Tue, 15 Dec 2020

New package catsim with initial version 0.2.3
Package: catsim
Type: Package
Title: Binary and Categorical Image Similarity Index
Version: 0.2.3
Authors@R: c(person(c("Geoffrey", "Thompson"),email="gzthompson@gmail.com", role = c("aut", "cre"), comment = c(ORCID = '0000-0003-2436-8822')))
Description: Computes a structural similarity metric (after the style of MS-SSIM for images) for binary and categorical 2D and 3D images. Can be based on accuracy (simple matching), Cohen's kappa, Rand index, adjusted Rand index, Jaccard index, Dice index, normalized mutual information, or adjusted mutual information. In addition, has fast computation of Cohen's kappa, the Rand indices, and the two mutual informations. Implements the methods of Thompson and Maitra (2020) <arXiv:2004.09073>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: Rcpp
RoxygenNote: 7.1.1
URL: https://github.com/gzt/catsim, https://gzt.github.io/catsim/
BugReports: https://github.com/gzt/catsim/issues
LinkingTo: Rcpp, testthat
Suggests: testthat, covr, knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2020-12-08 16:55:04 UTC; gzt
Author: Geoffrey Thompson [aut, cre] (<https://orcid.org/0000-0003-2436-8822>)
Maintainer: Geoffrey Thompson <gzthompson@gmail.com>
Repository: CRAN
Date/Publication: 2020-12-16 00:10:02 UTC

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New package dataPreparation with initial version 1.0.1
Package: dataPreparation
Title: Automated Data Preparation
Version: 1.0.1
Authors@R: person("Emmanuel-Lin", "Toulemonde", email = "el.toulemonde@protonmail.com", role = c("aut", "cre"))
Description: Do most of the painful data preparation for a data science project with a minimum amount of code; Take advantages of 'data.table' efficiency and use some algorithmic trick in order to perform data preparation in a time and RAM efficient way.
Depends: R (>= 3.3.0), lubridate, stringr, Matrix, progress
License: GPL-3 | file LICENSE
LazyData: true
Encoding: UTF-8
RoxygenNote: 7.1.1
Suggests: knitr, rmarkdown, kableExtra, pander, testthat (>= 2.0.0)
Imports: data.table
BugReports: https://github.com/ELToulemonde/dataPreparation/issues
NeedsCompilation: no
Packaged: 2020-12-15 20:08:09 UTC; Emmanuel Lin
Author: Emmanuel-Lin Toulemonde [aut, cre]
Maintainer: Emmanuel-Lin Toulemonde <el.toulemonde@protonmail.com>
Repository: CRAN
Date/Publication: 2020-12-16 00:00:02 UTC

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New package DataExplorer with initial version 0.8.2
Package: DataExplorer
Title: Automate Data Exploration and Treatment
Version: 0.8.2
Authors@R: person("Boxuan", "Cui", email = "boxuancui@gmail.com", role = c("aut", "cre"))
Description: Automated data exploration process for analytic tasks and predictive modeling, so that users could focus on understanding data and extracting insights. The package scans and analyzes each variable, and visualizes them with typical graphical techniques. Common data processing methods are also available to treat and format data.
Depends: R (>= 3.6)
Imports: data.table (>= 1.13.4), reshape2 (>= 1.4.3), scales (>= 1.1.0), ggplot2, gridExtra, rmarkdown (>= 2.5), networkD3 (>= 0.4), stats, utils, tools, parallel
Suggests: testthat, covr, knitr, jsonlite, nycflights13
SystemRequirements: pandoc (>= 1.12.3) - http://pandoc.org
License: MIT + file LICENSE
Language: en-US
LazyData: true
URL: http://boxuancui.github.io/DataExplorer/
BugReports: https://github.com/boxuancui/DataExplorer/issues
RoxygenNote: 7.1.1
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2020-12-08 16:31:09 UTC; bocui
Author: Boxuan Cui [aut, cre]
Maintainer: Boxuan Cui <boxuancui@gmail.com>
Repository: CRAN
Date/Publication: 2020-12-15 23:30:03 UTC

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New package VBLPCM with initial version 2.4.7
Package: VBLPCM
Type: Package
Title: Variational Bayes Latent Position Cluster Model for Networks
Version: 2.4.7
Date: 2020-12-04
Author: Michael Salter-Townshend
Maintainer: Michael Salter-Townshend <mike.saltertownshend@gmail.com>
Description: Fit and simulate latent position and cluster models for network data, using a fast Variational Bayes approximation.
Depends: ergm, network
Imports: mclust, sna
SystemRequirements: Gnu Scientific Library
URL: https://www.r-project.org, https://mststats.github.io/#software
License: GPL (>= 2)
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2020-12-08 15:40:19 UTC; mst
Repository: CRAN
Date/Publication: 2020-12-15 22:30:18 UTC

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Package sparkwarc updated to version 0.1.5 with previous version 0.1.1 dated 2017-01-13

Title: Load WARC Files into Apache Spark
Description: Load WARC (Web ARChive) files into Apache Spark using 'sparklyr'. This allows to read files from the Common Crawl project <http://commoncrawl.org/>.
Author: Yitao Li [aut, cre] (<https://orcid.org/0000-0002-1261-905X>), Javier Luraschi [aut]
Maintainer: Yitao Li <yitao@rstudio.com>

Diff between sparkwarc versions 0.1.1 dated 2017-01-13 and 0.1.5 dated 2020-12-15

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Package rscontract updated to version 0.1.2 with previous version 0.1.1 dated 2020-02-10

Title: Generic implementation of the 'RStudio' connections contract
Description: Provides a generic implementation of the 'RStudio' connection contract to make it easier for database connections, and other type of connections, opened via R packages integrate with the connections pane inside the 'RStudio' interactive development environment (IDE).
Author: Nathan Stephens [aut, cre], Edgar Ruiz [aut]
Maintainer: Nathan Stephens <nathan@rstudio.com>

Diff between rscontract versions 0.1.1 dated 2020-02-10 and 0.1.2 dated 2020-12-15

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Package RcppAnnoy updated to version 0.0.18 with previous version 0.0.17 dated 2020-11-16

Title: 'Rcpp' Bindings for 'Annoy', a Library for Approximate Nearest Neighbors
Description: 'Annoy' is a small C++ library for Approximate Nearest Neighbors written for efficient memory usage as well an ability to load from / save to disk. This package provides an R interface by relying on the 'Rcpp' package, exposing the same interface as the original Python wrapper to 'Annoy'. See <https://github.com/spotify/annoy> for more on 'Annoy'. 'Annoy' is released under Version 2.0 of the Apache License. Also included is a small Windows port of 'mmap' which is released under the MIT license.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package pkgbuild updated to version 1.2.0 with previous version 1.1.0 dated 2020-07-13

