Sun, 13 Sep 2020

Package reactable updated to version 0.2.2 with previous version 0.2.1 dated 2020-09-01

Title: Interactive Data Tables Based on 'React Table'
Description: Interactive data tables for R, based on the 'React Table' JavaScript library. Provides an HTML widget that can be used in 'R Markdown' documents and 'Shiny' applications, or viewed from an R console.
Author: Greg Lin [aut, cre], Tanner Linsley [ctb, cph] (React Table library), Emotion team and other contributors [ctb, cph] (Emotion library)
Maintainer: Greg Lin <glin@glin.io>

Diff between reactable versions 0.2.1 dated 2020-09-01 and 0.2.2 dated 2020-09-13

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Package precautionary updated to version 0.1-3 with previous version 0.1-2 dated 2020-08-01

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

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More information about precautionary at CRAN
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Package mlr3pipelines updated to version 0.3.0 with previous version 0.2.1 dated 2020-08-18

Title: Preprocessing Operators and Pipelines for 'mlr3'
Description: Dataflow programming toolkit that enriches 'mlr3' with a diverse set of pipelining operators ('PipeOps') that can be composed into graphs. Operations exist for data preprocessing, model fitting, and ensemble learning. Graphs can themselves be treated as 'mlr3' 'Learners' and can therefore be resampled, benchmarked, and tuned.
Author: Martin Binder [aut, cre], Florian Pfisterer [aut] (<https://orcid.org/0000-0001-8867-762X>), Lennart Schneider [aut] (<https://orcid.org/0000-0003-4152-5308>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Susanne Dandl [aut]
Maintainer: Martin Binder <mlr.developer@mb706.com>

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More information about mlr3pipelines at CRAN
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New package MALDIrppa with initial version 1.0.5
Package: MALDIrppa
Type: Package
Title: MALDI Mass Spectrometry Data Robust Pre-Processing and Analysis
Version: 1.0.5
Authors@R: c(person(given = "Javier", family = "Palarea-Albaladejo", role = c("cre","aut"), email = "javier.palarea@bioss.ac.uk", comment = c(ORCID = "0000-0003-0162-669X")), person(given = "Paolo", family = "Ribeca", role = c("ctb"), email = "paolo.ribeca@bioss.ac.uk", comment = c(ORCID = "0000-0001-5599-3933")), person(given = "William", family = "Constantine", role = c("ctb"), comment = "Author of original C code used in archived wtmsa and ifultools R packages."), person(given = "Keith L.", family = "Davidson", role = c("ctb"), comment = "Author of original C code used in archived wtmsa and ifultools R packages."), person(given = "Insightful Corp.", role = c("cph"), comment = "Copyright holder named in some original C code used in archived wtmsa and ifultools R packages.") )
Date: 2020-08-21
Maintainer: Javier Palarea-Albaladejo <javier.palarea@bioss.ac.uk>
Depends: R (>= 3.2.5), MALDIquant, signal, robustbase, lattice
ByteCompile: yes
Description: Provides methods for quality control and robust pre-processing and analysis of MALDI mass spectrometry data (Palarea-Albaladejo et al. (2018) <doi:10.1093/bioinformatics/btx628>).
License: GPL (>= 2)
Repository: CRAN
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2020-09-11 10:10:31 UTC; Japal
Author: Javier Palarea-Albaladejo [cre, aut] (<https://orcid.org/0000-0003-0162-669X>), Paolo Ribeca [ctb] (<https://orcid.org/0000-0001-5599-3933>), William Constantine [ctb] (Author of original C code used in archived wtmsa and ifultools R packages.), Keith L. Davidson [ctb] (Author of original C code used in archived wtmsa and ifultools R packages.), Insightful Corp. [cph] (Copyright holder named in some original C code used in archived wtmsa and ifultools R packages.)
Date/Publication: 2020-09-13 21:40:06 UTC

More information about MALDIrppa at CRAN
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Package ggdendro updated to version 0.1.22 with previous version 0.1.21 dated 2020-08-11

Title: Create Dendrograms and Tree Diagrams Using 'ggplot2'
Description: This is a set of tools for dendrograms and tree plots using 'ggplot2'. The 'ggplot2' philosophy is to clearly separate data from the presentation. Unfortunately the plot method for dendrograms plots directly to a plot device without exposing the data. The 'ggdendro' package resolves this by making available functions that extract the dendrogram plot data. The package provides implementations for 'tree', 'rpart', as well as diana and agnes (from 'cluster') diagrams.
Author: Andrie de Vries [aut, cre], Brian D. Ripley [aut] (author of package tree)
Maintainer: Andrie de Vries <apdevries@gmail.com>

