Thu, 02 Sep 2021

Package Sequential updated to version 3.4 with previous version 3.3.3 dated 2021-08-21

Title: Exact Sequential Analysis for Poisson and Binomial Data
Description: Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled.
Author: Ivair Ramos Silva and Martin Kulldorff
Maintainer: Ivair Ramos Silva <ivair@ufop.edu.br>

Diff between Sequential versions 3.3.3 dated 2021-08-21 and 3.4 dated 2021-09-02

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Package sensitivity updated to version 1.26.1 with previous version 1.26.0 dated 2021-07-09

Title: Global Sensitivity Analysis of Model Outputs
Description: A collection of functions for factor screening, global sensitivity analysis and robustness analysis. Most of the functions have to be applied on model with scalar output, but several functions support multi-dimensional outputs.
Author: Bertrand Iooss, Sebastien Da Veiga, Alexandre Janon and Gilles Pujol, with contributions from Baptiste Broto, Khalid Boumhaout, Thibault Delage, Reda El Amri, Jana Fruth, Laurent Gilquin, Joseph Guillaume, Marouane Il Idrissi, Loic Le Gratiet, Paul Lemaitre, Amandine Marrel, Anouar Meynaoui, Barry L. Nelson, Filippo Monari, Roelof Oomen, Oldrich Rakovec, Bernardo Ramos, Olivier Roustant, Eunhye Song, Jeremy Staum, Roman Sueur, Taieb Touati, Vanessa Verges, Frank Weber
Maintainer: Bertrand Iooss <biooss@yahoo.fr>

Diff between sensitivity versions 1.26.0 dated 2021-07-09 and 1.26.1 dated 2021-09-02

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Package RQuantLib updated to version 0.4.13 with previous version 0.4.12 dated 2020-04-02

Title: R Interface to the 'QuantLib' Library
Description: The 'RQuantLib' package makes parts of 'QuantLib' accessible from R The 'QuantLib' project aims to provide a comprehensive software framework for quantitative finance. The goal is to provide a standard open source library for quantitative analysis, modeling, trading, and risk management of financial assets.
Author: Dirk Eddelbuettel, Khanh Nguyen (2009-2010), Terry Leitch (since 2016)
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RQuantLib versions 0.4.12 dated 2020-04-02 and 0.4.13 dated 2021-09-02

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Package RobustGaSP updated to version 0.6.3 with previous version 0.6.2 dated 2021-05-17

Title: Robust Gaussian Stochastic Process Emulation
Description: Robust parameter estimation and prediction of Gaussian stochastic process emulators. It allows for robust parameter estimation and prediction using Gaussian stochastic process emulator. It also implements the parallel partial Gaussian stochastic process emulator for computer model with massive outputs See the reference: Mengyang Gu and Jim Berger, 2016, Annals of Applied Statistics; Mengyang Gu, Xiaojing Wang and Jim Berger, 2018, Annals of Statistics.
Author: Mengyang Gu [aut, cre], Jesus Palomo [aut], James Berger [aut]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>

Diff between RobustGaSP versions 0.6.2 dated 2021-05-17 and 0.6.3 dated 2021-09-02

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Package mlr3cluster updated to version 0.1.2 with previous version 0.1.1 dated 2020-11-15

Title: Cluster Extension for 'mlr3'
Description: Extends the 'mlr3' package with cluster analysis.
Author: Damir Pulatov [cre, aut], Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Damir Pulatov <damirpolat@protonmail.com>

Diff between mlr3cluster versions 0.1.1 dated 2020-11-15 and 0.1.2 dated 2021-09-02

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Package landscapemetrics updated to version 1.5.4 with previous version 1.5.3 dated 2021-07-06

Title: Landscape Metrics for Categorical Map Patterns
Description: Calculates landscape metrics for categorical landscape patterns in a tidy workflow. 'landscapemetrics' reimplements the most common metrics from 'FRAGSTATS' (<https://www.umass.edu/landeco/research/fragstats/fragstats.html>) and new ones from the current literature on landscape metrics. This package supports 'raster' spatial objects and takes RasterLayer, RasterStacks, RasterBricks or lists of RasterLayer from the 'raster' package as input arguments. It further provides utility functions to visualize patches, select metrics and building blocks to develop new metrics.
Author: Maximillian H.K. Hesselbarth [aut, cre] (<https://orcid.org/0000-0003-1125-9918>), Marco Sciaini [aut] (<https://orcid.org/0000-0002-3042-5435>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Sebastian Hanss [aut] (<https://orcid.org/0000-0002-3990-4897>), Laura J. Graham [ctb] (Input on package structure), Jeffrey Hollister [ctb] (Input on package structure), Kimberly A. With [ctb] (Input on package structure), Florian Privé [ctb] (Original author of underlying C++ code for get_nearestneighbour() function), Project Nayuki [ctb] (Original author of underlying C++ code for get_circumscribingcircle and lsm_p_circle), Matt Strimas-Mackey [ctb] (Bugfix in sample_metrics())
Maintainer: Maximillian H.K. Hesselbarth <mhk.hesselbarth@gmail.com>

Diff between landscapemetrics versions 1.5.3 dated 2021-07-06 and 1.5.4 dated 2021-09-02

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Package image.textlinedetector updated to version 0.1.5 with previous version 0.1.4 dated 2021-07-07

Title: Segment Images in Text Lines and Words
Description: Find text lines in scanned images and segment the lines into words. Includes implementations of the paper 'Novel A* Path Planning Algorithm for Line Segmentation of Handwritten Documents' by Surinta O. et al (2014) <doi:10.1109/ICFHR.2014.37> available at <https://github.com/smeucci/LineSegm>, an implementation of 'A Statistical approach to line segmentation in handwritten documents' by Arivazhagan M. et al (2007) <doi:10.1117/12.704538>, and a wrapper for an image segmentation technique to detect words in text lines as described in the paper 'Scale Space Technique for Word Segmentation in Handwritten Documents' by Manmatha R. and Srimal N. (1999) paper at <doi:10.1007/3-540-48236-9_3>, wrapper for code available at <https://github.com/arthurflor23/text-segmentation>.
Author: Jan Wijffels [aut, cre, cph] (R wrapper), Vrije Universiteit Brussel - DIGI: Brussels Platform for Digital Humanities [cph] (R wrapper), Jeroen Ooms [ctb, cph] (More details in LICENSE.note file), Arthur Flôr [ctb, cph] (More details in LICENSE.note file), Saverio Meucci [ctb, cph] (More details in LICENSE.note file), Yeara Kozlov [ctb, cph] (More details in LICENSE.note file), Tino Weinkauf [ctb, cph] (More details in LICENSE.note file)
Maintainer: Jan Wijffels <jan.wijffels@vub.be>

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Package healthyR.ai updated to version 0.0.2 with previous version 0.0.1 dated 2021-08-20

Title: The Machine Learning and AI Modeling Companion to 'healthyR'
Description: Hospital machine learning and ai data analysis workflow tools, modeling, and automations. This library provides many useful tools to review common administrative hospital data. Some of these include predicting length of stay, and readmits. The aim is to provide a simple and consistent verb framework that takes the guesswork out of everything.
Author: Steven Sanderson [aut, cre, cph]
Maintainer: Steven Sanderson <spsanderson@gmail.com>

Diff between healthyR.ai versions 0.0.1 dated 2021-08-20 and 0.0.2 dated 2021-09-02

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Package HDShOP updated to version 0.1.1 with previous version 0.1.0 dated 2021-08-02

Title: High-Dimensional Shrinkage Optimal Portfolios
Description: Constructs shrinkage estimators of high-dimensional mean-variance portfolios and performs high-dimensional tests on optimality of a given portfolio. The techniques developed in Bodnar et al. (2018) <doi:10.1016/j.ejor.2017.09.028>, Bodnar et al. (2019) <doi:10.1109/TSP.2019.2929964>, Bodnar et al. (2020) <doi:10.1109/TSP.2020.3037369> are central to the package. They provide simple and feasible estimators and tests for optimal portfolio weights, which are applicable for 'large p and large n' situations where p is the portfolio dimension (number of stocks) and n is the sample size. The package also includes tools for constructing portfolios based on shrinkage estimators of the mean vector and covariance matrix as well as a new Bayesian estimator for the Markowitz efficient frontier recently developed by Bauder et al. (2021) <doi:10.1080/14697688.2020.1748214>.
Author: Taras Bodnar [aut] (<https://orcid.org/0000-0001-7855-8221>), Solomiia Dmytriv [aut] (<https://orcid.org/0000-0003-1855-3044>), Yarema Okhrin [aut] (<https://orcid.org/0000-0003-4704-5233>), Dmitry Otryakhin [aut, cre] (<https://orcid.org/0000-0002-4700-7221>), Nestor Parolya [aut] (<https://orcid.org/0000-0003-2147-2288>)
Maintainer: Dmitry Otryakhin <d.otryakhin.acad@protonmail.ch>

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Package ffscrapr updated to version 1.4.6 with previous version 1.4.5 dated 2021-07-25

Title: API Client for Fantasy Football League Platforms
Description: Helps access various Fantasy Football APIs by handling authentication and rate-limiting, forming appropriate calls, and returning tidy dataframes which can be easily connected to other data sources.
Author: Tan Ho [aut, cre], Tony ElHabr [ctb], Joe Sydlowski [ctb]
Maintainer: Tan Ho <tan@tanho.ca>

Diff between ffscrapr versions 1.4.5 dated 2021-07-25 and 1.4.6 dated 2021-09-02

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Package dsb updated to version 0.2.0 with previous version 0.1.0 dated 2021-02-08

Title: Normalize & Denoise Droplet Single Cell Protein Data (CITE-Seq)
Description: This lightweight R package provides a method for normalizing and denoising protein expression data from droplet based single cell experiments. Raw protein Unique Molecular Index (UMI) counts from sequencing DNA-conjugated antibodies in droplets (e.g. 'CITE-seq') have substantial measurement noise. Our experiments and computational modeling revealed two major components of this noise: 1) protein-specific noise originating from ambient, unbound antibody encapsulated in droplets that can be accurately inferred via the expected protein counts detected in empty droplets, and 2) droplet/cell-specific noise revealed via the shared variance component associated with isotype antibody controls and background protein counts in each cell. This package normalizes and removes both of these sources of noise from raw protein data derived from methods such as 'CITE-seq', 'REAP-seq', 'ASAP-seq', 'TEA-seq', 'proteogenomic' data from the Mission Bio platform, etc. See the vignette for tutorials on how to integrate dsb with 'Seurat', 'Bioconductor' and the AnnData class in 'Python'. Please also see our preprint Mulè M.P., Martins A.J., and Tsang J.S. (2020) <https://www.biorxiv.org/content/10.1101/2020.02.24.963603v3> for more details on the dsb method.
Author: Matthew Mulè [aut, cre] (<https://orcid.org/0000-0001-8457-2716>), Andrew Martins [aut] (<https://orcid.org/0000-0002-1832-1924>), John Tsang [pdr] (<https://orcid.org/0000-0003-3186-3047>)
Maintainer: Matthew Mulè <mattmule@gmail.com>

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Package blockmodeling updated to version 1.0.5 with previous version 1.0.0 dated 2020-07-01

Title: Generalized and Classical Blockmodeling of Valued Networks
Description: This is primarily meant as an implementation of generalized blockmodeling for valued networks. In addition, measures of similarity or dissimilarity based on structural equivalence and regular equivalence (REGE algorithms) can be computed and partitioned matrices can be plotted: Žiberna (2007)<doi:10.1016/j.socnet.2006.04.002>, Žiberna (2008)<doi:10.1080/00222500701790207>, Žiberna (2014)<doi:10.1016/j.socnet.2014.04.002>.
Author: Aleš Žiberna [aut, cre]
Maintainer: Aleš Žiberna <ales.ziberna@gmail.com>

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Package bayestestR updated to version 0.11.0 with previous version 0.10.5 dated 2021-07-26

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors).
Author: Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>, @mattansb), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Michael D. Wilson [aut] (<https://orcid.org/0000-0003-4143-7308>), Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>, @bmwiernik), Paul-Christian Bürkner [rev], Tristan Mahr [rev] (<https://orcid.org/0000-0002-8890-5116>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Quentin F. Gronau [ctb] (<https://orcid.org/0000-0001-5510-6943>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

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Package wdnr.gis updated to version 0.1.2 with previous version 0.1.0 dated 2021-03-05

Title: Pull Spatial Layers from 'WDNR ArcGIS REST API'
Description: Functions for finding and pulling data from the 'Wisconsin Department of Natural Resources ArcGIS REST APIs' <https://dnrmaps.wi.gov/arcgis/rest/services> and <https://dnrmaps.wi.gov/arcgis2/rest/services>.
Author: Paul Frater [aut, cre] (<https://orcid.org/0000-0002-7237-6563>), Zac Driscoll [aut] (<https://orcid.org/0000-0002-8233-0980>)
Maintainer: Paul Frater <paul.frater@wisconsin.gov>

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Package troopdata updated to version 0.1.4 with previous version 0.1.3 dated 2021-04-12

Title: Tools for Analyzing Cross-National Military Deployment and Basing Data
Description: These functions generate data frames on troop deployments and military basing using U.S. Department of Defense data on overseas military deployments. This package provides functions for pulling country-year troop deployment and basing data. Subsequent versions will hopefully include cross-national data on deploying countries.
Author: Michael Flynn [aut, cre] (<https://orcid.org/0000-0002-6064-740X>)
Maintainer: Michael Flynn <meflynn@ksu.edu>

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Package quarks updated to version 1.0.8 with previous version 1.0.7 dated 2021-09-02

Title: Simple Methods for Calculating Value at Risk and Expected Shortfall
Description: Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain-, age-, volatility-weighted- and filtered historical simulation are implemented in this package. Volatility weighting can be carried out via an exponentially weighted moving average model (EWMA) or other GARCH-type models. The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525>.
Author: Sebastian Letmathe [aut, cre] (Paderborn University, Germany)
Maintainer: Sebastian Letmathe <sebastian.letmathe@uni-paderborn.de>

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Package ggplotify updated to version 0.1.0 with previous version 0.0.9 dated 2021-08-20

Title: Convert Plot to 'grob' or 'ggplot' Object
Description: Convert plot function call (using expression or formula) to 'grob' or 'ggplot' object that compatible to the 'grid' and 'ggplot2' ecosystem. With this package, we are able to e.g. using 'cowplot' to align plots produced by 'base' graphics, 'ComplexHeatmap', 'eulerr', 'grid', 'lattice', 'magick', 'pheatmap', 'vcd' etc. by converting them to 'ggplot' objects.
Author: Guangchuang Yu [aut, cre] (<https://orcid.org/0000-0002-6485-8781>)
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package FastGaSP updated to version 0.5.2 with previous version 0.5.1 dated 2019-04-12

Title: Fast and Exact Computation of Gaussian Stochastic Process
Description: Implements fast and exact computation of Gaussian stochastic process with the Matern kernel using forward filtering and backward smoothing algorithm. It allows for the cases with or without a noise. See the reference: Mengyang Gu and Yanxun Xu (2017), <arXiv:1711.11501>.
Author: Mengyang Gu [aut, cre]
Maintainer: Mengyang Gu <mengyang@pstat.ucsb.edu>

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Package fasano.franceschini.test updated to version 1.1.0 with previous version 1.0.1 dated 2021-07-17

Title: Fasano-Franceschini Test: A 2-D Kolmogorov-Smirnov Two-Sample Test
Description: An implementation of the 2-D Kolmogorov-Smirnov (KS) two-sample test as defined by Fasano and Franceschini (Fasano and Franceschini 1987). The 'fasano.franceschini.test' package provides three improvements over the current 2-D KS test on the Comprehensive R Archive Network (CRAN): (i) the Fasano and Franceschini test has been shown to run in O(n^2) versus the Peacock implementation which runs in O(n^3); (ii) the package implements a procedure for handling ties in the data; and (iii) the package implements a parallelized permutation procedure for improved significance testing. Ultimately, the 'fasano.franceschini.test' package presents a robust statistical test for analyzing random samples defined in 2-dimensions.
Author: Elan Ness-Cohn [aut, cre] (<https://orcid.org/0000-0002-3935-6667>), Rosemary Braun [ctb, ths] (<https://orcid.org/0000-0001-9668-9866>)
Maintainer: Elan Ness-Cohn <elanness-cohn2017@u.northwestern.edu>

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Package dmlalg updated to version 1.0.1 with previous version 0.0.2 dated 2021-06-21