Title: Find Tools Needed to Build R Packages
Description: Provides functions used to build R packages. Locates compilers needed to build R packages on various platforms and ensures the PATH is configured appropriately so R can use them.
Author: Hadley Wickham [aut], Jim Hester [aut, cre], RStudio [cph]
Maintainer: Jim Hester <jim.hester@rstudio.com>

Diff between pkgbuild versions 1.1.0 dated 2020-07-13 and 1.2.0 dated 2020-12-15

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Package OptCirClust updated to version 0.0.2 with previous version 0.0.1 dated 2020-12-09

Title: Circular, Periodic, or Framed Data Clustering: Fast, Optimal, and Reproducible
Description: Fast, optimal, and reproducible clustering algorithms for circular, periodic, or framed data. The algorithms introduced in this package are based on a core optimal framed clustering algorithm. The runtime of these algorithms is O(K N log^2 N), where K is the number of clusters and N is the number of circular data points. On a desktop computer using a single processor core, millions of circular data points can be clustered within seconds. One can use the algorithms to characterize events along circular DNA molecules, circular RNA molecules, and circular genomes of bacteria, chloroplast, and mitochondria. One can also cluster climate data along any given longitude or latitude. Periodic data clustering can be formulated as circular clustering. The algorithms offer a general high-performance solution to circular, periodic, or framed data clustering.
Author: Tathagata Debnath [aut] (<https://orcid.org/0000-0001-6445-275X>), Joe Song [aut, cre] (<https://orcid.org/0000-0002-6883-6547>)
Maintainer: Joe Song <joemsong@cs.nmsu.edu>

Diff between OptCirClust versions 0.0.1 dated 2020-12-09 and 0.0.2 dated 2020-12-15

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New package mssm with initial version 0.1.4
Package: mssm
Type: Package
Title: Multivariate State Space Models
Version: 0.1.4
Authors@R: c( person("Benjamin", "Christoffersen", email = "boennecd@gmail.com", role = c("cre", "aut")), person("Anthony", "Williams", role = c("cph")))
Description: Provides methods to perform parameter estimation and make analysis of multivariate observed outcomes through time which depends on a latent state variable. All methods scale well in the dimension of the observed outcomes at each time point. The package contains an implementation of a Laplace approximation, particle filters like suggested by Lin, Zhang, Cheng, & Chen (2005) <doi:10.1198/016214505000000349>, and the gradient and observed information matrix approximation suggested by Poyiadjis, Doucet, & Singh (2011) <doi:10.1093/biomet/asq062>.
License: GPL-2
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0), stats, graphics
LinkingTo: Rcpp, RcppArmadillo, testthat, nloptr (>= 1.2.0)
Imports: Rcpp, nloptr (>= 1.2.0)
RoxygenNote: 6.1.1
SystemRequirements: C++11
Suggests: testthat, Ecdat
NeedsCompilation: yes
Packaged: 2020-12-14 10:19:46 UTC; boennecd
Author: Benjamin Christoffersen [cre, aut], Anthony Williams [cph]
Maintainer: Benjamin Christoffersen <boennecd@gmail.com>
Repository: CRAN
Date/Publication: 2020-12-15 22:30:08 UTC

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Package midrangeMCP updated to version 3.1.1 with previous version 3.1 dated 2020-06-29

Title: Multiples Comparisons Procedures Based on Studentized Midrange and Range Distributions
Description: Apply tests of multiple comparisons based on studentized 'midrange' and 'range' distributions. The tests are: Tukey Midrange ('TM' test), Student-Newman-Keuls Midrange ('SNKM' test), Means Grouping Midrange ('MGM' test) and Means Grouping Range ('MGR' test). The first two tests were published by Batista and Ferreira (2020) <doi:10.1590/1413-7054202044008020>. The last two are being published.
Author: Ben Deivide [aut, cre] (<https://orcid.org/0000-0001-7019-8794>), Daniel Furtado [aut] (<https://orcid.org/0000-0002-4371-5239>), Diego Arthur [ctb]
Maintainer: Ben Deivide <ben.deivide@ufsj.edu.br>

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Package locStra updated to version 1.6 with previous version 1.5 dated 2020-12-02

Title: Fast Implementation of (Local) Population Stratification Methods
Description: Fast implementations to compute the genetic covariance matrix, the Jaccard similarity matrix, the s-matrix (the weighted Jaccard similarity matrix), and the (classic or robust) genomic relationship matrix of a (dense or sparse) input matrix. Full support for sparse matrices from the R-package 'Matrix'. Additionally, an implementation of the power method (von Mises iteration) to compute the largest eigenvector of a matrix is included, a function to perform an automated full run of global and local correlations in population stratification data, and a function to compute sliding windows. New functionality in locStra allows one to extract the k leading eigenvectors of the genetic covariance matrix, Jaccard similarity matrix, s-matrix, and genomic relationship matrix without actually computing the similarity matrices.
Author: Georg Hahn [aut,cre], Sharon M. Lutz [ctb], Christoph Lange [ctb]
Maintainer: Georg Hahn <ghahn@hsph.harvard.edu>

Diff between locStra versions 1.5 dated 2020-12-02 and 1.6 dated 2020-12-15

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Package fiery updated to version 1.1.3 with previous version 1.1.2 dated 2019-09-27

Title: A Lightweight and Flexible Web Framework
Description: A very flexible framework for building server side logic in R. The framework is unopinionated when it comes to how HTTP requests and WebSocket messages are handled and supports all levels of app complexity; from serving static content to full-blown dynamic web-apps. Fiery does not hold your hand as much as e.g. the shiny package does, but instead sets you free to create your web app the way you want.
Author: Thomas Lin Pedersen [cre, aut] (<https://orcid.org/0000-0002-5147-4711>)
Maintainer: Thomas Lin Pedersen <thomasp85@gmail.com>

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Package dtrSurv updated to version 1.1 with previous version 1.0 dated 2020-12-09

Title: Dynamic Treatment Regimes for Survival Analysis
Description: Provides methods for estimating multi-stage optimal dynamic treatment regimes for survival outcomes with dependent censoring. Cho, H., Holloway, S. T., and Kosorok, M. R. (2020) <arXiv:2012.03294>.
Author: Shannon T. Holloway, Hunyong Cho
Maintainer: Shannon T. Holloway <sthollow@ncsu.edu>

