Sun, 30 Sep 2018

Package vip updated to version 0.1.2 with previous version 0.1.1 dated 2018-09-27

Title: Variable Importance Plots
Description: A general framework for constructing variable importance plots from various types machine learning models in R. Aside from some standard model- based variable importance measures, this package also provides a novel approach based on partial dependence plots (PDPs) and individual conditional expectation (ICE) curves as described in Greenwell et al. (2018) <arXiv:1805.04755>.
Author: Brandon Greenwell [aut, cre] (<https://orcid.org/0000-0002-8120-0084>), Brad Boehmke [aut] (<https://orcid.org/0000-0002-3611-8516>), Bernie Gray [aut]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>

Diff between vip versions 0.1.1 dated 2018-09-27 and 0.1.2 dated 2018-09-30

 DESCRIPTION     |   10 +++++-----
 MD5             |   19 ++++++++++---------
 NAMESPACE       |    6 ++++++
 NEWS.md         |    7 +++++++
 R/utils.R       |   26 ++++++++++++++++++++++++++
 R/vi.R          |    3 +++
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 R/vip.R         |   47 +++++++++++++++++++++++++++++++++++++----------
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 11 files changed, 164 insertions(+), 27 deletions(-)

More information about vip at CRAN
Permanent link

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

More information about SpNMF at CRAN
Permanent link

Package landscapemetrics updated to version 0.2 with previous version 0.1.1 dated 2018-08-14

Title: Landscape Metrics for Categorical Map Patterns
Description: Calculates landscape metrics for categorical landscape patterns in a tidy workflow. 'landscapemetrics' reimplements the most common metrics from 'FRAGSTATS' (<https://www.umass.edu/landeco/research/fragstats/fragstats.html>) and new ones from the current literature on landscape metrics. This package supports 'raster' spatial objects and takes RasterLayer, RasterStacks, RasterBricks or lists of RasterLayer from the 'raster' package as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Laura J. Graham [ctb] (<https://orcid.org/0000-0002-1057-3721>), Kimberly A. With [ctb] (<https://orcid.org/0000-0001-5570-1515>), Jeffrey Hollister [ctb] (<https://orcid.org/0000-0002-3611-7281>), Matt Strimas-Mackey [ctb] (<https://orcid.org/0000-0001-8929-7776>), Jeremy VanDerWal [ctb] (Original author of underlying C code for get_patches() function), Florian Privé [ctb] (Original author of underlying C++ code for get_nearestneighbour() function)
Maintainer: Maximillian H.K. Hesselbarth <maximilian.hesselbarth@uni-goettingen.de>

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

More information about cap at CRAN
Permanent link

Package effectR updated to version 1.0.2 with previous version 1.0.1 dated 2018-04-25

Title: Predicts Oomycete Effectors
Description: Predicts cytoplasmic effector proteins using genomic data by searching for motifs of interest using regular expression searches and hidden Markov models (HMM) based in Haas et al. (2009) <doi:10.1038/nature08358>.
Author: Javier Tabima [aut, cre], Niklaus J. Grunwald [ths]
Maintainer: Javier Tabima <tabimaj@oregonstate.edu>

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Package loon updated to version 1.2.0 with previous version 1.1.1 dated 2018-03-01

Title: Interactive Statistical Data Visualization
Description: An extendable toolkit for interactive data visualization and exploration.
Author: Adrian Waddell [aut, cre], R. Wayne Oldford [aut], Zehao Xu [ctb]
Maintainer: Adrian Waddell <adrian@waddell.ch>

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 146 files changed, 1616 insertions(+), 698 deletions(-)

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Package jstor updated to version 0.3.3 with previous version 0.3.2 dated 2018-07-20

Title: Read Data from JSTOR/DfR
Description: Functions and helpers to import metadata, ngrams and full-texts delivered by Data for Research by JSTOR.
Author: Thomas Klebel [aut, cre] (<https://orcid.org/0000-0002-7331-4751>)
Maintainer: Thomas Klebel <t.klebel@hotmail.com>