Title: Double Machine Learning Algorithms
Description: Implementation of double machine learning (DML) algorithms in R, based on Emmenegger and Buehlmann (2021) "Regularizing Double Machine Learning in Partially Linear Endogenous Models" <arXiv:2101.12525> and Emmenegger and Buehlmann (2021) <arXiv:2108.13657> "Double Machine Learning for Partially Linear Mixed-Effects Models with Repeated Measurements". First part: our goal is to perform inference for the linear parameter in partially linear models with confounding variables. The standard DML estimator of the linear parameter has a two-stage least squares interpretation, which can lead to a large variance and overwide confidence intervals. We apply regularization to reduce the variance of the estimator, which produces narrower confidence intervals that are approximately valid. Nuisance terms can be flexibly estimated with machine learning algorithms. Second part: our goal is to estimate and perform inference for the linear coefficient in a partially linear mixed-effects model with DML. Machine learning algorithms allows us to incorporate more complex interaction structures and high-dimensional variables.
Author: Corinne Emmenegger [aut, cre] (<https://orcid.org/0000-0003-0353-8888>), Peter Buehlmann [ths] (<https://orcid.org/0000-0002-1782-6015>)
Maintainer: Corinne Emmenegger <emmenegger@stat.math.ethz.ch>

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Package SynthETIC updated to version 1.0.2 with previous version 1.0.1 dated 2021-06-26

Title: Synthetic Experience Tracking Insurance Claims
Description: Creation of an individual claims simulator which generates various features of non-life insurance claims. An initial set of test parameters, designed to mirror the experience of an Auto Liability portfolio, were set up and applied by default to generate a realistic test data set of individual claims (see vignette). The simulated data set then allows practitioners to back-test the validity of various reserving models and to prove and/or disprove certain actuarial assumptions made in claims modelling. The distributional assumptions used to generate this data set can be easily modified by users to match their experiences. Reference: Avanzi B, Taylor G, Wang M, Wong B (2020) "SynthETIC: an individual insurance claim simulator with feature control" <arXiv:2008.05693>.
Author: Benjamin Avanzi [aut], Greg Taylor [aut], Melantha Wang [aut, cre], Bernard Wong [aut]
Maintainer: Melantha Wang <wang.melantha@gmail.com>

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Package soc.ca updated to version 0.8.0 with previous version 0.7.3 dated 2016-02-09

Title: Specific Correspondence Analysis for the Social Sciences
Description: Specific and class specific multiple correspondence analysis on survey-like data. Soc.ca is optimized to the needs of the social scientist and presents easily interpretable results in near publication ready quality.
Author: Anton Grau Larsen and Jacob Lunding with contributions from Christoph Ellersgaard and Stefan Andrade
Maintainer: Anton Grau Larsen <agraul@ruc.dk>

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Package QTLEMM updated to version 1.0.0 with previous version 0.1.0 dated 2021-06-11

Title: QTL Mapping and Hotspots Detection
Description: For QTL mapping, it consists of several functions to perform various tasks, including simulating or analyzing data, computing the significance thresholds and visualizing the QTL mapping results. The single-QTL or multiple-QTL method that allows a host of statistical models to be fitted and compared is applied to analyze the data for the estimation of QTL parameters. The models include the linear regression, permutation test, normal mixture model and truncated normal mixture model. The Gaussian stochastic process is implemented to compute the significance thresholds for QTL detection onto a genetic linkage map in the experimental populations. Two types of data, the complete genotyping or selective genotyping data, from various experimental populations, including backcross, F2, recombinant inbred (RI) populations, advanced intercrossed (AI) populations, are considered in the QTL mapping analysis. For QTL hotpot detection, the statistical methods can be developed based on either using the individual-level data or using the summarized data. We have proposed a statistical framework that can handle both the individual-level data and summarized QTL data for QTL hotspots detection. Our statistical framework can overcome the underestimation of threshold arising from ignoring the correlation structure among traits, and also identify the different types of hotspots with very low computational cost during the detection process. Here, we attempt to provide the R codes of our QTL mapping and hotspot detection methods for general use in genes, genomics and genetics studies. The QTL mapping methods for the complete and selective genotyping designs are based on the multiple interval mapping (MIM) model proposed by Kao, C.-H. , Z.-B. Zeng and R. D. Teasdale (1999) <doi:10.1534/genetics.103.021642> and H.-I Lee, H.-A. Ho and C.-H. Kao (2014) <doi:10.1534/genetics.114.168385>, respectively. The QTL hotspot detection analysis is based on the method by Wu, P.-Y., M.-.H. Yang, and C.-H. Kao (2021) .
Author: Ping-Yuan Chung [cre], Chen-Hung Kao [aut]
Maintainer: Ping-Yuan Chung <pychung@webmail.stat.sinica.edu.tw>

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Package polyRAD updated to version 1.5 with previous version 1.4 dated 2021-03-22

Title: Genotype Calling with Uncertainty from Sequencing Data in Polyploids and Diploids
Description: Read depth data from genotyping-by-sequencing (GBS) or restriction site-associated DNA sequencing (RAD-seq) are imported and used to make Bayesian probability estimates of genotypes in polyploids or diploids. The genotype probabilities, posterior mean genotypes, or most probable genotypes can then be exported for downstream analysis. 'polyRAD' is described by Clark et al. (2019) <doi:10.1534/g3.118.200913>. A variant calling pipeline for highly duplicated genomes is also included and is described by Clark et al. (2020) <doi:10.1101/2020.01.11.902890>.
Author: Lindsay V. Clark [aut, cre] (<https://orcid.org/0000-0002-3881-9252>), U.S. National Science Foundation [fnd]
Maintainer: Lindsay V. Clark <lvclark@illinois.edu>

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Package NGSSEML updated to version 2.2 with previous version 2.1 dated 2020-10-19

Title: Non-Gaussian State-Space with Exact Marginal Likelihood
Description: Due to a large quantity of non-Gaussian time series and reliability data, the R-package non-Gaussian state-space with exact marginal likelihood is useful for modeling and forecasting non-Gaussian time series and reliability data via non-Gaussian state-space models with the exact marginal likelihood easily, see Gamerman, Santos and Franco (2013) <doi:10.1111/jtsa.12039> and Santos, Gamerman and Franco (2017) <doi:10.1109/TR.2017.2670142>. The package gives codes for formulating and specifying the non-Gaussian state-space models in the R language. Inferences for the parameters of the model can be made under the classical and Bayesian. Furthermore, prediction, filtering, and smoothing procedures can be used to perform inferences for the latent parameters. Applications include, e.g., count, volatility, piecewise exponential, and software reliability data.
Author: Thiago Rezende dos Santos <thiagords@est.ufmg.br>, Dani Gamerman <dani@im.ufrj.br>, Glaura da Conceicao Franco <glaura@est.ufmg.br>
Maintainer: T. R. dos Santos <thiagords@est.ufmg.br>

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Package metamisc updated to version 0.2.4 with previous version 0.2.3 dated 2020-09-24

Title: Meta-Analysis of Diagnosis and Prognosis Research Studies
Description: Facilitate frequentist and Bayesian meta-analysis of diagnosis and prognosis research studies. It includes functions to summarize multiple estimates of prediction model discrimination and calibration performance (Debray et al., 2019) <doi:10.1177/0962280218785504>. It also includes functions to evaluate funnel plot asymmetry (Debray et al., 2018) <doi:10.1002/jrsm.1266>. Finally, the package provides functions for developing multivariable prediction models from datasets with clustering (de Jong et al., 2021) <doi:10.1002/sim.8981>.
Author: Thomas Debray [aut, cre] (<https://orcid.org/0000-0002-1790-2719>), Valentijn de Jong [aut] (<https://orcid.org/0000-0001-9921-3468>)
Maintainer: Thomas Debray <thomas.debray@gmail.com>

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Package markmyassignment updated to version 0.8.6 with previous version 0.8.3 dated 2020-09-12

Title: Automatic Marking of R Assignments
Description: Automatic marking of R assignments for students and teachers based on 'testthat' test suites.
Author: Mans Magnusson, Oscar Pettersson
Maintainer: Mans Magnusson <mons.magnusson@gmail.com>

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Package JSmediation updated to version 0.2.0 with previous version 0.1.2 dated 2021-06-18

Title: Mediation Analysis Using Joint Significance
Description: A set of helper functions to conduct joint-significance tests for mediation analysis, as recommended by Yzerbyt, Muller, Batailler, & Judd. (2018) <doi:10.1037/pspa0000132>.
Author: Cédric Batailler [aut, cre] (<https://orcid.org/0000-0003-0553-6827>), Dominique Muller [aut] (<https://orcid.org/0000-0001-9544-5317>), Vincent Yzerbyt [aut], Charles Judd [aut], Yoann Julliard [ctb] (<https://orcid.org/0000-0002-5428-6994>), Arnold Ho [dtc], Nour Kteily [dtc], Jacqueline Chen [dtc], Simone Dohle [dtc], Michael Siegrist [dtc]
Maintainer: Cédric Batailler <cedric.batailler@gmail.com>

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Package gets updated to version 0.29 with previous version 0.27 dated 2021-02-21

Title: General-to-Specific (GETS) Modelling and Indicator Saturation Methods
Description: Automated General-to-Specific (GETS) modelling of the mean and variance of a regression, and indicator saturation methods for detecting and testing for structural breaks in the mean, see Pretis, Reade and Sucarrat (2018) <doi:10.18637/jss.v086.i03>.
Author: Genaro Sucarrat [aut, cre], Felix Pretis [aut], James Reade [aut], Jonas Kurle [ctb], Moritz Schwarz [ctb]
Maintainer: Genaro Sucarrat <genaro.sucarrat@bi.no>

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Package Fiscore updated to version 0.1.3 with previous version 0.1.2 dated 2021-08-17

Title: Effective Protein Structural Data Visualisation and Exploration
Description: Collection of structural analysis tolls to compliment the research paper "Fi-score: a novel approach to characterise protein topology and aid in drug discovery studies" ;<doi:10.1080/07391102.2020.1854859>. 'Fiscore' package allows to explore and identify new topologically and functionally relevant structural features by applying integrated Gaussian Mixture Models.
Author: Auste Kanapeckaite
Maintainer: Auste Kanapeckaite <auste.kan@algorithm379.com>

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Package DDIwR updated to version 0.8 with previous version 0.7 dated 2021-08-19

Title: DDI with R
Description: Useful functions for various DDI (Data Documentation Initiative) related inputs and outputs. Converts data files to and from SPSS, Stata, SAS, R and Excel, including user declared missing values.
Author: Adrian Dusa [aut, cre, cph] (<https://orcid.org/0000-0002-3525-9253>)
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package CoTiMA updated to version 0.4.3 with previous version 0.4.0 dated 2021-05-20

Title: Continuous Time Meta-Analysis ('CoTiMA')
Description: The 'CoTiMA' package performs meta-analyses of correlation matrices of repeatedly measured variables taken from studies that used different time intervals. Different time intervals between measurement occasions impose problems for meta-analyses because the effects (e.g. cross-lagged effects) cannot be simply aggregated, for example, by means of common fixed or random effects analysis. However, continuous time math, which is applied in 'CoTiMA', can be used to extrapolate or intrapolate the results from all studies to any desired time lag. By this, effects obtained in studies that used different time intervals can be meta-analyzed. 'CoTiMA' fits models to empirical data using the structural equation model (SEM) package 'ctsem', the effects specified in a SEM are related to parameters that are not directly included in the model (i.e., continuous time parameters; together, they represent the continuous time structural equation model, CTSEM). Statistical model comparisons and significance tests are then performed on the continuous time parameter estimates. 'CoTiMA' also allows analysis of publication bias (Egger's test, PET-PEESE estimates, zcurve analysis etc.) and analysis of statistical power (post hoc power, required sample sizes). See Dormann, C., Guthier, C., & Cortina, J. M. (2019) <doi:10.1177/1094428119847277>. and Guthier, C., Dormann, C., & Voelkle, M. C. (2020) <doi:10.1037/bul0000304>.
Author: Christian Dormann [aut, cph], Markus Homberg [aut, com, cre], Christina Guthier [ctb], Manuel Voelkle [ctb]
Maintainer: Markus Homberg <cotima@uni-mainz.de>

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Package asremlPlus updated to version 4.3-19 with previous version 4.2-32 dated 2021-03-21

Title: Augments 'ASReml-R' in Fitting Mixed Models and Packages Generally in Exploring Prediction Differences
Description: Assists in automating the selection of terms to include in mixed models when 'asreml' is used to fit the models. Also used to display, in tables and graphs, predictions obtained using any model fitting function and to explore differences between predictions. The content falls into the following natural groupings: (i) Data, (ii) Object manipulation functions, (iii) Model modification functions, (iv) Model testing functions, (v) Model diagnostics functions, (vi) Prediction production and presentation functions, (vii) Response transformation functions, and (viii) Miscellaneous functions (for further details see 'asremlPlus-package' in help). A history of the fitting of a sequence of models is kept in a data frame. Procedures are available for choosing models that conform to the hierarchy or marginality principle and for displaying predictions for significant terms in tables and graphs. The 'asreml' package provides a computationally efficient algorithm for fitting mixed models using Residual Maximum Likelihood. It is a commercial package that can be purchased from 'VSNi' <https://www.vsni.co.uk/> as 'asreml-R', who will supply a zip file for local installation/updating (see <https://asreml.kb.vsni.co.uk/>). It is not needed for functions that are methods for 'alldiffs' and 'data.frame' objects. The package 'asremPlus' can also be installed from <http://chris.brien.name/rpackages/>.
Author: Chris Brien [aut, cre] (<https://orcid.org/0000-0003-0581-1817>)
Maintainer: Chris Brien <chris.brien@adelaide.edu.au>

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Package SWMPr updated to version 2.4.1 with previous version 2.4.0 dated 2021-01-05

Title: Retrieving, Organizing, and Analyzing Estuary Monitoring Data
Description: Tools for retrieving, organizing, and analyzing environmental data from the System Wide Monitoring Program of the National Estuarine Research Reserve System <http://cdmo.baruch.sc.edu/>. These tools address common challenges associated with continuous time series data for environmental decision making.
Author: Marcus W. Beck [aut, cre], Kimberly Cressman [ctb]
Maintainer: Marcus W. Beck <mbeck@tbep.org>

Diff between SWMPr versions 2.4.0 dated 2021-01-05 and 2.4.1 dated 2021-09-02

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Package StratifiedMedicine updated to version 1.0.4 with previous version 1.0.3 dated 2021-01-07

Title: Stratified Medicine
Description: A toolkit for stratified medicine, subgroup identification, and precision medicine. Current tools include (1) filtering models (reduce covariate space), (2) patient-level estimate models (counterfactual patient-level quantities, such as the conditional average treatment effect), (3) subgroup identification models (find subsets of patients with similar treatment effects), and (4) treatment effect estimation and inference (for the overall population and discovered subgroups). These tools can be customized and are directly used in PRISM (patient response identifiers for stratified medicine; Jemielita and Mehrotra 2019 <arXiv:1912.03337>. This package is in beta and will be continually updated.
Author: Thomas Jemielita [aut, cre]
Maintainer: Thomas Jemielita <thomasjemielita@gmail.com>

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Permanent link

New package splash with initial version 1.0.0
Package: splash
Title: Simple Process-Led Algorithms for Simulating Habitats
Version: 1.0.0
Description: This program calculates bioclimatic indices and fluxes (radiation, evapotranspiration, soil moisture) for use in studies of ecosystem function, species distribution, and vegetation dynamics under changing climate scenarios. Predictions are based on a minimum of required inputs: latitude, precipitation, air temperature, and cloudiness. Davis et al. (2017) <doi:10.5194/gmd-10-689-2017>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.2.3)
Language: en-GB
URL: https://github.com/villegar/splash/, https://villegar.github.io/splash/, https://bitbucket.org/labprentice/splash/
BugReports: https://github.com/villegar/splash/issues/
NeedsCompilation: no
Packaged: 2021-09-01 12:02:04 UTC; roberto.villegas-diaz
Author: Tyler W. Davis [aut] (<https://orcid.org/0000-0003-4312-919X>), Iain Colin Prentice [aut] (<https://orcid.org/0000-0002-1296-6764>), Benjamin D. Stocker [aut] (<https://orcid.org/0000-0003-2697-9096>), Rebecca T. Thomas [aut], Rhys J. Whitley [aut], Han Wang [aut] (<https://orcid.org/0000-0003-2482-1818>), Bradley J. Evans [aut], Angela V. Gallego-Sala [aut], Martin T. Sykes [aut], Wolfgang Cramer [aut] (<https://orcid.org/0000-0002-9205-5812>), Roberto Villegas-Diaz [cre] (<https://orcid.org/0000-0001-5036-8661>)
Maintainer: Roberto Villegas-Diaz <r.villegas-diaz@reading.ac.uk>
Repository: CRAN
Date/Publication: 2021-09-02 22:00:02 UTC

