Mon, 27 Jul 2020

New package scLink with initial version 1.0.0
Package: scLink
Title: Inferring Functional Gene Co-Expression Networks from Single Cell Data
Version: 1.0.0
Authors@R: person(given = "Wei Vivian", family = "Li", role = c("aut", "cre"), email = "vivian.li@rutgers.edu", comment = c(ORCID = "0000-0002-2087-2709"))
Description: Uses statistical network modeling to understand the co-expression relationships among genes and to construct sparse gene co-expression networks from single-cell gene expression data.
License: GPL-2
Depends: R (>= 3.5.0), parallel
Suggests: QUIC, knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-07-27 01:16:20 UTC; wei
Author: Wei Vivian Li [aut, cre] (<https://orcid.org/0000-0002-2087-2709>)
Maintainer: Wei Vivian Li <vivian.li@rutgers.edu>
Repository: CRAN
Date/Publication: 2020-07-28 02:40:03 UTC

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Package ztpln updated to version 0.1.1 with previous version 0.1.0 dated 2020-07-24

Title: Zero-Truncated Poisson Lognormal Distribution
Description: Functions for obtaining the density, random variates and maximum likelihood estimates of the Zero-truncated Poisson lognormal distribution and their mixture distribution.
Author: Masatoshi Katabuchi
Maintainer: Masatoshi Katabuchi <mattocci27@gmail.com>

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Package RBNZ updated to version 1.1.0 with previous version 1.0.1 dated 2020-04-10

Title: Download Data from the Reserve Bank of New Zealand Website
Description: Provides a convenient way of accessing data published by the Reserve Bank of New Zealand (RBNZ) on their website, <https://www.rbnz.govt.nz/statistics>. A range of financial and economic data is provided in spreadsheet format including exchange and interest rates, commercial lending statistics, Reserve Bank market operations, financial institution statistics, household financial data, New Zealand debt security information, and economic indicators. This package provides a method to download those spreadsheets and read them directly into R.
Author: Jasper Watson [aut, cre]
Maintainer: Jasper Watson <jasper.g.watson@gmail.com>

Diff between RBNZ versions 1.0.1 dated 2020-04-10 and 1.1.0 dated 2020-07-27

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Package nntrf updated to version 0.1.2 with previous version 0.1.1 dated 2020-07-21

Title: Supervised Data Transformation by Means of Neural Network Hidden Layer
Description: A supervised transformation of datasets is performed. The aim is similar to that of Principal Component Analysis (PCA), that is, to carry out data transformation and dimensionality reduction, but in a non-linear supervised way. This is achieved by first training a 3-layer Multi-Layer Perceptron and then using the activations of the hidden layer as a transformation of the input features. In fact, it takes advantage of the change of representation provided by the hidden layer of a neural network. This can be useful as data pre-processing for Machine Learning methods in general, specially for those that do not work well with many irrelevant or redundant features. Rumelhart, D.E., Hinton, G.E. and Williams, R.J. (1986) "Learning representations by back-propagating errors" <doi:10.1038/323533a0>.
Author: Ricardo Aler [aut, cre], Jose Valls [aut], Ines Galvan [aut], David Camacho [aut]
Maintainer: Ricardo Aler <ricardo.aler@uc3m.es>

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Package journalabbr updated to version 0.2.1 with previous version 0.2.0 dated 2020-07-26

Title: Journal Abbreviations for BibTeX Documents
Description: Since the reference management software (such as 'Zotero', 'Mendeley') exports Bib file journal abbreviation is not detailed enough, the 'journalabbr' package only abbreviates the journal field of Bib file, and then outputs a new Bib file for generating reference format with journal abbreviation on other software (such as 'texstudio'). The abbreviation table is from 'JabRef'. At the same time, 'Shiny' application is provided to generate 'thebibliography', a reference format that can be directly used for latex paper writing based on 'Rmd' files.
Author: ShuCai Zou [aut, cre], Yu Chen [aut]
Maintainer: ShuCai Zou <zscmoyujian@163.com>

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Package GermaParl updated to version 1.5.1 with previous version 1.5.0 dated 2020-07-24

Title: Download and Augment the Corpus of Plenary Protocols of the German Bundestag
Description: Data package to disseminate the 'GermaParl' corpus of parliamentary debates of the German Bundestag prepared in the 'PolMine Project'. The package includes a small subset of the corpus for demonstration and testing purposes. The package includes functionality to download the full corpus and supplementary data from the open science repository 'Zenodo'.
Author: Andreas Blaette [aut, cre], Christoph Leonhardt [ctb]
Maintainer: Andreas Blaette <andreas.blaette@uni-due.de>

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Package chicane updated to version 0.1.2 with previous version 0.1.1 dated 2019-10-01

Title: Capture Hi-C Analysis Engine
Description: Toolkit for processing and calling interactions in capture Hi-C data. Converts BAM files into counts of reads linking restriction fragments, and identifies pairs of fragments that interact more than expected by chance. Significant interactions are identified by comparing the observed read count to the expected background rate from a count regression model.
Author: Erle Holgersen [aut, cre], Olivia Leavy [aut], Olivia Fletcher [aut], Frank Dudbridge [aut], Syed Haider [aut]
Maintainer: Erle Holgersen <erle.holgersen@gmail.com>

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New package ascii with initial version 2.3
Package: ascii
Maintainer: Mark Clements <mark.clements@ki.se>
License: GPL (>= 2)
Title: Export R Objects to Several Markup Languages
Type: Package
Authors@R: c(person("David", "Hajage", role="aut", email="dhajage@gmail.com"), person("Mark", "Clements", role=c("cre","ctb"), email="mark.clements@ki.se"), person("Seth", "Falcon", role="ctb", email="seth@userprimary.net"), person("Terry", "Therneau", role="ctb", email="therneau.terry@mayo.edu"), person("Matti","Pastell", role="ctb"), person("Friedrich", "Leisch", role="ctb"))
Description: Coerce R object to 'asciidoc', 'txt2tags', 'restructuredText', 'org', 'textile' or 'pandoc' syntax. Package comes with a set of drivers for 'Sweave'.
Version: 2.3
URL: http://github.com/mclements/ascii
BugReports: http://github.com/mclements/ascii/issues
Date: 2020-07-27
Depends: R (>= 2.13), methods
Imports: utils, digest, codetools, survival, stats, grDevices
Suggests: Hmisc, xtable, R2HTML, knitr
Collate: 'asciiAnova.r' 'asciiDataFrame.r' 'asciiDefault.r' 'asciiDensity.r' 'asciiDescr.r' 'asciiEpi.r' 'asciiGlm.r' 'asciiHmisc.r' 'asciiHtest.r' 'asciiList.r' 'asciiLm.r' 'asciiMatrix.r' 'asciiMemisc.r' 'asciiPrcomp.r' 'asciiSmoothSpline.r' 'asciiSummaryTable.r' 'asciiSurvival.r' 'asciiTable.r' 'asciiTs.r' 'asciiVector.r' 'bind.r' 'cbind.r' 'export.r' 'generic.r' 'groups.r' 'interleave.r' 'paste.matrix.r' 'plim.r' 'print.character.matrix.r' 'RweaveAscii.r' 'show.asciidoc.r' 'show.org.r' 'show.pandoc.r' 'show.r' 'show.rest.r' 'show.t2t.r' 'show.textile.r' 'SweaveAscii.r' 'tocharac.r' 'weaverAscii.r' 'zzz.r' 'print.r' 'cache_expr.R' 'weaver.R' 'unexported.R'
RoxygenNote: 7.0.2
NeedsCompilation: no
Packaged: 2020-07-27 20:52:53 UTC; marcle
Author: David Hajage [aut], Mark Clements [cre, ctb], Seth Falcon [ctb], Terry Therneau [ctb], Matti Pastell [ctb], Friedrich Leisch [ctb]
Repository: CRAN
Date/Publication: 2020-07-27 23:50:02 UTC

