effects and visualizes these.
License: GPL
LazyData: TRUE
Imports: utils, plyr, data.table, grDevices, graphics
Suggests: parallel, shiny, survival, DT
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-19 07:51:25 UTC; sgfpj
Repository: CRAN
Date/Publication: 2017-07-19 14:04:46 UTC

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New package scifigure with initial version 0.1.1
Package: scifigure
Title: Visualize Reproducibility and Replicability in a Comparison of Scientific Studies
Version: 0.1.1
Authors@R: person("Prasad", "Patil", email = "prpatil42@gmail.com", role = c("aut", "cre"))
Description: Users may specify what fundamental qualities of a new study have or have not changed in an attempt to reproduce or replicate an original study. A comparison of the differences is visualized. Visualization approach follows Patil, Peng, and Leek (2016) <doi:10.1101/066803>.
Depends: R (>= 3.3.1)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: grid
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-18 22:38:26 UTC; Prasad
Author: Prasad Patil [aut, cre]
Maintainer: Prasad Patil <prpatil42@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-19 10:31:55 UTC

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New package BayesianGLasso with initial version 0.2.0
Package: BayesianGLasso
Title: Bayesian Graphical Lasso
Version: 0.2.0
Authors@R: c(person("Patrick","Trainor",email="patrick.trainor@louisville.edu", role = c("aut", "cre")),person("Hao","Wang",email="haowang@msu.edu",role="aut"))
Description: Implements a data-augmented block Gibbs sampler for simulating the posterior distribution of concentration matrices for specifying the topology and parameterization of a Gaussian Graphical Model (GGM). This sampler was originally proposed in Wang (2012) <doi:10.1214/12-BA729>.
Depends: R (>= 3.0.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: statmod, MASS
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-18 22:45:03 UTC; patrick
Author: Patrick Trainor [aut, cre], Hao Wang [aut]
Maintainer: Patrick Trainor <patrick.trainor@louisville.edu>
Repository: CRAN
Date/Publication: 2017-07-19 10:52:36 UTC

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Tue, 18 Jul 2017

New package social with initial version 1.0
Package: social
Type: Package
Title: Social Autocorrelation
Version: 1.0
Date: 2017-07-16
Author: Tom Pike
Maintainer: Tom Pike <tpike@lincoln.ac.uk>
Description: A set of functions to quantify and visualise social autocorrelation.
License: GPL (>= 2)
Imports: Rcpp (>= 0.12.9)
LinkingTo: Rcpp
Depends: stats, graphics
RoxygenNote: 6.0.1
LazyData: true
NeedsCompilation: yes
Packaged: 2017-07-18 20:21:09 UTC; Tom Pike
Repository: CRAN
Date/Publication: 2017-07-18 21:43:17 UTC

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New package sgmcmc with initial version 0.1.0
Package: sgmcmc
Type: Package
Title: Stochastic Gradient Markov Chain Monte Carlo
Version: 0.1.0
Authors@R: c( person("Jack", "Baker", email = "j.baker1@lancaster.ac.uk", role = c("aut", "cre", "cph")), person( "Christopher", "Nemeth", role = c("aut", "cph") ), person( "Paul", "Fearnhead", role = c( "aut", "cph" ) ), person( "Emily B.", "Fox", role = c("aut", "cph") ), person( "STOR-i", role = c( "cph" ) ))
Description: Provides functions that performs popular stochastic gradient Markov chain Monte Carlo (SGMCMC) methods on user specified models. The required gradients are automatically calculated using 'TensorFlow' <https://www.tensorflow.org/>, an efficient library for numerical computation. This means only the log likelihood and log prior functions need to be specified. The methods implemented include stochastic gradient Langevin dynamics (SGLD), stochastic gradient Hamiltonian Monte Carlo (SGHMC), stochastic gradient Nose-Hoover thermostat (SGNHT) and their respective control variate versions for increased efficiency.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.0), tensorflow
SystemRequirements: TensorFlow (https://www.tensorflow.org/)
Suggests: testthat, MASS, knitr, ggplot2, rmarkdown
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
URL: https://github.com/STOR-i/sgmcmc
BugReports: https://github.com/STOR-i/sgmcmc/issues
NeedsCompilation: no
Packaged: 2017-07-18 19:07:06 UTC; jbaker
Author: Jack Baker [aut, cre, cph], Christopher Nemeth [aut, cph], Paul Fearnhead [aut, cph], Emily B. Fox [aut, cph], STOR-i [cph]
Maintainer: Jack Baker <j.baker1@lancaster.ac.uk>
Repository: CRAN
Date/Publication: 2017-07-18 21:55:24 UTC

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New package PLmixed with initial version 0.1.0
Package: PLmixed
Title: Estimate (Generalized) Linear Mixed Models with Factor Structures
Version: 0.1.0
Authors@R: c(person("Minjeong", "Jeon", role = "aut"), person("Nicholas", "Rockwood", email = "rockwood.19@osu.edu", role = c("aut", "cre")))
Description: Utilizes the 'lme4' package and the optim() function from 'stats' to estimate (generalized) linear mixed models (GLMM) with factor structures using a profile likelihood approach, as outlined in Jeon and Rabe-Hesketh (2012) <doi:10.3102/1076998611417628>. Factor analysis and item response models can be extended to allow for an arbitrary number of nested and crossed random effects, making it useful for multilevel and cross-classified models.
Depends: R (>= 3.2.2)
Imports: lme4, Matrix (>= 1.1.1), numDeriv, stats
Encoding: UTF-8
License: GPL (>= 2)
LazyData: true
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-07-18 19:42:03 UTC; nickrockwood
Author: Minjeong Jeon [aut], Nicholas Rockwood [aut, cre]
Maintainer: Nicholas Rockwood <rockwood.19@osu.edu>
Repository: CRAN
Date/Publication: 2017-07-18 21:49:57 UTC

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New package denoiSeq with initial version 0.1.0
Package: denoiSeq
Type: Package
Title: Differential Expression Analysis Using a Bottom-Up Model
Version: 0.1.0
Authors@R: c(person("Gershom", "Buri", email = "buri@aims.edu.gh", role = c("aut","cre")),person("Wilfred", "Ndifon", email = "ndifon@gmail.com", role = "aut"))
Description: Given count data from two conditions, it determines which transcripts are differentially expressed across the two conditions using Bayesian inference of the parameters of a bottom-up model for PCR amplification. This model is developed in Ndifon Wilfred, Hilah Gal, Eric Shifrut, Rina Aharoni, Nissan Yissachar, Nir Waysbort, Shlomit Reich Zeliger, Ruth Arnon, and Nir Friedman (2012), <http://www.pnas.org/content/109/39/15865.full>, and results in a distribution for the counts that is a superposition of the binomial and negative binomial distribution.
License: GPL-2
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Imports: methods, stats, utils
Suggests: devtools, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-18 19:00:16 UTC; buri
Author: Gershom Buri [aut, cre], Wilfred Ndifon [aut]
Maintainer: Gershom Buri <buri@aims.edu.gh>
Repository: CRAN
Date/Publication: 2017-07-18 19:15:45 UTC