Diff between jstor versions 0.3.2 dated 2018-07-20 and 0.3.3 dated 2018-09-30

 DESCRIPTION                            |   14 +--
 MD5                                    |   78 +++++++++---------
 NEWS.md                                |   24 +++++
 R/augmentations.R                      |   20 ++++
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 man/read_full_text.Rd                  |    6 +
 tests/testthat/test-import-spec.R      |    5 +
 tests/testthat/test-journal-overview.R |   12 ++
 vignettes/automating-file-import.Rmd   |    4 
 42 files changed, 477 insertions(+), 226 deletions(-)

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Package tidytransit updated to version 0.3.4 with previous version 0.3.2 dated 2018-09-03

Title: Read, Validate, Analyze, and Map Files in the General Transit Feed Specification
Description: Read General Transit Feed Specification (GTFS) zipfiles into a list of R dataframes. Perform validation of the data structure against the specification. Analyze the headways and frequencies at routes and stops. Create maps and perform spatial analysis on the routes and stops. Please see the GTFS documentation here for more detail: <http://gtfs.org/>.
Author: Tom Buckley [aut, cre], Danton Noriega-Goodwin [aut], Flavio Poletti [aut], Angela Li [aut], Patrick Hausmann [ctb], Bob Rudis [ctb], Mark Padgham [ctb], Kearey Smith [ctb], Dave Vautin [ctb], Kyle Walker [ctb], Elaine McVey [cph], Charles Hans Thompson [cph], Michael Sumner [cph]
Maintainer: Tom Buckley <tom@tbuckl.com>

Diff between tidytransit versions 0.3.2 dated 2018-09-03 and 0.3.4 dated 2018-09-30

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 tidytransit-0.3.4/tidytransit/R/joins.R                              |   34 
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 tidytransit-0.3.4/tidytransit/R/time.R                               |   95 ++
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 34 files changed, 594 insertions(+), 629 deletions(-)

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Package rsMove updated to version 0.2.5 with previous version 0.2.4 dated 2018-07-04

Title: Remote Sensing for Movement Ecology
Description: Tools that support the combined use of animal movement and remote sensing data. Based on the paper on the paper by Remelgado et al. (2015) <doi:10.1002/rse2.70>.
Author: Ruben Remelgado [aut, cre]
Maintainer: Ruben Remelgado <ruben.remelgado@uni-wuerzburg.de>

Diff between rsMove versions 0.2.4 dated 2018-07-04 and 0.2.5 dated 2018-09-30

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 rsMove-0.2.5/rsMove/NAMESPACE                          |    7 
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 rsMove-0.2.5/rsMove/R/hotMoveStats.R                   |  161 ++++++-----------
 rsMove-0.2.5/rsMove/R/imgInt.R                         |   25 +-
 rsMove-0.2.5/rsMove/R/labelSample.R                    |   80 +++-----
 rsMove-0.2.5/rsMove/R/moveCloud.R                      |   60 +++---
 rsMove-0.2.5/rsMove/R/moveReduce.R                     |   23 --
 rsMove-0.2.5/rsMove/R/moveSeg.R                        |   95 ++++++----
 rsMove-0.2.5/rsMove/R/plausibilityTest.R               |   18 -
 rsMove-0.2.5/rsMove/R/plotMove.R                       |    6 
 rsMove-0.2.5/rsMove/R/predictResources.R               |   37 ++-
 rsMove-0.2.5/rsMove/R/rsComposite.R                    |  113 +++++------
 rsMove-0.2.5/rsMove/R/sampleMove.R                     |   30 ++-
 rsMove-0.2.5/rsMove/R/segRaster.R                      |   29 +--
 rsMove-0.2.5/rsMove/R/spaceDir.R                       |  123 ++++++------
 rsMove-0.2.5/rsMove/R/specVar.R                        |   46 ++--
 rsMove-0.2.5/rsMove/R/timeDir.R                        |   49 ++---
 rsMove-0.2.5/rsMove/README.md                          |    2 
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 rsMove-0.2.5/rsMove/inst/doc/resource_suitability.R    |   21 +-
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 rsMove-0.2.5/rsMove/man/predictResources.Rd            |   32 +--
 rsMove-0.2.5/rsMove/man/rsComposite.Rd                 |   36 +--
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 53 files changed, 880 insertions(+), 911 deletions(-)