Diff between ggdendro versions 0.1.21 dated 2020-08-11 and 0.1.22 dated 2020-09-13

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Package dalmatian updated to version 0.6.1 with previous version 0.3.0 dated 2018-01-29

Title: Automating the Fitting of Double Linear Mixed Models in 'JAGS' and 'nimble'
Description: Automates fitting of double GLM in 'JAGS'. Includes automatic generation of 'JAGS' scripts, running 'JAGS' or 'nimble' via the 'rjags' and 'nimble' package, and summarizing the resulting output.
Author: Simon Bonner [aut, cre] (<https://orcid.org/0000-0003-2063-4572>), Hanna Kim [aut]
Maintainer: Simon Bonner <simon.bonner@uwo.ca>

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Package snahelper updated to version 1.2.0 with previous version 1.1.0 dated 2020-03-03

Title: 'RStudio' Addin for Network Analysis and Visualization
Description: 'RStudio' addin which provides a GUI to visualize and analyse networks. After finishing a session, the code to produce the plot is inserted in the current script. Alternatively, the function SNAhelperGadget() can be used directly from the console. Additional addins include the Netreader() for reading network files, Netbuilder() to create small networks via point and click, and the Componentlayouter() to layout networks with many components manually.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>

Diff between snahelper versions 1.1.0 dated 2020-03-03 and 1.2.0 dated 2020-09-13

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Permanent link

Package ipmisc updated to version 3.2.0 with previous version 3.1.0 dated 2020-06-19

Title: Miscellaneous Functions for Data Cleaning and Analysis
Description: Provides functions needed for data cleaning and formatting and forms data cleaning and wrangling backend for the following packages: 'broomExtra', 'ggstatsplot', 'groupedstats', 'pairwiseComparisons', 'statsExpressions', and 'tidyBF'.
Author: Indrajeet Patil [aut, cre, cph] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package DPWeibull updated to version 1.6 with previous version 1.5 dated 2020-01-08

Title: Dirichlet Process Weibull Mixture Model for Survival Data
Description: Use Dirichlet process Weibull mixture model and dependent Dirichlet process Weibull mixture model for survival data with and without competing risks. Dirichlet process Weibull mixture model is used for data without covariates and dependent Dirichlet process model is used for regression data. The package is designed to handle exact/right-censored/ interval-censored observations without competing risks and exact/right-censored observations for data with competing risks. Inside each cluster of Dirichlet process, we assume a multiplicative effect of covariates as in Cox model and Fine and Gray model. For wrapper of the DPdensity function from the R package DPpackage (already archived by CRAN) that uses the Low Information Omnibus prior, please check (<https://github.com/mjmartens/DPdensity-wrapper-with-LIO-prior>).
Author: Yushu Shi
Maintainer: Yushu Shi <shiyushu2006@gmail.com>

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Package wakefield updated to version 0.3.6 with previous version 0.3.3 dated 2018-05-19

Title: Generate Random Data Sets
Description: Generates random data sets including: data.frames, lists, and vectors.
Author: Tyler Rinker [aut, cre], Josh O'Brien [ctb], Ananda Mahto [ctb], Matthew Sigal [ctb], Jonathan Carroll [ctb], Scott Westenberger [ctb]
Maintainer: Tyler Rinker <tyler.rinker@gmail.com>

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Package tidyMicro updated to version 1.47 with previous version 1.43 dated 2020-03-28

Title: A Pipeline for Microbiome Analysis and Visualization
Description: A reliable alternative to popular microbiome analysis R packages. We provide standard tools as well as novel extensions on standard analyses to improve interpretability and the analyst’s ability to communicate results, all while maintaining object malleability to encourage open source collaboration.
Author: Charlie Carpenter [aut, cre], Dan Frank [aut], Kayla Williamson [aut], Rachel Johnson [ctb]
Maintainer: Charlie Carpenter <charles.carpenter@cuanschutz.edu>

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Package ubiquity updated to version 1.0.3 with previous version 1.0.2 dated 2020-07-05