More information about splash at CRAN
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Package Rvcg updated to version 0.20 with previous version 0.19.2 dated 2021-01-11

Title: Manipulations of Triangular Meshes Based on the 'VCGLIB' API
Description: Operations on triangular meshes based on 'VCGLIB'. This package integrates nicely with the R-package 'rgl' to render the meshes processed by 'Rvcg'. The Visualization and Computer Graphics Library (VCG for short) is an open source portable C++ templated library for manipulation, processing and displaying with OpenGL of triangle and tetrahedral meshes. The library, composed by more than 100k lines of code, is released under the GPL license, and it is the base of most of the software tools of the Visual Computing Lab of the Italian National Research Council Institute ISTI <http://vcg.isti.cnr.it>, like 'metro' and 'MeshLab'. The 'VCGLIB' source is pulled from trunk <https://github.com/cnr-isti-vclab/vcglib> and patched to work with options determined by the configure script as well as to work with the header files included by 'RcppEigen'.
Author: Stefan Schlager [aut, cre, cph], Girinon Francois [ctb], Tim Schaefer [ctb]
Maintainer: Stefan Schlager <zarquon42@gmail.com>

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Package rdrobust updated to version 1.0.6 with previous version 1.0.5 dated 2021-08-12

Title: Robust Data-Driven Statistical Inference in Regression-Discontinuity Designs
Description: Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Author: Sebastian Calonico <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>, Rocio Titiunik <titiunik@princeton.edu>
Maintainer: Sebastian Calonico <sebastian.calonico@columbia.edu>

Diff between rdrobust versions 1.0.5 dated 2021-08-12 and 1.0.6 dated 2021-09-02

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Package RcppSMC updated to version 0.2.4 with previous version 0.2.3 dated 2021-02-10

Title: Rcpp Bindings for Sequential Monte Carlo
Description: R access to the Sequential Monte Carlo Template Classes by Johansen <doi:10.18637/jss.v030.i06> is provided. At present, four additional examples have been added, and the first example from the JSS paper has been extended. Further integration and extensions are planned.
Author: Dirk Eddelbuettel, Adam M. Johansen, Leah F. South and Ilya Zarubin
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package proxyC updated to version 0.2.1 with previous version 0.2.0 dated 2021-05-11

Title: Computes Proximity in Large Sparse Matrices
Description: Computes proximity between rows or columns of large matrices efficiently in C++. Functions are optimised for large sparse matrices using the Armadillo and Intel TBB libraries. Among several built-in similarity/distance measures, computation of correlation, cosine similarity and Euclidean distance is particularly fast.
Author: Kohei Watanabe [cre, aut, cph] (<https://orcid.org/0000-0001-6519-5265>), Robrecht Cannoodt [aut] (<https://orcid.org/0000-0003-3641-729X>)
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

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More information about proxyC at CRAN
Permanent link

Package mbRes updated to version 0.1.1 with previous version 0.1.0 dated 2021-05-19

Title: Integrating Multiple Biomarker Responses in Aquatic Organisms using Effect Size, Statistical Uncertainty, and Ecological Relevance
Description: Compute and visualize the ps-index, a new integrated index for multiple biomarker responses, as described in Pham & Sokolova (2021, unpublished).
Author: Duy Nghia Pham [aut, cre] (<https://orcid.org/0000-0003-1349-1710>), Inna M. Sokolova [aut] (<https://orcid.org/0000-0002-2068-4302>)
Maintainer: Duy Nghia Pham <nghiapham@yandex.com>

Diff between mbRes versions 0.1.0 dated 2021-05-19 and 0.1.1 dated 2021-09-02

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Package Luminescence updated to version 0.9.15 with previous version 0.9.14 dated 2021-07-21

Title: Comprehensive Luminescence Dating Data Analysis
Description: A collection of various R functions for the purpose of Luminescence dating data analysis. This includes, amongst others, data import, export, application of age models, curve deconvolution, sequence analysis and plotting of equivalent dose distributions.
Author: Sebastian Kreutzer [aut, trl, cre, dtc] (<https://orcid.org/0000-0002-0734-2199>), Christoph Burow [aut, trl, dtc] (<https://orcid.org/0000-0002-5023-4046>), Michael Dietze [aut] (<https://orcid.org/0000-0001-6063-1726>), Margret C. Fuchs [aut] (<https://orcid.org/0000-0001-7210-1132>), Christoph Schmidt [aut] (<https://orcid.org/0000-0002-2309-3209>), Manfred Fischer [aut, trl], Johannes Friedrich [aut] (<https://orcid.org/0000-0002-0805-9547>), Norbert Mercier [aut] (<https://orcid.org/0000-0002-6375-9108>), Rachel K. Smedley [ctb] (<https://orcid.org/0000-0001-7773-5193>), Claire Christophe [ctb], Antoine Zink [ctb] (<https://orcid.org/0000-0001-7146-1101>), Julie Durcan [ctb] (<https://orcid.org/0000-0001-8724-8022>), Georgina E. King [ctb, dtc] (<https://orcid.org/0000-0003-1059-8192>), Anne Philippe [aut] (<https://orcid.org/0000-0002-5331-5087>), Guillaume Guerin [ctb] (<https://orcid.org/0000-0001-6298-5579>), Svenja Riedesel [aut] (<https://orcid.org/0000-0003-2936-8776>), Martin Autzen [aut] (<https://orcid.org/0000-0001-6249-426X>), Pierre Guibert [ctb] (<https://orcid.org/0000-0001-8969-8684>), Dirk Mittelstrass [aut] (<https://orcid.org/0000-0002-9567-8791>), Harrison J. Gray [aut] (<https://orcid.org/0000-0002-4555-7473>), Markus Fuchs [ths]
Maintainer: Sebastian Kreutzer <sebastian.kreutzer@aber.ac.uk>

Diff between Luminescence versions 0.9.14 dated 2021-07-21 and 0.9.15 dated 2021-09-02

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More information about Luminescence at CRAN
Permanent link

Package imp4p updated to version 1.2 with previous version 1.1 dated 2021-03-22

Title: Imputation for Proteomics
Description: Functions to analyse missing value mechanisms and to impute data sets in the context of bottom-up MS-based proteomics.
Author: Quentin Giai Gianetto
Maintainer: Quentin Giai Gianetto <quentin2g@yahoo.fr>

Diff between imp4p versions 1.1 dated 2021-03-22 and 1.2 dated 2021-09-02

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More information about imp4p at CRAN
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Package HelpersMG updated to version 4.7-0 with previous version 4.6 dated 2021-06-04

Title: Tools for Environmental Analyses, Ecotoxicology and Various R Functions
Description: Contains miscellaneous functions useful for managing 'NetCDF' files (see <https://en.wikipedia.org/wiki/NetCDF>), get moon phase and time for sun rise and fall, analyse and reconstruct periodic time series of temperature with irregular sinusoidal pattern, show scales and wind rose in plot with change of color of text, Metropolis-Hastings algorithm for Bayesian MCMC analysis, plot graphs or boxplot with error bars, search files in disk by there names or their content, read the contents of all files from a folder at one time.
Author: Marc Girondot
Maintainer: Marc Girondot <marc.girondot@gmail.com>

Diff between HelpersMG versions 4.6 dated 2021-06-04 and 4.7-0 dated 2021-09-02

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More information about HelpersMG at CRAN
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Package etasFLP updated to version 2.2.0 with previous version 2.1.0 dated 2020-07-17

Title: Mixed FLP and ML Estimation of ETAS Space-Time Point Processes for Earthquake Description
Description: Estimation of the components of an ETAS (Epidemic Type Aftershock Sequence) model for earthquake description. Non-parametric background seismicity can be estimated through FLP (Forward Likelihood Predictive). New version 2.0.0: covariates have been introduced to explain the effects of external factors on the induced seismicity; the parametrization has been changed; Chiodi, Adelfio (2017)<doi:10.18637/jss.v076.i03>.
Author: Marcello Chiodi [aut, cre], Giada Adelfio [aut]
Maintainer: Marcello Chiodi <marcello.chiodi@unipa.it>

Diff between etasFLP versions 2.1.0 dated 2020-07-17 and 2.2.0 dated 2021-09-02

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More information about etasFLP at CRAN
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Package emayili updated to version 0.4.17 with previous version 0.4.16 dated 2021-08-21

Title: Send Email Messages
Description: A light, simple tool for sending emails with minimal dependencies.
Author: Andrew B. Collier [aut, cre], Matt Dennis [ctb], Antoine Bichat [ctb] (<https://orcid.org/0000-0001-6599-7081>), Daniel Fahey [ctb], Johann R. Kleinbub [ctb], Panagiotis Moulos [ctb]
Maintainer: Andrew B. Collier <andrew.b.collier@gmail.com>

Diff between emayili versions 0.4.16 dated 2021-08-21 and 0.4.17 dated 2021-09-02

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More information about emayili at CRAN
Permanent link

Package dlookr updated to version 0.5.1 with previous version 0.5.0 dated 2021-07-30

Title: Tools for Data Diagnosis, Exploration, Transformation
Description: A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values and outliers and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and relationship between target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputates missing values and outliers, resolving skewness. And it creates automated reports that support these three tasks.
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu@gmail.com>

Diff between dlookr versions 0.5.0 dated 2021-07-30 and 0.5.1 dated 2021-09-02

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Package datawizard updated to version 0.2.0.1 with previous version 0.2.0 dated 2021-08-17

Title: Easy Data Wrangling
Description: A lightweight package to easily manipulate, clean, transform, and prepare your data for analysis. It also forms the data wrangling backend for the packages in the 'easystats' ecosystem.
Author: Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Indrajeet Patil [aut, cre] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>, @bmwiernik)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

Diff between datawizard versions 0.2.0 dated 2021-08-17 and 0.2.0.1 dated 2021-09-02

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Package DataSpaceR updated to version 0.7.5 with previous version 0.7.4 dated 2020-08-26

Title: Interface to 'the CAVD DataSpace'
Description: Provides a convenient API interface to access immunological data within 'the CAVD DataSpace'(<https://dataspace.cavd.org>), a data sharing and discovery tool that facilitates exploration of HIV immunological data from pre-clinical and clinical HIV vaccine studies.
Author: Ju Yeong Kim [aut], Sean Hughes [rev], Jason Taylor [aut, cre], Helen Miller [aut], CAVD DataSpace [cph]
Maintainer: Jason Taylor <jmtaylor@fredhutch.org>

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Package copBasic updated to version 2.1.6 with previous version 2.1.5 dated 2020-03-23

Title: General Bivariate Copula Theory and Many Utility Functions
Description: Extensive functions for bivariate copula (bicopula) computations and related operations for bicopula theory. The lower, upper, product, and select other bicopula are implemented along with operations including the diagonal, survival copula, dual of a copula, co-copula, and numerical bicopula density. Level sets, horizontal and vertical sections are supported. Numerical derivatives and inverses of a bicopula are provided through which simulation is implemented. Bicopula composition, convex combination, and products also are provided. Support extends to the Kendall Function as well as the Lmoments thereof. Kendall Tau, Spearman Rho and Footrule, Gini Gamma, Blomqvist Beta, Hoeffding Phi, Schweizer- Wolff Sigma, tail dependency, tail order, skewness, and bivariate Lmoments are implemented, and positive/negative quadrant dependency, left (right) increasing (decreasing) are available. Other features include Kullback-Leibler divergence, Vuong procedure, spectral measure, and Lcomoments for inference, maximum likelihood, and AIC, BIC, and RMSE for goodness-of-fit.
Author: William Asquith
Maintainer: William Asquith <william.asquith@ttu.edu>

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Package Compositional updated to version 4.9 with previous version 4.8 dated 2021-07-08

Title: Compositional Data Analysis
Description: Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include: a) Tsagris M.T., Preston S. and Wood A.T.A. (2011). A data-based power transformation for compositional data. Fourth International International Workshop on Compositional Data Analysis. b) Tsagris M. (2014). The k-NN algorithm for compositional data: a revised approach with and without zero values present. Journal of Data Science, 12(3):519--534. c) Tsagris M. (2015). A novel, divergence based, regression for compositional data. Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. d) Tsagris M. (2015). Regression analysis with compositional data containing zero values. Chilean Journal of Statistics, 6(2):47--57. e) Tsagris M., Preston S. and Wood A.T.A. (2016). Improved supervised classification for compositional data using the alpha-transformation. Journal of Classification, 33(2):243--261. <doi:10.1007/s00357-016-9207-5>. f) Tsagris M., Preston S. and Wood A.T.A. (2017). Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87(2): 406--422. <doi:10.1080/00949655.2016.1216554>. g) Tsagris M. and Stewart C. (2018). A Dirichlet regression model for compositional data with zeros. Lobachevskii Journal of Mathematics,39(3): 398--412. <doi:10.1134/S1995080218030198>. h) Alenazi A. (2019). Regression for compositional data with compositional data as predictor variables with or without zero values. Journal of Data Science, 17(1): 219--238. <doi:10.6339/JDS.201901_17(1).0010>. i) Tsagris M. and Stewart C. (2020). A folded model for compositional data analysis. Australian and New Zealand Journal of Statistics, 62(2):249--277. <doi:10.1111/anzs.12289>. j) Tsagris M., Alenazi A. and Stewart C. (2021). Non-parametric regression models for compositional data. <arXiv:2002.05137>. We further include functions for percentages (or proportions).
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package bookdown updated to version 0.24 with previous version 0.23 dated 2021-08-13

Title: Authoring Books and Technical Documents with R Markdown
Description: Output formats and utilities for authoring books and technical documents with R Markdown.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), JJ Allaire [ctb], Albert Kim [ctb], Alessandro Samuel-Rosa [ctb], Andrzej Oles [ctb], Atsushi Yasumoto [ctb] (<https://orcid.org/0000-0002-8335-495X>), Aust Frederik [ctb] (<https://orcid.org/0000-0003-4900-788X>), Bastiaan Quast [ctb], Ben Marwick [ctb], Chester Ismay [ctb], Christophe Dervieux [ctb], Clifton Franklund [ctb], Daniel Emaasit [ctb], David Shuman [ctb], Dean Attali [ctb], Drew Tyre [ctb], Ellis Valentiner [ctb], Frans van Dunne [ctb], Hadley Wickham [ctb], Jeff Allen [ctb], Jennifer Bryan [ctb], Jonathan McPhers [ctb], JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>), Joyce Robbins [ctb], Junwen Huang [ctb], Kevin Cheung [ctb], Kevin Ushey [ctb], Kim Seonghyun [ctb], Kirill Muller [ctb], Luciano Selzer [ctb], Matthew Lincoln [ctb], Maximilian Held [ctb], Michael Sachs [ctb], Michal Bojanowski [ctb], Nathan Werth [ctb], Noam Ross [ctb], Peter Hickey [ctb], Pedro Rafael D. Marinho [ctb] (<https://orcid.org/0000-0003-1591-8300>), Romain Lesur [ctb] (<https://orcid.org/0000-0002-0721-5595>), Sahir Bhatnagar [ctb], Shir Dekel [ctb] (<https://orcid.org/0000-0003-1773-2446>), Steve Simpson [ctb], Thierry Onkelinx [ctb] (<https://orcid.org/0000-0001-8804-4216>), Vincent Fulco [ctb], Yixuan Qiu [ctb], Zhuoer Dong [ctb], RStudio, PBC [cph], Bartek Szopka [ctb] (The jQuery Highlight plugin), Zeno Rocha [cph] (clipboard.js library), MathQuill contributors [ctb] (The MathQuill library; authors listed in inst/resources/AUTHORS), FriendCode Inc [cph, ctb] (The gitbook style, with modifications)
Maintainer: Yihui Xie <xie@yihui.name>

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Package WASP updated to version 1.4.1 with previous version 1.4.0 dated 2021-08-23

Title: Wavelet System Prediction
Description: The wavelet-based variance transformation method is used for system modelling and prediction. It refines predictor spectral representation using Wavelet Theory, which leads to improved model specifications and prediction accuracy. Details of methodologies used in the package can be found in Jiang, Z., Sharma, A., & Johnson, F. (2020) <doi:10.1029/2019WR026962>, Jiang, Z., Rashid, M. M., Johnson, F., & Sharma, A. (2020) <doi:10.1016/j.envsoft.2020.104907>, and Jiang, Z., Sharma, A., & Johnson, F. (2021) <doi:10.1016/J.JHYDROL.2021.126816>.
Author: Ze Jiang [aut, cre] (<https://orcid.org/0000-0002-3472-0829>), Ashish Sharma [aut] (<https://orcid.org/0000-0002-6758-0519>), Fiona Johnson [aut] (<https://orcid.org/0000-0001-5708-1807>)
Maintainer: Ze Jiang <ze.jiang@unsw.edu.au>