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

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

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

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

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

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

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

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

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

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

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

More information about piggyback at CRAN
Permanent link

Package nanotime updated to version 0.2.3 with previous version 0.2.2 dated 2018-07-18

Title: Nanosecond-Resolution Time for R
Description: Full 64-bit resolution date and time support with resolution up to nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type.
Author: Dirk Eddelbuettel and Leonardo Silvestri
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between nanotime versions 0.2.2 dated 2018-07-18 and 0.2.3 dated 2018-09-30

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

More information about linguisticsdown at CRAN
Permanent link

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

More information about lineqGPR at CRAN
Permanent link

Package htmlwidgets updated to version 1.3 with previous version 1.2 dated 2018-04-19

Title: HTML Widgets for R
Description: A framework for creating HTML widgets that render in various contexts including the R console, 'R Markdown' documents, and 'Shiny' web applications.
Author: Ramnath Vaidyanathan [aut, cph], Yihui Xie [aut], JJ Allaire [aut], Joe Cheng [aut, cre], Kenton Russell [aut, cph], RStudio [cph]
Maintainer: Joe Cheng <joe@rstudio.com>

Diff between htmlwidgets versions 1.2 dated 2018-04-19 and 1.3 dated 2018-09-30

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

More information about colourvalues at CRAN
Permanent link

Package carData updated to version 3.0-2 with previous version 3.0-1 dated 2018-03-28

Title: Companion to Applied Regression Data Sets
Description: Datasets to Accompany J. Fox and S. Weisberg, An R Companion to Applied Regression, Third Edition, Sage (forthcoming).
Author: John Fox [aut, cre], Sanford Weisberg [aut], Brad Price [aut]
Maintainer: John Fox <jfox@mcmaster.ca>

Diff between carData versions 3.0-1 dated 2018-03-28 and 3.0-2 dated 2018-09-30

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

More information about roptim at CRAN
Permanent link

Package optimx updated to version 2018-7.10 with previous version 2013.8.7 dated 2014-11-13

Title: Expanded Replacement and Extension of the 'optim' Function
Description: Provides a replacement and extension of the optim() function to call to several function minimization codes in R in a single statement. These methods handle smooth, possibly box constrained functions of several or many parameters. Note that function 'optimr()' was prepared to simplify the incorporation of minimization codes going forward. Also implements some utility codes and some extra solvers, including safeguarded Newton methods. Many methods previously separate are now included here.
Author: John C Nash [aut, cre], Ravi Varadhan [aut], Gabor Grothendieck [ctb]
Maintainer: John C Nash <nashjc@uottawa.ca>

Diff between optimx versions 2013.8.7 dated 2014-11-13 and 2018-7.10 dated 2018-09-30

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More information about optimx at CRAN
Permanent link

Package nloptr updated to version 1.2.0 with previous version 1.0.4 dated 2014-08-04

Title: R Interface to NLopt
Description: Solve optimization problems using an R interface to NLopt. NLopt is a free/open-source library for nonlinear optimization, providing a common interface for a number of different free optimization routines available online as well as original implementations of various other algorithms. See <http://ab-initio.mit.edu/wiki/index.php/NLopt_Introduction> for more information on the available algorithms. During installation of nloptr on Unix-based systems, the installer checks whether the NLopt library is installed on the system. If the NLopt library cannot be found, the code is compiled using the NLopt source included in the nloptr package.
Author: Jelmer Ypma <uctpjyy@ucl.ac.uk>, with contributions by Hans W. Borchers <hwborchers@googlemail.com> and Dirk Eddelbuettel <edd@debian.org>
Maintainer: Jelmer Ypma <uctpjyy@ucl.ac.uk>

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

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

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

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

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Package TAM updated to version 2.13-15 with previous version 2.12-18 dated 2018-05-25

Title: Test Analysis Modules
Description: Includes marginal maximum likelihood estimation and joint maximum likelihood estimation for unidimensional and multidimensional item response models. The package functionality covers the Rasch model, 2PL model, 3PL model, generalized partial credit model, multi-faceted Rasch model, nominal item response model, structured latent class model, mixture distribution IRT models, and located latent class models. Latent regression models and plausible value imputation are also supported. For details see Adams, Wilson and Wang, 1997 <doi:10.1177/0146621697211001>, Adams, Wilson and Wu, 1997 <doi:10.3102/10769986022001047>, Formann, 1982 <doi:10.1002/bimj.4710240209>, Formann, 1992 <doi:10.1080/01621459.1992.10475229>.
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Margaret Wu [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