Title: PKPD, PBPK, and Systems Pharmacology Modeling Tools
Description: Complete work flow for the analysis of pharmacokinetic pharmacodynamic (PKPD), physiologically-based pharmacokinetic (PBPK) and systems pharmacology models including: creation of ordinary differential equation-based models, pooled parameter estimation, individual/population based simulations, rule-based simulations for clinical trial design and modeling assays, deployment with a customizable 'Shiny' app, and non-compartmental analysis. System-specific analysis templates can be generated and each element includes integrated reporting with 'PowerPoint' and 'Word'.
Author: John Harrold [aut, cre]
Maintainer: John Harrold <john.m.harrold@gmail.com>

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Package tidyRSS updated to version 2.0.3 with previous version 2.0.2 dated 2020-06-01

Title: Tidy RSS for R
Description: With the objective of including data from RSS feeds into your analysis, 'tidyRSS' parses RSS, Atom and JSON feeds and returns a tidy data frame.
Author: Robert Myles McDonnell [aut, cre], Jonathan Carroll [ctb], Mike Smith [ctb], Joseph Stachelek [ctb]
Maintainer: Robert Myles McDonnell <robertmylesmcdonnell@gmail.com>

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Package starschemar updated to version 1.1.0 with previous version 1.0.0 dated 2020-08-07

Title: Obtaining Star Schemas from Flat Tables
Description: Data in multidimensional systems is obtained from operational systems and is transformed to adapt it to the new structure. Frequently, the operations to be performed aim to transform a flat table into a star schema. Transformations can be carried out using professional ETL (extract, transform and load) tools or tools intended for data transformation for end users. With the tools mentioned, this transformation can be carried out, but it requires a lot of work. The main objective this package is to define transformations that allow obtaining star schemas from flat tables easily. In addition, it includes basic data cleaning, dimension enrichment, incremental data refresh and query operations, adapted to this context.
Author: Jose Samos [aut, cre, cph] (<https://orcid.org/0000-0002-4457-3439>)
Maintainer: Jose Samos <jsamos@ugr.es>

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Package mem updated to version 2.16 with previous version 2.15 dated 2019-05-28

Title: The Moving Epidemic Method
Description: The Moving Epidemic Method, created by T Vega and JE Lozano (2012, 2015) <doi:10.1111/j.1750-2659.2012.00422.x>, <doi:10.1111/irv.12330>, allows the weekly assessment of the epidemic and intensity status to help in routine respiratory infections surveillance in health systems. Allows the comparison of different epidemic indicators, timing and shape with past epidemics and across different regions or countries with different surveillance systems. Also, it gives a measure of the performance of the method in terms of sensitivity and specificity of the alert week.
Author: Jose E. Lozano [aut, cre]
Maintainer: Jose E. Lozano <lozalojo@gmail.com>

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Package DTRreg updated to version 1.7 with previous version 1.6 dated 2020-08-11

Title: DTR Estimation and Inference via G-Estimation, Dynamic WOLS, Q-Learning, and Dynamic Weighted Survival Modeling (DWSurv)
Description: Dynamic treatment regime estimation and inference via G-estimation, dynamic weighted ordinary least squares (dWOLS) and Q-learning. Inference via bootstrap and (for G-estimation) recursive sandwich estimation. Estimation and inference for survival outcomes via Dynamic Weighted Survival Modeling (DWSurv). Extension to continuous treatment variables (gdwols). Wallace et al. (2017) <DOI:10.18637/jss.v080.i02>; Simoneau et al. (2020) <DOI:10.1080/00949655.2020.1793341>.
Author: Michael Wallace, Erica E M Moodie, David A Stephens, Gabrielle Simoneau and Juliana Schulz
Maintainer: Michael Wallace <michael.wallace@uwaterloo.ca>

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Package sparsebn updated to version 0.1.2 with previous version 0.1.1 dated 2020-09-10

Title: Learning Sparse Bayesian Networks from High-Dimensional Data
Description: Fast methods for learning sparse Bayesian networks from high-dimensional data using sparse regularization, as described in Aragam, Gu, and Zhou (2017) <arXiv:1703.04025>. Designed to handle mixed experimental and observational data with thousands of variables with either continuous or discrete observations.
Author: Bryon Aragam [aut, cre], Jiaying Gu [aut], Dacheng Zhang [aut], Qing Zhou [aut]
Maintainer: Bryon Aragam <sparsebn@gmail.com>