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Package listdown updated to version 0.2.21 with previous version 0.2.20 dated 2020-07-15

Title: Create R Markdown from Lists
Description: Programmatically create R Markdown documents from lists.
Author: Michael J. Kane [aut, cph, cre] (<https://orcid.org/0000-0003-1899-6662>)
Maintainer: Michael J. Kane <michael.kane@yale.edu>

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Package statar updated to version 0.7.2 with previous version 0.7.1 dated 2019-07-05

Title: Tools Inspired by 'Stata' to Manipulate Tabular Data
Description: A set of tools inspired by 'Stata' to explore data.frames ('summarize', 'tabulate', 'xtile', 'pctile', 'binscatter', elapsed quarters/month, lead/lag).
Author: Matthieu Gomez [aut, cre]
Maintainer: Matthieu Gomez <mg3901@columbia.edu>

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Package effectsize updated to version 0.3.2 with previous version 0.3.1 dated 2020-05-19

Title: Indices of Effect Size and Standardized Parameters
Description: Provide utilities to work with indices of effect size and standardized parameters for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), allowing computation and conversion of indices such as Cohen's d, r, odds, etc.
Author: Mattan S. Ben-Shachar [aut, cre] (<https://orcid.org/0000-0002-4287-4801>), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Ken Kelley [ctb], David Stanley [ctb]
Maintainer: Mattan S. Ben-Shachar <matanshm@post.bgu.ac.il>

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Package do updated to version 1.4.0.0 with previous version 1.3.0.0 dated 2020-06-30

Title: Data Operator
Description: Flexibly convert data between long and wide format using just two functions: reshape_toLong() and reshape_toWide().
Author: Jing Zhang, Zhi Jin
Maintainer: Jing Zhang<zj391120@163.com>

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Package rvmethod updated to version 0.1.1 with previous version 0.1.0 dated 2020-06-04

Title: Radial Velocity Method for Detecting Exoplanets
Description: Has various functions designed to implement the Hermite-Gaussian Radial Velocity (HGRV) estimation approach of Holzer et al. (2020) <arXiv:2005.14083>, which is a particular application of the radial velocity method for detecting exoplanets. The overall approach consists of four sequential steps, each of which has a function in this package: (1) estimate the template spectrum with the function estimate_template(), (2) find absorption features in the estimated template with the function findabsorptionfeatures(), (3) fit Gaussians to the absorption features with the function Gaussfit(), (4) apply the HGRV with simple linear regression by calling the function hgrv(). This package is meant to be open source. But please cite the paper Holzer et al. (2020) <arXiv:2005.14083> when publishing results that use this package.
Author: Parker Holzer
Maintainer: Parker Holzer <parker.holzer@yale.edu>

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Package bda updated to version 15.0.2 with previous version 14.3.19 dated 2020-03-30

Title: Binned Data Analysis
Description: Algorithms developed for binned data analysis, gene expression data analysis and measurement error models for ordinal data analysis.
Author: Bin Wang <bwang831@gmail.com>
Maintainer: Bin Wang <bwang831@gmail.com>

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Package ropenaq updated to version 0.2.10 with previous version 0.2.9 dated 2020-03-26

Title: Accesses Air Quality Data from the Open Data Platform OpenAQ
Description: Allows access to air quality data from the API of the OpenAQ platform <https://docs.openaq.org/>, with the different services the API offers (getting measurements for a given query, getting latest measurements, getting lists of available countries/cities/locations).
Author: Maëlle Salmon [aut, cre], Andrew MacDonald [rev] (Andrew MacDonald reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/24), Andy Teucher [rev] (Andy Teucher reviewed the package for rOpenSci, see https://github.com/ropensci/software-review/issues/24), Mikayla Murphy [ctb]
Maintainer: Maëlle Salmon <maelle.salmon@yahoo.se>

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Package implicitMeasures updated to version 0.2.0 with previous version 0.1.3 dated 2020-05-28

Title: Compute Scores for Different Implicit Measures
Description: A tool for computing the scores for the Implicit Association Test (IAT; Greenwald, McGhee & Schwartz (1998) <doi:10.1037/0022-3514.74.6.1464>) and the Single Category-IAT (SC-IAT: Karpinski & Steinman (2006) <doi:10.1037/0022-3514.91.1.16>). Functions for preparing the data (both for the IAT and the SC-IAT), plotting the results, and obtaining a table with the scores of implicit measures descriptive statistics are provided.
Author: Ottavia M. Epifania [aut, cre], Pasquale Anselmi [ctb], Egidio Robusto [ctb]
Maintainer: Ottavia M. Epifania <otta.epifania@gmail.com>

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Package VOSONDash updated to version 0.5.7 with previous version 0.5.4 dated 2020-05-20

Title: User Interface for Collecting and Analysing Social Networks
Description: A 'Shiny' application for the interactive visualisation and analysis of networks that also provides a web interface for collecting social media data using 'vosonSML'.
Author: Bryan Gertzel, Robert Ackland
Maintainer: Bryan Gertzel <bryan.gertzel@anu.edu.au>