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Package rATTAINS updated to version 0.1.1 with previous version 0.1.0 dated 2021-08-20

Title: Access EPA 'ATTAINS' Data
Description: An R interface to United States Environmental Protection Agency (EPA) Assessment, Total Maximum Daily Load (TMDL) Tracking and Implementation System ('ATTAINS') data. 'ATTAINS' is the EPA database used to track information provided by states about water quality assessments conducted under federal Clean Water Act requirements. ATTAINS information and API information is available at <https://www.epa.gov/waterdata/attains>.
Author: Michael Schramm [aut, cre, cph] (<https://orcid.org/0000-0003-1876-6592>)
Maintainer: Michael Schramm <mpschramm@gmail.com>

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Package PanelMatch updated to version 2.0.0 with previous version 1.0.0 dated 2020-02-28

Title: Matching Methods for Causal Inference with Time-Series Cross-Sectional Data
Description: Implements a set of methodological tools that enable researchers to apply matching methods to time-series cross-sectional data. Imai, Kim, and Wang (2021) <http://web.mit.edu/insong/www/pdf/tscs.pdf> proposes a nonparametric generalization of the difference-in-differences estimator, which does not rely on the linearity assumption as often done in practice. Researchers first select a method of matching each treated observation for a given unit in a particular time period with control observations from other units in the same time period that have a similar treatment and covariate history. These methods include standard matching methods based on propensity score and Mahalanobis distance, as well as weighting methods. Once matching is done, both short-term and long-term average treatment effects for the treated can be estimated with standard errors. The package also offers a visualization technique that allows researchers to assess the quality of matches by examining the resulting covariate balance.
Author: In Song Kim [aut, cre], Adam Rauh [aut], Erik Wang [aut], Kosuke Imai [aut]
Maintainer: In Song Kim <insong@mit.edu>

Diff between PanelMatch versions 1.0.0 dated 2020-02-28 and 2.0.0 dated 2021-09-02

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Package mschart updated to version 0.3.1 with previous version 0.3.0 dated 2021-04-19

Title: Chart Generation for 'Microsoft Word' and 'Microsoft PowerPoint' Documents
Description: Create native charts for 'Microsoft PowerPoint' and 'Microsoft Word' documents. These can then be edited and annotated. Functions are provided to let users create charts, modify and format their content. The chart's underlying data is automatically saved within the 'Word' document or 'PowerPoint' presentation. It extends package 'officer' that does not contain any feature for 'Microsoft' native charts production.
Author: David Gohel [aut, cre], ArData [cph], YouGov [fnd], Rokas Klydzia [ctb] (custom labels), David Camposeco [ctb] (chart_data_smooth function), Dan Joplin [ctb] (fix scatter plot data structure)
Maintainer: David Gohel <david.gohel@ardata.fr>

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Package fishflux updated to version 0.0.1.5 with previous version 0.0.1.4 dated 2021-04-27

Title: Model Elemental Fluxes in Fishes
Description: Model fluxes of carbon, nitrogen, and phosphorus with the use of a coupled bioenergetics and stoichiometric model that incorporates flexible elemental limitation. Additional functions to help the user to find parameters are included. Finally, functions to extract and visualize results are available as well. For an introduction, see vignette. For more information on the theoretical background of this model, see Schiettekatte et al. (2020) <doi:10.1111/1365-2435.13618>.
Author: Nina M. D. Schiettekatte [aut, cre], Diego Barneche [aut]
Maintainer: Nina M. D. Schiettekatte <nina.schiettekatte@gmail.com>

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Package convertid updated to version 0.1.2 with previous version 0.1.1 dated 2021-08-21

Title: Convert Gene IDs Between Each Other and Fetch Annotations from Biomart
Description: Gene Symbols or Ensembl Gene IDs are converted using the Bimap interface in 'AnnotationDbi' in convertId2() but that function is only provided as fallback mechanism for the most common use cases in data analysis. The main function in the package is convert.bm() which queries BioMart using the full capacity of the API provided through the 'biomaRt' package. Presets and defaults are provided for convenience but all "marts", "filters" and "attributes" can be set by the user. Function convert.alias() converts Gene Symbols to Aliases and vice versa and function likely_symbol() attempts to determine the most likely current Gene Symbol.
Author: Vidal Fey [aut, cre], Henrik Edgren [aut]
Maintainer: Vidal Fey <vidal.fey@gmail.com>

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Package arakno updated to version 1.1.1 with previous version 1.1.0 dated 2021-06-08

Title: ARAchnid KNowledge Online
Description: Allows the user to connect with the World Spider Catalogue (WSC; <https://wsc.nmbe.ch/>) and the World Spider Trait (WST; <https://spidertraits.sci.muni.cz/>) databases. Also performs several basic functions such as checking names validity, retrieving coordinate data from the Global Biodiversity Information Facility (GBIF; <https://www.gbif.org/>), and mapping.
Author: Pedro Cardoso [aut, cre]
Maintainer: Pedro Cardoso <pedro.cardoso@helsinki.fi>

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Package rtrend updated to version 0.1.1 with previous version 0.1.0 dated 2021-05-11

Title: Trend Estimating Tools
Description: The traditional linear regression trend, Modified Mann-Kendall (MK) non-parameter trend and bootstrap trend are included in this package. Linear regression trend is rewritten by '.lm.fit'. MK trend is rewritten by 'Rcpp'. Finally, those functions are about 10 times faster than previous version in R. Reference: Hamed, K. H., & Rao, A. R. (1998). A modified Mann-Kendall trend test for autocorrelated data. Journal of hydrology, 204(1-4), 182-196. <doi:10.1016/S0022-1694(97)00125-X>.
Author: Dongdong Kong [aut, cre] (<https://orcid.org/0000-0003-1836-8172>), Heyang Song [aut] (<https://orcid.org/0000-0002-4192-5603>)
Maintainer: Dongdong Kong <kongdd.sysu@gmail.com>

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Package RJcluster updated to version 3.2.1 with previous version 3.1.1 dated 2021-08-19

Title: A Fast Clustering Algorithm for High Dimensional Data Based on the Gram Matrix Decomposition
Description: Clustering algorithm for high dimensional data. Assuming that P feature measurements on N objects are arranged in an N×P matrix X, this package provides clustering based on the left Gram matrix XX^T. To simulate test data, type "help('simulate_HD_data')" and to learn how to use the clustering algorithm, type "help('RJclust')". To cite this package, type 'citation("RJcluster")'.
Author: Shahina Rahman [aut], Valen E. Johnson [aut], Suhasini Subba Rao [aut], Rachael Shudde [aut, cre, trl]
Maintainer: Rachael Shudde <rachael.shudde@gmail.com>

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Package recometrics updated to version 0.1.5 with previous version 0.1.3 dated 2021-07-20

Title: Evaluation Metrics for Implicit-Feedback Recommender Systems
Description: Calculates evaluation metrics for implicit-feedback recommender systems that are based on low-rank matrix factorization models, given the fitted model matrices and data, thus allowing to compare models from a variety of libraries. Metrics include P@K (precision-at-k, for top-K recommendations), R@K (recall at k), AP@K (average precision at k), NDCG@K (normalized discounted cumulative gain at k), Hit@K (from which the 'Hit Rate' is calculated), RR@K (reciprocal rank at k, from which the 'MRR' or 'mean reciprocal rank' is calculated), ROC-AUC (area under the receiver-operating characteristic curve), and PR-AUC (area under the precision-recall curve). These are calculated on a per-user basis according to the ranking of items induced by the model, using efficient multi-threaded routines. Also provides functions for creating train-test splits for model fitting and evaluation.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package mlflow updated to version 1.20.1 with previous version 1.19.0 dated 2021-07-14

Title: Interface to 'MLflow'
Description: R interface to 'MLflow', open source platform for the complete machine learning life cycle, see <https://mlflow.org/>. This package supports installing 'MLflow', tracking experiments, creating and running projects, and saving and serving models.
Author: Matei Zaharia [aut, cre], Javier Luraschi [aut], Kevin Kuo [aut] (<https://orcid.org/0000-0001-7803-7901>), RStudio [cph]
Maintainer: Matei Zaharia <matei@databricks.com>

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Package ISLR2 updated to version 1.1 with previous version 1.0 dated 2021-07-22

Title: Introduction to Statistical Learning, Second Edition
Description: We provide the collection of data-sets used in the book 'An Introduction to Statistical Learning with Applications in R, Second Edition'. These include many data-sets that we used in the first edition (some with minor changes), and some new datasets.
Author: Gareth James [aut], Daniela Witten [aut], Trevor Hastie [aut, cre], Rob Tibshirani [aut], Balasubramanian Narasimhan [ctb]
Maintainer: Trevor Hastie <hastie@stanford.edu>

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Package blogdown updated to version 1.5 with previous version 1.4 dated 2021-07-23

Title: Create Blogs and Websites with R Markdown
Description: Write blog posts and web pages in R Markdown. This package supports the static site generator 'Hugo' (<https://gohugo.io>) best, and it also supports 'Jekyll' (<https://jekyllrb.com>) and 'Hexo' (<https://hexo.io>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Christophe Dervieux [aut] (<https://orcid.org/0000-0003-4474-2498>), Alison Presmanes Hill [aut] (<https://orcid.org/0000-0002-8082-1890>), Amber Thomas [ctb], Beilei Bian [ctb], Brandon Greenwell [ctb], Brian Barkley [ctb], Deependra Dhakal [ctb], Eric Nantz [ctb], Forest Fang [ctb], Garrick Aden-Buie [ctb], Hiroaki Yutani [ctb], Ian Lyttle [ctb], Jake Barlow [ctb], James Balamuta [ctb], JJ Allaire [ctb], Jon Calder [ctb], Jozef Hajnala [ctb], Juan Manuel Vazquez [ctb], Kevin Ushey [ctb], Leonardo Collado-Torres [ctb], Maëlle Salmon [ctb], Maria Paula Caldas [ctb], Nicolas Roelandt [ctb], Oliver Madsen [ctb], Raniere Silva [ctb], TC Zhang [ctb], Xianying Tan [ctb], RStudio, PBC [cph]
Maintainer: Yihui Xie <xie@yihui.name>

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Package bestridge updated to version 1.0.6 with previous version 1.0.5 dated 2021-04-04

Title: A Comprehensive R Package for Best Subset Selection
Description: The bestridge package is designed to provide a one-stand service for users to successfully carry out best ridge regression in various complex situations via the primal dual active set algorithm proposed by Wen, C., Zhang, A., Quan, S. and Wang, X. (2020) <doi:10.18637/jss.v094.i04>. This package allows users to perform the regression, classification, count regression and censored regression for (ultra) high dimensional data, and it also supports advanced usages like group variable selection and nuisance variable selection.
Author: Liyuan Hu [aut, cre] (<https://orcid.org/0000-0003-2064-8990>), Jin Zhu [aut] (<https://orcid.org/0000-0001-8550-5822>), Junxian Zhu [aut], Kangkang Jiang [aut], Yanhang Zhang [aut], Xueqin Wang [aut] (<https://orcid.org/0000-0001-5205-9950>), Canhong Wen [aut]
Maintainer: Liyuan Hu <huly5@mail2.sysu.edu.cn>

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Package permutes updated to version 2.1 with previous version 2.0.1 dated 2021-02-24

Title: Permutation Tests for Time Series Data
Description: Helps you determine the analysis window to use when analyzing densely-sampled time-series data, such as EEG data, using permutation testing (Maris & Oostenveld, 2007) <doi:10.1016/j.jneumeth.2007.03.024>. These permutation tests can help identify the timepoints where significance of an effect begins and ends, and the results can be plotted in various types of heatmap for reporting. Mixed-effects models are supported using an implementation of the approach by Lee & Braun (2012) <doi:10.1111/j.1541-0420.2011.01675.x>.
Author: Cesko C. Voeten [aut, cre]
Maintainer: Cesko C. Voeten <cvoeten@gmail.com>

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Package OncoBayes2 updated to version 0.8-1 with previous version 0.7-0 dated 2021-05-07

Title: Bayesian Logistic Regression for Oncology Dose-Escalation Trials
Description: Bayesian logistic regression model with optional EXchangeability-NonEXchangeability parameter modelling for flexible borrowing from historical or concurrent data-sources. The safety model can guide dose-escalation decisions for adaptive oncology Phase I dose-escalation trials which involve an arbitrary number of drugs. Please refer to Neuenschwander et al. (2008) <doi:10.1002/sim.3230> and Neuenschwander et al. (2016) <doi:10.1080/19466315.2016.1174149> for details on the methodology.
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Lukas A. Widmer [aut], Andrew Bean [aut], Trustees of Columbia University [cph] (R/stanmodels.R, configure, configure.win)
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>

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Package NMproject updated to version 0.6.5 with previous version 0.6.4 dated 2021-08-18

Title: Script Based 'NONMEM' Model Development
Description: Industrialisation of 'NONMEM' <https://www.iconplc.com/innovation/nonmem/> via fully and rapidly reusable model development 'workflows' entirely within 'RStudio'. Quickly get started with new models by importing 'NONMEM' templates from the built-in code library. Manipulate 'NONMEM' code from within R either via the tracked 'manual edit' interface or 'programmatically' via convenience functions. Script 'workflows' by piping sequences of model building steps from control file creation, to execution, to post-processing and evaluation. Run caching makes 'workflows' R markdown friendly for easy documentation of thoughts and modelling decisions alongside executable code. Share, reuse and recycle 'workflows' for new problems.
Author: Tarj Sahota [aut, cre, cph], AstraZeneca [cph], Nuria Buil Bruna [ctb], Stein Schalkwijk [ctb]
Maintainer: Tarj Sahota <t.sahota0@gmail.com>

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Package gmgm updated to version 1.1.0 with previous version 1.0.2 dated 2021-04-17

Title: Gaussian Mixture Graphical Model Learning and Inference
Description: Gaussian mixture graphical models include Bayesian networks and dynamic Bayesian networks (their temporal extension) whose local probability distributions are described by Gaussian mixture models. They are powerful tools for graphically and quantitatively representing nonlinear dependencies between continuous variables. This package provides a complete framework to create, manipulate, learn the structure and the parameters, and perform inference in these models. Most of the algorithms are described in the PhD thesis of Roos (2018) <https://tel.archives-ouvertes.fr/tel-01943718>.
Author: Jérémy Roos [aut, cre, cph], RATP Group [fnd, cph]
Maintainer: Jérémy Roos <jeremy.roos@gmail.com>

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Package GE updated to version 0.2.1 with previous version 0.2.0 dated 2021-07-01

Title: General Equilibrium Modeling
Description: Some tools for developing general equilibrium models and some general equilibrium models. These models can be used for teaching economic theory and are built by the methods of new structural economics (see <https://www.nse.pku.edu.cn/> and LI Wu, 2019, ISBN: 9787521804225, General Equilibrium and Structural Dynamics: Perspectives of New Structural Economics. Beijing: Economic Science Press). The model form and mathematical methods can be traced back to von Neumann, J. (1945, A Model of General Economic Equilibrium. The Review of Economic Studies, 13. pp. 1-9) and Kemeny, J. G., O. Morgenstern and G. L. Thompson (1956, A Generalization of the von Neumann Model of an Expanding Economy, Econometrica, 24, pp. 115-135) et al. By the way, J. G. Kemeny is a co-inventor of the computer language BASIC.
Author: LI Wu <liwu@staff.shu.edu.cn>
Maintainer: LI Wu <liwu@staff.shu.edu.cn>

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Package DSSAT updated to version 0.0.4 with previous version 0.0.3 dated 2021-07-26

Title: A Comprehensive R Interface for the DSSAT Cropping Systems Model
Description: The purpose of this package is to provide a comprehensive R interface to the Decision Support System for Agrotechnology Transfer Cropping Systems Model (DSSAT-CSM; see <https://dssat.net> for more information). The package provides cross-platform functions to read and write input files, run DSSAT-CSM, and read output files.
Author: Phillip D. Alderman [aut, cre]
Maintainer: Phillip D. Alderman <phillip.alderman@okstate.edu>

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Package wrGraph updated to version 1.3.0 with previous version 1.2.5 dated 2021-07-08