Diff between TAM versions 2.12-18 dated 2018-05-25 and 2.13-15 dated 2018-09-30

 DESCRIPTION                                      |   13 +-
 MD5                                              |  141 +++++++++++------------
 NAMESPACE                                        |   17 +-
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 R/IRT.irfprob.tam.R                              |    3 
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 R/RcppExports.R                                  |    6 
 R/designMatrices.mfr.R                           |    4 
 R/designMatrices.mfr2.R                          |    4 
 R/lavaanify.IRT.R                                |   41 +++---
 R/lavpartable.grep.underbrace.R                  |   36 ++---
 R/summary.tam.R                                  |    8 -
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 src/RcppExports.cpp                              |   18 ++
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 74 files changed, 384 insertions(+), 262 deletions(-)

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

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Package metaplot updated to version 0.8.0 with previous version 0.7.0 dated 2018-08-09

Title: Data-Driven Plot Design
Description: Designs plots in terms of core structure. See 'example(metaplot)'. Primary arguments are (unquoted) column names; order and type (numeric or not) dictate the resulting plot. Specify any y variables, x variable, any groups variable, and any conditioning variables to metaplot() to generate density plots, boxplots, mosaic plots, scatterplots, scatterplot matrices, or conditioned plots. Use multiplot() to arrange plots in grids. Wherever present, scalar column attributes 'label' and 'guide' are honored, producing fully annotated plots with minimal effort. Attribute 'guide' is typically units, but may be encoded() to provide interpretations of categorical values (see '?encode'). Utility unpack() transforms scalar column attributes to row values and pack() does the reverse, supporting tool-neutral storage of metadata along with primary data. The package supports customizable aesthetics such as such as reference lines, unity lines, smooths, log transformation, and linear fits. The user may choose between trellis and ggplot output. Compact syntax and integrated metadata promote workflow scalability.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

Diff between metaplot versions 0.7.0 dated 2018-08-09 and 0.8.0 dated 2018-09-30

 DESCRIPTION                       |   10 -
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 NAMESPACE                         |    6 
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 R/categorical.R                   |  104 ++++++----
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 45 files changed, 1075 insertions(+), 781 deletions(-)

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Package fastGHQuad updated to version 1.0 with previous version 0.2 dated 2014-08-14

Title: Fast 'Rcpp' Implementation of Gauss-Hermite Quadrature
Description: Fast, numerically-stable Gauss-Hermite quadrature rules and utility functions for adaptive GH quadrature. See Liu, Q. and Pierce, D. A. (1994) <doi:10.2307/2337136> for a reference on these methods.
Author: Alexander W Blocker
Maintainer: Alexander W Blocker <ablocker@gmail.com>

Diff between fastGHQuad versions 0.2 dated 2014-08-14 and 1.0 dated 2018-09-30

 fastGHQuad-0.2/fastGHQuad/README                    |only
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 fastGHQuad-1.0/fastGHQuad/man/fastGHQuad-package.Rd |   16 +++++----
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 fastGHQuad-1.0/fastGHQuad/man/gaussHermiteData.Rd   |   10 ++---
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 20 files changed, 88 insertions(+), 71 deletions(-)

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Package data.table updated to version 1.11.8 with previous version 1.11.6 dated 2018-09-19

Title: Extension of `data.frame`
Description: Fast aggregation of large data (e.g. 100GB in RAM), fast ordered joins, fast add/modify/delete of columns by group using no copies at all, list columns, friendly and fast character-separated-value read/write. Offers a natural and flexible syntax, for faster development.
Author: Matt Dowle [aut, cre], Arun Srinivasan [aut], Jan Gorecki [ctb], Michael Chirico [ctb], Pasha Stetsenko [ctb], Tom Short [ctb], Steve Lianoglou [ctb], Eduard Antonyan [ctb], Markus Bonsch [ctb], Hugh Parsonage [ctb]
Maintainer: Matt Dowle <mattjdowle@gmail.com>