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Package policytree updated to version 1.0.3 with previous version 1.0.2 dated 2020-09-09

Title: Policy Learning via Doubly Robust Empirical Welfare Maximization over Trees
Description: Learn optimal policies via doubly robust empirical welfare maximization over trees. This package implements the multi-action doubly robust approach of Zhou, Athey and Wager (2018) <arXiv:1810.04778> in the case where we want to learn policies that belong to the class of depth k decision trees.
Author: Zhengyuan Zhou [aut], Susan Athey [aut], Stefan Wager [aut], Ayush Kanodia [aut], Erik Sverdrup [cre]
Maintainer: Erik Sverdrup <erikcs@stanford.edu>

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Package CVXR updated to version 1.0-8 with previous version 1.0-1 dated 2020-04-02

Title: Disciplined Convex Optimization
Description: An object-oriented modeling language for disciplined convex programming (DCP) as described in Fu, Narasimhan, and Boyd (2020, <doi:10.18637/jss.v094.i14>). It allows the user to formulate convex optimization problems in a natural way following mathematical convention and DCP rules. The system analyzes the problem, verifies its convexity, converts it into a canonical form, and hands it off to an appropriate solver to obtain the solution. Interfaces to solvers on CRAN and elsewhere are provided, both commercial and open source.
Author: Anqi Fu [aut, cre], Balasubramanian Narasimhan [aut], David W Kang [aut], Steven Diamond [aut], John Miller [aut], Stephen Boyd [ctb], Paul Kunsberg Rosenfield [ctb]
Maintainer: Anqi Fu <anqif@stanford.edu>

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New package autoFRK with initial version 1.3.3
Package: autoFRK
Type: Package
Title: Automatic Fixed Rank Kriging
Description: Automatic fixed rank kriging for (irregularly located) spatial data using a class of basis functions with multi-resolution features and ordered in terms of their resolutions. The model parameters are estimated by maximum likelihood (ML) and the number of basis functions is determined by Akaike's information criterion (AIC). For spatial data with either one realization or independent replicates, the ML estimates and AIC are efficiently computed using their closed-form expressions when no missing value occurs. Details regarding the basis function construction, parameter estimation, and AIC calculation can be found in Tzeng and Huang (2018) <doi:10.1080/00401706.2017.1345701>. For data with missing values, the ML estimates are obtained using the expectation- maximization algorithm. Apart from the number of basis functions, there are no other tuning parameters, making the method fully automatic. Users can also include a stationary structure in the spatial covariance, which utilizes 'LatticeKrig' package.
License: GPL (>= 2)
Version: 1.3.3
Date: 2020-09-09
Depends: R (>= 3.1), spam
Imports: fields (>= 6.9.1), filehashSQLite, filehash, MASS, mgcv, LatticeKrig (>= 5.4), FNN, filematrix, Rcpp, methods
LinkingTo: Rcpp, RSpectra, RcppEigen, RcppParallel
Author: ShengLi Tzeng [aut, cre], Hsin-Cheng Huang [aut], Wen-Ting Wang [ctb], Douglas Nychka [ctb], Colin Gillespie [ctb]
Maintainer: ShengLi Tzeng <slt.cmu@gmail.com>
NeedsCompilation: yes
Date/Publication: 2020-09-13 15:20:07 UTC
Packaged: 2020-09-10 00:59:58 UTC; h0h1
Repository: CRAN

More information about autoFRK at CRAN
Permanent link

New package TSA with initial version 1.3
Package: TSA
Type: Package
Title: Time Series Analysis
Version: 1.3
Date: 2020-9-11
Author: Kung-Sik Chan, Brian Ripley
Maintainer: Kung-Sik Chan <kungsik.chan@gmail.com>
Depends: R (>= 2.5.1)
Imports: leaps, locfit, mgcv, tseries
Description: Contains R functions and datasets detailed in the book "Time Series Analysis with Applications in R (second edition)" by Jonathan Cryer and Kung-Sik Chan.
License: GPL (>= 2)
URL: https://stat.uiowa.edu/~kchan/TSA.htm
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2020-09-11 18:23:18 UTC; kchan
Repository: CRAN
Date/Publication: 2020-09-13 15:00:11 UTC

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Package sf updated to version 0.9-6 with previous version 0.9-5 dated 2020-07-14