Title: Graphics in the Context of Analyzing High-Throughput Data
Description: Additional options for making graphics in the context of analyzing high-throughput data are available here. This includes automatic segmenting of the current device (eg window) to accommodate multiple new plots, automatic checking for optimal location of legends in plots, small histograms to insert as legends, histograms re-transforming axis labels to linear when plotting log2-transformed data, a violin-plot <doi:10.1080/00031305.1998.10480559> function for a wide variety of input-formats, principal components analysis (PCA) <doi:10.1080/14786440109462720> with bag-plots <doi:10.1080/00031305.1999.10474494> to highlight and compare the center areas for groups of samples, generic MA-plots (differential- versus average-value plots) <doi:10.1093/nar/30.4.e15>, staggered count plots and generation of mouse-over interactive html pages.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>

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Package segregation updated to version 0.6.0 with previous version 0.5.0 dated 2021-02-08

Title: Entropy-Based Segregation Indices
Description: Computes segregation indices, including the Index of Dissimilarity, as well as the information-theoretic indices developed by Theil (1971) <isbn:978-0471858454>, namely the Mutual Information Index (M) and Theil's Information Index (H). The M, further described by Mora and Ruiz-Castillo (2011) <doi:10.1111/j.1467-9531.2011.01237.x> and Frankel and Volij (2011) <doi:10.1016/j.jet.2010.10.008>, is a measure of segregation that is highly decomposable. The package provides tools to decompose the index by units and groups (local segregation), and by within and between terms. The package also provides a method to decompose differences in segregation as described by Elbers (2021) <doi:10.1177/0049124121986204>. The package includes standard error estimation by bootstrapping, which also corrects for small sample bias.
Author: Benjamin Elbers [aut, cre] (<https://orcid.org/0000-0001-5392-3448>)
Maintainer: Benjamin Elbers <be2239@columbia.edu>

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Package prettifyAddins updated to version 2.2.0 with previous version 2.1.2 dated 2021-08-16

Title: 'RStudio' Addins to Prettify 'JavaScript', 'C++', 'Python', and More
Description: Provides 'RStudio' addins to prettify 'HTML', 'CSS', 'SCSS', 'JavaScript', 'JSX', 'Markdown', 'C(++)', 'LaTeX', 'Python', 'Julia', 'XML', 'Java', 'JSON', 'Ruby', and to reindent 'C(++)', 'Fortran', 'Java', 'Julia', 'Python', 'SAS', 'Scala', 'Shell' and 'SQL'. Two kinds of addins are provided: 'Prettify' and 'Indent'. The 'Indent' addins only reindent the code, while the 'Prettify' addins also modify the code, e.g. trailing semi-colons are added to 'JavaScript' code when they are missing.
Author: Stéphane Laurent [aut, cre], James Long and contributors [ctb, cph] ('Prettier' library), Zeb Zhao [ctb, cph] ('indent.js' library), Marijn Haverbeke [ctb, cph] ('CodeMirror' library)
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package GreedyEPL updated to version 1.2 with previous version 1.1 dated 2021-05-11

Title: Greedy Expected Posterior Loss
Description: Summarises a collection of partitions into a single optimal partition. The objective function is the expected posterior loss, and the minimisation is performed through a greedy algorithm described in Rastelli, R. and Friel, N. (2017) "Optimal Bayesian estimators for latent variable cluster models" <DOI:10.1007/s11222-017-9786-y>.
Author: Riccardo Rastelli [aut, cre]
Maintainer: Riccardo Rastelli <riccardoras@gmail.com>

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Package fastverse updated to version 0.2.1 with previous version 0.1.8 dated 2021-08-12

Title: A Suite of High-Performance Packages for Statistics and Data Manipulation
Description: Easy installation, loading and management, of a complementary set of high-performance packages for statistical computing and data manipulation. The core 'fastverse' consists of 6 packages: 'data.table', 'collapse', 'matrixStats', 'kit', 'magrittr' and 'fst', that jointly only depend on 'Rcpp'. These packages are attached and harmonized through the 'fastverse'. In addition, the 'fastverse' can be freely and permanently extended with additional packages, both globally or for individual projects. Entirely separate package verses can also be created. Selected fast and low-dependency packages are suggested for various topics such as time series, dates and times, strings, spatial data, statistics and data serialization (see GitHub / website).
Author: Sebastian Krantz [aut, cre], Hadley Wickham [ctb]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>

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Package Exact updated to version 3.0 with previous version 2.1 dated 2020-10-02

Title: Unconditional Exact Test
Description: Performs unconditional exact tests and power calculations for 2x2 contingency tables. For comparing two independent proportions, performs Barnard's test (1945) <doi:10.1038/156177a0> using the original CSM test (Barnard, 1947 <doi:10.1093/biomet/34.1-2.123>), using Fisher's p-value referred to as Boschloo's test (1970) <doi:10.1111/j.1467-9574.1970.tb00104.x>, or using a Z-statistic (Suissa and Shuster, 1985, <doi:10.2307/2981892>). For comparing two binary proportions, performs unconditional exact test using McNemar's Z-statistic (Berger and Sidik, 2003, <doi:10.1191/0962280203sm312ra>), using McNemar's Z-statistic with continuity correction, or using CSM test. Calculates confidence intervals for the difference in proportion. This package interacts with pre-computed data available through the ExactData R package, which is available in a 'drat' repository. Install the ExactData R package from GitHub at <https://pcalhoun1.github.io/drat/>. The ExactData R package is approximately 25 MB.
Author: Peter Calhoun [aut, cre]
Maintainer: Peter Calhoun <calhoun.peter@gmail.com>

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Package DoE.base updated to version 1.2 with previous version 1.1-6 dated 2021-02-05

Title: Full Factorials, Orthogonal Arrays and Base Utilities for DoE Packages
Description: Creates full factorial experimental designs and designs based on orthogonal arrays for (industrial) experiments. Provides diverse quality criteria. Provides utility functions for the class design, which is also used by other packages for designed experiments.
Author: Ulrike Groemping [aut, cre], Boyko Amarov [ctb], Hongquan Xu [ctb]
Maintainer: Ulrike Groemping <groemping@beuth-hochschule.de>

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Package TestDataImputation updated to version 2.2 with previous version 2.1 dated 2021-07-28

Title: Missing Item Responses Imputation for Test and Assessment Data
Description: Functions for imputing missing item responses for dichotomous and polytomous test and assessment data. This package enables missing imputation methods that are suitable for test and assessment data, including: listwise (LW) deletion (see De Ayala et al. 2001 <doi:10.1111/j.1745-3984.2001.tb01124.x>), treating as incorrect (IN, see Lord, 1974 <doi: 10.1111/j.1745-3984.1974.tb00996.x>; Mislevy & Wu, 1996 <doi: 10.1002/j.2333-8504.1996.tb01708.x>; Pohl et al., 2014 <doi: 10.1177/0013164413504926>), person mean imputation (PM), item mean imputation (IM), two-way (TW) and response function (RF) imputation (see Sijtsma & van der Ark, 2003 <doi: 10.1207/s15327906mbr3804_4>), logistic regression (LR) imputation, and expectation–maximization (EM) imputation (see Finch, 2008 <doi: 10.1111/j.1745-3984.2008.00062.x>).
Author: Shenghai Dai [aut, cre], Xiaolin Wang [aut], Dubravka Svetina [aut]
Maintainer: Shenghai Dai <s.dai@wsu.edu>

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Package SqlRender updated to version 1.8.0 with previous version 1.7.0 dated 2021-03-02

Title: Rendering Parameterized SQL and Translation to Dialects
Description: A rendering tool for parameterized SQL that also translates into different SQL dialects. These dialects include 'Microsoft Sql Server', 'Oracle', 'PostgreSql', 'Amazon RedShift', 'Apache Impala', 'IBM Netezza', 'Google BigQuery', 'Microsoft PDW', 'Apache Spark', and 'SQLite'.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package samc updated to version 1.4.1 with previous version 1.4.0 dated 2021-06-27

Title: Spatial Absorbing Markov Chains
Description: Implements functions for working with absorbing Markov chains. The implementation is based on the framework described in "Toward a unified framework for connectivity that disentangles movement and mortality in space and time" by Fletcher et al. (2019) <doi:10.1111/ele.13333>, which applies them to spatial ecology. This framework incorporates both resistance and absorption with spatial absorbing Markov chains (SAMC) to provide several short-term and long-term predictions for metrics related to connectivity in landscapes. Despite the ecological context of the framework, this package can be used in any application of absorbing Markov chains.
Author: Andrew Marx [aut, cre, cph] (<https://orcid.org/0000-0002-7456-1631>), Robert Fletcher [ctb] (<https://orcid.org/0000-0003-1717-5707>), Miguel Acevedo [ctb] (<https://orcid.org/0000-0002-8289-1497>), Jorge Sefair [ctb] (<https://orcid.org/0000-0002-5887-8938>), Chao Wang [ctb] (<https://orcid.org/0000-0003-2706-5122>)
Maintainer: Andrew Marx <andrewjmarx@ufl.edu>

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Package quarks updated to version 1.0.7 with previous version 1.0.6 dated 2021-04-25

Title: Simple Methods for Calculating Value at Risk and Expected Shortfall
Description: Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain-, age-, volatility-weighted- and filtered historical simulation are implemented in this package. Volatility weighting can be carried out via an exponentially weighted moving average model (EWMA) or other GARCH-type models. The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525>.
Author: Sebastian Letmathe [aut, cre] (Paderborn University, Germany)
Maintainer: Sebastian Letmathe <sebastian.letmathe@uni-paderborn.de>

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Package QCA updated to version 3.13 with previous version 3.12 dated 2021-06-15

Title: Qualitative Comparative Analysis
Description: An extensive set of functions to perform Qualitative Comparative Analysis: crisp sets ('csQCA'), temporal ('tQCA'), multi-value ('mvQCA') and fuzzy sets ('fsQCA'), using a GUI - graphical user interface. 'QCA' is a methodology that bridges the qualitative and quantitative divide in social science research. It uses a Boolean algorithm, resulting in a minimal causal configuration that explains a given phenomenon.
Author: Adrian Dusa [aut, cre, cph] (<https://orcid.org/0000-0002-3525-9253>), Ciprian Paduraru [ctb] (<https://orcid.org/0000-0002-4518-374X>), jQuery Foundation [cph] (jQuery library and jQuery UI library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/gui/www/lib/jquery-AUTHORS.txt), lp_solve [cph] (http://lpsolve.sourceforge.net), Vasil Dinkov [ctb, cph] (jquery.smartmenus.js library), Dmitry Baranovskiy [ctb, cph] (raphael.js library), Emmanuel Quentin [ctb, cph] (raphael.inline_text_editing.js library), Jimmy Breck-McKye [ctb, cph] (raphael-paragraph.js library), Alrik Thiem [aut] (from version 1.0-0 up to version 1.1-3)
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package openssl updated to version 1.4.5 with previous version 1.4.4 dated 2021-04-30

Title: Toolkit for Encryption, Signatures and Certificates Based on OpenSSL
Description: Bindings to OpenSSL libssl and libcrypto, plus custom SSH key parsers. Supports RSA, DSA and EC curves P-256, P-384, P-521, and curve25519. Cryptographic signatures can either be created and verified manually or via x509 certificates. AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric (public key) encryption or EC for Diffie Hellman. High-level envelope functions combine RSA and AES for encrypting arbitrary sized data. Other utilities include key generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random number generator, and 'bignum' math methods for manually performing crypto calculations on large multibyte integers.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>), Oliver Keyes [ctb]
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package nlist updated to version 0.3.3 with previous version 0.3.2 dated 2021-08-05

Title: Lists of Numeric Atomic Objects
Description: Create and manipulate numeric list ('nlist') objects. An 'nlist' is an S3 list of uniquely named numeric objects. An numeric object is an integer or double vector, matrix or array. An 'nlists' object is a S3 class list of 'nlist' objects with the same names, dimensionalities and typeofs. Numeric list objects are of interest because they are the raw data inputs for analytic engines such as 'JAGS', 'STAN' and 'TMB'. Numeric lists objects, which are useful for storing multiple realizations of of simulated data sets, can be converted to coda::mcmc and coda::mcmc.list objects.
Author: Joe Thorley [aut, cre] (<https://orcid.org/0000-0002-7683-4592>), Poisson Consulting [cph, fnd]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

Diff between nlist versions 0.3.2 dated 2021-08-05 and 0.3.3 dated 2021-09-02

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Package neonUtilities updated to version 2.1.2 with previous version 2.1.1 dated 2021-07-27

Title: Utilities for Working with NEON Data
Description: NEON data packages can be accessed through the NEON Data Portal <https://www.neonscience.org> or through the NEON Data API (see <https://data.neonscience.org/data-api> for documentation). Data delivered from the Data Portal are provided as monthly zip files packaged within a parent zip file, while individual files can be accessed from the API. This package provides tools that aid in discovering, downloading, and reformatting data prior to use in analyses. This includes downloading data via the API, merging data tables by type, and converting formats. For more information, see the readme file at <https://github.com/NEONScience/NEON-utilities>.
Author: Claire Lunch [aut, cre, ctb], Christine Laney [aut, ctb], Nathan Mietkiewicz [aut, ctb], Eric Sokol [aut, ctb], Kaelin Cawley [aut, ctb], NEON (National Ecological Observatory Network) [aut]
Maintainer: Claire Lunch <clunch@battelleecology.org>

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Package mlt updated to version 1.3-2 with previous version 1.3-0 dated 2021-03-09

Title: Most Likely Transformations
Description: Likelihood-based estimation of conditional transformation models via the most likely transformation approach described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291> and Hothorn (2020) <DOI:10.18637/jss.v092.i01>.
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 MBmca updated to version 1.0.1-2 with previous version 1.0.1-1 dated 2021-03-09

Title: Nucleic Acid Melting Curve Analysis
Description: Lightweight utilities for nucleic acid melting curve analysis are important in life sciences and diagnostics. This software can be used for the analysis and presentation of melting curve data from microbead-based assays (surface melting curve analysis) and reactions in solution (e.g., quantitative PCR (qPCR), real-time isothermal Amplification). Further information are described in detail in two publications in The R Journal [ <https://journal.r-project.org/archive/2013-2/roediger-bohm-schimke.pdf>; <https://journal.r-project.org/archive/2015-1/RJ-2015-1.pdf>].
Author: Stefan Roediger [cre, aut] (<https://orcid.org/0000-0002-1441-6512>), Michal Burdukiewicz [aut] (<https://orcid.org/0000-0001-8926-582X>)
Maintainer: Stefan Roediger <stefan_roediger@gmx.de>

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Package matsbyname updated to version 0.4.23 with previous version 0.4.20 dated 2021-07-21

Title: An Implementation of Matrix Mathematics
Description: An implementation of matrix mathematics wherein operations are performed "by name."
Author: Matthew Heun [aut, cre] (<https://orcid.org/0000-0002-7438-214X>)
Maintainer: Matthew Heun <matthew.heun@me.com>

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Package lava updated to version 1.6.10 with previous version 1.6.9 dated 2021-03-11

Title: Latent Variable Models
Description: A general implementation of Structural Equation Models with latent variables (MLE, 2SLS, and composite likelihood estimators) with both continuous, censored, and ordinal outcomes (Holst and Budtz-Joergensen (2013) <doi:10.1007/s00180-012-0344-y>). Mixture latent variable models and non-linear latent variable models (Holst and Budtz-Joergensen (2019) <doi:10.1093/biostatistics/kxy082>). The package also provides methods for graph exploration (d-separation, back-door criterion), simulation of general non-linear latent variable models, and estimation of influence functions for a broad range of statistical models.
Author: Klaus K. Holst [aut, cre], Brice Ozenne [ctb], Thomas Gerds [ctb]
Maintainer: Klaus K. Holst <klaus@holst.it>

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Package khroma updated to version 1.7.0 with previous version 1.6.0 dated 2021-06-14

Title: Colour Schemes for Scientific Data Visualization
Description: Colour schemes ready for each type of data (qualitative, diverging or sequential), with colours that are distinct for all people, including colour-blind readers. This package provides an implementation of Paul Tol (2018) and Fabio Crameri (2018) <doi: 10.5194/gmd-11-2541-2018> colour schemes for use with 'graphics' or 'ggplot2'. It provides tools to simulate colour-blindness and to test how well the colours of any palette are identifiable. Several scientific thematic schemes (geologic timescale, land cover, FAO soils, etc.) are also implemented.
Author: Nicolas Frerebeau [aut, cre] (<https://orcid.org/0000-0001-5759-4944>), Brice Lebrun [ctb] (<https://orcid.org/0000-0001-7503-8685>), Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-2042-7063>)
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>