Diff between data.table versions 1.11.6 dated 2018-09-19 and 1.11.8 dated 2018-09-30

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 data.table-1.11.8/data.table/R/fcast.R                                                   |   12 
 data.table-1.11.8/data.table/R/fmelt.R                                                   |   19 
 data.table-1.11.8/data.table/R/fread.R                                                   |   15 
 data.table-1.11.8/data.table/R/setkey.R                                                  |    2 
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Package commonmark updated to version 1.6 with previous version 1.5 dated 2018-04-28

Title: High Performance CommonMark and Github Markdown Rendering in R
Description: The CommonMark specification defines a rationalized version of markdown syntax. This package uses the 'cmark' reference implementation for converting markdown text into various formats including html, latex and groff man. In addition it exposes the markdown parse tree in xml format. Also inlcudes opt-in support for GFM extensions including tables, autolinks, and strikethrough text.
Author: Jeroen Ooms [aut, cre], John MacFarlane [cph] (Author of cmark)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

Diff between commonmark versions 1.5 dated 2018-04-28 and 1.6 dated 2018-09-30

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 commonmark-1.6/commonmark/DESCRIPTION                                  |   14 
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 commonmark-1.6/commonmark/NEWS                                         |    3 
 commonmark-1.6/commonmark/src/cmark/arena.c                            |    4 
 commonmark-1.6/commonmark/src/cmark/blocks.c                           |   36 
 commonmark-1.6/commonmark/src/cmark/buffer.h                           |   46 
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New package colorfindr with initial version 0.1.0
Package: colorfindr
Type: Package
Title: Extract Colors from Windows BMP, JPEG, PNG, TIFF, and SVG Format Images
Version: 0.1.0
Authors@R: person("David", "Zumbach", role = c("aut", "cre"), email = "david.zumbach@gfzb.ch")
Description: Extracts colors from various image types, returns customized reports and plots treemaps of image compositions. Selected colors and color ranges can be excluded from the analysis.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
BugReports: https://github.com/zumbov2/colorfindr/issues
RoxygenNote: 6.1.0
Imports: purrr, stringr, pixmap, tibble, treemap, rsvg, png, jpeg, tiff, bmp
Suggests: dplyr
NeedsCompilation: no
Packaged: 2018-09-20 00:17:22 UTC; David Zumbach
Author: David Zumbach [aut, cre]
Maintainer: David Zumbach <david.zumbach@gfzb.ch>
Repository: CRAN
Date/Publication: 2018-09-30 13:50:10 UTC

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

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Package Ball updated to version 1.3.0 with previous version 1.2.0 dated 2018-06-17

Title: Statistical Inference and Sure Independence Screening via Ball Statistics
Description: Hypothesis tests and sure independence screening (SIS) procedure based on ball statistics, including ball divergence <doi:10.1214/17-AOS1579>, ball covariance, and ball correlation <doi:10.1080/01621459.2018.1462709>, are developed to analyze complex data. The ball divergence and ball covariance based distribution-free tests are implemented to examine equality of multivariate distributions and independence between random vectors of arbitrary dimensions. Furthermore, a generic non-parametric SIS procedure based on ball correlation and all of its variants are implemented to tackle the challenge in the context of ultra high dimensional data.
Author: Xueqin Wang, Wenliang Pan, Heping Zhang, Hongtu Zhu, Yuan Tian, Weinan Xiao, Chengfeng Liu, Jin Zhu
Maintainer: Jin Zhu <zhuj37@mail2.sysu.edu.cn>

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

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

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Package CDM updated to version 6.6-5 with previous version 6.5-12 dated 2018-08-16