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New package arenar with initial version 0.1.8
Package: arenar
Title: Arena for the Exploration and Comparison of any ML Models
Version: 0.1.8
Authors@R: c(person("Piotr", "Piątyszek", role = c("aut", "cre"), email = "piotrp@wektor.xyz"), person("Przemyslaw", "Biecek", role = c("aut"), comment = c(ORCID = "0000-0001-8423-1823")))
Description: Generates data for challenging machine learning models in 'Arena' <https://arena.drwhy.ai> - an interactive web application. You can start the server with XAI (Explainable Artificial Intelligence) plots to be generated on-demand or precalculate and auto-upload data file beside shareable 'Arena' URL.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.0
Depends: R (>= 3.6)
Imports: ingredients, iBreakDown, gistr, jsonlite, plumber, parallel, utils, stats, methods, auditor, DALEX (>= 1.3.0)
Suggests: testthat, knitr, rmarkdown, dplyr, pkgdown, covr, ranger
VignetteBuilder: knitr
URL: https://arenar.drwhy.ai, https://github.com/ModelOriented/ArenaR
BugReports: https://github.com/ModelOriented/ArenaR/issues
NeedsCompilation: no
Packaged: 2020-07-22 01:29:42 UTC; piotrp
Author: Piotr Piątyszek [aut, cre], Przemyslaw Biecek [aut] (<https://orcid.org/0000-0001-8423-1823>)
Maintainer: Piotr Piątyszek <piotrp@wektor.xyz>
Repository: CRAN
Date/Publication: 2020-07-27 13:10:02 UTC

More information about arenar at CRAN
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New package runonce with initial version 0.2.2
Package: runonce
Title: Run Once and Save Result
Version: 0.2.2
Authors@R: person(given = "Florian", family = "Privé", role = c("aut", "cre"), email = "florian.prive.21@gmail.com")
Description: Package 'runonce' helps automating the saving of long-running code to help running the same code multiple times. If you run some long-running code once, it saves the result in a file on disk. Then, if the result already exists, i.e. if the code has already been run and its output has already been saved, it just read the result from the stored file instead of running the code again.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.0.2
Imports: bigassertr, urltools
Suggests: testthat (>= 2.1.0)
URL: https://github.com/privefl/runonce
BugReports: https://github.com/privefl/runonce/issues
NeedsCompilation: no
Packaged: 2020-07-14 11:31:24 UTC; au639593
Author: Florian Privé [aut, cre]
Maintainer: Florian Privé <florian.prive.21@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-27 12:00:02 UTC

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New package image.Otsu with initial version 0.1
Package: image.Otsu
Type: Package
Title: Otsu's Image Segmentation Method
Description: An implementation of the Otsu's Image Segmentation Method described in the paper: "A C++ Implementation of Otsu's Image Segmentation Method". The algorithm is explained at <doi:10.5201/ipol.2016.158>.
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be", comment = "R wrapper"), person("BNOSAC", role = "cph", comment = "R wrapper"), person("Juan Pablo Balarini", role = c("ctb", "cph"), comment = "Otsu C++ code"), person("Sergio Nesmachnow", role = c("ctb", "cph"), comment = "Otsu C++ code"))
License: MIT + file LICENSE
Version: 0.1
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.8)
LinkingTo: Rcpp
Suggests: magick
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-20 19:44:04 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Juan Pablo Balarini [ctb, cph] (Otsu C++ code), Sergio Nesmachnow [ctb, cph] (Otsu C++ code)
Repository: CRAN
Date/Publication: 2020-07-27 12:30:10 UTC

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New package image.LineSegmentDetector with initial version 0.1.0
Package: image.LineSegmentDetector
Type: Package
Title: Detect Line Segments in Images
Description: An implementation of the Line Segment Detector on digital images described in the paper: "LSD: A Fast Line Segment Detector with a False Detection Control" by Rafael Grompone von Gioi et al (2012). The algorithm is explained at <doi:10.5201/ipol.2012.gjmr-lsd>.
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be", comment = "R wrapper"), person("BNOSAC", role = "cph", comment = "R wrapper"), person("Rafael Grompone von Gioi", role = c("ctb", "cph"), email = "grompone@gmail.com", comment = "src/lsd"))
License: AGPL-3
Version: 0.1.0
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.8), sp
LinkingTo: Rcpp
Suggests: pixmap, magick
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-20 15:42:54 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Rafael Grompone von Gioi [ctb, cph] (src/lsd)
Repository: CRAN
Date/Publication: 2020-07-27 12:30:13 UTC

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New package image.libfacedetection with initial version 0.1
Package: image.libfacedetection
Type: Package
Title: Convolutional Neural Network for Face Detection
Description: An open source library for face detection in images. Provides a pretrained convolutional neural network based on <https://github.com/ShiqiYu/libfacedetection> which can be used to detect faces which have size greater than 10x10 pixels.
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be", comment = "R wrapper"), person("BNOSAC", role = "cph", comment = "R wrapper"), person("Shiqi Yu", role = c("ctb", "cph"), comment = "libfacedetection C++ code"))
License: BSD_3_clause + file LICENSE
Version: 0.1
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.8), graphics
LinkingTo: Rcpp
Suggests: magick
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-22 08:05:55 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Shiqi Yu [ctb, cph] (libfacedetection C++ code)
Repository: CRAN
Date/Publication: 2020-07-27 12:30:03 UTC

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New package image.dlib with initial version 0.1.0
Package: image.dlib
Type: Package
Title: Image Processing Functionality using the 'dlib' Package
Version: 0.1.0
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be", comment = "R wrapper"), person("BNOSAC", role = "cph", comment = "R wrapper"), person("Davis E. King", role = c("ctb", "cph"), comment = "Main contributor of dlib - files in inst/dlib"), person("dlib authors", role = c("ctb", "cph"), comment = "see file AUTHORS"))
Description: Facility wrappers around the image processing functionality of 'dlib'. 'Dlib' <http://dlib.net> is a 'C++' toolkit containing machine learning algorithms and computer vision tools. Currently the package allows to find feature descriptors of digital images, in particular 'SURF' and 'HOG' descriptors.
License: BSL-1.0
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.9)
LinkingTo: Rcpp
Suggests: magick, FNN
SystemRequirements: C++11
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-23 15:51:20 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Davis E. King [ctb, cph] (Main contributor of dlib - files in inst/dlib), dlib authors [ctb, cph] (see file AUTHORS)
Repository: CRAN
Date/Publication: 2020-07-27 12:40:03 UTC