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Package icensmis updated to version 1.5.0 with previous version 1.4.0 dated 2020-10-02

Title: Study Design and Data Analysis in the Presence of Error-Prone Diagnostic Tests and Self-Reported Outcomes
Description: We consider studies in which information from error-prone diagnostic tests or self-reports are gathered sequentially to determine the occurrence of a silent event. Using a likelihood-based approach incorporating the proportional hazards assumption, we provide functions to estimate the survival distribution and covariate effects. We also provide functions for power and sample size calculations for this setting. Please refer to Xiangdong Gu, Yunsheng Ma, and Raji Balasubramanian (2015) <doi: 10.1214/15-AOAS810>, Xiangdong Gu and Raji Balasubramanian (2016) <doi: 10.1002/sim.6962>, Xiangdong Gu, Mahlet G Tadesse, Andrea S Foulkes, Yunsheng Ma, and Raji Balasubramanian (2020) <doi: 10.1186/s12911-020-01223-w>.
Author: Xiangdong Gu and Raji Balasubramanian
Maintainer: Xiangdong Gu <ustcgxd@gmail.com>

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Package haplo.stats updated to version 1.8.7 with previous version 1.8.6 dated 2020-10-14

Title: Statistical Analysis of Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous
Description: Routines for the analysis of indirectly measured haplotypes. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed examples in the vignette.
Author: Sinnwell JP, Schaid DJ
Maintainer: Jason P. Sinnwell <sinnwell.jason@mayo.edu>

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Package DT updated to version 0.19 with previous version 0.18 dated 2021-04-14

Title: A Wrapper of the JavaScript Library 'DataTables'
Description: Data objects in R can be rendered as HTML tables using the JavaScript library 'DataTables' (typically via R Markdown or Shiny). The 'DataTables' library has been included in this R package. The package name 'DT' is an abbreviation of 'DataTables'.
Author: Yihui Xie [aut, cre], Joe Cheng [aut], Xianying Tan [aut], JJ Allaire [ctb], Maximilian Girlich [ctb], Greg Freedman Ellis [ctb], Johannes Rauh [ctb], SpryMedia Limited [ctb, cph] (DataTables in htmlwidgets/lib), Brian Reavis [ctb, cph] (selectize.js in htmlwidgets/lib), Leon Gersen [ctb, cph] (noUiSlider in htmlwidgets/lib), Bartek Szopka [ctb, cph] (jquery.highlight.js in htmlwidgets/lib), Alex Pickering [ctb], RStudio, PBC [cph]
Maintainer: Yihui Xie <xie@yihui.name>

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Package dotwhisker updated to version 0.7.4 with previous version 0.7.3 dated 2021-08-22

Title: Dot-and-Whisker Plots of Regression Results
Description: Quick and easy dot-and-whisker plots of regression results.
Author: Frederick Solt [aut], Yue Hu [aut, cre], Os Keyes [ctb], Ben Bolker [ctb], Stefan Müller [ctb], Thomas Leeper [ctb], Chris Wallace [ctb], Christopher Warshaw [ctb]
Maintainer: Yue Hu <yuehu@tsinghua.edu.cn>

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Package declared updated to version 0.7 with previous version 0.6 dated 2021-08-18

Title: Functions to Declare Missing Values
Description: A set of functions that offer an alternative to package 'haven', to deal with labelled objects with existing values declared as missing.
Author: Adrian Dusa [aut, cre, cph] (<https://orcid.org/0000-0002-3525-9253>)
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package CALANGO updated to version 1.0.5 with previous version 1.0.2 dated 2021-07-07

Title: Comparative Analysis with Annotation-Based Genomic Components
Description: A first-principle, phylogeny-aware comparative genomics tool for investigating associations between terms used to annotate genomic components (e.g., Pfam IDs, Gene Ontology terms,) with quantitative or rank variables such as number of cell types, genome size, or density of specific genomic elements. See the project website for more information, documentation and examples.
Author: Francisco Lobo [aut], Felipe Campelo [aut, cre], Jorge Augusto Hongo [aut], Giovanni Marques de Castro [aut], Gabriel Almeida [sad, dnc]
Maintainer: Felipe Campelo <fcampelo@gmail.com>

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Package bslib updated to version 0.3.0 with previous version 0.2.5.1 dated 2021-05-18

Title: Custom 'Bootstrap' 'Sass' Themes for 'shiny' and 'rmarkdown'
Description: Simplifies custom 'CSS' styling of both 'shiny' and 'rmarkdown' via 'Bootstrap' 'Sass'. Supports both 'Bootstrap' 3 and 4 as well as their various 'Bootswatch' themes. An interactive widget is also provided for previewing themes in real time.
Author: Carson Sievert [aut, cre] (<https://orcid.org/0000-0002-4958-2844>), Joe Cheng [aut], RStudio [cph], Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Javi Aguilar [ctb, cph] (Bootstrap colorpicker library), Thomas Park [ctb, cph] (Bootswatch library), PayPal [ctb, cph] (Bootstrap accessibility plugin)
Maintainer: Carson Sievert <carson@rstudio.com>

Diff between bslib versions 0.2.5.1 dated 2021-05-18 and 0.3.0 dated 2021-09-02

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Permanent link

Package bestNormalize updated to version 1.8.1 with previous version 1.8.0 dated 2021-06-03

Title: Normalizing Transformation Functions
Description: Estimate a suite of normalizing transformations, including a new adaptation of a technique based on ranks which can guarantee normally distributed transformed data if there are no ties: ordered quantile normalization (ORQ). ORQ normalization combines a rank-mapping approach with a shifted logit approximation that allows the transformation to work on data outside the original domain. It is also able to handle new data within the original domain via linear interpolation. The package is built to estimate the best normalizing transformation for a vector consistently and accurately. It implements the Box-Cox transformation, the Yeo-Johnson transformation, three types of Lambert WxF transformations, and the ordered quantile normalization transformation. It estimates the normalization efficacy of other commonly used transformations, and it allows users to specify custom transformations or normalization statistics. Finally, functionality can be integrated into a machine learning workflow via recipes.
Author: Ryan Andrew Peterson [aut, cre]
Maintainer: Ryan Andrew Peterson <ryan.a.peterson@cuanschutz.edu>

Diff between bestNormalize versions 1.8.0 dated 2021-06-03 and 1.8.1 dated 2021-09-02

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 inst/doc/customization.html       |    4 ++--
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 tests/testthat/test_bn_parallel.R |    2 +-
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More information about bestNormalize at CRAN
Permanent link

Package astsa updated to version 1.14 with previous version 1.13 dated 2021-05-15

Title: Applied Statistical Time Series Analysis
Description: Data sets and scripts to accompany Time Series Analysis and Its Applications: With R Examples (4th ed), by R.H. Shumway and D.S. Stoffer. Springer Texts in Statistics, 2017, <DOI:10.1007/978-3-319-52452-8>, and Time Series: A Data Analysis Approach Using R. Chapman-Hall, 2019, <DOI:10.1201/9780429273285>.
Author: David Stoffer
Maintainer: David Stoffer <stoffer@pitt.edu>

Diff between astsa versions 1.13 dated 2021-05-15 and 1.14 dated 2021-09-02

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More information about astsa at CRAN
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Package arcpullr updated to version 0.2.1 with previous version 0.2.0 dated 2021-06-15

Title: Pull Data from an 'ArcGIS REST' API
Description: Functions to efficiently query 'ArcGIS REST' APIs <https://developers.arcgis.com/rest/>. Both spatial and SQL queries can be used to retrieve data. Simple Feature (sf) objects are utilized to perform spatial queries. This package was neither produced nor is maintained by Esri.
Author: Paul Frater [aut, cre] (<https://orcid.org/0000-0002-7237-6563>), Zac Driscoll [aut] (<https://orcid.org/0000-0002-8233-0980>)
Maintainer: Paul Frater <paul.frater@wisconsin.gov>

Diff between arcpullr versions 0.2.0 dated 2021-06-15 and 0.2.1 dated 2021-09-02

 DESCRIPTION              |    6 +--
 MD5                      |   10 ++---
 R/retrieve_layers.R      |    7 +++
 R/utilities.R            |   87 +++++++++++++++++++++++++++++++++++++++--------
 man/get_geometry_type.Rd |    4 --
 man/get_service_type.Rd  |   23 ++++++++++--
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More information about arcpullr at CRAN
Permanent link

Package vote updated to version 2.3-1 with previous version 2.3-0 dated 2021-08-13

Title: Election Vote Counting
Description: Counting election votes and determining election results by different methods, including the single transferable vote or ranked choice, approval, score, plurality, condorcet and two-round runoff methods (Raftery et al. (2021) <arXiv:2102.05801>).
Author: Hana Sevcikova, Bernard Silverman, Adrian Raftery
Maintainer: Hana Sevcikova<hanas@uw.edu>

Diff between vote versions 2.3-0 dated 2021-08-13 and 2.3-1 dated 2021-09-02

 ChangeLog   |    4 ++++
 DESCRIPTION |    8 ++++----
 MD5         |    6 +++---
 R/stv.R     |   22 ++++++++++++++--------
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More information about vote at CRAN
Permanent link

Package ReviewR updated to version 2.3.7 with previous version 2.3.6 dated 2021-04-02

Title: A Light-Weight, Portable Tool for Reviewing Individual Patient Records
Description: A portable Shiny tool to explore patient-level electronic health record data and perform chart review in a single integrated framework. This tool supports browsing clinical data in many different formats including multiple versions of the 'OMOP' common data model as well as the 'MIMIC-III' data model. In addition, chart review information is captured and stored securely via the Shiny interface in a 'REDCap' (Research Electronic Data Capture) project using the 'REDCap' API. See the 'ReviewR' website for additional information, documentation, and examples.
Author: Laura Wiley [aut] (<https://orcid.org/0000-0001-6681-9754>), Luke Rasmussen [aut] (<https://orcid.org/0000-0002-4497-8049>), David Mayer [cre, aut], The Wiley Lab [cph, fnd]
Maintainer: David Mayer <david.mayer@cuanschutz.edu>

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Package RCzechia updated to version 1.8.3 with previous version 1.8.2 dated 2021-07-21

Title: Spatial Objects of the Czech Republic
Description: Administrative regions and other spatial objects of the Czech Republic.
Author: Jindra Lacko
Maintainer: Jindra Lacko <jindra.lacko@gmail.com>

Diff between RCzechia versions 1.8.2 dated 2021-07-21 and 1.8.3 dated 2021-09-02

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Package basedosdados updated to version 0.1.0 with previous version 0.0.5 dated 2021-04-26

Title: 'Base Dos Dados' R Client
Description: An R interface to the 'Base dos Dados' API <https:basedosdados.github.io/mais/py_reference_api/>). Authenticate your project, query our tables, save data to disk and memory, all from R.
Author: Pedro Cavalcante [aut, cre]
Maintainer: Pedro Cavalcante <pedrocolrj@gmail.com>

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New package traitdataform with initial version 0.6.6
Package: traitdataform
Title: Formatting and Harmonizing Ecological Trait-Data
Version: 0.6.6
Date: 2021-08-31
Description: Assistance for handling ecological trait data and applying the Ecological Trait-Data Standard terminology (Schneider et al. 2019 <doi:10.1111/2041-210X.13288>). There are two major use cases: (1) preparation of own trait datasets for publication, and (2) harmonizing trait datasets from different sources by re-formatting them into a unified format. See 'traitdataform' website for full documentation.
License: MIT + file LICENSE
Depends: R (>= 2.10)
Imports: data.table, stats, reshape2, taxize, getPass, units, XML, RCurl, plyr
URL: https://ecologicaltraitdata.github.io/traitdataform/, https://github.com/ecologicaltraitdata/traitdataform
BugReports: https://github.com/ecologicaltraitdata/traitdataform/issues
VignetteBuilder: knitr
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat
NeedsCompilation: no
Packaged: 2021-09-01 17:12:06 UTC; Flo
Author: Florian D. Schneider [aut, cre] (<https://orcid.org/0000-0002-1494-5684>), Caterina Penone [ctb] (<https://orcid.org/0000-0002-8170-6659>), Andreas Ostrowski [ctb] (<https://orcid.org/0000-0002-2033-779X>), Dennis Heimann [ctb], Felix Neff [ctb], Markus J. Ankenbrand [ctb], Jessica Burnett [ctb], Iñaki Ucar [ctb], Matthias Grenié [ctb]
Maintainer: Florian D. Schneider <florian.dirk.schneider@gmail.com>
Repository: CRAN
Date/Publication: 2021-09-02 12:30:02 UTC

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Package replacer updated to version 1.0.1 with previous version 1.0.0 dated 2021-08-18

Title: A Value Replacement Utility
Description: Updates values within csv format data files using a custom, User-built csv format lookup file. Based on 'data.table' package.
Author: Bandur Dragos [aut, cre]
Maintainer: Bandur Dragos <dbandur@sympatico.ca>

Diff between replacer versions 1.0.0 dated 2021-08-18 and 1.0.1 dated 2021-09-02

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Package JMbayes2 updated to version 0.1-8 with previous version 0.1-7 dated 2021-07-07

Title: Extended Joint Models for Longitudinal and Time-to-Event Data
Description: Fit joint models for longitudinal and time-to-event data under the Bayesian approach. Multiple longitudinal outcomes of mixed type (continuous/categorical) and multiple event times (competing risks and multi-state processes) are accommodated. Rizopoulos (2012, ISBN:9781439872864).
Author: Dimitris Rizopoulos [aut, cre] (<https://orcid.org/0000-0001-9397-0900>), Grigorios Papageorgiou [aut], Pedro Miranda Afonso [aut]
Maintainer: Dimitris Rizopoulos <d.rizopoulos@erasmusmc.nl>

Diff between JMbayes2 versions 0.1-7 dated 2021-07-07 and 0.1-8 dated 2021-09-02

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Package BayesSenMC updated to version 0.1.3 with previous version 0.1.2 dated 2020-05-26

Title: Different Models of Posterior Distributions of Adjusted Odds Ratio
Description: Generates different posterior distributions of adjusted odds ratio under different priors of sensitivity and specificity, and plots the models for comparison. It also provides estimations for the specifications of the models using diagnostics of exposure status with a non-linear mixed effects model. It implements the methods that are first proposed in <doi:10.1016/j.annepidem.2006.04.001> and <doi:10.1177/0272989X09353452>.
Author: Jinhui Yang, Haitao Chu, and Lifeng Lin
Maintainer: Jinhui Yang <james.yangjinhui@gmail.com>

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Package scorecard (with last version 0.3.4) was removed from CRAN

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

2021-08-04 0.3.4
2021-06-11 0.3.3
2021-03-14 0.3.2
2020-08-30 0.3.1
2020-04-10 0.3.0
2020-03-28 0.2.9
2019-12-11 0.2.8.1
2019-12-04 0.2.8
2019-10-17 0.2.7
2019-09-01 0.2.6
2019-07-04 0.2.5
2019-03-26 0.2.4
2019-02-10 0.2.3
2019-01-14 0.2.1
2019-01-14 0.2.2
2019-01-07 0.2.0
2018-09-11 0.1.9
2018-06-12 0.1.8
2018-04-27 0.1.7
2018-03-13 0.1.6
2018-01-21 0.1.5
2017-12-17 0.1.4
2017-11-17 0.1.3
2017-10-19 0.1.2
2017-10-17 0.1.1
2017-09-16 0.1.0

Permanent link
Package uFTIR (with last version 0.1.2) was removed from CRAN

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

2020-05-11 0.1.2
2020-03-11 0.1.1
2020-03-06 0.1.0

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Package rpst (with last version 1.0.0) was removed from CRAN

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

2017-06-06 1.0.0

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Package WienR updated to version 0.2-2 with previous version 0.2-1 dated 2021-08-20