Title: Cognitive Diagnosis Modeling
Description: Functions for cognitive diagnosis modeling and multidimensional item response modeling for dichotomous and polytomous item responses. This package enables the estimation of the DINA and DINO model (Junker & Sijtsma, 2001, <doi:10.1177/01466210122032064>), the multiple group (polytomous) GDINA model (de la Torre, 2011, <doi:10.1007/s11336-011-9207-7>), the multiple choice DINA model (de la Torre, 2009, <doi:10.1177/0146621608320523>), the general diagnostic model (GDM; von Davier, 2008, <doi:10.1348/000711007X193957>), the structured latent class model (SLCA; Formann, 1992, <doi:10.1080/01621459.1992.10475229>) and regularized latent class analysis (Chen, Li, Liu, & Ying, 2017, <doi:10.1007/s11336-016-9545-6>). See George, Robitzsch, Kiefer, Gross, and Uenlue (2017) <doi:10.18637/jss.v074.i02> for further details on estimation and the package structure. For tutorials on how to use the CDM package see George and Robitzsch (2015, <doi:10.20982/tqmp.11.3.p189>) as well as Ravand and Robitzsch (2015).
Author: Alexander Robitzsch [aut, cre], Thomas Kiefer [aut], Ann Cathrice George [aut], Ali Uenlue [aut]
Maintainer: Alexander Robitzsch <robitzsch@ipn.uni-kiel.de>

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Package ungroup updated to version 1.1.0 with previous version 1.0.0 dated 2018-09-03

Title: Penalized Composite Link Model for Efficient Estimation of Smooth Distributions from Coarsely Binned Data
Description: Versatile method for ungrouping histograms (binned count data) assuming that counts are Poisson distributed and that the underlying sequence on a fine grid to be estimated is smooth. The method is based on the composite link model and estimation is achieved by maximizing a penalized likelihood. Smooth detailed sequences of counts and rates are so estimated from the binned counts. Ungrouping binned data can be desirable for many reasons: Bins can be too coarse to allow for accurate analysis; comparisons can be hindered when different grouping approaches are used in different histograms; and the last interval is often wide and open-ended and, thus, covers a lot of information in the tail area. Age-at-death distributions grouped in age classes and abridged life tables are examples of binned data. Because of modest assumptions, the approach is suitable for many demographic and epidemiological applications. For a detailed description of the method and applications see Rizzi et al. (2015) <doi:10.1093/aje/kwv020>.
Author: Marius D. Pascariu [aut, cre] (<https://orcid.org/0000-0002-2568-6489>), Silvia Rizzi [aut], Jonas Schoeley [aut] (<https://orcid.org/0000-0002-3340-8518>), Maciej J. Danko [aut] (<https://orcid.org/0000-0002-7924-9022>)
Maintainer: Marius D. Pascariu <rpascariu@outlook.com>

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Package nonmemica updated to version 0.8.3 with previous version 0.8.2 dated 2018-03-29

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <http://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package MLML2R updated to version 0.3.0 with previous version 0.2.1 dated 2018-05-16

Title: Maximum Likelihood Estimation of DNA Methylation and Hydroxymethylation Proportions
Description: Maximum likelihood estimates (MLE) of the proportions of 5-mC and 5-hmC in the DNA using information from BS-conversion, TAB-conversion, and oxBS-conversion methods. One can use information from all three methods or any combination of two of them. Estimates are based on Binomial model by Qu et al. (2013) <doi:10.1093/bioinformatics/btt459> and Kiihl et al. (2018, to appear).
Author: Samara Kiihl [aut, cre], Maria Jose Martinez-Garrido [aut], Arce Domingo-Relloso [aut], Jose Bermudez [aut], Maria Tellez-Plaza [aut]
Maintainer: Samara Kiihl <samara@ime.unicamp.br>

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Package eplusr updated to version 0.9.2 with previous version 0.9.1 dated 2018-08-29

Title: A Toolkit for Using Whole Building Simulation Program 'EnergyPlus'
Description: A rich toolkit of using the whole building simulation program 'EnergyPlus'(<https://energyplus.net>), which enables programmatic navigation, modification of 'EnergyPlus' models and makes it less painful to do parametric simulations and analysis.
Author: Hongyuan Jia [aut, cre] (<https://orcid.org/0000-0002-0075-8183>)
Maintainer: Hongyuan Jia <hongyuanjia@cqu.edu.cn>

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Package drake updated to version 6.0.0 with previous version 5.4.0 dated 2018-08-07