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New package uptasticsearch with initial version 0.0.2
Package: uptasticsearch
Type: Package
Title: Get Data Frame Representations of 'Elasticsearch' Results
Version: 0.0.2
Authors@R: c( person("James", "Lamb", email = "james.lamb@uptake.com", role = c("aut", "cre")), person("Nick", "Paras", email = "nick.paras@uptake.com", role = c("aut")), person("Austin", "Dickey", email = "austin.dickey@uptake.com", role = c("aut")), person("Uptake Technologies Inc.", role = c("cph")))
Maintainer: James Lamb <james.lamb@uptake.com>
Description: 'Elasticsearch' is an open-source, distributed, document-based datastore (<https://www.elastic.co/products/elasticsearch>). It provides an 'HTTP' 'API' for querying the database and extracting datasets, but that 'API' was not designed for common data science workflows like pulling large batches of records and normalizing those documents into a data frame that can be used as a training dataset for statistical models. 'uptasticsearch' provides an interface for 'Elasticsearch' that is explicitly designed to make these data science workflows easy and fun.
Depends: R (>= 3.3.0)
Imports: data.table, futile.logger, httr, jsonlite, purrr, stringr, uuid
Suggests: knitr, testthat, rmarkdown
License: BSD_3_clause + file LICENSE
URL: https://github.com/UptakeOpenSource/uptasticsearch
BugReports: https://github.com/UptakeOpenSource/uptasticsearch/issues
LazyData: TRUE
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-18 13:53:36 UTC; jlamb
Author: James Lamb [aut, cre], Nick Paras [aut], Austin Dickey [aut], Uptake Technologies Inc. [cph]
Repository: CRAN
Date/Publication: 2017-07-18 14:26:54 UTC

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New package coda.base with initial version 0.1.3
Package: coda.base
Type: Package
Title: A Basic Set of Functions for Compositional Data Analysis
Version: 0.1.3
Date: 2017-07-17
Authors@R: c(person("Marc", "Comas-Cufí", role = c("aut", "cre"), email = "mcomas@imae.udg.edu"))
Description: A minimum set of functions to perform compositional data analysis using the log-ratio approach introduced by John Aitchison in 1982. Main functions have been implemented in c++ for better performance.
Depends: R (>= 3.0.2)
Imports: Rcpp (>= 0.12.12), MASS
LinkingTo: Rcpp, RcppArmadillo
License: GPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: yes
RoxygenNote: 6.0.1
Packaged: 2017-07-18 12:31:47 UTC; marc
Author: Marc Comas-Cufí [aut, cre]
Maintainer: Marc Comas-Cufí <mcomas@imae.udg.edu>
Repository: CRAN
Date/Publication: 2017-07-18 13:07:13 UTC

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New package diffpriv with initial version 0.4.2
Package: diffpriv
Type: Package
Title: Easy Differential Privacy
Version: 0.4.2
Date: 2017-07-16
Authors@R: c( person("Benjamin", "Rubinstein", email = "brubinstein@unimelb.edu.au", role = c("aut", "cre")), person("Francesco", "Aldà", email = "francesco.alda@gmail.com", role = "aut"))
Description: An implementation of major general-purpose mechanisms for privatizing statistics, models, and machine learners, within the framework of differential privacy of Dwork et al. (2006) <doi:10.1007/11681878_14>. Example mechanisms include the Laplace mechanism for releasing numeric aggregates, and the exponential mechanism for releasing set elements. A sensitivity sampler (Rubinstein & Alda, 2017) <arXiv:1706.02562> permits sampling target non-private function sensitivity; combined with the generic mechanisms, it permits turn-key privatization of arbitrary programs.
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.4.0)
Imports: gsl, methods, stats
URL: https://github.com/brubinstein/diffpriv, http://brubinstein.github.io/diffpriv
BugReports: https://github.com/brubinstein/diffpriv/issues
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Encoding: UTF-8
Suggests: randomNames, testthat, knitr, rmarkdown
Collate: 'utils.R' 'bernstein_polynomials.R' 'privacy_params.R' 'mechanisms.R' 'bernstein_mechanism.R' 'diffpriv.R' 'exponential_mechanism.R' 'numeric_mechanism.R' 'gaussian_mechanism.R' 'laplace_mechanism.R' 'sensitivity_sampler.R'
NeedsCompilation: no
Packaged: 2017-07-18 10:59:01 UTC; brubinstein
Author: Benjamin Rubinstein [aut, cre], Francesco Aldà [aut]
Maintainer: Benjamin Rubinstein <brubinstein@unimelb.edu.au>
Repository: CRAN
Date/Publication: 2017-07-18 11:42:21 UTC

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New package bsplinePsd with initial version 0.1.0
Package: bsplinePsd
Type: Package
Title: Bayesian Nonparametric Spectral Density Estimation Using B-Spline Priors
Version: 0.1.0
Date: 2017-07-16
Author: Matthew C. Edwards [aut, cre], Renate Meyer [aut], Nelson Christensen [aut]
Maintainer: Matthew C. Edwards <matt.edwards@auckland.ac.nz>
Description: Implementation of a Metropolis-within-Gibbs MCMC algorithm to flexibly estimate the spectral density of a stationary time series. The algorithm updates a nonparametric B-spline prior using the Whittle likelihood to produce pseudo-posterior samples and is based on the work presented by Edwards, Meyer, and Christensen (2017) <arXiv:1707.04878>.
License: GPL (>= 3)
Imports: Rcpp (>= 0.12.5), splines (>= 3.2.3)
LinkingTo: Rcpp
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-07-18 02:40:32 UTC; mattedwards
Repository: CRAN
Date/Publication: 2017-07-18 09:16:27 UTC

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New package mau with initial version 0.1.0
Package: mau
Type: Package
Title: Decision Models with Multi Attribute Utility Theory
Version: 0.1.0
Encoding: UTF-8
Date: 2017-07-17
Author: Felipe Aguirre, Julio Andrade, Pedro Guarderas, Daniel Lagos, Andres Lopez, Nelson Recalde, Edison Salazar.
Maintainer: Pedro Guarderas <pedro.felipe.guarderas@gmail.com>
Description: Build and test decision models based in Multi Attribute Utility Theory (MAUT). Automatic evaluation of utilities at any level of the decision tree, weight simulations for sensitivity analysis.
License: LGPL-3
URL: https://github.com/pedroguarderas/mau
Depends: R (>= 3.0)
Imports: data.table, gtools, stringr, igraph, RColorBrewer, ggplot2
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-07-18 01:35:42 UTC; aju
Repository: CRAN
Date/Publication: 2017-07-18 08:10:09 UTC