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Package cld2 updated to version 1.2.1 with previous version 1.2 dated 2018-05-11

Title: Google's Compact Language Detector 2
Description: Bindings to Google's C++ library Compact Language Detector 2 (see <https://github.com/cld2owners/cld2#readme> for more information). Probabilistically detects over 80 languages in plain text or HTML. For mixed-language input it returns the top three detected languages and their approximate proportion of the total classified text bytes (e.g. 80% English and 20% French out of 1000 bytes). There is also a 'cld3' package on CRAN which uses a neural network model instead.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), Dirk Sites [cph] (Author of CLD2 C++ library)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package RMySQL updated to version 0.10.21 with previous version 0.10.20 dated 2020-03-14

Title: Database Interface and 'MySQL' Driver for R
Description: Legacy 'DBI' interface to 'MySQL' / 'MariaDB' based on old code ported from S-PLUS. A modern 'MySQL' client based on 'Rcpp' is available from the 'RMariaDB' package.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), David James [aut], Saikat DebRoy [aut], Hadley Wickham [aut], Jeffrey Horner [aut], RStudio [cph]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package gen3sis updated to version 1.2 with previous version 1.1 dated 2020-08-29

Title: General Engine for Eco-Evolutionary Simulations
Description: Contains an engine for spatially-explicit eco-evolutionary mechanistic models with a modular implementation and several support functions. It allows exploring the consequences of ecological and macroevolutionary processes across realistic or theoretical spatio-temporal landscapes on biodiversity patterns as a general term.
Author: ETH Zürich [cph], Oskar Hagen [aut, cre] (Landscape Ecology, WSL and ETH Zürich, Switzerland), Benjamin Flueck [aut] (Landscape Ecology, WSL and ETH Zürich, Switzerland), Fabian Fopp [aut] (Landscape Ecology, WSL and ETH Zürich, Switzerland), Juliano S. Cabral [aut] (Ecosystem Modeling, Center for Computational and Theoretical Biology, University of Würzburg, Würzburg, Germany), Florian Hartig [aut] (Theoretical Ecology, University of Regensburg, Regensburg, Germany), Mikael Pontarp [aut] (Department of Biology, Lund University, Lund, Sweden), Charles Novaes de Santana [ctb] (Landscape Ecology, WSL and ETH Zürich, Switzerland), Thiago F. Rangel [aut] (Department of Ecology, Universidade Federal de Goiás, Goiás, Brazil), Theo Gaboriau [ctb] (Depatment of Computational Biology, Lausanne University, Switzerland), Loïc Pellissier [aut, ths] (Landscape Ecology, WSL and ETH Zürich, Switzerland)
Maintainer: Oskar Hagen <oskar@hagen.bio>

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 gen3sis-1.2/gen3sis/vignettes/design_landscape.Rmd                                                    |    6 
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Package zcurve updated to version 1.0.7 with previous version 1.0.6 dated 2020-09-26

Title: An Implementation of Z-Curves
Description: An implementation of z-curves - a method for estimating expected discovery and replicability rates on the bases of test-statistics of published studies. The package provides functions for fitting the new density and EM version (Bartoš & Schimmack, 2020, <doi:10.31234/osf.io/urgtn>) as well as the original density z-curve (Brunner & Schimmack, 2017, <doi:10.31219/osf.io/wr93f>). Furthermore, the package provides summarizing and plotting functions for the fitted z-curve objects. See the aforementioned articles for more information about the z-curves, expected discovery and replicability rates, validation studies, and limitations.
Author: František Bartoš [aut, cre], Ulrich Schimmack [aut]
Maintainer: František Bartoš <f.bartos96@gmail.com>

Diff between zcurve versions 1.0.6 dated 2020-09-26 and 1.0.7 dated 2020-12-15

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Package TideTables updated to version 0.0.3 with previous version 0.0.2 dated 2017-09-11

Title: Tide Analysis and Prediction of Predominantly Semi-Diurnal Tides
Description: Tide analysis and prediction of predominantly semi-diurnal tides with two high waters and two low waters during one lunar day (~24.842 hours, ~1.035 days). The analysis should preferably cover an observation period of at least 19 years. For shorter periods, for example, the nodal cycle can not be taken into account, which particularly affects the height calculation. The main objective of this package is to produce tide tables.
Author: Moritz Mueller-Navarra [aut, cre], Sylvin Mueller-Navarra [aut] ((2019) <https://doi.org/10.5194/os-15-1363-2019>), Andreas Boesch [ctb] ((2019) <https://doi.org/10.5194/os-15-1363-2019>)
Maintainer: Moritz Mueller-Navarra <muellernavarra@gmail.com>

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Package RcppDynProg updated to version 0.2.0 with previous version 0.1.6 dated 2020-11-13

Title: 'Rcpp' Dynamic Programming
Description: Dynamic Programming implemented in 'Rcpp'. Includes example partition and out of sample fitting applications. Also supplies additional custom coders for the 'vtreat' package.
Author: John Mount [aut, cre], Nina Zumel [aut], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between RcppDynProg versions 0.1.6 dated 2020-11-13 and 0.2.0 dated 2020-12-15

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Package KarsTS updated to version 2.4 with previous version 2.3 dated 2020-06-07

Title: An Interface for Microclimate Time Series Analysis
Description: An R code with a GUI for microclimate time series, with an emphasis on underground environments. 'KarsTS' provides linear and nonlinear methods, including recurrence analysis (Marwan et al. (2007) <10.1016/j.physrep.2006.11.001>) and filling methods (Moffat et al. (2007) <doi:10.1016/j.agrformet.2007.08.011>), as well as tools to manipulate easily time series and gap sets.
Author: Marina Saez [aut, cre], David Benavente [ths], Soledad Cuezva [ths], Concepcion Pla [ctb]
Maintainer: Marina Saez <marinasaez_andreu@hotmail.com>

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Permanent link

Package quantdr updated to version 1.1.0 with previous version 1.0.0 dated 2020-10-07

Title: Dimension Reduction Techniques for Conditional Quantiles
Description: An implementation of dimension reduction techniques for conditional quantiles. Nonparametric estimation of conditional quantiles is also available.
Author: Eliana Christou [aut, cre] (<https://orcid.org/0000-0001-5044-0969>)
Maintainer: Eliana Christou <echris15@uncc.edu>