Title: A Pipeline Toolkit for Reproducible Computation at Scale
Description: A general-purpose computational engine for data analysis, drake rebuilds intermediate data objects when their dependencies change, and it skips work when the results are already up to date. Not every execution starts from scratch, and completed projects have tangible evidence that they are reproducible. Extensive documentation, from beginner-friendly tutorials to practical examples and more, is available at the reference website <https://ropensci.github.io/drake/> and the online manual <https://ropenscilabs.github.io/drake-manual/>.
Author: William Michael Landau [aut, cre], Alex Axthelm [ctb], Jasper Clarkberg [ctb], Kirill Müller [ctb], Ben Marwick [rev], Peter Slaughter [rev], Eli Lilly and Company [cph]
Maintainer: William Michael Landau <will.landau@gmail.com>

Diff between drake versions 5.4.0 dated 2018-08-07 and 6.0.0 dated 2018-09-30

 drake-5.4.0/drake/R/drake_plan_class.R                    |only
 drake-5.4.0/drake/R/drake_plan_print.R                    |only
 drake-5.4.0/drake/man/as_drake_plan.Rd                    |only
 drake-5.4.0/drake/man/loadd.Rd                            |only
 drake-6.0.0/drake/DESCRIPTION                             |   25 
 drake-6.0.0/drake/MD5                                     |  185 ++---
 drake-6.0.0/drake/NAMESPACE                               |   17 
 drake-6.0.0/drake/NEWS.md                                 |   44 +
 drake-6.0.0/drake/R/build.R                               |    2 
 drake-6.0.0/drake/R/build_drake_graph.R                   |  502 ++++++++------
 drake-6.0.0/drake/R/build_times.R                         |    2 
 drake-6.0.0/drake/R/cache.R                               |   60 +
 drake-6.0.0/drake/R/cache_log.R                           |    2 
 drake-6.0.0/drake/R/cache_namespaces.R                    |    1 
 drake-6.0.0/drake/R/clean.R                               |   10 
 drake-6.0.0/drake/R/clustermq.R                           |only
 drake-6.0.0/drake/R/code_to_plan.R                        |only
 drake-6.0.0/drake/R/color.R                               |    3 
 drake-6.0.0/drake/R/config.R                              |   20 
 drake-6.0.0/drake/R/console.R                             |   22 
 drake-6.0.0/drake/R/dependencies.R                        |  207 ++++-
 drake-6.0.0/drake/R/deprecate.R                           |   62 +
 drake-6.0.0/drake/R/drake_graph_info.R                    |    1 
 drake-6.0.0/drake/R/drake_graph_info_utils.R              |   55 -
 drake-6.0.0/drake/R/drake_plan.R                          |    2 
 drake-6.0.0/drake/R/drake_plan_source.R                   |only
 drake-6.0.0/drake/R/envir.R                               |    3 
 drake-6.0.0/drake/R/examples.R                            |    4 
 drake-6.0.0/drake/R/future.R                              |    4 
 drake-6.0.0/drake/R/future_lapply.R                       |    4 
 drake-6.0.0/drake/R/generate_plans.R                      |  129 +++
 drake-6.0.0/drake/R/ggraph.R                              |   10 
 drake-6.0.0/drake/R/knitr.R                               |    9 
 drake-6.0.0/drake/R/make.R                                |    6 
 drake-6.0.0/drake/R/mc_utils.R                            |    5 
 drake-6.0.0/drake/R/mclapply.R                            |    8 
 drake-6.0.0/drake/R/meta.R                                |   21 
 drake-6.0.0/drake/R/mtcars_example.R                      |    3 
 drake-6.0.0/drake/R/package.R                             |    9 
 drake-6.0.0/drake/R/parLapply.R                           |    1 
 drake-6.0.0/drake/R/parallel.R                            |   14 
 drake-6.0.0/drake/R/parallel_ui.R                         |    3 
 drake-6.0.0/drake/R/predict_runtime.R                     |    2 
 drake-6.0.0/drake/R/priority_queue.R                      |    4 