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Mon, 17 Jul 2017

New package sergeant with initial version 0.5.2
Package: sergeant
Title: Tools to Transform and Query Data with 'Apache' 'Drill'
Version: 0.5.2
Authors@R: c(person("Bob", "Rudis", email = "bob@rud.is", role = c("aut", "cre")), person("Edward", "Visel", email = "edward.visel@gmail.com", role = "ctb"))
Description: 'Apache Drill' is a low-latency distributed query engine designed to enable data exploration and 'analytics' on both relational and non-relational 'datastores', scaling to petabytes of data. Methods are provided that enable working with 'Apache' 'Drill' instances via the 'REST' 'API', 'JDBC' interface (optional), 'DBI' 'methods' and using 'dplyr'/'dbplyr' idioms.
Depends: R (>= 3.1.2), DBI (>= 0.7), dplyr (>= 0.7.0), dbplyr (>= 1.1.0)
URL: https://github.com/hrbrmstr/sergeant
BugReports: https://github.com/hrbrmstr/sergeant/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: httr (>= 1.2.1), jsonlite (>= 1.5.0), htmltools (>= 0.3.6), readr (>= 1.1.1), purrr (>= 0.2.2), scales (>= 0.4.1), utils, methods
Suggests: RJDBC (>= 0.2-5), rJava (>= 0.9-8), testthat (>= 1.0.2), covr (>= 3.0.0)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-17 16:37:01 UTC; bob
Author: Bob Rudis [aut, cre], Edward Visel [ctb]
Maintainer: Bob Rudis <bob@rud.is>
Repository: CRAN
Date/Publication: 2017-07-17 22:36:26 UTC

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New package multiApply with initial version 0.0.1
Package: multiApply
Title: Apply Functions to Multiple Multidimensional Arguments
Version: 0.0.1
Authors@R: c( person("BSC-CNS", role = c("aut", "cph")), person("Alasdair", "Hunter", , "alasdair.hunter@bsc.es", role = c("aut", "cre")), person("Nicolau", "Manubens", , "nicolau.manubens@bsc.es", role = "aut"))
Description: The base apply function and its variants, as well as the related functions in the 'plyr' package, typically apply user-defined functions to a single argument (or a list of vectorized arguments in the case of mapply). The 'multiApply' package extends this paradigm to functions taking a list of multiple unidimensional or multidimensional arguments (or combinations thereof) as input, which can have different numbers of dimensions as well as different dimension lengths.
Depends: R (>= 3.2.0)
Imports: abind, plyr, doParallel, future, foreach
License: LGPL-3
URL: https://earth.bsc.es/gitlab/ces/multiApply
BugReports: https://earth.bsc.es/gitlab/ces/multiApply/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 5.0.0
NeedsCompilation: no
Packaged: 2017-07-17 14:16:05 UTC; ahunter
Author: BSC-CNS [aut, cph], Alasdair Hunter [aut, cre], Nicolau Manubens [aut]
Maintainer: Alasdair Hunter <alasdair.hunter@bsc.es>
Repository: CRAN
Date/Publication: 2017-07-17 22:41:10 UTC

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New package LCox with initial version 0.1.0
Package: LCox
Type: Package
Title: A Tool for Selecting Genes Related to Survival Outcomes using Longitudinal Gene Expression Data
Version: 0.1.0
Author: Jiehuan Sun [aut, cre], Jose D. Herazo-Maya [aut], Jane-Ling Wang [aut], Naftali Kaminski [aut], and Hongyu Zhao [aut]
Maintainer: Jiehuan Sun <jiehuan.sun@yale.edu>
Description: Longitudinal genomics data and survival outcome are common in biomedical studies. It is of great interest to select genes related to the survival outcome. LCox is a computationally efficient tool for selecting genes related to the survival outcome using the longitudinal genomics data. LCox is powerful to detect different forms of dependence between the longitudinal biomarkers and the survival outcome.
License: GPL-2
LazyData: TRUE
Depends: R (>= 3.4.0), fdapace (>= 0.3.0), survival (>= 2.41-3)
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-17 16:07:52 UTC; JiehuanSun
Repository: CRAN
Date/Publication: 2017-07-17 17:10:39 UTC

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New package dataCompareR with initial version 0.1.0
Package: dataCompareR
Title: Compare Two Data Frames and Summarise the Difference
Version: 0.1.0
Authors@R: c(person("Rob", "Noble-Eddy", email = "opensource@capitalone.com", role = c("aut", "cre")), person("Sarah", "Johnston", role = c("aut")), person("Sarah", "Pollicott", role = c("aut")), person("Merlijn", "van Horssen", role = c("aut")), person("Lukas", "Drapal", role = c("ctb")), person("Nikolaos", "Perrakis", role = c("ctb")), person("Nikhil", "Thomas Joy", role = c("ctb")), person("Shahriar", "Asta", role = c("ctb")), person("Karandeep", "Lidher", role = c("ctb")), person("Dan", "Kellett", role = c("ctb")), person("Kevin", "Chisholm", role = c("ctb")), person("Laura", "Joy", role = c("ctb")), person("Fergus", "Wadsley", role = c("ctb")), person("Heather", "Hackett", role = c("ctb")), person("David", "Robinson", role = c("ctb")), person("Cheryl", "Renton", role = c("ctb")), person("Matt", "Triggs", role = c("ctb")), person("Krishan", "Bhasin", role = c("ctb")), person("Carola", "Deppe", role = c("ctb")) )
Description: Easy comparison of two tabular data objects in R. Specifically designed to show differences between two sets of data in a useful way that should make it easier to understand the differences, and if necessary, help you work out how to remedy them. Aims to offer a more useful output than all.equal() when your two data sets do not match, but isn't intended to replace all.equal() as a way to test for equality.
Depends: R (>= 3.2.3)
Imports: dplyr, knitr, stringi, markdown
License: Apache License 2.0 | file LICENSE
LazyData: true
RoxygenNote: 6.0.1
Suggests: testthat, data.table, tibble, bit64, rmarkdown, titanic
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-17 10:47:12 UTC; ODY153
Author: Rob Noble-Eddy [aut, cre], Sarah Johnston [aut], Sarah Pollicott [aut], Merlijn van Horssen [aut], Lukas Drapal [ctb], Nikolaos Perrakis [ctb], Nikhil Thomas Joy [ctb], Shahriar Asta [ctb], Karandeep Lidher [ctb], Dan Kellett [ctb], Kevin Chisholm [ctb], Laura Joy [ctb], Fergus Wadsley [ctb], Heather Hackett [ctb], David Robinson [ctb], Cheryl Renton [ctb], Matt Triggs [ctb], Krishan Bhasin [ctb], Carola Deppe [ctb]
Maintainer: Rob Noble-Eddy <opensource@capitalone.com>
Repository: CRAN
Date/Publication: 2017-07-17 17:16:22 UTC