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Package GrapheR updated to version 1.9-86-3 with previous version 1.9-86 dated 2016-12-13

Title: A Multi-Platform GUI for Drawing Customizable Graphs in R
Description: A multi-platform user interface for drawing highly customizable graphs in R. It aims to be a valuable help to quickly draw publishable graphs without any knowledge of R commands. Six kinds of graph are available: histogram, box-and-whisker plot, bar plot, pie chart, curve and scatter plot.
Author: Maxime Herv<e9>
Maintainer: Maxime Herv<e9> <maxime.herve@univ-rennes1.fr>

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Package atable updated to version 0.1.10 with previous version 0.1.9 dated 2020-09-19

Title: Create Tables for Reporting Clinical Trials
Description: Create Tables for Reporting Clinical Trials. Calculates descriptive statistics and hypothesis tests, arranges the results in a table ready for reporting with LaTeX, HTML or Word.
Author: Armin Ströbel [aut, cre] (<https://orcid.org/0000-0002-6873-5332>), Alan Haynes [aut] (<https://orcid.org/0000-0003-1374-081X>)
Maintainer: Armin Ströbel <arminstroebel@web.de>

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Package UniprotR updated to version 2.0.1 with previous version 2.0.0 dated 2020-12-13

Title: Retrieving Information of Proteins from Uniprot
Description: Connect to Uniprot <https://www.uniprot.org/> to retrieve information about proteins using their accession number such information could be name or taxonomy information, For detailed information kindly read the publication <https://www.sciencedirect.com/science/article/pii/S1874391919303859>.
Author: Mohamed Soudy [aut, cre], Ali Mostafa [aut]
Maintainer: Mohamed Soudy <MohmedSoudy2009@gmail.com>

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Package RJafroc updated to version 2.0.1 with previous version 1.3.2 dated 2020-03-06

Title: Artificial Intelligence Systems and Observer Performance
Description: Analyzing the performance of artificial intelligence (AI) systems/algorithms characterized by a "search-and-report" strategy. While historically observer performance has dealt with measuring radiologists' performance in search tasks – i.e., searching for lesions in medical images and reporting them - the software described here applies equally to any task involving searching for and reporting arbitrary targets in images. The package can be used to analyze the performance of AI systems, compare AI performance to a group of human readers or optimize the reporting threshold of an AI system. In addition to performing conventional receiver operating characteristic (ROC) analysis (localization information ignored), the software also performs free-response receiver operating characteristic (FROC) analysis, where lesion localization information is integral to the analyzed data. A book using the software has been published: Chakraborty DP: Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples, Taylor-Francis LLC; 2017. An online update of this book is at <https://dpc10ster.github.io/RJafrocBook/>. Illustrations of the software (vignettes) are at <https://dpc10ster.github.io/RJafroc/>. Supported data collection paradigms are the ROC, FROC and the location ROC (LROC). ROC data consists of single ratings per images, where a rating is the perceived confidence level that the image is that of a diseased patient. An ROC curve is a plot of true positive fraction vs. false positive fraction. FROC data consists of a variable number (zero or more) of mark-rating pairs per image, where a mark is the location of a reported suspicious region and the rating is the confidence level that it is a real lesion. LROC data consists of a rating and a location of the most suspicious region, for every image. Four models of observer performance, and curve-fitting software, are implemented: the binormal model (BM), the contaminated binormal model (CBM), the correlated contaminated binormal model (CORCBM), and the radiological search model (RSM). Unlike the binormal model, CBM, CORCBM and RSM predict "proper" ROC curves that do not inappropriately cross the chance diagonal. Additionally, RSM parameters are related to search performance (not measured in conventional ROC analysis) and classification performance. Search performance refers to finding lesions, i.e., true positives, while simultaneously not finding false positive locations. Classification performance measures the ability to distinguish between true and false positive locations. Knowing these separate performances allows principled optimization of reader or AI system performance. RJafroc supersedes Windows JAFROC (jackknife alternative FROC) software V4.2.1, <https://github.com/dpc10ster/WindowsJafroc>. Package functions are organized as follows. Data file related function names are preceded by "Df", curve fitting functions by "Fit", included data sets by "dataset", plotting functions by "Plot", significance testing functions by "St", sample size related functions by "Ss", data simulation functions by "Simulate" and utility functions by "Util". Implemented are figures of merit (FOMs) for quantifying performance and functions for visualizing empirical or fitted operating characteristics: e.g., ROC, FROC, alternative FROC (AFROC) and weighted AFROC (wAFROC) curves. For fully crossed study designs significance testing of reader-averaged FOM differences between modalities is implemented via either Dorfman-Berbaum-Metz or the Obuchowski-Rockette methods. Also implemented is single treatment analysis, which allows comparison of performance of a group of radiologists to a specified value, or comparison of AI to a group of radiologists interpreting the same cases. Crossed-modality analysis is implemented wherein there are two crossed treatment factors and the aim is to determined performance in each treatment factor averaged over all levels of the second factor. Sample size estimation tools are provided for ROC and FROC studies; these use estimates of the relevant variances from a pilot study to predict required numbers of readers and cases in a pivotal study to achieve the desired power. Utility and data file manipulation functions allow data to be read in any of the currently used input formats, including Excel, and the results of the analysis can be viewed in text or Excel output files. The methods are illustrated with several included datasets from the author's collaborations. This version corrects bugs, simplifies usage of the software and updates the dataset structure. All changes are noted in NEWS.
Author: Dev Chakraborty [cre, aut, cph], Peter Phillips [aut], Xuetong Zhai [aut]
Maintainer: Dev Chakraborty <dpc10ster@gmail.com>

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Package rgugik updated to version 0.2.1 with previous version 0.2.0 dated 2020-12-09

Title: Search and Retrieve Spatial Data from 'GUGiK'
Description: Automatic open data acquisition from resources of Polish Head Office of Geodesy and Cartography ('Główny Urząd Geodezji i Kartografii') (<www.gugik.gov.pl>). Available datasets include various types of numeric, raster and vector data, such as orthophotomaps, digital elevation models (digital terrain models, digital surface model, point clouds), state register of borders, spatial databases, geometries of cadastral parcels, 3D models of buildings, and more. It is also possible to geocode addresses or objects using the geocodePL_get() function.
Author: Krzysztof Dyba [aut, cre] (<https://orcid.org/0000-0002-8614-3816>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Maciej Beręsewicz [ctb] (<https://orcid.org/0000-0002-8281-4301>), GUGiK [ctb] (source of the data)
Maintainer: Krzysztof Dyba <adres7@gmail.com>