Title: Derivatives of the Diffusion Density and Cumulative Distribution Function
Description: Calculates the partial derivative of the first-passage time diffusion probability density function (PDF) and cumulative distribution function (CDF) with respect to the first-passage time t (only for PDF), the upper barrier a, the drift rate v, the relative starting point w, the non-decision time t0, the inter-trial variability of the drift rate sv, the inter-trial variability of the rel. starting point sw, and the inter-trial variability of the non-decision time st0. In addition the PDF and CDF themselves are also provided. Most calculations are done on the logarithmic scale to make it more stable. Since the PDF, CDF, and their derivatives are represented as infinite series, we give the user the option to control the approximation errors with the argument 'precision'. For the numerical integration we used the C library cubature by Johnson, S. G. (2005-2013) <https://github.com/stevengj/cubature>. Numerical integration is required whenever sv, sw, and/or st0 is not zero. Note that numerical integration reduces speed of the computation and the precision cannot be guaranteed anymore. Therefore, whenever numerical integration is used an estimate of the approximation error is provided in the output list.
Author: Raphael Hartmann [aut, cre], Karl C. Klauer [cph, aut, ctb, ths], Steven G. Johnson [ctb], Jean M. Linhart [ctb], Brian Gough [ctb], Gerard Jungman [ctb], Rudolf Schuerer [ctb], Przemyslaw Sliwa [ctb], Jason H. Stover [ctb]
Maintainer: Raphael Hartmann <raphael.hartmann@protonmail.com>

Diff between WienR versions 0.2-1 dated 2021-08-20 and 0.2-2 dated 2021-09-02

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Package seplyr updated to version 1.0.4 with previous version 1.0.3 dated 2021-06-12

Title: Improved Standard Evaluation Interfaces for Common Data Manipulation Tasks
Description: The 'seplyr' (standard evaluation plying) package supplies improved standard evaluation adapter methods for important common 'dplyr' data manipulation tasks. In addition the 'seplyr' package supplies several new "key operations bound together" methods. These include 'group_summarize()' (which combines grouping, arranging and calculation in an atomic unit), 'add_group_summaries()' (which joins grouped summaries into a 'data.frame' in a well documented manner), 'add_group_indices()' (which adds per-group identifiers to a 'data.frame' without depending on row-order), 'partition_mutate_qt()' (which optimizes mutate sequences), and 'if_else_device()' (which simulates per-row if-else blocks in expression sequences).
Author: John Mount [aut, cre], Win-Vector LLC [cph]
Maintainer: John Mount <jmount@win-vector.com>

Diff between seplyr versions 1.0.3 dated 2021-06-12 and 1.0.4 dated 2021-09-02

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Package seminr updated to version 2.2.1 with previous version 2.2.0 dated 2021-08-18

Title: Building and Estimating Structural Equation Models
Description: A powerful, easy to syntax for specifying and estimating complex Structural Equation Models. Models can be estimated using Partial Least Squares Path Modeling or Covariance-Based Structural Equation Modeling or covariance based Confirmatory Factor Analysis. Methods described in Ray, Danks, and Valdez (2021).
Author: Soumya Ray [aut, ths], Nicholas Patrick Danks [aut, cre], André Calero Valdez [aut], Juan Manuel Velasquez Estrada [ctb], James Uanhoro [ctb], Johannes Nakayama [ctb], Lilian Koyan [ctb], Laura Burbach [ctb], Arturo Heynar Cano Bejar [ctb], Susanne Adler [ctb]
Maintainer: Nicholas Patrick Danks <nicholasdanks@hotmail.com>

Diff between seminr versions 2.2.0 dated 2021-08-18 and 2.2.1 dated 2021-09-02

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Package Rforestry updated to version 0.9.0.57 with previous version 0.9.0.47 dated 2021-07-05

Title: Random Forests, Linear Trees, and Gradient Boosting for Inference and Interpretability
Description: Provides fast implementations of Honest Random Forests, Gradient Boosting, and Linear Random Forests, with an emphasis on inference and interpretability. Additionally contains methods for variable importance, out-of-bag prediction, regression monotonicity, and several methods for missing data imputation. Soren R. Kunzel, Theo F. Saarinen, Edward W. Liu, Jasjeet S. Sekhon (2019) <arXiv:1906.06463>.
Author: Sören Künzel [aut], Theo Saarinen [aut, cre], Simon Walter [aut], Edward Liu [aut], Allen Tang [aut], Jasjeet Sekhon [aut]
Maintainer: Theo Saarinen <theo_s@berkeley.edu>

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Package RcppML updated to version 0.3.5 with previous version 0.1.0 dated 2021-07-28

Title: Rcpp Machine Learning Library
Description: High-performance machine learning algorithms, including matrix factorization and divisive clustering for large sparse and dense matrices.
Author: Zachary DeBruine [aut, cre] (<https://orcid.org/0000-0003-2234-4827>)
Maintainer: Zachary DeBruine <zacharydebruine@gmail.com>

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Package ldaPrototype updated to version 0.3.1 with previous version 0.3.0 dated 2020-12-02

Title: Prototype of Multiple Latent Dirichlet Allocation Runs
Description: Determine a Prototype from a number of runs of Latent Dirichlet Allocation (LDA) measuring its similarities with S-CLOP: A procedure to select the LDA run with highest mean pairwise similarity, which is measured by S-CLOP (Similarity of multiple sets by Clustering with Local Pruning), to all other runs. LDA runs are specified by its assignments leading to estimators for distribution parameters. Repeated runs lead to different results, which we encounter by choosing the most representative LDA run as prototype.
Author: Jonas Rieger [aut, cre] (<https://orcid.org/0000-0002-0007-4478>)
Maintainer: Jonas Rieger <jonas.rieger@tu-dortmund.de>

Diff between ldaPrototype versions 0.3.0 dated 2020-12-02 and 0.3.1 dated 2021-09-02

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Package Biostatistics updated to version 1.0.3 with previous version 1.0.2 dated 2021-07-11

Title: Statistics Tutorials for Biologists
Description: Tutorials for statistics, aimed at biological scientists. Subjects range from basic descriptive statistics through to complex linear modelling. The tutorials include text, videos, interactive coding exercises and multiple choice quizzes. The package also includes 19 datasets which are used in the tutorials.
Author: Rob Knell
Maintainer: Rob Knell <r.knell@qmul.ac.uk>

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Package CorporaCoCo (with last version 1.1-0) was removed from CRAN

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

2017-11-23 1.1-0
2017-03-31 1.0-2
2017-03-27 1.0-1

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Package dstack (with last version 0.2.1) was removed from CRAN

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

2020-08-12 0.2.1
2020-04-09 0.2.0
2020-03-24 0.1.0

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Package srt updated to version 1.0.3 with previous version 1.0.2 dated 2021-02-16

Title: Read Subtitle Files as Tabular Data
Description: Read 'SubRip' <https://sourceforge.net/projects/subrip/> subtitle files as data frames for easy text analysis or manipulation. Easily shift numeric timings and export subtitles back into valid 'SubRip' timestamp format to sync subtitles and audio.
Author: Kiernan Nicholls [aut, cre]
Maintainer: Kiernan Nicholls <kiernann@protonmail.com>

Diff between srt versions 1.0.2 dated 2021-02-16 and 1.0.3 dated 2021-09-02

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Package pagemap updated to version 0.1.3 with previous version 0.1.2 dated 2021-08-13

Title: Create Mini Map for Web Pages
Description: Quickly and easily add a mini map to your 'rmarkdown' html documents.
Author: Wei Su [aut, cre] (<https://orcid.org/0000-0002-9302-5332>), Lars Jung [aut, cph] (pagemap library in htmlwidgets/lib, https://github.com/lrsjng/pagemap)
Maintainer: Wei Su <swsoyee@gmail.com>

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Package DesignLibrary updated to version 0.1.8 with previous version 0.1.6 dated 2021-03-02

Title: Library of Research Designs
Description: A simple interface to build designs using the package 'DeclareDesign'. In one line of code, users can specify the parameters of individual designs and diagnose their properties. The designers can also be used to compare performance of a given design across a range of combinations of parameters, such as effect size, sample size, and assignment probabilities.
Author: Graeme Blair [aut], Jasper Cooper [aut, cre], Alexander Coppock [aut], Macartan Humphreys [aut], Clara Bicalho [aut], Neal Fultz [aut], Lily Medina [aut]
Maintainer: Jasper Cooper <jjc2247@columbia.edu>

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Package campfin updated to version 1.0.8 with previous version 1.0.7 dated 2021-04-12

Title: Wrangle Campaign Finance Data
Description: Explore and normalize American campaign finance data. Created by the Investigative Reporting Workshop to facilitate work on The Accountability Project, an effort to collect public data into a central, standard database that is more easily searched: <https://publicaccountability.org/>.
Author: Kiernan Nicholls [aut, cre, cph], Investigative Reporting Workshop [cph], Yanqi Xu [aut], Schuyler Erle [cph]
Maintainer: Kiernan Nicholls <kiernann@protonmail.com>

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Package amanpg updated to version 0.3.1 with previous version 0.3.0 dated 2021-07-26

Title: Alternating Manifold Proximal Gradient Method for Sparse PCA
Description: Alternating Manifold Proximal Gradient Method for Sparse PCA uses the Alternating Manifold Proximal Gradient (AManPG) method to find sparse principal components from a data or covariance matrix. Provides a novel algorithm for solving the sparse principal component analysis problem which provides advantages over existing methods in terms of efficiency and convergence guarantees. Chen, S., Ma, S., Xue, L., & Zou, H. (2020) <doi:10.1287/ijoo.2019.0032>. Zou, H., Hastie, T., & Tibshirani, R. (2006) <doi:10.1198/106186006X113430>. Zou, H., & Xue, L. (2018) <doi:10.1109/JPROC.2018.2846588>.
Author: Shixiang Chen [aut], Justin Huang [aut], Benjamin Jochem [aut], Shiqian Ma [aut], Lingzhou Xue [cre, aut], Hui Zou [aut]
Maintainer: Lingzhou Xue <lzxue@psu.edu>

Diff between amanpg versions 0.3.0 dated 2021-07-26 and 0.3.1 dated 2021-09-02

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New package simfam with initial version 1.0.2
Package: simfam
Title: Simulate and Model Family Pedigrees with Structured Founders
Version: 1.0.2
Description: The focus is on simulating and modeling families with founders drawn from a structured population (for example, with different ancestries or other potentially non-family relatedness), in contrast to traditional pedigree analysis that treats all founders as equally unrelated. Main function simulates a random pedigree for many generations, avoiding close relatives, pairing closest individuals according to a 1D geography and their randomly-drawn sex, and with variable children sizes to result in a target population size per generation. Auxiliary functions calculate kinship matrices, admixture matrices, and draw random genotypes across arbitrary pedigree structures starting from the corresponding founder values. The code is built around the plink FAM table format for pedigrees. Partially described in Yao and Ochoa (2019) <doi:10.1101/858399>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: Rcpp, stats, tibble
Suggests: testthat (>= 3.0.0), popkin, bnpsd (>= 1.3.2), kinship2, RColorBrewer, knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: Rcpp
URL: https://github.com/OchoaLab/simfam
BugReports: https://github.com/OchoaLab/simfam/issues
NeedsCompilation: yes
Packaged: 2021-09-01 12:34:30 UTC; viiia
Author: Alejandro Ochoa [aut, cre] (<https://orcid.org/0000-0003-4928-3403>)
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>
Repository: CRAN
Date/Publication: 2021-09-02 09:20:02 UTC

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New package Rnvd3 with initial version 1.0.0
Package: Rnvd3
Title: An Incomplete Wrapper of the 'nvd3' JavaScript Library
Version: 1.0.0
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>
Description: Creates JavaScript charts with the 'nvd3' library. So far only the multibar chart, the horizontal multibar chart, the line chart and the line chart with focus are available.
License: GPL-3
Encoding: UTF-8
URL: https://github.com/stla/Rnvd3
BugReports: https://github.com/stla/Rnvd3/issues
Imports: lubridate, data.table, htmlwidgets, lazyeval, viridisLite, htmltools, jsonlite, grDevices, utils
Suggests: reshape2, shiny
NeedsCompilation: no
Packaged: 2021-09-01 12:39:26 UTC; SDL96354
Author: Stéphane Laurent [aut, cre], Novus Partners, Inc. [cph] ('nvd3.js' library), Michael Bostock [cph] ('d3.js' library)
Repository: CRAN
Date/Publication: 2021-09-02 09:20:05 UTC

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Package precautionary (with last version 0.2.6) was removed from CRAN

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

2021-08-09 0.2.6
2021-01-12 0.2-1
2020-12-15 0.2-0
2020-11-03 0.1-5
2020-09-21 0.1-4
2020-09-13 0.1-3
2020-08-01 0.1-2
2020-07-20 0.1-1

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Package helsinki (with last version 1.0.1) was removed from CRAN

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

2021-05-09 1.0.1
2017-02-18 0.9.29
2015-05-06 0.9.27
2014-12-22 0.9.24
2014-12-19 0.9.22
2014-06-09 0.9.20
2014-05-14 0.9.18
2014-04-13 0.9.12

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Package PandemicLP (with last version 0.2.1) was removed from CRAN

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

2021-02-09 0.2.1
2020-11-30 0.2.0

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Package macleish (with last version 0.3.7) was removed from CRAN

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

2021-08-06 0.3.7
2020-06-03 0.3.6

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Package WaterML (with last version 1.9.8) was removed from CRAN

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

2021-04-10 1.9.8

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Package zipcodeR updated to version 0.3.2 with previous version 0.3.1 dated 2021-06-10

Title: Data & Functions for Working with US ZIP Codes
Description: Make working with ZIP codes in R painless with an integrated dataset of U.S. ZIP codes and functions for working with them. Search ZIP codes by multiple geographies, including state, county, city & across time zones. Also included are functions for relating ZIP codes to Census data, geocoding & distance calculations.
Author: Gavin Rozzi [aut, cre] (<https://orcid.org/0000-0002-9969-8175>)
Maintainer: Gavin Rozzi <gr@gavinrozzi.com>

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New package TIGERr with initial version 0.1.0
Package: TIGERr
Title: Technical Variation Elimination with Ensemble Learning Architecture
Version: 0.1.0
Author: Siyu Han [aut, cre], Jialing Huang [aut], Francesco Foppiano [aut], Cornelia Prehn [aut], Jerzy Adamski [aut], Karsten Suhre [aut], Giuseppe Matullo [aut], Freimut Schliess [aut], Christian Gieger [aut], Annette Peters [aut], Rui Wang-Sattler [aut]
Maintainer: Siyu Han <siyu.han@helmholtz-muenchen.de>
Acknowledgments: TAI Yun-hsiu, WANG Ruoyu, CHENG Ming, GUO Yuan, LI Han, FAN Linrui
Description: The R implementation of TIGER. TIGER integrates random forest algorithm into an innovative ensemble learning architecture. Benefiting from this advanced architecture, TIGER is resilient to outliers, free from model tuning and less likely to be affected by specific hyperparameters. TIGER supports targeted and untargeted metabolomics data and is competent to perform both intra- and inter-batch technical variation removal. TIGER can also be used for cross-kit adjustment to ensure data obtained from different analytical assays can be effectively combined and compared. Reference: Han S. et al. (2021) TIGER: technical variation elimination for metabolomics data using ensemble learning architecture (submitted).
License: GPL (>= 3)
Depends: R (>= 3.5.0)
Imports: caret (>= 6.0-71), parallel (>= 2.1.0), pbapply (>= 1.4-3), ppcor (>= 1.1), randomForest (>= 4.6-14), stats (>= 4.0.3)
BugReports: https://github.com/HAN-Siyu/TIGER/issues
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2021-09-01 08:35:05 UTC; siyu.han
Repository: CRAN
Date/Publication: 2021-09-02 07:50:02 UTC

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New package sphunif with initial version 1.0.1
Package: sphunif
Title: Uniformity Tests on the Circle, Sphere, and Hypersphere
Version: 1.0.1
Date: 2021-09-01
Description: Implementation of uniformity tests on the circle and (hyper)sphere. The main function of the package is unif_test(), which conveniently collects more than 30 tests for assessing uniformity on S^{p-1}={x in R^p : ||x||=1}, p >= 2. The test statistics are implemented in the unif_stat() function, which allows computing several statistics to several samples within a single call, thus facilitating Monte Carlo experiments. Furthermore, the unif_stat_MC() function allows parallelizing them in a simple way. The asymptotic null distributions of the statistics are available through the function unif_stat_distr(). The core of 'sphunif' is coded in C++ by relying on the 'Rcpp' package. The package also provides several novel datasets and gives the reproducibility for the data application in García-Portugués, Navarro-Esteban and Cuesta-Albertos (2020) <arXiv:2008.09897>.
License: GPL-3
LazyData: true
Depends: R (>= 3.5.0), Rcpp
Imports: doFuture, foreach, future, gsl, rotasym
Suggests: CompQuadForm, dgof, goftest, knitr, markdown, mvtnorm, numDeriv, progress, progressr, rmarkdown, scatterplot3d, testthat, viridisLite
LinkingTo: Rcpp, RcppArmadillo
URL: https://github.com/egarpor/sphunif
BugReports: https://github.com/egarpor/sphunif
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-09-01 06:31:37 UTC; Eduardo
Author: Eduardo García-Portugués [aut, cre] (<https://orcid.org/0000-0002-9224-4111>), Thomas Verdebout [aut] (<https://orcid.org/0000-0002-3277-9587>), Paula Navarro [ctb]
Maintainer: Eduardo García-Portugués <edgarcia@est-econ.uc3m.es>
Repository: CRAN
Date/Publication: 2021-09-02 07:40:02 UTC