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New package image.CornerDetectionHarris with initial version 0.1.0
Package: image.CornerDetectionHarris
Type: Package
Title: Implementation of the Harris Corner Detection for Images
Description: An implementation of the Harris Corner Detection as described in the paper "An Analysis and Implementation of the Harris Corner Detector" by Sánchez J. et al (2018) available at <doi:10.5201/ipol.2018.229>. The package allows to detect relevant points in images which are characteristic to the digital image.
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be", comment = "R wrapper"), person("BNOSAC", role = "cph", comment = "R wrapper"), person("Javier Sánchez Pérez", role = c("ctb", "cph"), comment = "Harris Corner Detector C/C++ code"), person("Pascal Getreuer", role = c("ctb", "cph"), comment = "src/gaussian.cpp"))
License: BSD_2_clause + file LICENSE
Version: 0.1.0
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.8)
LinkingTo: Rcpp
Suggests: magick
RoxygenNote: 7.1.0
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2020-07-20 14:17:52 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Javier Sánchez Pérez [ctb, cph] (Harris Corner Detector C/C++ code), Pascal Getreuer [ctb, cph] (src/gaussian.cpp)
Repository: CRAN
Date/Publication: 2020-07-27 12:30:17 UTC

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New package image.CornerDetectionF9 with initial version 0.1.0
Package: image.CornerDetectionF9
Type: Package
Title: Find Corners in Digital Images with FAST-9
Version: 0.1.0
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be"), person("BNOSAC", role = "cph"), person("Julien Cayzac", role = c("ctb", "cph")))
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Description: An implementation of the "FAST-9" corner detection algorithm explained in the paper 'FASTER and better: A machine learning approach to corner detection' by Rosten E., Porter R. and Drummond T. (2008), available at <arXiv:0810.2434>. The package allows to detect corners in digital images.
License: BSD_2_clause + file LICENSE
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.8)
Suggests: pixmap, magick
LinkingTo: Rcpp
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-21 08:01:18 UTC; Jan
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Julien Cayzac [ctb, cph]
Repository: CRAN
Date/Publication: 2020-07-27 12:30:21 UTC

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New package image.ContourDetector with initial version 0.1.0
Package: image.ContourDetector
Type: Package
Title: Implementation of the Unsupervised Smooth Contour Line Detection for Images
Description: An implementation of the Unsupervised Smooth Contour Detection algorithm for digital images as described in the paper: "Unsupervised Smooth Contour Detection" by Rafael Grompone von Gioi, and Gregory Randall (2016). The algorithm is explained at <doi:10.5201/ipol.2016.175>.
Maintainer: Jan Wijffels <jwijffels@bnosac.be>
Authors@R: c( person("Jan", "Wijffels", role = c("aut", "cre", "cph"), email = "jwijffels@bnosac.be", comment = "R wrapper"), person("BNOSAC", role = "cph", comment = "R wrapper"), person("Rafael Grompone von Gioi", role = c("ctb", "cph"), email = "grompone@gmail.com", comment = "src/smooth_contours"), person("Gregory Randall", role = c("ctb", "cph"), email = "randall@fing.edu.uy", comment = "src/smooth_contours"))
License: AGPL-3
Version: 0.1.0
URL: https://github.com/bnosac/image
Imports: Rcpp (>= 0.12.8), sp
LinkingTo: Rcpp
Suggests: pixmap, magick
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2020-07-20 15:45:31 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), BNOSAC [cph] (R wrapper), Rafael Grompone von Gioi [ctb, cph] (src/smooth_contours), Gregory Randall [ctb, cph] (src/smooth_contours)
Repository: CRAN
Date/Publication: 2020-07-27 12:30:24 UTC

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New package image.binarization with initial version 0.1.0
Package: image.binarization
Type: Package
Title: Binarize Images for Enhancing Optical Character Recognition
Version: 0.1.0
Maintainer: Jan Wijffels <jan.wijffels@vub.be>
Authors@R: c( person('Jan', 'Wijffels', role = c('aut', 'cre', 'cph'), email = 'jan.wijffels@vub.be', comment = "R wrapper"), person('Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities', role = 'cph', comment = "R wrapper"), person('Brandon M. Petty', role = c('ctb', 'cph'), comment = "Files in src/Doxa"))
Description: Improve optical character recognition by binarizing images. The package focuses primarily on local adaptive thresholding algorithms. In English, this means that it has the ability to turn a color or gray scale image into a black and white image. This is particularly useful as a preprocessing step for optical character recognition or handwritten text recognition.
License: MPL-2.0
URL: https://github.com/DIGI-VUB/image.binarization
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: Rcpp, magick, grDevices
LinkingTo: Rcpp
RoxygenNote: 7.1.0
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2020-07-20 10:30:32 UTC; Jan
Author: Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Brandon M. Petty [ctb, cph] (Files in src/Doxa)
Repository: CRAN
Date/Publication: 2020-07-27 12:30:07 UTC

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New package nortsTest with initial version 1.0.0
Package: nortsTest
Title: Assessing Normality of Stationary Process
Version: 1.0.0
Authors@R: c( person("Asael","Alonzo Matamoros", role = c("aut", "cre"),email = "asael.alonzo@gmail.com"), person("Alicia","Nieto-Reyes", role = 'aut', email = "alicia.nieto@unican.es"), person("Rob", "Hyndman", email="Rob.Hyndman@monash.edu", role = "ctb"), person("Mitchell", "O'Hara-Wild", role = "ctb"), person("Trapletti", "A.", role = "ctb") )
Description: Despite that several tests for normality in stationary processes have been proposed in the literature, consistent implementations of these tests in programming languages are limited. Four normality test are implemented. The Lobato and Velasco's, Epps, Psaradakis and Vavra, and the random projections tests for stationary process. Some other diagnostics such as, unit root test for stationarity, seasonal tests for seasonality, and arch effect test for volatility; are also performed. The package also offers residual diagnostic for linear time series models developed in several packages.
License: LGPL
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 7.1.0
Depends: R (>= 3.5.0), methods
Imports: forecast, nortest, ggplot2, gridExtra, tseries, uroot, MASS, zoo
URL: https://github.com/asael697/nortsTest
BugReports: https://github.com/asael697/nortsTest/issues
Packaged: 2020-07-15 15:55:37 UTC; asael
Author: Asael Alonzo Matamoros [aut, cre], Alicia Nieto-Reyes [aut], Rob Hyndman [ctb], Mitchell O'Hara-Wild [ctb], Trapletti A. [ctb]
Maintainer: Asael Alonzo Matamoros <asael.alonzo@gmail.com>
Repository: CRAN
Date/Publication: 2020-07-27 11:50:03 UTC

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Package ggeffects updated to version 0.15.1 with previous version 0.15.0 dated 2020-06-16

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The main functions are ggpredict(), ggemmeans() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between ggeffects versions 0.15.0 dated 2020-06-16 and 0.15.1 dated 2020-07-27