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Package ResearchAssociate updated to version 1.0.1 with previous version 1.0.0 dated 2020-12-09

Title: Retrieving Publications from PubMed Database Based on User Query
Description: Connects to Pubmed <https://pubmed.ncbi.nlm.nih.gov/> to retrieve publications related to user-defined search query.
Author: Mohamed Soudy [aut, cre], Ali Mostafa [aut]
Maintainer: Mohamed Soudy <MohmedSoudy2009@gmail.com>

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Package mlt.docreg updated to version 1.0-9 with previous version 1.0-8 dated 2020-09-21

Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and regression tests for package mlt.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package eha updated to version 2.8.4 with previous version 2.8.1 dated 2020-04-01

Title: Event History Analysis
Description: Parametric proportional hazards fitting with left truncation and right censoring for common families of distributions, piecewise constant hazards, and discrete models. Parametric accelerated failure time models for left truncated and right censored data. Proportional hazards models for tabular and register data. Sampling of risk sets in Cox regression, selections in the Lexis diagram, bootstrapping. Broström (2012) <doi:10.1201/9781315373942>.
Author: Göran Broström [aut, cre], Jianming Jin [ctb]
Maintainer: Göran Broström <goran.brostrom@umu.se>

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Package spant updated to version 1.9.0 with previous version 1.8.0 dated 2020-11-18

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.
Author: Martin Wilson [cre, aut] (<https://orcid.org/0000-0002-2089-3956>), Yong Wang [ctb], John Muschelli [ctb]
Maintainer: Martin Wilson <martin@pipegrep.co.uk>

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Package GetoptLong updated to version 1.0.5 with previous version 1.0.4 dated 2020-10-19

Title: Parsing Command-Line Arguments and Simple Variable Interpolation
Description: This is a command-line argument parser which wraps the powerful Perl module Getopt::Long and with some adaptations for easier use in R. It also provides a simple way for variable interpolation in R.
Author: Zuguang Gu
Maintainer: Zuguang Gu <z.gu@dkfz.de>

Diff between GetoptLong versions 1.0.4 dated 2020-10-19 and 1.0.5 dated 2020-12-15

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Package CME.assistant updated to version 1.1.1 with previous version 1.1.0 dated 2020-11-25

Title: Reusable Assisting Functions for Child Mortality Estimation
Description: Provide helper functions for UNICEF child mortality estimation.
Author: Yang Liu [aut, cre] (<https://orcid.org/0000-0001-6557-6439>)
Maintainer: Yang Liu <lyhello@gmail.com>

Diff between CME.assistant versions 1.1.0 dated 2020-11-25 and 1.1.1 dated 2020-12-15

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Package gdimap (with last version 0.1-9) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2015-01-07 0.1-9
2014-11-07 0.1-8
2014-07-14 0.1-6
2014-02-03 0.1-3
2013-06-04 0.1-1
2013-03-20 0.0-3
2012-11-28 0.0-2

Permanent link
Package uwot updated to version 0.1.10 with previous version 0.1.9 dated 2020-11-15

Title: The Uniform Manifold Approximation and Projection (UMAP) Method for Dimensionality Reduction
Description: An implementation of the Uniform Manifold Approximation and Projection dimensionality reduction by McInnes et al. (2018) <arXiv:1802.03426>. It also provides means to transform new data and to carry out supervised dimensionality reduction. An implementation of the related LargeVis method of Tang et al. (2016) <arXiv:1602.00370> is also provided. This is a complete re-implementation in R (and C++, via the 'Rcpp' package): no Python installation is required. See the uwot website (<https://github.com/jlmelville/uwot>) for more documentation and examples.
Author: James Melville [aut, cre], Aaron Lun [ctb], Mohamed Nadhir Djekidel [ctb], Yuhan Hao [ctb]
Maintainer: James Melville <jlmelville@gmail.com>

Diff between uwot versions 0.1.9 dated 2020-11-15 and 0.1.10 dated 2020-12-15

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Package r2dii.analysis updated to version 0.1.3 with previous version 0.1.2 dated 2020-12-05

Title: Tools to Calculate Climate Targets for Financial Portfolios
Description: These tools help you to assess if a financial portfolio aligns with climate goals. They summarize key metrics attributed to the portfolio (e.g. production, emission factors), and calculate targets based on climate scenarios. They implement in R the last step of the free software 'PACTA' (Paris Agreement Capital Transition Assessment; <https://2degrees-investing.org/>). Financial institutions use 'PACTA' to study how their capital allocation impacts the climate.
Author: Jackson Hoffart [aut, cre] (<https://orcid.org/0000-0002-8600-5042>), Mauro Lepore [aut, ctr] (<https://orcid.org/0000-0002-1986-7988>), Klaus Hogedorn [aut], 2 Degrees Investing Initiative [cph, fnd]
Maintainer: Jackson Hoffart <jackson.hoffart@gmail.com>

Diff between r2dii.analysis versions 0.1.2 dated 2020-12-05 and 0.1.3 dated 2020-12-15

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Package pacotest updated to version 0.4.0 with previous version 0.3.1 dated 2019-03-11

Title: Testing for Partial Copulas and the Simplifying Assumption in Vine Copulas
Description: Routines for two different test types, the Constant Conditional Correlation (CCC) test and the Vectorial Independence (VI) test are provided (Kurz and Spanhel (2017) <arXiv:1706.02338>). The tests can be applied to check whether a conditional copula coincides with its partial copula. Functions to test whether a regular vine copula satisfies the so-called simplifying assumption or to test a single copula within a regular vine copula to be a (j-1)-th order partial copula are available. The CCC test comes with a decision tree approach to allow testing in high-dimensional settings.
Author: Malte S. Kurz [aut, cre]
Maintainer: Malte S. Kurz <malte.simon.kurz@uni-hamburg.de>