Title: Simple Features for R
Description: Support for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations. Optionally uses the 's2' package for spherical geometry operations on geographic coordinates.
Author: Edzer Pebesma [aut, cre] (<https://orcid.org/0000-0001-8049-7069>), Roger Bivand [ctb] (<https://orcid.org/0000-0003-2392-6140>), Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] (<https://orcid.org/0000-0002-4035-0289>), Kirill Müller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [ctb]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package rhoR updated to version 1.3.0.3 with previous version 1.3.0.2 dated 2019-12-06

Title: Rho for Inter Rater Reliability
Description: Rho is used to test the generalization of inter rater reliability (IRR) statistics. Calculating rho starts by generating a large number of simulated, fully-coded data sets: a sizable collection of hypothetical populations, all of which have a kappa value below a given threshold -- which indicates unacceptable agreement. Then kappa is calculated on a sample from each of those sets in the collection to see if it is equal to or higher than the kappa in then real sample. If less than five percent of the distribution of samples from the simulated data sets is greater than actual observed kappa, the null hypothesis is rejected and one can conclude that if the two raters had coded the rest of the data, we would have acceptable agreement (kappa above the threshold).
Author: Brendan Eagan [aut], Brad Rogers [aut], Rebecca Pozen [aut], Cody L Marquart [cre, aut] (<https://orcid.org/0000-0002-3387-6792>), David Williamson Shaffer [aut]
Maintainer: Cody L Marquart <cody.marquart@wisc.edu>

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Package mosaicData updated to version 0.20.1 with previous version 0.18.0 dated 2020-05-15

Title: Project MOSAIC Data Sets
Description: Data sets from Project MOSAIC (<http://mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.
Author: Randall Pruim <rpruim@calvin.edu>, Daniel Kaplan <kaplan@macalester.edu>, Nicholas Horton <nhorton@amherst.edu>
Maintainer: Randall Pruim <rpruim@calvin.edu>

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Package mosaicCore updated to version 0.8.0 with previous version 0.6.0 dated 2018-06-24

Title: Common Utilities for Other MOSAIC-Family Packages
Description: Common utilities used in other MOSAIC-family packages are collected here.
Author: Randall Pruim <rpruim@calvin.edu>, Daniel T. Kaplan <kaplan@macalester.edu>, Nicholas J. Horton <nhorton@amherst.edu>
Maintainer: Randall Pruim <rpruim@calvin.edu>

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Package shape updated to version 1.4.5 with previous version 1.4.4 dated 2018-02-07

Title: Functions for Plotting Graphical Shapes, Colors
Description: Functions for plotting graphical shapes such as ellipses, circles, cylinders, arrows, ...
Author: Karline Soetaert <karline.soetaert@nioz.nl>
Maintainer: Karline Soetaert <karline.soetaert@nioz.nl>

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Package mlr3 updated to version 0.6.0 with previous version 0.5.0 dated 2020-08-07

Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>), Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [aut]
Maintainer: Michel Lang <michellang@gmail.com>

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Package ggeffects updated to version 0.16.0 with previous version 0.15.1 dated 2020-07-27

Title: Create Tidy Data Frames of Marginal Effects for 'ggplot' from Model Outputs
Description: Compute marginal effects from statistical models and returns the result as tidy data frames. These data frames are ready to use with the 'ggplot2'-package. Marginal effects can be calculated for many different models. Interaction terms, splines and polynomial terms are also supported. The main functions are ggpredict(), ggemmeans() and ggeffect(). There is a generic plot()-method to plot the results using 'ggplot2'.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Sam Crawley [ctb] (<https://orcid.org/0000-0002-7847-0411>), Mattan S. Ben-Shachar [ctb] (<https://orcid.org/0000-0002-4287-4801>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package deldir updated to version 0.1-29 with previous version 0.1-28 dated 2020-07-15

Title: Delaunay Triangulation and Dirichlet (Voronoi) Tessellation
Description: Calculates the Delaunay triangulation and the Dirichlet or Voronoi tessellation (with respect to the entire plane) of a planar point set. Plots triangulations and tessellations in various ways. Clips tessellations to sub-windows. Calculates perimeters of tessellations. Summarises information about the tiles of the tessellation.
Author: Rolf Turner
Maintainer: Rolf Turner <r.turner@auckland.ac.nz>

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Package cna updated to version 3.0.0 with previous version 2.2.3 dated 2020-05-13