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New package Census2016 with initial version 0.2.0
Package: Census2016
Type: Package
Title: Data from the Australian Census 2016
Version: 0.2.0
Date: 2017-07-16
Authors@R: c(person("Hugh", "Parsonage", role = c("aut", "cre"), email = "hugh.parsonage@gmail.com"), person("Nick", "Evershed", role = "dtc"), person(family = "Australian Bureau of Statistics", role = "cph"))
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>
Description: Contains selected variables from the time series profiles for statistical areas level 2 from the 2006, 2011, and 2016 censuses of population and housing, Australia. Also provides methods for viewing the questions asked for convenience during analysis.
Depends: R (>= 2.10)
Imports: data.table
LazyData: true
License: CC BY 4.0
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, ggplot2, ggrepel, magrittr, scales, testthat, png,
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-17 12:20:09 UTC; hughp
Author: Hugh Parsonage [aut, cre], Nick Evershed [dtc], Australian Bureau of Statistics [cph]
Repository: CRAN
Date/Publication: 2017-07-17 17:47:09 UTC

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New package ercv with initial version 1.0.0
Package: ercv
Type: Package
Title: Fitting Tails by the Empirical Residual Coefficient of Variation
Version: 1.0.0
Date: 2017-07-17
Encoding: UTF-8
Author: Joan del Castillo, David Moriña Soler and Isabel Serra
Maintainer: Isabel Serra <iserra@crm.cat>
Description: Provides a methodology simple and trustworthy for the analysis of extreme values and multiple threshold tests for a generalized Pareto distribution, together with an automatic threshold selection algorithm. See del Castillo, J, Daoudi, J and Lockhart, R (2014) <doi:10.1111/sjos.12037>.
Depends: R (>= 2.15.0)
Suggests: poweRlaw, evir
Repository: CRAN
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-07-17 13:06:44 UTC; 47642555X
Date/Publication: 2017-07-17 15:08:01 UTC

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New package constants with initial version 0.0.1
Package: constants
Type: Package
Title: Reference on Constants, Units and Uncertainty
Version: 0.0.1
Authors@R: c( person("Iñaki", "Ucar", email="i.ucar86@gmail.com", role=c("aut", "cph", "cre")))
Description: CODATA internationally recommended values of the fundamental physical constants, provided as symbols for direct use within the R language. Optionally, the values with errors and/or the values with units are also provided if the 'errors' and/or the 'units' packages are installed. The Committee on Data for Science and Technology (CODATA) is an interdisciplinary committee of the International Council for Science which periodically provides the internationally accepted set of values of the fundamental physical constants. This package contains the "2014 CODATA" version, published on 25 June 2015: Mohr, P. J., Newell, D. B. and Taylor, B. N. (2016) <DOI:10.1103/RevModPhys.88.035009>, <DOI:10.1063/1.4954402>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
URL: https://github.com/Enchufa2/constants
BugReports: https://github.com/Enchufa2/constants/issues
Depends: R (>= 3.0.0)
Suggests: errors, units, testthat
ByteCompile: yes
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-17 10:43:37 UTC; inaki
Author: Iñaki Ucar [aut, cph, cre]
Maintainer: Iñaki Ucar <i.ucar86@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-17 10:53:00 UTC

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New package OHPL with initial version 1.2
Package: OHPL
Type: Package
Title: Ordered Homogeneity Pursuit Lasso for Group Variable Selection
Version: 1.2
Authors@R: c( person("You-Wu", "Lin", email = "lyw015813@126.com", role = c("aut")), person("Nan", "Xiao", email = "me@nanx.me", role = "cre"))
Maintainer: Nan Xiao <me@nanx.me>
Description: Ordered homogeneity pursuit lasso (OHPL) algorithm for group variable selection proposed in Lin et al. (2017) <DOI:10.1016/j.chemolab.2017.07.004>. The OHPL method takes the homogeneity structure in high-dimensional data into account and enjoys the grouping effect to select groups of important variables automatically. This feature makes it particularly useful for high-dimensional datasets with strongly correlated variables, such as spectroscopic data.
License: GPL-3 | file LICENSE
URL: https://ohpl.io, https://github.com/road2stat/OHPL
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/road2stat/OHPL/issues
Depends: R (>= 3.0.2)
Imports: glmnet, pls, mvtnorm
RoxygenNote: 5.0.1
NeedsCompilation: no
Packaged: 2017-07-16 22:57:45 UTC; nanx
Author: You-Wu Lin [aut], Nan Xiao [cre]
Repository: CRAN
Date/Publication: 2017-07-17 09:44:53 UTC

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New package cnbdistr with initial version 1.0.1
Package: cnbdistr
Type: Package
Title: Conditional Negative Binomial Distribution
Version: 1.0.1
Date: 2017-07-04
Author: Xiaotian Zhu
Maintainer: Xiaotian Zhu <xiaotian.zhu.psualum@gmail.com>
Description: Provided R functions for working with the Conditional Negative Binomial distribution.
License: GPL-3
Depends: R (>= 3.2.2)
Imports: hypergeo (>= 1.2-13), stats (>= 3.3.2)
Suggests: rmutil (>= 1.1.0), testthat (>= 1.0.2), knitr (>= 1.16), rmarkdown (>= 1.6)
NeedsCompilation: no
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
VignetteBuilder: knitr
Packaged: 2017-07-17 02:43:49 UTC; SAINT
Repository: CRAN
Date/Publication: 2017-07-17 09:50:23 UTC

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New package APML0 with initial version 0.2
Package: APML0
Type: Package
Title: Augmented and Penalized Minimization Method L0
Version: 0.2
Author: Xiang Li, Shanghong Xie, Donglin Zeng and Yuanjia Wang
Maintainer: Xiang Li <xli256@its.jnj.com>
Description: Fit linear and Cox models regularized with L0, lasso (L1), elastic-net (L1 and L2), or net (L1 and Laplacian) penalty, and their adaptive forms, such as adaptive lasso / elastic-net and net adjusting for signs of linked coefficients. It solves L0 penalty problem by simultaneously selecting regularization parameters and the number of non-zero coefficients. This augmented and penalized minimization method provides an approximation solution to the L0 penalty problem, but runs as fast as L1 regularization problem. The package uses one-step coordinate descent algorithm and runs extremely fast by taking into account the sparsity structure of coefficients. It could deal with very high dimensional data and has superior selection performance.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: Rcpp (>= 0.12.11)
LinkingTo: Rcpp, RcppEigen
Depends: Matrix (>= 1.2-10)
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-07-17 01:50:33 UTC; spiri
Repository: CRAN
Date/Publication: 2017-07-17 09:47:52 UTC