Diff between pacotest versions 0.3.1 dated 2019-03-11 and 0.4.0 dated 2020-12-15

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New package portes with initial version 5.0
Package: portes
Type: Package
Title: Portmanteau Tests for Univariate and Multivariate Time Series Models
Version: 5.0
Date: 2020-12-12
Authors@R: c(person("Esam", "Mahdi", role = c("aut", "cre"), email = "emahdi@qu.edu.qa"), person("Ian", "McLeod", role = "ctb", email = "aimcleod@uwo.ca"))
Author: Esam Mahdi [aut, cre], Ian McLeod [ctb]
Maintainer: Esam Mahdi <emahdi@qu.edu.qa>
Description: Contains common univariate and multivariate portmanteau test statistics in time series based on the asymptotic distributions and the Monte Carlo significance tests. Simulate univariate and multivariate data from seasonal and nonseasonal time series models. See Mahdi and McLeod (2012) <doi:10.1111/j.1467-9892.2011.00752.x> and Mahdi and McLeod (2020) <arXiv:2005.00931>.
Depends: parallel, forecast
Suggests: akima, car, fGarch, FitAR, fracdiff, gstat, tseries, vars
LazyLoad: yes
LazyData: yes
Classification/ACM: G.3, G.4, I.5.1
Classification/MSC: 62M10, 91B84
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-12-15 09:26:54 UTC; EM17548
Repository: CRAN
Date/Publication: 2020-12-15 12:40:03 UTC

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Package MatchIt updated to version 4.1.0 with previous version 4.0.1 dated 2020-11-27

Title: Nonparametric Preprocessing for Parametric Causal Inference
Description: Selects matched samples of the original treated and control groups with similar covariate distributions -- can be used to match exactly on covariates, to match on propensity scores, or perform a variety of other matching procedures. The package also implements a series of recommendations offered in Ho, Imai, King, and Stuart (2007) <DOI:10.1093/pan/mpl013>.
Author: Daniel Ho [aut] (<https://orcid.org/0000-0002-2195-5469>), Kosuke Imai [aut] (<https://orcid.org/0000-0002-2748-1022>), Gary King [aut] (<https://orcid.org/0000-0002-5327-7631>), Elizabeth Stuart [aut] (<https://orcid.org/0000-0002-9042-8611>), Alex Whitworth [ctb], Noah Greifer [ctb, cre, aut] (<https://orcid.org/0000-0003-3067-7154>)
Maintainer: Noah Greifer <noah.greifer@gmail.com>

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Package bayesmeta updated to version 2.6 with previous version 2.5 dated 2020-04-20

Title: Bayesian Random-Effects Meta-Analysis
Description: A collection of functions allowing to derive the posterior distribution of the two parameters in a random-effects meta-analysis, and providing functionality to evaluate joint and marginal posterior probability distributions, predictive distributions, shrinkage effects, posterior predictive p-values, etc.; For more details, see also Roever C (2020) <doi:10.18637/jss.v093.i06>.
Author: Christian Roever [aut, cre] (<https://orcid.org/0000-0002-6911-698X>), Tim Friede [ctb] (<https://orcid.org/0000-0001-5347-7441>)
Maintainer: Christian Roever <christian.roever@med.uni-goettingen.de>

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New package srcr with initial version 1.0.0
Package: srcr
Type: Package
Title: Simplify Connections to Database Sources
Version: 1.0.0
Authors@R: c(person('Charles', 'Bailey', email = 'baileyc@chop.edu', role = c('aut', 'cre')), person('Hanieh', 'Razzaghi', email = 'razzaghih@chop.edu', role = c('aut')))
Maintainer: Charles Bailey <baileyc@chop.edu>
Description: Connecting to databases requires boilerplate code to specify connection parameters and to set up sessions properly with the DBMS. This package provides a simple tool to fill two purposes: abstracting connection details, including secret credentials, out of your source code and managing configuration for frequently-used database connections in a persistent and flexible way, while minimizing requirements on the runtime environment.
License: Artistic-2.0
Encoding: UTF-8
LazyData: TRUE
ByteCompile: TRUE
Imports: DBI, dplyr, jsonlite, utils
Suggests: knitr, rmarkdown, RSQLite
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-12-13 07:16:44 UTC; baileyc
Author: Charles Bailey [aut, cre], Hanieh Razzaghi [aut]
Repository: CRAN
Date/Publication: 2020-12-15 10:30:02 UTC

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Package Seurat updated to version 3.2.3 with previous version 3.2.2 dated 2020-09-26

Title: Tools for Single Cell Genomics
Description: A toolkit for quality control, analysis, and exploration of single cell RNA sequencing data. 'Seurat' aims to enable users to identify and interpret sources of heterogeneity from single cell transcriptomic measurements, and to integrate diverse types of single cell data. See Satija R, Farrell J, Gennert D, et al (2015) <doi:10.1038/nbt.3192>, Macosko E, Basu A, Satija R, et al (2015) <doi:10.1016/j.cell.2015.05.002>, and Stuart T, Butler A, et al (2019) <doi:10.1016/j.cell.2019.05.031> for more details.
Author: Rahul Satija [aut] (<https://orcid.org/0000-0001-9448-8833>), Andrew Butler [aut] (<https://orcid.org/0000-0003-3608-0463>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Tim Stuart [aut] (<https://orcid.org/0000-0002-3044-0897>), Jeff Farrell [ctb], Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Patrick Roelli [ctb], Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>)
Maintainer: Paul Hoffman <nygcSatijalab@nygenome.org>

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Package nomnoml updated to version 0.2.3 with previous version 0.2.0 dated 2020-05-26

Title: Sassy 'UML' Diagrams
Description: A tool for drawing sassy 'UML' diagrams based on a simple syntax, see <https://www.nomnoml.com>. Supports styling, R Markdown and exporting diagrams in the PNG format.
Author: Andrie de Vries [aut, cre], Javier Luraschi [aut], Daniel Kallin [cph] (nomnoml.js library, https://nomnoml.com), RStudio [cph, fnd]
Maintainer: Andrie de Vries <apdevries@gmail.com>

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Package mully updated to version 2.1.30 with previous version 2.1.26 dated 2020-11-18

Title: Create, Modify and Visualize Multi-Layered Networks
Description: Allows the user to create graph with multiple layers. The user can also modify the layers, the nodes, and the edges. The graph can also be visualized. Zaynab Hammoud and Frank Kramer (2018) <doi:10.3390/genes9110519>. More about multilayered graphs and their usage can be found in our review paper: Zaynab Hammoud and Frank Kramer (2020) <doi:10.1186/s41044-020-00046-0>.
Author: Zaynab Hammoud
Maintainer: Zaynab Hammoud <zaynabhassanhammoud@gmail.com>

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Package AnalyzeFMRI updated to version 1.1-23 with previous version 1.1-22 dated 2020-12-13