 DESCRIPTION                                      |   14 
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 NEWS.md                                          |   12 
 R/efc.R                                          |   13 
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 R/get_predictions_mclogit.R                      |only
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 tests/testthat/test-rstanarm-ppd.R               |    4 
 tests/testthat/test-rstanarm.R                   |    4 
 tests/testthat/test-zeroinfl.R                   |    4 
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 40 files changed, 1888 insertions(+), 1589 deletions(-)

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New package utilityFunctionTools with initial version 0.1.0
Package: utilityFunctionTools
Type: Package
Title: P-Spline Regression for Utility Functions and Derived Measures
Description: Predicts a smooth and continuous (individual) utility function from utility points, and computes measures of intensity for risk and higher order risk measures (or any other measure computed with user-written function) based on this utility function and its derivatives according to the method introduced in Schneider (2017) <http://hdl.handle.net/11858/00-1735-0000-002E-E306-0>.
Version: 0.1.0
Authors@R: c( person("Sebastian O.", "Schneider", email = "sschneider@coll.mpg.de", role = c("aut", "cre", "prg")), person("Giulia", "Baldini", email = "giulia.baldini@uni-bonn.de", role = c("edt", "prg")), person("Paul", "Eilers", comment = "Functions tpower and bbase, see Package JOPS at http://statweb.lsu.edu/faculty/marx/JOPS_0.1.0.tar.gz", role = "ctb"))
Maintainer: Sebastian O. Schneider <sschneider@coll.mpg.de>
URL: http://www.sebastianschneider.eu
License: GPL-3
Imports: spatstat
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-07-21 13:29:31 UTC; schneider
Author: Sebastian O. Schneider [aut, cre, prg], Giulia Baldini [edt, prg], Paul Eilers [ctb] (Functions tpower and bbase, see Package JOPS at http://statweb.lsu.edu/faculty/marx/JOPS_0.1.0.tar.gz)
Repository: CRAN
Date/Publication: 2020-07-27 09:40:02 UTC

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Package rstan updated to version 2.21.2 with previous version 2.21.1 dated 2020-07-08

Title: R Interface to Stan
Description: User-facing R functions are provided to parse, compile, test, estimate, and analyze Stan models by accessing the header-only Stan library provided by the 'StanHeaders' package. The Stan project develops a probabilistic programming language that implements full Bayesian statistical inference via Markov Chain Monte Carlo, rough Bayesian inference via 'variational' approximation, and (optionally penalized) maximum likelihood estimation via optimization. In all three cases, automatic differentiation is used to quickly and accurately evaluate gradients without burdening the user with the need to derive the partial derivatives.
Author: Jiqiang Guo [aut], Jonah Gabry [aut], Ben Goodrich [cre, aut], Sebastian Weber [aut], Daniel Lee [ctb], Krzysztof Sakrejda [ctb], Modrak Martin [ctb], Trustees of Columbia University [cph], Oleg Sklyar [cph] (R/cxxfunplus.R), The R Core Team [cph] (R/pairs.R, R/dynGet.R), Jens Oehlschlaegel-Akiyoshi [cph] (R/pairs.R), John Maddock [cph] (gamma.hpp), Paul Bristow [cph] (gamma.hpp), Nikhar Agrawal [cph] (gamma.hpp), Christopher Kormanyos [cph] (gamma.hpp), Bronder Steve [ctb]
Maintainer: Ben Goodrich <benjamin.goodrich@columbia.edu>

Diff between rstan versions 2.21.1 dated 2020-07-08 and 2.21.2 dated 2020-07-27

 DESCRIPTION                   |   17 ++--
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Package easySdcTable updated to version 0.6.0 with previous version 0.5.0 dated 2020-04-04

Title: Easy Interface to the Statistical Disclosure Control Package 'sdcTable'
Description: The main function, ProtectTable(), performs table suppression according to a frequency rule with a data set as the only required input. Within this function, protectTable(), protectLinkedTables() or runArgusBatchFile() in package 'sdcTable' is called. Lists of level-hierarchy (parameter 'dimList') and other required input to these functions are created automatically. The function, PTgui(), starts a graphical user interface based on the shiny package.
Author: Øyvind Langsrud [aut, cre]
Maintainer: Øyvind Langsrud <oyl@ssb.no>

Diff between easySdcTable versions 0.5.0 dated 2020-04-04 and 0.6.0 dated 2020-07-27

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 NAMESPACE                          |    1 
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 man/sosialFiktiv.Rd                |   40 +-
 tests/testthat/test-ProtectTable.R |   43 ++
 19 files changed, 986 insertions(+), 750 deletions(-)

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Package ctrdata updated to version 1.3.0 with previous version 1.2.1 dated 2020-05-18

Title: Retrieve and Analyze Clinical Trials in Public Registers
Description: Provides functions for querying, retrieving and analysing protocol- and results-related information on clinical trials from two public registers, the European Union Clinical Trials Register (EUCTR, <https://www.clinicaltrialsregister.eu/>) and ClinicalTrials.gov (CTGOV, <https://clinicaltrials.gov/>). The information is transformed and then stored in a database (nodbi). Functions are provided for accessing and analysing the locally stored information on the clinical trials, as well as for identifying duplicate records. The package is motivated by the need for aggregating and trend-analysing the design, conduct and outcomes across clinical trials.
Author: Ralf Herold [aut, cre] (<https://orcid.org/0000-0002-8148-6748>)
Maintainer: Ralf Herold <ralf.herold@mailbox.org>

Diff between ctrdata versions 1.2.1 dated 2020-05-18 and 1.3.0 dated 2020-07-27

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Package stormwindmodel updated to version 0.1.4 with previous version 0.1.3 dated 2020-04-01

Title: Model Tropical Cyclone Wind Speeds
Description: Allows users to input tracking data for a hurricane or other tropical storm, along with a data frame of grid points at which to model wind speeds. Functions in this package will then calculate wind speeds at each point based on wind model equations. This modeling framework is currently set up to model winds for North American locations with Atlantic basin storms. This work was supported in part by grants from the National Institute of Environmental Health Sciences (R00ES022631), the National Science Foundation (1331399), and the Department of Energy (DE-FG02-08ER64644).
Author: Brooke Anderson [aut, cre], Andrea Schumacher [aut], Seth Guikema [aut], Steven Quiring [aut], Joshua Ferreri [aut], Andrea Staid [ctb], Michael Guo [ctb], Lei Ming [ctb], Laiyin Zhu [ctb]
Maintainer: Brooke Anderson <brooke.anderson@colostate.edu>

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Package see updated to version 0.5.2 with previous version 0.5.1 dated 2020-06-13