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Sun, 16 Jul 2017

New package taxa with initial version 0.1.0
Package: taxa
Type: Package
Title: Taxonomic Classes
Description: Provides taxonomic classes for groupings of taxonomic names without data, and those with data. Methods provided are "taxonomically aware", in that they know about ordering of ranks, and methods that filter based on taxonomy also filter associated data.
Version: 0.1.0
Authors@R: c( person("Scott", "Chamberlain", role = c("aut", "cre"), email = "myrmecocystus+r@gmail.com"), person("Zachary", "Foster", role = "aut", email = "zacharyfoster1989@gmail.com") )
Depends: R (>= 3.0.2)
VignetteBuilder: knitr
LazyLoad: yes
LazyData: yes
License: MIT + file LICENSE
URL: https://github.com/ropensci/taxa
BugReports: https://github.com/ropensci/taxa/issues
Imports: R6, jsonlite, dplyr, lazyeval, magrittr, tibble, knitr, rlang, stringr
Suggests: roxygen2 (>= 6.0.1), testthat, rmarkdown (>= 0.9.6), taxize
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-16 21:36:34 UTC; sacmac
Author: Scott Chamberlain [aut, cre], Zachary Foster [aut]
Maintainer: Scott Chamberlain <myrmecocystus+r@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-16 21:51:40 UTC

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New package rPraat with initial version 1.0.8
Package: rPraat
Type: Package
Title: Interface to Praat
Version: 1.0.8
Encoding: UTF-8
Authors@R: person("Tomas", "Boril", email = "borilt@gmail.com", role = c("aut", "cre"))
Maintainer: Tomas Boril <borilt@gmail.com>
Description: Read, write and manipulate 'Praat' <http://www.fon.hum.uva.nl/praat/> TextGrid <http://www.fon.hum.uva.nl/praat/manual/TextGrid.html>, PitchTier <http://www.fon.hum.uva.nl/praat/manual/PitchTier.html> and Pitch <http://www.fon.hum.uva.nl/praat/manual/Pitch.html> files.
URL: https://github.com/bbTomas/rPraat/
BugReports: https://github.com/bbTomas/rPraat/issues
License: MIT + file LICENSE
LazyData: TRUE
Depends: R (>= 3.4.1)
Imports: graphics (>= 3.4.1), dplyr (>= 0.7.1), stringr (>= 1.2.0), readr(>= 1.1.1), dygraphs (>= 1.1.1.4),
RoxygenNote: 6.0.1
Suggests: testthat
NeedsCompilation: no
Packaged: 2017-07-16 17:32:58 UTC; tomas
Author: Tomas Boril [aut, cre]
Repository: CRAN
Date/Publication: 2017-07-16 21:08:39 UTC

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New package senstrat with initial version 1.0.3
Package: senstrat
Type: Package
Title: Sensitivity Analysis for Stratified Observational Studies
Version: 1.0.3
Author: Paul R. Rosenbaum
Maintainer: Paul R. Rosenbaum <rosenbaum@wharton.upenn.edu>
Description: Sensitivity analysis in unmatched observational studies, with or without strata. The main functions are sen2sample() and senstrat(). See Rosenbaum, P. R. and Krieger, A. M. (1990), JASA, 85, 493-498, <doi:10.1080/01621459.1990.10476226> and Gastwirth, Krieger and Rosenbaum (2000), JRSS-B, 62, 545–555 <doi:10.1111/1467-9868.00249> .
License: GPL-2
Imports: stats, BiasedUrn, MASS
Suggests: sensitivitymw
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2017-07-16 19:12:47 UTC; Rosenbaum
Repository: CRAN
Date/Publication: 2017-07-16 21:01:17 UTC

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New package llogistic with initial version 1.0.0
Package: llogistic
Title: The L-Logistic Distribution
Version: 1.0.0
Authors@R: c(person("Rosineide", "Fernando da Paz", email = "rfpaz2@gmail.com", role = c("aut", "cre")),person("Jorge Luís", "Bazán", role = "ctb"))
Description: Density, distribution function, quantile function and random generation for the L-Logistic distribution with parameters m and b. The parameter m is the median of the distribution.
Imports: stats
Depends: R (>= 3.3.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-16 14:12:12 UTC; rosid
Author: Rosineide Fernando da Paz [aut, cre], Jorge Luís Bazán [ctb]
Maintainer: Rosineide Fernando da Paz <rfpaz2@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-16 20:32:28 UTC

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New package gh with initial version 1.0.1
Package: gh
Title: 'GitHub' 'API'
Version: 1.0.1
Authors@R: c(person("Gábor", "Csárdi",, "csardi.gabor@gmail.com", c("cre", "ctb")), person("Jennifer", "Bryan", role = "aut"), person("Hadley", "Wickham", role = "aut"))
Description: Minimal client to access the 'GitHub' 'API'.
License: MIT + file LICENSE
LazyData: true
URL: https://github.com/r-lib/gh#readme
BugReports: https://github.com/r-lib/gh/issues
Suggests: covr, pingr, testthat
Imports: ini, jsonlite, httr
RoxygenNote: 6.0.1.9000
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2017-07-16 16:36:29 UTC; gaborcsardi
Author: Gábor Csárdi [cre, ctb], Jennifer Bryan [aut], Hadley Wickham [aut]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-16 20:28:25 UTC

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New package spNNGP with initial version 0.1.0
Package: spNNGP
Title: Spatial Regression Models using Nearest Neighbor Gaussian Processes
Version: 0.1.0
Date: 2017-07-14
Authors@R: c(person("Andrew", "Finley", role=c("aut", "cre"), email="finleya@msu.edu"), person("Abhirup", "Datta", role="aut", email="abhidatta@jhu.edu"), person("Sudipto", "Banerjee", role="aut", email="sudipto@ucla.edu"), person("Alexander", "Mckim", role="ctb", email="amckim@g.clemson.edu"))
Maintainer: Andrew Finley <finleya@msu.edu>
Author: Andrew Finley [aut, cre], Abhirup Datta [aut], Sudipto Banerjee [aut], Alexander Mckim [ctb]
Depends: R (>= 2.10), coda, Formula, RANN
Description: Fits Gaussian univariate Bayesian spatial regression models using Nearest Neighbor Gaussian Processes (NNGP) detailed in Datta, A., S. Banerjee, A.O. Finley, and A.E. Gelfand (2016) <doi:10.1080/01621459.2015.1044091> and Finley, A.O., A. Datta, B.C. Cook, D.C. Morton, H.E. Andersen, and S. Banerjee (2017) <arXiv:1702.00434v2>.
License: GPL (>= 2)
Encoding: UTF-8
URL: http://blue.for.msu.edu/software.html
Repository: CRAN
NeedsCompilation: yes
Packaged: 2017-07-16 15:32:45 UTC; andy
Date/Publication: 2017-07-16 15:50:34 UTC