Title: Functions for Analysis of fMRI Datasets Stored in the ANALYZE or NIFTI Format
Description: Functions for I/O, visualisation and analysis of functional Magnetic Resonance Imaging (fMRI) datasets stored in the ANALYZE or NIFTI format. Note that the latest version of XQuartz seems to be necessary under MacOS.
Author: Pierre Lafaye De Micheaux [aut, cre], Jonathan L Marchini [aut], Cleve Moler [cph] (LAPACK/BLAS routines in src), Jack Dongarra [cph] (LAPACK/BLAS routines in src), Richard Hanson [cph] (LAPACK/BLAS routines in src), Sven Hammarling [cph] (LAPACK/BLAS routines in src), Jeremy Du Croz [cph] (LAPACK/BLAS routines in src)
Maintainer: Pierre Lafaye De Micheaux <lafaye@unsw.edu.au>

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Package torch updated to version 0.2.0 with previous version 0.1.1 dated 2020-10-20

Title: Tensors and Neural Networks with 'GPU' Acceleration
Description: Provides functionality to define and train neural networks similar to 'PyTorch' by Paszke et al (2019) <arXiv:1912.01703> but written entirely in R using the 'libtorch' library. Also supports low-level tensor operations and 'GPU' acceleration.
Author: Daniel Falbel [aut, cre, cph], Javier Luraschi [aut], Dmitriy Selivanov [ctb], Athos Damiani [ctb], RStudio [cph]
Maintainer: Daniel Falbel <daniel@rstudio.com>

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Package modelsummary updated to version 0.6.4 with previous version 0.6.3 dated 2020-10-24

Title: Summary Tables and Plots for Statistical Models and Data: Beautiful, Customizable, and Publication-Ready
Description: Create beautiful and customizable tables to summarize several statistical models side-by-side. Draw coefficient plots, multi-level cross-tabs, dataset summaries, balance tables (a.k.a. "Table 1s"), and correlation matrices. This package supports dozens of statistical models, and it can produce tables in HTML, LaTeX, Word, Markdown, PDF, PowerPoint, Excel, RTF, JPG, or PNG. Tables can easily be embedded in 'Rmarkdown' or 'knitr' dynamic documents.
Author: Vincent Arel-Bundock [aut, cre] (<https://orcid.org/0000-0003-2042-7063>)
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

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Package seawaveQ updated to version 2.0.2 with previous version 2.0.1 dated 2020-08-04

Title: SEAWAVE-Q Model
Description: A model and utilities for analyzing trends in chemical concentrations in streams with a seasonal wave (seawave) and adjustment for streamflow (Q) and other ancillary variables. See Ryberg and York, 2020, <doi:10.3133/ofr20201082>.
Author: Karen R. Ryberg [aut, cre], Aldo V. Vecchia [aut], Benjamin York [ctb]
Maintainer: Karen R. Ryberg <kryberg@usgs.gov>

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Package schoRsch updated to version 1.9.1 with previous version 1.9 dated 2020-12-11

Title: Tools for Analyzing Factorial Experiments
Description: Offers a helping hand to psychologists and other behavioral scientists who routinely deal with experimental data from factorial experiments. It includes several functions to format output from other R functions according to the style guidelines of the APA (American Psychological Association). This formatted output can be copied directly into manuscripts to facilitate data reporting. These features are backed up by a toolkit of several small helper functions, e.g., offering out-of-the-box outlier removal. The package lends its name to Georg "Schorsch" Schuessler, ingenious technician at the Department of Psychology III, University of Wuerzburg. For details on the implemented methods, see Roland Pfister and Markus Janczyk (2016) <doi: 10.20982/tqmp.12.2.p147>.
Author: Roland Pfister, Markus Janczyk
Maintainer: Roland Pfister <roland.pfister@psychologie.uni-wuerzburg.de>

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Package precautionary updated to version 0.2-0 with previous version 0.1-5 dated 2020-11-03

Title: Safety Diagnostics for Dose-Escalation Trial Designs
Description: Enhances various R packages that support the design and simulation of phase 1 dose-escalation trials, adding diagnostics to examine the safety characteristics of these designs in light of expected inter-individual variation in pharmacokinetics and pharmacodynamics. See Norris (2020b), "Retrospective analysis of a fatal dose-finding trial" <arXiv:2004.12755> and (2020c) "What Were They Thinking? Pharmacologic priors implicit in a choice of 3+3 dose-escalation design" <arXiv:2012:05301>.
Author: David C. Norris [aut, cre, cph] (<https://orcid.org/0000-0001-9593-6343>), Markus Triska [ctb]
Maintainer: David C. Norris <david@precisionmethods.guru>

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Package NutrienTrackeR updated to version 1.0.0 with previous version 0.99.3 dated 2020-10-06

Title: Food Composition Information and Dietary Assessment
Description: Provides a tool set for food information and dietary assessment. It uses food composition data from several reference databases, including: 'USDA' (United States), 'CIQUAL' (France), and 'BEDCA' (Spain). 'NutrienTrackeR' calculates the intake levels for both macronutrient and micronutrients, and compares them with the recommended dietary allowances (RDA). It includes a number of visualization tools, such as time series plots of nutrient intake, and pie-charts showing the main foods contributing to the intake level of a given nutrient.
Author: Andrea Rodriguez-Martinez, Rafael Ayala, Yacine Debbabi, Lara Selles Vidal
Maintainer: Rafael Ayala <r.ayala14@imperial.ac.uk>

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Package CNVScope updated to version 3.3.9 with previous version 3.3.7 dated 2020-11-28

Title: A Versatile Toolkit for Copy Number Variation Relationship Data Analysis and Visualization
Description: Provides the ability to create interaction maps, discover CNV map domains (edges), gene annotate interactions, and create interactive visualizations of these CNV interaction maps.
Author: James Dalgeish, Yonghong Wang, Jack Zhu, Paul Meltzer
Maintainer: James Dalgleish <james.dalgleish@nih.gov>

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Package blatent updated to version 0.1.1 with previous version 0.1.0 dated 2020-12-08

Title: Bayesian Latent Variable Models
Description: Estimation of latent variable models using Bayesian methods. Currently estimates the loglinear cognitive diagnosis model of Henson, Templin, and Willse (2009) <doi:10.1007/s11336-008-9089-5>.
Author: Jonathan Templin [aut, cre] (<https://orcid.org/0000-0001-7616-0973>)
Maintainer: Jonathan Templin <jonathan-templin@uiowa.edu>

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Package googlePolylines updated to version 0.8.2 with previous version 0.8.1 dated 2020-11-01