Title: Visualisation Toolbox for 'easystats' and Extra Geoms, Themes and Color Palettes for 'ggplot2'
Description: Provides plotting utilities supporting easystats-packages (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://www.materialui.co/colors>.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, inv] (<https://orcid.org/0000-0001-5375-9967>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package ChannelAttribution updated to version 2.0.2 with previous version 2.0.1 dated 2020-07-14

Title: Markov Model for Online Multi-Channel Attribution
Description: Advertisers use a variety of online marketing channels to reach consumers and they want to know the degree each channel contributes to their marketing success. This is called online multi-channel attribution problem. This package contains a probabilistic algorithm for the attribution problem. The model uses a k-order Markov representation to identify structural correlations in the customer journey data. The package also contains three heuristic algorithms (first-touch, last-touch and linear-touch approach) for the same problem. The algorithms are implemented in C++.
Author: Davide Altomare, David Loris
Maintainer: Davide Altomare <info@channelattribution.net>

Diff between ChannelAttribution versions 2.0.1 dated 2020-07-14 and 2.0.2 dated 2020-07-27

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New package PGRdup with initial version 0.2.3.6
Package: PGRdup
Title: Discover Probable Duplicates in Plant Genetic Resources Collections
Version: 0.2.3.6
Authors@R: c( person(given = "J.", family = "Aravind", email = "j.aravind@icar.gov.in", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4791-442X")), person(given = "J.", family = "Radhamani", email = "jalli.radhamani@icar.gov.in", role = "aut"), person(family = c("Kalyani Srinivasan"), email = "kalyani.srinivasan@icar.gov.in", role = "aut"), person(given = "B.", family = c("Ananda Subhash"), email = "anandasubhash@gmail.com", role = "aut"), person(given = c("Rishi", "Kumar"), family = "Tyagi", email = "rishi.tyagi@icar.gov.in", role = "aut"), person("ICAR-NBGPR", role = "cph", comment = c(url = "www.nbpgr.ernet.in")), person(given = "Maurice", family = "Aubrey", email = "maurice@hevanet.com", comment = "Double Metaphone", role = "ctb"), person(given = "Kevin", family = "Atkinson", email = "kevina@users.sourceforge.net", comment = "Double Metaphone", role = "ctb"), person(given = "Lawrence", family = "Philips", comment = "Double Metaphone", role = "ctb"))
Description: Provides functions to aid the identification of probable/possible duplicates in Plant Genetic Resources (PGR) collections using 'passport databases' comprising of information records of each constituent sample. These include methods for cleaning the data, creation of a searchable Key Word in Context (KWIC) index of keywords associated with sample records and the identification of nearly identical records with similar information by fuzzy, phonetic and semantic matching of keywords.
Depends: R (>= 3.0.2)
Imports: data.table (>= 1.9.3), igraph, stringdist (>= 0.9.4), stringi, ggplot2, grid, gridExtra, methods, utils, stats
Suggests: diagram, wordcloud, microbenchmark, XML, knitr, rmarkdown, pander
Copyright: 2014-2020, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: latin1
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
URL: https://cran.r-project.org/package=PGRdup, https://github.com/aravind-j/PGRdup, https://doi.org/10.5281/zenodo.841963, https://aravind-j.github.io/PGRdup/, https://www.rdocumentation.org/packages/PGRdup
BugReports: https://github.com/aravind-j/PGRdup/issues
NeedsCompilation: yes
Packaged: 2020-07-26 11:58:37 UTC; J. Aravind
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), J. Radhamani [aut], Kalyani Srinivasan [aut], B. Ananda Subhash [aut], Rishi Kumar Tyagi [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in), Maurice Aubrey [ctb] (Double Metaphone), Kevin Atkinson [ctb] (Double Metaphone), Lawrence Philips [ctb] (Double Metaphone)
Maintainer: J. Aravind <j.aravind@icar.gov.in>
Repository: CRAN
Date/Publication: 2020-07-27 06:40:11 UTC

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Package NlinTS updated to version 1.4.1 with previous version 1.4.0 dated 2020-07-21

Title: Models for Non Linear Causality Detection in Time Series
Description: Models for non-linear time series analysis and causality detection. The main functionalities of this package consist of an implementation of the classical causality test (C.W.J.Granger 1980) <doi:10.1016/0165-1889(80)90069-X>, and a non-linear version of it based on feed-forward neural networks. This package contains also an implementation of the Transfer Entropy <doi:10.1103/PhysRevLett.85.461>, and the continuous Transfer Entropy using an approximation based on the k-nearest neighbors <doi:10.1103/PhysRevE.69.066138>. There are also some other useful tools, like the VARNN (Vector Auto-Regressive Neural Network) prediction model, the Augmented test of stationarity, and the discrete and continuous entropy and mutual information.
Author: Youssef Hmamouche [aut, cre]
Maintainer: Youssef Hmamouche <hmamoucheyussef@gmail.com>

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Package mlma updated to version 5.1-0 with previous version 5.0-0 dated 2020-05-08

Title: Multilevel Mediation Analysis
Description: Do multilevel mediation analysis with generalized additive multilevel models. The analysis method is described in Yu and Li (2020), "Third-Variable Effect Analysis with Multilevel Additive Models", submitted.
Author: Qingzhao Yu, Bin Li
Maintainer: Qingzhao Yu <qyu@lsuhsc.edu>

Diff between mlma versions 5.0-0 dated 2020-05-08 and 5.1-0 dated 2020-07-27

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Package icpsrdata updated to version 0.5.0 with previous version 0.4.0 dated 2019-05-24

Title: Reproducible Data Retrieval from the ICPSR Archive
Description: Reproducible, programmatic retrieval of datasets from the Inter-university Consortium for Political and Social Research archive.
Author: Frederick Solt [aut, cre, cph], Kellen Gracey [aut], Eric Persson [ctb], Joanna Pepin [ctb], J. Hathaway [ctb], Jennifer Lin [ctb], John Bulloch [ctb]
Maintainer: Frederick Solt <frederick-solt@uiowa.edu>