Title: Causal Modeling with Coincidence Analysis
Description: Provides comprehensive functionalities for causal modeling with Coincidence Analysis (CNA), which is a configurational comparative method of causal data analysis that was first introduced in Baumgartner (2009) <doi:10.1177/0049124109339369>, and generalized in Baumgartner & Ambuehl (2018) <doi:10.1017/psrm.2018.45>. CNA is designed to recover INUS-causation from data, which is particularly relevant for analyzing processes featuring conjunctural causation (component causation) and equifinality (alternative causation). CNA is currently the only method for INUS-discovery that allows for multiple effects (outcomes/endogenous factors), meaning it can analyze common-cause and causal chain structures.
Author: Mathias Ambuehl [aut, cre, cph], Michael Baumgartner [aut, cph], Ruedi Epple [ctb], Veli-Pekka Parkkinen [ctb], Alrik Thiem [ctb]
Maintainer: Mathias Ambuehl <mathias.ambuehl@consultag.ch>

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Package bivariate updated to version 0.6.0 with previous version 0.5.0 dated 2020-02-26

Title: Bivariate Probability Distributions
Description: Convenience functions for plotting/evaluating bivariate (uniform, binomial, Poisson, categorical, normal and bimodal) distributions, trivariate (normal and Dirichlet) distributions, bivariate kernel density estimates and bivariate empirical cumulative distribution functions. Supports their probability mass functions (PMFs), probability density functions (PDFs) and cumulative distribution functions (CDFs), generally where applicable.
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>

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Package arrangements updated to version 1.1.9 with previous version 1.1.8 dated 2020-01-08

Title: Fast Generators and Iterators for Permutations, Combinations, Integer Partitions and Compositions
Description: Fast generators and iterators for permutations, combinations, integer partitions and compositions. The arrangements are in lexicographical order and generated iteratively in a memory efficient manner. It has been demonstrated that 'arrangements' outperforms most existing packages of similar kind. Benchmarks could be found at <https://randy3k.github.io/arrangements/articles/benchmark.html>.
Author: Randy Lai [aut, cre]
Maintainer: Randy Lai <randy.cs.lai@gmail.com>

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Package MRTSampleSize updated to version 0.3.0 with previous version 0.2.0 dated 2020-05-20

Title: A Sample Size Calculator for Micro-Randomized Trials
Description: Provide a sample size calculator for micro-randomized trials (MRTs) based on methodology developed in Sample Size Calculations for Micro-randomized Trials in mHealth by Liao et al. (2016) <DOI:10.1002/sim.6847>.
Author: Peng Liao [aut, cre], Liying Huang [aut], Nicholas J. Seewald [aut], Ji Sun [aut]
Maintainer: Peng Liao <pengliao@umich.edu>

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Package lcc updated to version 1.1.1 with previous version 1.1.0 dated 2020-05-22

Title: Longitudinal Concordance Correlation
Description: Estimates the longitudinal concordance correlation to access the longitudinal agreement profile. The estimation approach implemented is variance components approach based on polynomial mixed effects regression model, as proposed by Oliveira, Hinde and Zocchi (2018) <doi:10.1007/s13253-018-0321-1>. In addition, non-parametric confidence intervals were implemented using percentile method or normal-approximation based on Fisher Z-transformation.
Author: Thiago de Paula Oliveira [aut, cre], Rafael de Andrade Moral [aut], Silvio Sandoval Zocchi [ctb], Clarice Garcia Borges Demetrio [ctb], John Hinde [aut]
Maintainer: Thiago de Paula Oliveira <thiago.paula.oliveira@alumni.usp.br>

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Package waiter updated to version 0.1.3 with previous version 0.1.2 dated 2020-07-12

Title: Loading Screen for 'Shiny'
Description: Full screen and partial loading screens for 'Shiny' with spinners, progress bars, and notifications.
Author: John Coene [aut, cre], Jinhwan Kim [ctb]
Maintainer: John Coene <jcoenep@gmail.com>

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Package shinybrms updated to version 1.4.0 with previous version 1.3.0 dated 2020-08-06

Title: Graphical User Interface ('Shiny' App) for Package 'brms'
Description: A graphical user interface (GUI) for fitting Bayesian regression models using the package 'brms' which in turn relies on 'Stan' (<https://mc-stan.org/>). The 'shinybrms' GUI is a 'Shiny' (<https://shiny.rstudio.com/>) app.
Author: Frank Weber [aut, cre] (<https://orcid.org/0000-0002-4842-7922>)
Maintainer: Frank Weber <fweber144@protonmail.com>