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Package SimDesign updated to version 2.7.1 with previous version 2.7 dated 2021-08-13

Title: Structure for Organizing Monte Carlo Simulation Designs
Description: Provides tools to safely and efficiently organize and execute Monte Carlo simulation experiments in R. The package controls the structure and back-end of Monte Carlo simulation experiments by utilizing a generate-analyse-summarise workflow. The workflow safeguards against common simulation coding issues, such as automatically re-simulating non-convergent results, prevents inadvertently overwriting simulation files, catches error and warning messages during execution, and implicitly supports parallel processing. For a pedagogical introduction to the package see Sigal and Chalmers (2016) <doi:10.1080/10691898.2016.1246953>. For a more in-depth overview of the package and its design philosophy see Chalmers and Adkins (2020) <doi:10.20982/tqmp.16.4.p248>.
Author: Phil Chalmers [aut, cre] (<https://orcid.org/0000-0001-5332-2810>), Matthew Sigal [ctb], Ogreden Oguzhan [ctb]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>

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Package SCEM updated to version 1.1.0 with previous version 1.0.0 dated 2021-08-06

Title: Splitting-Coalescence-Estimation Method
Description: We introduce improved methods for statistically assessing birth seasonality and intra-annual variation. The first method we propose is a new idea that uses a nonparametric clustering procedure to group individuals with similar time series data and estimate birth seasonality based on the clusters. One can use the function SCEM() to implement this method. The second method estimates input parameters for use with a previously-developed parametric approach (Tornero et al., 2013). The relevant code for this approach is makeFits_OLS(), while makeFits_initial() is the code to implement the same method but with given initial conditions for two parameters. The latter can be used to show the disadvantage of the existing approach. One can use the function makeFits() to generate parametric birth seasonality estimates using either initialization. Detailed description can be found here: Chazin Hannah, Soudeep Deb, Joshua Falk, and Arun Srinivasan. (2019) "New Statistical Approaches to Intra-Individual Isotopic Analysis and Modeling Birth Seasonality in Studies of Herd Animals." <doi:10.1111/arcm.12432>.
Author: Hannah Chazin [aut], Soudeep Deb [aut], Joshua Falk [aut], Arun Srinivasan [aut], Kyung Serk Cho [cre]
Maintainer: Kyung Serk Cho <kyslf1994@gmail.com>

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Package MARVEL updated to version 1.2.0 with previous version 1.1.0 dated 2021-03-31

Title: Revealing Splicing Dynamics at Single-Cell Resolution
Description: Alternative splicing represents an additional and underappreciated layer of complexity underlying gene expression profiles. Nevertheless, there remains hitherto a paucity of softwares to investigate splicing dynamics at single-cell resolution. 'MARVEL' quantifies percent spliced-in (PSI) values for the five primary exon-level splicing events, namely skipped-exon (SE), mutually exclusive exons (MXE), retained intron (RI), alternative 5' and 3' splice sites (A5SS and A3SS, respectively). Additionally, 'MARVEL' performs differential splicing analysis to identify splicing events whose PSI distribution differ between groups of cells. Finally, 'MARVEL' models the PSI distribution for each event as a beta distribution and categorises each distribution into modalities (inspired by Song (2017) <doi:10.1016/j.molcel.2017.06.003>).
Author: Sean Wen
Maintainer: Sean Wen <sean.wenwx@gmail.com>

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New package isobxr with initial version 1.0.0
Package: isobxr
Title: Stable Isotope Box Modelling in R
Version: 1.0.0
Description: A set of functions to run simple and composite box-models to describe the dynamic or static distribution of stable isotopes in open or closed systems. The package also allows the sweeping of many parameters in both static and dynamic conditions. It also comes with a post-run plotting interface built under shiny. The mathematical models used in this package are derived from Albarede, 1995, Introduction to Geochemical Modelling, Cambridge University Press, Cambridge <doi:10.1017/CBO9780511622960>.
Depends: R (>= 3.5.0)
License: GPL-3
URL: https://github.com/ttacail/isobxr, https://ttacail.github.io/isobxr_web/, https://ttacail.github.io/isobxr/
BugReports: https://github.com/ttacail/isobxr/issues
Encoding: UTF-8
LazyData: false
Imports: stringr, readxl, dplyr, data.table, deSolve, rlang, grid, metR, shiny, shinyFiles, shinythemes, shinyjs, DT, ggplot2, ggrepel, qgraph, writexl, R.utils, fs
Suggests: knitr, rmarkdown, devtools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-09-01 09:37:09 UTC; sz18642
Author: Theo Tacail [aut, cre]
Maintainer: Theo Tacail <theo.tacail@protonmail.com>
Repository: CRAN
Date/Publication: 2021-09-02 08:00:02 UTC

More information about isobxr at CRAN
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Package hashr updated to version 0.1.4 with previous version 0.1.3 dated 2020-07-22

Title: Hash R Objects to Integers Fast
Description: Apply an adaptation of the SuperFastHash algorithm to any R object. Hash whole R objects or, for vectors or lists, hash R objects to obtain a set of hash values that is stored in a structure equivalent to the input. See <http://www.azillionmonkeys.com/qed/hash.html> for a description of the hash algorithm.
Author: Mark van der Loo [aut, cre], Paul Hsieh [ctb]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

Diff between hashr versions 0.1.3 dated 2020-07-22 and 0.1.4 dated 2021-09-02

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Package europepmc updated to version 0.4.1 with previous version 0.4 dated 2020-05-31

Title: R Interface to the Europe PubMed Central RESTful Web Service
Description: An R Client for the Europe PubMed Central RESTful Web Service (see <https://europepmc.org/RestfulWebService> for more information). It gives access to both metadata on life science literature and open access full texts. Europe PMC indexes all PubMed content and other literature sources including Agricola, a bibliographic database of citations to the agricultural literature, or Biological Patents. In addition to bibliographic metadata, the client allows users to fetch citations and reference lists. Links between life-science literature and other EBI databases, including ENA, PDB or ChEMBL are also accessible. No registration or API key is required. See the vignettes for usage examples.
Author: Najko Jahn [aut, cre, cph], Maëlle Salmon [ctb]
Maintainer: Najko Jahn <najko.jahn@gmail.com>

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Package deeptime updated to version 0.2.0 with previous version 0.1.0 dated 2021-07-23

Title: Plotting Tools for Anyone Working in Deep Time
Description: Extends the functionality of other plotting packages like 'ggplot2' and 'lattice' to help facilitate the plotting of data over long time intervals, including, but not limited to, geological, evolutionary, and ecological data. The primary goal of 'deeptime' is to enable users to add highly customizable timescales to their visualizations. Other functions are also included to assist with other areas of deep time visualization.
Author: William Gearty [aut, cre]
Maintainer: William Gearty <willgearty@gmail.com>

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Package zoolog updated to version 0.4.1 with previous version 0.4.0 dated 2021-08-02

Title: Zooarchaeological Analysis with Log-Ratios
Description: Includes functions and reference data to generate and manipulate log-ratios (also known as log size index (LSI) values) from measurements obtained on zooarchaeological material. Log ratios are used to compare the relative (rather than the absolute) dimensions of animals from archaeological contexts (Meadow 1999, ISBN: 9783896463883). zoolog is also able to seamlessly integrate data and references with heterogeneous nomenclature, which is internally managed by a zoolog thesaurus. A preliminary version of the zoolog methods was first used by Trentacoste, Nieto-Espinet, and Valenzuela-Lamas (2018) <doi:10.1371/journal.pone.0208109>.
Author: Jose M Pozo [aut, cre] (<https://orcid.org/0000-0002-0759-3510>), Silvia Valenzuela-Lamas [aut] (<https://orcid.org/0000-0001-9886-0372>), Angela Trentacoste [aut] (<https://orcid.org/0000-0001-7096-5252>), Ariadna Nieto-Espinet [aut] (<https://orcid.org/0000-0003-2567-1735>), Silvia Guimarães Chiarelli [aut] (<https://orcid.org/0000-0002-3778-3315>)
Maintainer: Jose M Pozo <josmpozo@gmail.com>

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Package uGMAR updated to version 3.4.0 with previous version 3.3.2 dated 2021-07-08

Title: Estimate Univariate Gaussian or Student's t Mixture Autoregressive Model
Description: Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR), Student's t Mixture Autoregressive (StMAR), and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Mika Meitz, Daniel Preve, Pentti Saikkonen (2021) <doi:10.1080/03610926.2021.1916531>, Savi Virolainen (2021) <doi:10.1515/snde-2020-0060>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>

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Package tvgarch updated to version 2.1 with previous version 2.0 dated 2021-04-16

Title: Time Varying GARCH Modelling
Description: Simulation, estimation and inference for univariate and multivariate TV(s)-GARCH(p,q,r)-X models, where s indicates the number and shape of the transition functions, p is the ARCH order, q is the GARCH order, r is the asymmetry order, and 'X' indicates that covariates can be included. In the multivariate case, variances are estimated equation by equation and dynamic conditional correlations are allowed. The TV long-term component of the variance as in the multiplicative TV-GARCH model of Amado and Ter{\"a}svirta (2013) <doi:10.1016/j.jeconom.2013.03.006> introduces non-stationarity whereas the GARCH-X short-term component describes conditional heteroscedasticity. Maximisation by parts leads to consistent and asymptotically normal estimates.
Author: Susana Campos-Martins [aut, cre], Genaro Sucarrat [ctb]
Maintainer: Susana Campos-Martins <susana.martins@nuffield.ox.ac.uk>

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Package DisImpact updated to version 0.0.15 with previous version 0.0.14 dated 2020-09-19

Title: Calculates Disproportionate Impact When Binary Success Data are Disaggregated by Subgroups
Description: Implements methods for calculating disproportionate impact: the percentage point gap, proportionality index, and the 80% index. California Community Colleges Chancellor's Office (2017). Percentage Point Gap Method. <https://www.cccco.edu/-/media/CCCCO-Website/About-Us/Divisions/Digital-Innovation-and-Infrastructure/Research/Files/PercentagePointGapMethod2017.ashx>. California Community Colleges Chancellor's Office (2014). Guidelines for Measuring Disproportionate Impact in Equity Plans. <https://www.cccco.edu/-/media/CCCCO-Website/Files/DII/guidelines-for-measuring-disproportionate-impact-in-equity-plans-tfa-ada.pdf>.
Author: Vinh Nguyen [aut, cre]
Maintainer: Vinh Nguyen <nguyenvq714@gmail.com>

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Package baggr updated to version 0.6.9 with previous version 0.6.4 dated 2021-05-11

Title: Bayesian Aggregate Treatment Effects
Description: Running and comparing meta-analyses of data with hierarchical Bayesian models in Stan, including convenience functions for formatting data, plotting and pooling measures specific to meta-analysis. This implements many models from Meager (2019) <doi:10.1257/app.20170299>.
Author: Witold Wiecek [cre, aut], Rachael Meager [aut], Brice Green [ctb] (predict(), loo_compare, many visuals), Trustees of Columbia University [cph] (tools/make_cc.R)
Maintainer: Witold Wiecek <witold.wiecek@gmail.com>

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Package SortedEffects updated to version 1.5.0 with previous version 1.4.0 dated 2021-05-06

Title: Estimation and Inference Methods for Sorted Causal Effects and Classification Analysis
Description: Implements the estimation and inference methods for sorted causal effects and classification analysis as in Chernozhukov, Fernandez-Val and Luo (2018) <doi:10.3982/ECTA14415>.
Author: Shuowen Chen [aut, cre], Victor Chernozhukov [aut], Ivan Fernandez-Val [aut], Ye Luo [aut]
Maintainer: Shuowen Chen <swchen@bu.edu>

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Package poismf updated to version 0.3.1-2 with previous version 0.3.1-1 dated 2021-08-21

Title: Factorization of Sparse Counts Matrices Through Poisson Likelihood
Description: Creates a low-rank factorization of a sparse counts matrix by maximizing Poisson likelihood with l1/l2 regularization with all non-negative latent factors (e.g. for recommender systems or topic modeling) (Cortes, (2018) <arXiv:1811.01908>). Similar to hierarchical Poisson factorization, but follows an optimization-based approach with regularization instead of a hierarchical structure, and is fit through gradient-based methods instead of variational inference.
Author: David Cortes [aut, cre, cph], Jean-Sebastien Roy [cph] (Copyright holder of included tnc library), Stephen Nash [cph] (Copyright holder of included tnc library)
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package onbrand updated to version 1.0.1 with previous version 1.0.0 dated 2021-07-12

Title: Templated Reporting Workflows in Word and PowerPoint
Description: Automated reporting in Word and PowerPoint can require customization for each organizational template. This package works around this by adding standard reporting functions and an abstraction layer to facilitate automated reporting workflows that can be replicated across different organizational templates.
Author: John Harrold [aut, cre] (<https://orcid.org/0000-0003-2052-4373>), Bryan Smith [aut]
Maintainer: John Harrold <john.m.harrold@gmail.com>

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Package nflreadr updated to version 1.1.0 with previous version 1.0.0 dated 2021-08-09

Title: Download 'nflverse' Data
Description: A low-level package for downloading data from 'GitHub' repositories of the 'nflverse' project.
Author: Tan Ho [aut, cre, cph] (<https://orcid.org/0000-0001-8388-5155>), Sebastian Carl [aut], John Edwards [ctb], Ben Baldwin [ctb], Thomas Mock [ctb], Lee Sharpe [ctb]
Maintainer: Tan Ho <tan@tanho.ca>

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Package MCM updated to version 0.1.3 with previous version 0.1.2 dated 2021-08-17

Title: Estimating and Testing Intergenerational Social Mobility Effect
Description: Estimate and test inter-generational social mobility effect on an outcome with cross-sectional or longitudinal data.
Author: Jiahui Xu [aut, cre], Liying Luo [aut]
Maintainer: Jiahui Xu <jpx5053@psu.edu>

Diff between MCM versions 0.1.2 dated 2021-08-17 and 0.1.3 dated 2021-09-02

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Package insight updated to version 0.14.4 with previous version 0.14.3 dated 2021-08-17

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>, @strengejacke), Dominique Makowski [aut, ctb] (<https://orcid.org/0000-0001-5375-9967>, @Dom_Makowski), Indrajeet Patil [aut, ctb] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut, ctb] (<https://orcid.org/0000-0002-4287-4801>), Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>, @bmwiernik), Alex Hayes [rev] (<https://orcid.org/0000-0002-4985-5160>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package hdme updated to version 0.3.4 with previous version 0.3.3 dated 2020-05-18

Title: High-Dimensional Regression with Measurement Error
Description: Penalized regression for generalized linear models for measurement error problems (aka. errors-in-variables). The package contains a version of the lasso (L1-penalization) which corrects for measurement error (Sorensen et al. (2015) <doi:10.5705/ss.2013.180>). It also contains an implementation of the Generalized Matrix Uncertainty Selector, which is a version the (Generalized) Dantzig Selector for the case of measurement error (Sorensen et al. (2018) <doi:10.1080/10618600.2018.1425626>).
Author: Oystein Sorensen [aut, cre] (<https://orcid.org/0000-0003-0724-3542>)
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

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Package BIGL updated to version 1.6.4 with previous version 1.6.3 dated 2021-06-29

Title: Biochemically Intuitive Generalized Loewe Model
Description: Response surface methods for drug synergy analysis. Available methods include generalized and classical Loewe formulations as well as Highest Single Agent methodology. Response surfaces can be plotted in an interactive 3-D plot and formal statistical tests for presence of synergistic effects are available. Implemented methods and tests are described in the article "BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism" by Koen Van der Borght, Annelies Tourny, Rytis Bagdziunas, Olivier Thas, Maxim Nazarov, Heather Turner, Bie Verbist & Hugo Ceulemans (2017) <doi:10.1038/s41598-017-18068-5>.
Author: Heather Turner, Annelies Tourny, Olivier Thas, Maxim Nazarov, Rytis Bagdziunas, Stijn Hawinkel
Maintainer: Maxim Nazarov <maxim.nazarov@openanalytics.eu>

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