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New package gravity with initial version 0.9.9
Package: gravity
Type: Package
Title: Estimation Methods for Gravity Models
Version: 0.9.9
Authors@R: c( person("Anna-Lena", "Woelwer", role = c("aut", "cph"), email = "woelwer@uni-trier.de"), person("Jan Pablo", "Burgard", role = c("aut", "cph"), email = "burgardj@uni-trier.de"), person("Joshua", "Kunst", role = c("aut", "cph"), email = "jbkunst@gmail.com"), person("Mauricio", "Vargas", role = c("aut","cre","cph"), email = "mvargas@dcc.uchile.cl", comment = c(ORCID = "0000-0003-1017-7574")), person("Romain", "Francois", role = "ctb", email = "romain@purrple.cat", comment = "adapted parts of the code to use dplyr 0.8.0"), person("Lionel", "Henry", role = c("ctb"), email = "lionel@rstudio.com", comment = "simplified parts of the code"), person("Hrisyana", "Doytchinova", role = c("rev"), email = "hrisyana.doytchinova@un.org", comment = "sent us different suggestions and bug reports") )
Description: A wrapper of different standard estimation methods for gravity models. This package provides estimation methods for log-log models and multiplicative models.
URL: http://pachamaltese.github.io/gravity
BugReports: https://github.com/pachamaltese/gravity/issues
Imports: lmtest, sandwich, glm2, MASS, stats, censReg, survival, multiwayvcov, tibble, magrittr, dplyr, tidyr, purrr, rlang, Rdpack, utils
RdMacros: Rdpack
Depends: R(>= 3.4.0)
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, testthat, broom
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-07-27 02:35:53 UTC; pacha
Author: Anna-Lena Woelwer [aut, cph], Jan Pablo Burgard [aut, cph], Joshua Kunst [aut, cph], Mauricio Vargas [aut, cre, cph] (<https://orcid.org/0000-0003-1017-7574>), Romain Francois [ctb] (adapted parts of the code to use dplyr 0.8.0), Lionel Henry [ctb] (simplified parts of the code), Hrisyana Doytchinova [rev] (sent us different suggestions and bug reports)
Maintainer: Mauricio Vargas <mvargas@dcc.uchile.cl>
Repository: CRAN
Date/Publication: 2020-07-27 06:40:02 UTC

More information about gravity at CRAN
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New package augmentedRCBD with initial version 0.1.3
Package: augmentedRCBD
Title: Analysis of Augmented Randomised Complete Block Designs
Version: 0.1.3
Authors@R: c( person(given = "J.", family = "Aravind", email = "j.aravind@icar.gov.in", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-4791-442X")), person(given = "S.", family = "Mukesh Sankar", email = "mukeshsankar@gmail.com", role = "aut"), person(given = c("Dhammaprakash", "Pandhari"), family = "Wankhede", email = "d.wankhede@icar.gov.in", role = "aut", comment = c(ORCID = "0000-0001-6384-8664")), person(given = "Vikender", family = "Kaur", email = "vikender.kaur@icar.gov.in", role = "aut"), person("ICAR-NBGPR", role = c("cph"), comment = c(url = "www.nbpgr.ernet.in")))
Description: Functions for analysis of data generated from experiments in augmented randomised complete block design according to Federer, W.T. (1961) <doi:10.2307/2527837>. Computes analysis of variance, adjusted means, descriptive statistics, genetic variability statistics etc. Further includes data visualization and report generation functions.
Copyright: 2015-2018, ICAR-NBPGR
License: GPL-2 | GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.0.1)
VignetteBuilder: knitr
RoxygenNote: 7.1.1
URL: https://github.com/aravind-j/augmentedRCBD https://CRAN.R-project.org/package=augmentedRCBD https://aravind-j.github.io/augmentedRCBD https://doi.org/10.5281/zenodo.1310011
BugReports: https://github.com/aravind-j/augmentedRCBD/issues
Imports: emmeans, dplyr, flextable, ggplot2, grDevices, methods, moments, multcomp, multcompView, Rdpack, stats, stringi, officer, reshape2, utils
Suggests: knitr, rmarkdown, pander, testthat
RdMacros: Rdpack
NeedsCompilation: no
Packaged: 2020-07-26 17:42:29 UTC; J. Aravind
Author: J. Aravind [aut, cre] (<https://orcid.org/0000-0002-4791-442X>), S. Mukesh Sankar [aut], Dhammaprakash Pandhari Wankhede [aut] (<https://orcid.org/0000-0001-6384-8664>), Vikender Kaur [aut], ICAR-NBGPR [cph] (www.nbpgr.ernet.in)
Maintainer: J. Aravind <j.aravind@icar.gov.in>
Repository: CRAN
Date/Publication: 2020-07-27 06:40:07 UTC

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Package TMB updated to version 1.7.18 with previous version 1.7.17 dated 2020-07-23

Title: Template Model Builder: A General Random Effect Tool Inspired by 'ADMB'
Description: With this tool, a user should be able to quickly implement complex random effect models through simple C++ templates. The package combines 'CppAD' (C++ automatic differentiation), 'Eigen' (templated matrix-vector library) and 'CHOLMOD' (sparse matrix routines available from R) to obtain an efficient implementation of the applied Laplace approximation with exact derivatives. Key features are: Automatic sparseness detection, parallelism through 'BLAS' and parallel user templates.
Author: Kasper Kristensen [aut, cre, cph], Brad Bell [cph], Hans Skaug [ctb], Arni Magnusson [ctb], Casper Berg [ctb], Anders Nielsen [ctb], Martin Maechler [ctb], Theo Michelot [ctb], Mollie Brooks [ctb], Alex Forrence [ctb], Christoffer Moesgaard Albertsen [ctb], Cole Monnahan [ctb]
Maintainer: Kasper Kristensen <kaskr@dtu.dk>

Diff between TMB versions 1.7.17 dated 2020-07-23 and 1.7.18 dated 2020-07-27

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Package set6 updated to version 0.1.8 with previous version 0.1.7 dated 2020-07-18

Title: R6 Mathematical Sets Interface
Description: An object-oriented package for mathematical sets, upgrading the current gold-standard {sets}. Many forms of mathematical sets are implemented, including (countably finite) sets, tuples, intervals (countably infinite or uncountable), and fuzzy variants. Wrappers extend functionality by allowing symbolic representations of complex operations on sets, including unions, (cartesian) products, exponentiation, and differences (asymmetric and symmetric).
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut]
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>

Diff between set6 versions 0.1.7 dated 2020-07-18 and 0.1.8 dated 2020-07-27

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 set6-0.1.8/set6/MD5                                            |   15 ++++-----
 set6-0.1.8/set6/NEWS.md                                        |    6 +++
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 set6-0.1.8/set6/tests/testthat/test_operations_setintersect.R  |    9 +++--
 set6-0.1.8/set6/tests/testthat/test_operations_setunion.R      |   16 +++++-----
 9 files changed, 38 insertions(+), 27 deletions(-)

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Package quanteda updated to version 2.1.1 with previous version 2.1.0 dated 2020-07-05