Title: Encoding Coordinates into 'Google' Polylines
Description: Encodes simple feature ('sf') objects and coordinates, and decodes polylines using the 'Google' polyline encoding algorithm (<https://developers.google.com/maps/documentation/utilities/polylinealgorithm>).
Author: David Cooley [aut, cre], Paulo Barcelos [ctb] (Author of c++ decode_polyline), Chris Muir [ctb]
Maintainer: David Cooley <dcooley@symbolix.com.au>

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Package sampleSelection updated to version 1.2-12 with previous version 1.2-10 dated 2020-11-04

Title: Sample Selection Models
Description: Two-step and maximum likelihood estimation of Heckman-type sample selection models: standard sample selection models (Tobit-2), endogenous switching regression models (Tobit-5), sample selection models with binary dependent outcome variable, interval regression with sample selection (only ML estimation), and endogenous treatment effects models. These methods are described in the three vignettes that are included in this package and in econometric textbooks such as Greene (2011, Econometric Analysis, 7th edition, Pearson).
Author: Arne Henningsen [aut, cre], Ott Toomet [aut], Sebastian Petersen [ctb]
Maintainer: Arne Henningsen <arne.henningsen@gmail.com>

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Package irtplay updated to version 1.6.2 with previous version 1.6.1 dated 2020-08-13

Title: Unidimensional Item Response Theory Modeling
Description: Fit unidimensional item response theory (IRT) models to a mixture of dichotomous and polytomous data, calibrate online item parameters (i.e., pretest and operational items), estimate examinees abilities, and examine the IRT model-data fit on item-level in different ways as well as provide useful functions related to unidimensional IRT models. For the item parameter estimation, marginal maximum likelihood estimation with expectation-maximization (MMLE-EM) algorithm (Bock & Aitkin (1981) <doi:10.1007/BF02294168>) is used. For the online calibration, Stocking's Method A (Ban, Hanson, Wang, Yi, & Harris (2011) <doi:10.1111/j.1745-3984.2001.tb01123.x>) and the fixed item parameter calibration (FIPC) method (Kim (2006) <doi:10.1111/j.1745-3984.2006.00021.x>) are provided. For the ability estimation, several popular scoring methods (e.g., MLE, EAP, and MAP) are implemented. In terms of assessing the IRT model-data fit, one of distinguished features of this package is that it gives not only well-known item fit statistics (e.g., chi-square (X2), likelihood ratio chi-square (G2), infit and oufit statistics, and S-X2 statistic (Ames & Penfield (2015) <doi:10.1111/emip.12067>)) but also graphical displays to look at residuals between the observed data and model-based predictions (Hambleton, Swaminathan, & Rogers (1991, ISBN:9780803936478)). In addition, there are many useful functions such as computing asymptotic variance-covariance matrices of item parameter estimates (Li & Lissitz (2004) <doi:10.1111/j.1745-3984.2004.tb01109.x>), importing item and/or ability parameters from popular IRT software, running 'flexMIRT' (Cai, 2017) through R, generating simulated data, computing the conditional distribution of observed scores using the Lord-Wingersky recursion formula (Lord & Wingersky (1984) <doi:10.1177/014662168400800409>), computing the loglikelihood of individual items, computing the loglikelihood of abilities, computing item and test information functions, computing item and test characteristic curve functions, and plotting item and test characteristic curves and item and test information functions.
Author: Hwanggyu Lim [aut, cre], Craig S. Wells [ctb]
Maintainer: Hwanggyu Lim <hglim83@gmail.com>

Diff between irtplay versions 1.6.1 dated 2020-08-13 and 1.6.2 dated 2020-12-15

 DESCRIPTION            |    8 
 MD5                    |  104 ++++----
 NAMESPACE              |    5 
 NEWS.md                |   17 +
 R/back2df.R            |    2 
 R/bring_output.R       |  600 ++++++++++++++++++++++++++++++++++++++++++++++---
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 R/eap_sum.R            |    6 
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 R/est_item.R           |   55 ++--
 R/est_score.R          |   54 ++--
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 R/irtmodel.R           |   14 -
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 R/loglike_score.R      |   20 -
 R/lwrc.R               |   32 +-
 R/plot_info.R          |    2 
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 R/post_den.R           |   10 
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 R/shape_df.R           |   26 +-
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 R/sx2_fit.R            |   22 -
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 R/trace.R              |   14 -
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 R/write_flexmirt.R     |   16 -
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 53 files changed, 1487 insertions(+), 826 deletions(-)

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Package clusterGeneration updated to version 1.3.7 with previous version 1.3.6 dated 2020-11-22

Title: Random Cluster Generation (with Specified Degree of Separation)
Description: We developed the clusterGeneration package to provide functions for generating random clusters, generating random covariance/correlation matrices, calculating a separation index (data and population version) for pairs of clusters or cluster distributions, and 1-D and 2-D projection plots to visualize clusters. The package also contains a function to generate random clusters based on factorial designs with factors such as degree of separation, number of clusters, number of variables, number of noisy variables.
Author: Weiliang Qiu <stwxq@channing.harvard.edu>, Harry Joe <harry@stat.ubc.ca>.
Maintainer: Weiliang Qiu <weiliang.qiu@gmail.com>

Diff between clusterGeneration versions 1.3.6 dated 2020-11-22 and 1.3.7 dated 2020-12-15

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Package readabs updated to version 0.4.6.900 with previous version 0.4.6 dated 2020-11-20

Title: Download and Tidy Time Series Data from the Australian Bureau of Statistics
Description: Downloads, imports, and tidies time series data from the Australian Bureau of Statistics <https://www.abs.gov.au/>.
Author: Matt Cowgill [aut, cre], Zoe Meers [aut], Jaron Lee [aut], David Diviny [aut], Hugh Parsonage [ctb]
Maintainer: Matt Cowgill <mattcowgill@gmail.com>

Diff between readabs versions 0.4.6 dated 2020-11-20 and 0.4.6.900 dated 2020-12-15

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Package hacksaw updated to version 0.0.2 with previous version 0.0.1 dated 2020-07-18

Title: Additional Tools for Splitting and Cleaning Data
Description: Move between data frames and lists more efficiently with precision splitting via 'dplyr' verbs. Easily cast variables to different data types. Keep rows with NAs. Shift row values.
Author: David Ranzolin [aut, cre, cph]
Maintainer: David Ranzolin <daranzolin@gmail.com>

Diff between hacksaw versions 0.0.1 dated 2020-07-18 and 0.0.2 dated 2020-12-15

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 10 files changed, 196 insertions(+), 69 deletions(-)

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