 drake-6.0.0/drake/R/random.R                              |    8 
 drake-6.0.0/drake/R/read.R                                |   55 +
 drake-6.0.0/drake/R/sanitize.R                            |    1 
 drake-6.0.0/drake/R/sankey_drake_graph.R                  |    6 
 drake-6.0.0/drake/R/staged.R                              |   62 +
 drake-6.0.0/drake/R/test.R                                |    8 
 drake-6.0.0/drake/R/test_scenarios.R                      |    2 
 drake-6.0.0/drake/R/timestamp.R                           |    3 
 drake-6.0.0/drake/R/utils.R                               |   29 
 drake-6.0.0/drake/R/vis_drake_graph.R                     |   80 --
 drake-6.0.0/drake/inst/doc/drake.html                     |    4 
 drake-6.0.0/drake/inst/testing/knitr/test.Rmd             |    8 
 drake-6.0.0/drake/inst/testing/scenarios.csv              |    2 
 drake-6.0.0/drake/man/build_drake_graph.Rd                |    4 
 drake-6.0.0/drake/man/cmq_build.Rd                        |only
 drake-6.0.0/drake/man/cmq_staged_build.Rd                 |    2 
 drake-6.0.0/drake/man/code_to_plan.Rd                     |only
 drake-6.0.0/drake/man/dependency_profile.Rd               |   46 -
 drake-6.0.0/drake/man/deps.Rd                             |   24 
 drake-6.0.0/drake/man/deps_code.Rd                        |    9 
 drake-6.0.0/drake/man/deps_target.Rd                      |only
 drake-6.0.0/drake/man/deps_targets.Rd                     |   16 
 drake-6.0.0/drake/man/drake_config.Rd                     |   14 
 drake-6.0.0/drake/man/drake_ggraph.Rd                     |    2 
 drake-6.0.0/drake/man/drake_hpc_template_files.Rd         |    2 
 drake-6.0.0/drake/man/drake_plan_source.Rd                |only
 drake-6.0.0/drake/man/eager_load_target.Rd                |    9 
 drake-6.0.0/drake/man/evaluate_plan.Rd                    |    2 
 drake-6.0.0/drake/man/gather_by.Rd                        |only
 drake-6.0.0/drake/man/make.Rd                             |   14 
 drake-6.0.0/drake/man/readd.Rd                            |  137 +++
 drake-6.0.0/drake/man/reduce_by.Rd                        |only
 drake-6.0.0/drake/man/render_drake_ggraph.Rd              |    2 
 drake-6.0.0/drake/man/render_drake_graph.Rd               |    7 
 drake-6.0.0/drake/man/vis_drake_graph.Rd                  |    7 
 drake-6.0.0/drake/tests/testthat/test-Makefile.R          |    7 
 drake-6.0.0/drake/tests/testthat/test-cache.R             |   53 +
 drake-6.0.0/drake/tests/testthat/test-clustermq.R         |   42 -
 drake-6.0.0/drake/tests/testthat/test-console.R           |    6 
 drake-6.0.0/drake/tests/testthat/test-dependencies.R      |   95 +-
 drake-6.0.0/drake/tests/testthat/test-deprecate.R         |   14 
 drake-6.0.0/drake/tests/testthat/test-edge-cases.R        |   11 
 drake-6.0.0/drake/tests/testthat/test-full-build.R        |    2 
 drake-6.0.0/drake/tests/testthat/test-future.R            |    1 
 drake-6.0.0/drake/tests/testthat/test-generate.R          |  158 ++++
 drake-6.0.0/drake/tests/testthat/test-graph.R             |   14 
 drake-6.0.0/drake/tests/testthat/test-intermediate-file.R |   21 
 drake-6.0.0/drake/tests/testthat/test-knitr.R             |    2 
 drake-6.0.0/drake/tests/testthat/test-mtcars-example.R    |   18 
 drake-6.0.0/drake/tests/testthat/test-other-features.R    |   17 
 drake-6.0.0/drake/tests/testthat/test-parallel.R          |    2 
 drake-6.0.0/drake/tests/testthat/test-plans.R             |   69 +
 drake-6.0.0/drake/tests/testthat/test-random.R            |   19 
 drake-6.0.0/drake/tests/testthat/test-time.R              |    1 
 drake-6.0.0/drake/tests/testthat/test-triggers.R          |    8 
 drake-6.0.0/drake/tests/testthat/test-visuals.R           |   10 
 100 files changed, 1806 insertions(+), 790 deletions(-)

More information about drake at CRAN
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