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Sat, 15 Jul 2017

New package vennLasso with initial version 0.1
Package: vennLasso
Type: Package
Title: Variable Selection for Heterogeneous Populations
Version: 0.1
Date: 2017-07-05
Authors@R: c( person("Jared", "Huling", , "jaredhuling@gmail.com", c("aut", "cre")), person("Muxuan", "Liang", , , c("ctb")), person("Yixuan", "Qiu", , , c("cph")) )
Description: Provides variable selection and estimation routines for models stratified based on binary factors.
URL: https://github.com/jaredhuling/vennLasso
BugReports: https://github.com/jaredhuling/vennLasso/issues
License: GPL (>= 2)
LazyData: TRUE
Depends: R (>= 3.2.0)
Imports: Rcpp (>= 0.11.0), foreach, survival, MASS, Matrix, VennDiagram, visNetwork, igraph, methods
LinkingTo: Rcpp, RcppEigen, RcppNumerical
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2017-07-15 15:16:28 UTC; Jared
Author: Jared Huling [aut, cre], Muxuan Liang [ctb], Yixuan Qiu [cph]
Maintainer: Jared Huling <jaredhuling@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-15 21:06:36 UTC

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New package tetraclasse with initial version 0.1.21
Package: tetraclasse
Type: Package
Title: Satisfaction Analysis using Tetraclasse Model and Llosa Matrix
Version: 0.1.21
Author: vincent guyader
Maintainer: vincent guyader <vincent@thinkr.fr>
Description: The satisfaction Analysis using the tetraclasse model from Sylvie Llosa. Llosa (1997) <http://www.jstor.org/stable/40592578>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ggplot2, reshape2, tidyr, FactoMineR, magrittr, tibble, ggrepel, dplyr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-15 13:46:16 UTC; vincent
Repository: CRAN
Date/Publication: 2017-07-15 21:14:59 UTC

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New package aiRthermo with initial version 1.0
Package: aiRthermo
Type: Package
Title: Atmospheric Thermodynamics and Visualization
Version: 1.0
Date: 2017-07-11
Author: Jon Sáenz, Santos J. González-Rojí, Sheila Carreno-Madinabeitia and Gabriel Ibarra-Berastegi
Maintainer: Santos J. González-Rojí <santosjose.gonzalez@ehu.eus>
Description: Deals with many computations related to the thermodynamics of atmospheric processes. It includes many functions designed to consider the density of air with varying degrees of water vapour in it, saturation pressures and mixing ratios, conversion of moisture indices, computation of atmospheric states of parcels subject to dry or pseudoadiabatic vertical evolutions and atmospheric instability indices that are routinely used for operational weather forecasts or meteorological diagnostics.
License: GPL-3
Encoding: UTF-8
Repository: CRAN
NeedsCompilation: yes
Packaged: 2017-07-15 12:17:49 UTC; Santitxu
Date/Publication: 2017-07-15 21:03:26 UTC

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New package DrImpute with initial version 1.0
Package: DrImpute
Version: 1.0
Date: 2017-7-15
Title: Imputing Dropout Events in Single-Cell RNA-Sequencing Data
Description: R codes for imputing dropout events. Many statistical methods in cell type identification, visualization and lineage reconstruction do not account for dropout events ('PCAreduce', 'SC3', 'PCA', 't-SNE', 'Monocle', 'TSCAN', etc). 'DrImpute' can improve the performance of such software by imputing dropout events.
Author: Il-Youp Kwak with contributions from Wuming Gong
Maintainer: Il-Youp Kwak <ilyoup.kwak@gmail.com>
Depends: R (>= 3.1.0)
Imports: Rcpp
Suggests: knitr, rmarkdown, devtools, roxygen2, irlba
License: GPL-3
VignetteBuilder: knitr
URL: https://github.com/ikwak2/DrImpute
LinkingTo: Rcpp, RcppArmadillo
RoxygenNote: 6.0.1
NeedsCompilation: yes
Packaged: 2017-07-15 12:47:22 UTC; ikwak
Repository: CRAN
Date/Publication: 2017-07-15 21:00:01 UTC

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New package CINNA with initial version 1.0.0
Package: CINNA
Type: Package
Title: Deciphering Central Informative Nodes in Network Analysis
Version: 1.0.0
Date: 2017-07-04
Author: Minoo Ashtiani[aut], Mohieddin Jafari[aut,cre]
Maintainer: Minoo Ashtiani <m_ashtiani@pasteur.ac.ir>
Description: Functions for computing, comparing and demonstrating top informative centrality measures within a network.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Imports: igraph, network, sna, centiserve, FactoMineR, factoextra, GGally, pheatmap, corrplot, dendextend, circlize, viridis, ggplot2, Rtsne, qdapTools, plyr
NeedsCompilation: no
Packaged: 2017-07-15 14:49:16 UTC; MINoOo
Repository: CRAN
Date/Publication: 2017-07-15 21:00:03 UTC

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New package randomForestExplainer with initial version 0.9
Package: randomForestExplainer
Title: Explaining and Visualizing Random Forests in Terms of Variable Importance
Version: 0.9
Authors@R: c( person("Aleksandra", "Paluszynska", email = "ola.paluszynska@gmail.com", role = c("aut", "cre")), person("Przemyslaw", "Biecek", email = "przemyslaw.biecek@gmail.com", role = c("aut","ths")) )
Description: A set of tools to help explain which variables are most important in a random forests. Various variable importance measures are calculated and visualized in different settings in order to get an idea on how their importance changes depending on our criteria (Hemant Ishwaran and Udaya B. Kogalur and Eiran Z. Gorodeski and Andy J. Minn and Michael S. Lauer (2010) <doi:10.1198/jasa.2009.tm08622>, Leo Breiman (2001) <doi:10.1023/A:1010933404324>).
Depends: R (>= 3.0)
License: GPL
Encoding: UTF-8
LazyData: true
Imports: data.table (>= 1.10.4), dplyr (>= 0.7.1), dtplyr (>= 0.0.2), DT (>= 0.2), GGally (>= 1.3.0), ggplot2 (>= 2.2.1), ggrepel (>= 0.6.5), MASS (>= 7.3.47), randomForest (>= 4.6.12), reshape2 (>= 1.4.2), rmarkdown (>= 1.5)
Suggests: knitr
VignetteBuilder: knitr
RoxygenNote: 6.0.1
URL: https://github.com/MI2DataLab/randomForestExplainer
NeedsCompilation: no
Packaged: 2017-07-15 17:04:58 UTC; Ola
Author: Aleksandra Paluszynska [aut, cre], Przemyslaw Biecek [aut, ths]
Maintainer: Aleksandra Paluszynska <ola.paluszynska@gmail.com>
Repository: CRAN
Date/Publication: 2017-07-15 18:42:37 UTC