Title: Quantitative Analysis of Textual Data
Description: A fast, flexible, and comprehensive framework for quantitative text analysis in R. Provides functionality for corpus management, creating and manipulating tokens and ngrams, exploring keywords in context, forming and manipulating sparse matrices of documents by features and feature co-occurrences, analyzing keywords, computing feature similarities and distances, applying content dictionaries, applying supervised and unsupervised machine learning, visually representing text and text analyses, and more.
Author: Kenneth Benoit [cre, aut, cph] (<https://orcid.org/0000-0002-0797-564X>), Kohei Watanabe [aut] (<https://orcid.org/0000-0001-6519-5265>), Haiyan Wang [aut] (<https://orcid.org/0000-0003-4992-4311>), Paul Nulty [aut] (<https://orcid.org/0000-0002-7214-4666>), Adam Obeng [aut] (<https://orcid.org/0000-0002-2906-4775>), Stefan Müller [aut] (<https://orcid.org/0000-0002-6315-4125>), Akitaka Matsuo [aut] (<https://orcid.org/0000-0002-3323-6330>), Jiong Wei Lua [aut], Jouni Kuha [aut] (<https://orcid.org/0000-0002-1156-8465>), William Lowe [aut] (<https://orcid.org/0000-0002-1549-6163>), Christian Müller [ctb], Lori Young [dtc] (Lexicoder Sentiment Dictionary 2015), Stuart Soroka [dtc] (Lexicoder Sentiment Dictionary 2015), Ian Fellows [cph] (authored wordcloud C source code (modified)), European Research Council [fnd] (ERC-2011-StG 283794-QUANTESS)
Maintainer: Kenneth Benoit <kbenoit@lse.ac.uk>

Diff between quanteda versions 2.1.0 dated 2020-07-05 and 2.1.1 dated 2020-07-27

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Package performance updated to version 0.4.8 with previous version 0.4.7 dated 2020-06-14

Title: Assessment of Regression Models Performance
Description: Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

Diff between performance versions 0.4.7 dated 2020-06-14 and 0.4.8 dated 2020-07-27

 DESCRIPTION                                      |   12 
 MD5                                              |  115 +++----
 NAMESPACE                                        |    9 
 NEWS.md                                          |   15 
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 R/check_itemscale.R                              |    4 
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 R/cronbachs_alpha.R                              |    2 
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 R/performance_lrt.R                              |    6 
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 man/r2_tjur.Rd                                   |   56 +--
 man/r2_xu.Rd                                     |   58 +--
 man/r2_zeroinflated.Rd                           |   80 ++---
 tests/testthat/test-check_collinearity.R         |   25 +
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 tests/testthat/test-model_performance.bayesian.R |   27 -
 59 files changed, 2076 insertions(+), 1954 deletions(-)

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Package hmclearn updated to version 0.0.4 with previous version 0.0.3 dated 2020-06-25

Title: Fit Statistical Models Using Hamiltonian Monte Carlo
Description: Provide users with a framework to learn the intricacies of the Hamiltonian Monte Carlo algorithm with hands-on experience by tuning and fitting their own models. All of the code is written in R. Theoretical references are listed below:. Neal, Radford (2011) "Handbook of Markov Chain Monte Carlo" ISBN: 978-1420079418, Betancourt, Michael (2017) "A Conceptual Introduction to Hamiltonian Monte Carlo" <arXiv:1701.02434>, Thomas, S., Tu, W. (2020) "Learning Hamiltonian Monte Carlo in R" <arXiv: arXiv:2006.16194>, Gelman, A., Carlin, J. B., Stern, H. S., Dunson, D. B., Vehtari, A., & Rubin, D. B. (2013) "Bayesian Data Analysis" ISBN: 978-1439840955, Agresti, Alan (2015) "Foundations of Linear and Generalized Linear Models ISBN: 978-1118730034, Pinheiro, J., Bates, D. (2006) "Mixed-effects Models in S and S-Plus" ISBN: 978-1441903174.
Author: Samuel Thomas [cre, aut], Wanzhu Tu [ctb]
Maintainer: Samuel Thomas <samthoma@iu.edu>

Diff between hmclearn versions 0.0.3 dated 2020-06-25 and 0.0.4 dated 2020-07-27

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Package fasterize updated to version 1.0.3 with previous version 1.0.2 dated 2020-03-25

Title: Fast Polygon to Raster Conversion
Description: Provides a drop-in replacement for rasterize() from the 'raster' package that takes 'sf'-type objects, and is much faster. There is support for the main options provided by the rasterize() function, including setting the field used and background value, and options for aggregating multi-layer rasters. Uses the scan line algorithm attributed to Wylie et al. (1967) <doi:10.1145/1465611.1465619>.
Author: Noam Ross [aut, cre] (<https://orcid.org/0000-0002-2136-0000>), Michael Sumner [ctb] (<https://orcid.org/0000-0002-2471-7511>), EcoHealth Alliance [cph], USAID PREDICT [fnd]
Maintainer: Noam Ross <ross@ecohealthalliance.org>

Diff between fasterize versions 1.0.2 dated 2020-03-25 and 1.0.3 dated 2020-07-27

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Package arm updated to version 1.11-2 with previous version 1.11-1 dated 2020-04-27

Title: Data Analysis Using Regression and Multilevel/Hierarchical Models
Description: Functions to accompany A. Gelman and J. Hill, Data Analysis Using Regression and Multilevel/Hierarchical Models, Cambridge University Press, 2007.
Author: Andrew Gelman [aut], Yu-Sung Su [aut, cre], Masanao Yajima [ctb], Jennifer Hill [ctb], Maria Grazia Pittau [ctb], Jouni Kerman [ctb], Tian Zheng [ctb], Vincent Dorie [ctb]
Maintainer: Yu-Sung Su <suyusung@tsinghua.edu.cn>

Diff between arm versions 1.11-1 dated 2020-04-27 and 1.11-2 dated 2020-07-27

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 9 files changed, 346 insertions(+), 264 deletions(-)

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Package IRISMustangMetrics updated to version 2.4.1 with previous version 2.4.0 dated 2020-07-09

Title: Statistics and Metrics for Seismic Data
Description: Classes and functions for metrics calculation as part of the 'IRIS DMC MUSTANG' project. The functionality in this package builds upon the base classes of the 'IRISSeismic' package. Metrics include basic statistics as well as higher level 'health' metrics that can help identify problematic seismometers.
Author: Jonathan Callahan [aut], Rob Casey [aut], Mary Templeton [aut], Gillian Sharer [aut, cre]
Maintainer: Gillian Sharer <gillian@iris.washington.edu>

Diff between IRISMustangMetrics versions 2.4.0 dated 2020-07-09 and 2.4.1 dated 2020-07-27

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