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New package parlitools with initial version 0.1.0
Package: parlitools
Type: Package
Title: Tools for Analysing UK Politics
Date: 2017-07-15
Version: 0.1.0
Authors@R: person("Evan Odell", email="evanodell91@gmail.com", role=c("aut", "cre"))
Author: Evan Odell [aut, cre]
Maintainer: Evan Odell <evanodell91@gmail.com>
Description: Provides various tools for analysing UK political data, including creating political cartograms and retrieving data.
URL: http://docs.evanodell.com/parlitools
BugReports: https://github.com/EvanOdell/parlitools/issues
License: MIT + file LICENSE
LazyData: TRUE
Depends: R(>= 2.10.0)
Imports: mnis, hansard, dplyr, utils, tibble, httr, jsonlite, stringi, sf
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat, covr, rgdal, devtools, leaflet, htmltools, cartogram, htmlwidgets
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2017-07-15 10:44:18 UTC; evanodell
Repository: CRAN
Date/Publication: 2017-07-15 12:20:09 UTC

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New package ambhasGW with initial version 0.0.1
Package: ambhasGW
Title: Ground Water Modelling
Version: 0.0.1
Authors@R: c( person("Sat", "Tomer", email = "sat.kumar@aapahinnovations.com", role = c("aut", "cre")), person("Sekhar", "Muddu", email="muddu@civil.iisc.ernet.in", role="aut"), person("Vishal", "Mehta", email="vishal.mehta@sei-us.org", role="aut"), person("Subash", "Yegina", email="subash.yeggina@gmail.com", role="aut"), person("Thiyaku", "S.", email = "thiyaku@aapahinnovations.com", role = c("aut")))
Description: Implements distributed transient groundwater modelling. The model is based on the groundwater flow equation solved numerically using the finite difference explicit scheme.
Depends: R (>= 3.2.3)
Imports: yaml, raster, stats, rgdal
License: GPL (>= 3)
Repository: CRAN
Encoding: UTF-8
RoxygenNote: 6.0.1.9000
NeedsCompilation: no
Packaged: 2017-07-15 11:10:02 UTC; thiyaku
Author: Sat Tomer [aut, cre], Sekhar Muddu [aut], Vishal Mehta [aut], Subash Yegina [aut], Thiyaku S. [aut]
Maintainer: Sat Tomer <sat.kumar@aapahinnovations.com>
Date/Publication: 2017-07-15 12:15:48 UTC

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New package centiserve with initial version 1.0.0
Package: centiserve
Type: Package
Title: Find Graph Centrality Indices
Version: 1.0.0
Depends: igraph (>= 0.7.1), Matrix (>= 1.1-4)
Date: 2017-07-15
Author: Mahdi Jalili <m_jalili@farabi.tums.ac.ir>
Maintainer: Mahdi Jalili <m_jalili@farabi.tums.ac.ir>
Description: Calculates centrality indices additional to the 'igraph' package centrality functions.
License: GPL (>= 2)
Suggests: expm (>= 0.99-1.1), linkcomm (>= 1.0-11)
URL: http://www.centiserver.org/
BugReports: http://www.centiserver.org/?q1=contact
Packaged: 2017-07-15 09:19:59 UTC; Mahdi
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2017-07-15 09:34:41 UTC

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New package TSF with initial version 0.1.1
Package: TSF
Type: Package
Title: Two Stage Forecasting (TSF) for Long Memory Time Series in Presence of Structural Break
Version: 0.1.1
Author: Sandipan Samanta, Ranjit Kumar Paul and Dipankar Mitra
Maintainer: Dr. Ranjit Kumar Paul <ranjitstat@gmail.com>
Description: Forecasting of long memory time series in presence of structural break by using TSF algorithm by Papailias and Dias (2015) <doi:10.1016/j.ijforecast.2015.01.006>.
License: GPL
Imports: stats, fracdiff, forecast
LazyData: TRUE
NeedsCompilation: no
Packaged: 2017-07-15 06:50:30 UTC; ranjitstat
Repository: CRAN
Date/Publication: 2017-07-15 06:49:07 UTC

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New package seplyr with initial version 0.1.0
Package: seplyr
Type: Package
Title: Standard Evaluation Interfaces for Common 'dplyr' Tasks
Version: 0.1.0
Author: John Mount
Maintainer: John Mount <jmount@win-vector.com>
Description: The 'seplyr' (standard evaluation data.frame 'dplyr') package supplies standard evaluation adapter methods for important common 'dplyr' methods that currently have a non-standard programming interface. This allows the analyst to use 'dplyr' to perform fundamental data transformation steps such as arranging rows, grouping rows, aggregating selecting columns without having to use learn the details of 'rlang'/'tidyeval' non-standard evaluation and without continuing to rely on now deprecated 'dplyr' "underscore verbs." In addition the 'seplyr' package supplies several new "key operations bound together" methods. These include 'group_summarize()' (which combines grouping, arranging and calculation in an atomic unit), 'add_group_summaries()' (which joins grouped summaries into a 'data.frame' in a well documented manner), and 'add_group_indices()' (which adds per-group identifies to a 'data.frame' without depending on row-order).
License: GPL-3
Encoding: UTF-8
Depends: dplyr (>= 0.7.1)
Imports: rlang (>= 0.1.1), datasets
LazyData: true
RoxygenNote: 6.0.1
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
ByteCompile: true
NeedsCompilation: no
Packaged: 2017-07-14 22:26:14 UTC; johnmount
Repository: CRAN
Date/Publication: 2017-07-15 06:31:15 UTC

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New package rsMove with initial version 0.1
Package: rsMove
Type: Package
Title: Remote Sensing for Movement Ecology
Version: 0.1
Date: 2017-07-14
Authors@R: person("Ruben", "Remelgado", role = c("aut", "cre"), email="ruben.remelgado@uni-wuerzburg.de")
URL: https://github.com/RRemelgado/rsMove/tree/master/
BugReports: https://github.com/RRemelgado/rsMove/issues/
Maintainer: Ruben Remelgado <ruben.remelgado@uni-wuerzburg.de>
Description: Tools to analyze animal tracking data with remote sensing.
LazyData: TRUE
Imports: raster, sp, caret, grDevices, rgdal
RoxygenNote: 6.0.1
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2017-07-14 22:43:14 UTC; rus14jh
Author: Ruben Remelgado [aut, cre]
Repository: CRAN
Date/Publication: 2017-07-15 06:30:30 UTC

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Fri, 14 Jul 2017

New package dendroExtra with initial version 0.0.1
Package: dendroExtra
Type: Package
Title: Nonlinear Methods for Analyzing Dendroclimatological Data
Version: 0.0.1
Author: Jernej Jevsenak [aut, cre], Tom Levanic [ctb]
Maintainer: Jernej Jevsenak <jernej.jevsenak@gmail.com>
Description: Provides novel dendroclimatological methods, primarily used by the Tree-ring research community. The core function is daily_response(), which finds the optimal sequence of days that are linearly or nonlinearly related to one or more tree-ring proxy records.
License: GPL-3
URL: http://github.com/jernejjevsenak/dendroExtra
BugReports: http://github.com/jernejjevsenak/dendroExtra/issues
Encoding: UTF-8
LazyData: true
Suggests: testthat, dplyr, dplR
RoxygenNote: 6.0.1
Imports: ggplot2 (>= 2.2.0), brnn (>= 0.6), reshape2 (>= 1.4.2), oce (>= 0.9-21), stats (>= 3.4.0), scales (>= 0.4.1)
Depends: R (>= 3.1)
NeedsCompilation: no
Packaged: 2017-07-14 17:56:16 UTC; JernejJ
Repository: CRAN
Date/Publication: 2017-07-14 18:44:08 UTC

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New package BimodalIndex with initial version 1.1.5
Package: BimodalIndex
Version: 1.1.5
Date: 2017-07-11
Title: The Bimodality Index
Author: Kevin R. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>
Depends: R (>= 3.0)
Imports: oompaBase (>= 3.0.1), mclust
Suggests: oompaData
Description: Defines the functions used to compute the bimodal index as defined by Wang et al. (2009) <https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2730180/>.
License: Apache License (== 2.0)
LazyLoad: yes
biocViews: Microarray
URL: http://oompa.r-forge.r-project.org/
NeedsCompilation: no
Packaged: 2017-07-12 00:01:37 UTC; Kevin
Repository: CRAN
Date/Publication: 2017-07-14 19:56:57 UTC

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New package ggjoy with initial version 0.1
Package: ggjoy
Type: Package
Title: Joyplots in 'ggplot2'
Version: 0.1
Authors@R: c( person("Claus O.", "Wilke", , "wilke@austin.utexas.edu", c("cre", "aut")), person("RStudio", role = c("cph")))
Description: Joyplots provide a convenient way of visualizing changes in distributions over time or space. This package enables the creation of such plots in 'ggplot2'.
URL: https://github.com/clauswilke/ggjoy
Depends: R (>= 3.3.0), ggplot2 (>= 2.2.0),
Imports: grid (>= 3.0.0), plyr (>= 1.8.0)
License: GPL-2 | file LICENSE
LazyData: true
Suggests: knitr, ggplot2movies, cowplot
VignetteBuilder: knitr
Collate: 'data.R' 'ggjoy.R' 'geoms.R' 'stats.R' 'theme.R' 'utils_ggplot2.R'
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-14 16:17:14 UTC; wilke
Author: Claus O. Wilke [cre, aut], RStudio [cph]
Maintainer: Claus O. Wilke <wilke@austin.utexas.edu>
Repository: CRAN
Date/Publication: 2017-07-14 16:25:47 UTC

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New package credsubs with initial version 1.0
Package: credsubs
Title: Credible Subsets
Version: 1.0
Date: 2017-07-14
Author: Patrick Schnell, Brad Carlin
Maintainer: Patrick Schnell <schnell.31@osu.edu>
Description: Functions for constructing simultaneous credible bands and identifying subsets via the "credible subsets" (also called "credible subgroups") method.
Suggests: ff, shiny
License: GPL-3
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-14 15:29:18 UTC; patrick
Repository: CRAN
Date/Publication: 2017-07-14 16:13:53 UTC

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New package BibPlots with initial version 0.0.1
Package: BibPlots
Title: Plot Functions for JIF (Journal Impact Factor) and Paper Percentiles
Version: 0.0.1
Authors@R: person("Robin", "Haunschild", email = "R.Haunschild@fkf.mpg.de", role = c("aut", "cre"))
Description: Currently, the package provides two functions for plotting and analyzing bibliometric data (JIF and paper percentile values). Further extension to more plot variants is planned.
Depends: R (>= 3.1.2)
License: EUPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2017-07-14 15:18:11 UTC; rhaun
Author: Robin Haunschild [aut, cre]
Maintainer: Robin Haunschild <R.Haunschild@fkf.mpg.de>
Repository: CRAN
Date/Publication: 2017-07-14 16:14:26 UTC

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New package bayeslm with initial version 0.1.0
Package: bayeslm
Type: Package
Title: Efficient Sampling for Gaussian Linear Regression with Arbitrary Priors
Version: 0.1.0
Date: 2017-07-09
Author: P. Richard Hahn, Jingyu He and Hedibert Lopes
Maintainer: Jingyu He <jingyu.he@chicagobooth.edu>
Description: Efficient sampling for Gaussian linear regression with arbitrary priors.
License: LGPL (>= 2)
Imports: Rcpp (>= 0.12.7)
SystemRequirements: A C++11 compiler.
Depends: R (>= 2.10)
URL: http://jingyuhe.com/software.html
NeedsCompilation: yes
LinkingTo: Rcpp, RcppArmadillo
Packaged: 2017-07-14 16:19:43 UTC; jingyuh0
Repository: CRAN
Date/Publication: 2017-07-14 16:30:59 UTC

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New package survtmle with initial version 1.0.0
Package: survtmle
Title: Compute Targeted Minimum Loss-Based Estimates in Right-Censored Survival Settings
Version: 1.0.0
Authors@R: c(person("David","Benkeser",role = c("aut","cre","cph"),email="benkeser@emory.edu"), person("Nima","Hejazi",role = c("aut"), email = "nheajzi@berkeley.edu"))
Description: Targeted estimates of marginal cumulative incidence estimates in survival settings with and without competing risks, including estimators that respect bounds (Benkeser, Carone, and Gilbert (2017) <doi: 10.1002/sim.7337>).
Depends: R (>= 3.0.0)
Imports: SuperLearner, Matrix, plyr, tidyr, stringr, ggplot2
Suggests: testthat, knitr, rmarkdown, survival, cmprsk, tibble
License: MIT + file LICENSE
URL: https://github.com/benkeser/survtmle
BugReports: https://github.com/benkeser/survtmle/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 6.0.1
NeedsCompilation: no
Packaged: 2017-07-14 12:30:29 UTC; benkeser
Author: David Benkeser [aut, cre, cph], Nima Hejazi [aut]
Maintainer: David Benkeser <benkeser@emory.edu>
Repository: CRAN
Date/Publication: 2017-07-14 14:35:08 UTC

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New package sitreeE with initial version 0.0-1
Package: sitreeE
Version: 0.0-1
Date: 2017-07-14
Title: Sitree Extensions
Authors@R: c(person("Clara", "Anton Fernandez", role = c("aut", "cre"), email = "caf@nibio.no"))
Author: Clara Anton Fernandez [aut, cre]
Maintainer: Clara Anton Fernandez <caf@nibio.no>
Depends: R (>= 3.1.0), sitree
Description: Provides extensions for package 'sitree' for allometric variables, growth, mortality, recruitment, management, tree removal and external modifiers functions.
License: GPL (>= 2)
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
NeedsCompilation: no
Packaged: 2017-07-14 07:22:40 UTC; caf
Repository: CRAN
Date/Publication: 2017-07-14 13:29:02 UTC

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