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Package see updated to version 0.6.0 with previous version 0.5.2 dated 2020-07-27

Title: Visualisation Toolbox for 'easystats' and Extra Geoms, Themes and Color Palettes for 'ggplot2'
Description: Provides plotting utilities supporting easystats-packages (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://www.materialui.co/colors>.
Author: Daniel Lüdecke [aut, cre] (<https://orcid.org/0000-0002-8895-3206>), Dominique Makowski [aut, inv] (<https://orcid.org/0000-0001-5375-9967>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Brenton M. Wiernik [ctb] (<https://orcid.org/0000-0001-9560-6336>)
Maintainer: Daniel Lüdecke <d.luedecke@uke.de>

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Package SimInf updated to version 8.0.0 with previous version 7.0.1 dated 2020-06-18

Title: A Framework for Data-Driven Stochastic Disease Spread Simulations
Description: Provides an efficient and very flexible framework to conduct data-driven epidemiological modeling in realistic large scale disease spread simulations. The framework integrates infection dynamics in subpopulations as continuous-time Markov chains using the Gillespie stochastic simulation algorithm and incorporates available data such as births, deaths and movements as scheduled events at predefined time-points. Using C code for the numerical solvers and 'OpenMP' (if available) to divide work over multiple processors ensures high performance when simulating a sample outcome. One of our design goals was to make the package extendable and enable usage of the numerical solvers from other R extension packages in order to facilitate complex epidemiological research. The package contains template models and can be extended with user-defined models. For more details see the paper by Widgren, Bauer, Eriksson and Engblom (2019) <doi:10.18637/jss.v091.i12>.
Author: Stefan Widgren [aut, cre] (<https://orcid.org/0000-0001-5745-2284>), Robin Eriksson [aut] (<https://orcid.org/0000-0002-4291-712X>), Stefan Engblom [aut] (<https://orcid.org/0000-0002-3614-1732>), Pavol Bauer [aut] (<https://orcid.org/0000-0003-4328-7171>), Thomas Rosendal [ctb] (<https://orcid.org/0000-0002-6576-9668>), Attractive Chaos [cph] (Author of 'kvec.h'.)
Maintainer: Stefan Widgren <stefan.widgren@gmail.com>

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Package ggstatsplot updated to version 0.6.0 with previous version 0.5.0 dated 2020-05-30

Title: 'ggplot2' Based Plots with Statistical Details
Description: Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides easier API to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports only the most common types of statistical tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses.
Author: Indrajeet Patil [cre, aut, cph] (<https://orcid.org/0000-0003-1995-6531>)
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package torch (with last version 0.0.2) was removed from CRAN

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

2020-08-31 0.0.2

Permanent link
Package plotmo updated to version 3.6.0 with previous version 3.5.7 dated 2020-04-15

Title: Plot a Model's Residuals, Response, and Partial Dependence Plots
Description: Plot model surfaces for a wide variety of models using partial dependence plots and other techniques. Also plot model residuals and other information on the model.
Author: Stephen Milborrow
Maintainer: Stephen Milborrow <milbo@sonic.net>

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Package collapse updated to version 1.3.2 with previous version 1.3.1 dated 2020-08-27

Title: Advanced and Fast Data Transformation
Description: A C/C++ based package for advanced data transformation and statistical computing in R that is extremely fast, flexible and parsimonious to code with and programmer friendly. It is well integrated with 'dplyr', 'plm' and 'data.table'. --- Key Features: --- (1) Advanced statistical programming: A full set of fast statistical functions supporting grouped and weighted computations on vectors, matrices and data frames. Fast and programmable grouping, ordering, unique values / rows, factor generation and interactions. Fast and flexible functions for data manipulation and data object conversions. (2) Advanced aggregation: Fast and easy multi-data-type, multi-function, weighted, parallelized and fully customized data aggregation. (3) Advanced transformations: Fast (grouped) replacing and sweeping out of statistics, and (grouped, weighted) scaling / standardizing, between (averaging) and (quasi-)within (centering / demeaning) transformations, higher-dimensional centering (i.e. multiple fixed effects transformations), linear prediction and partialling-out. (4) Advanced time-computations: Fast (sequences of) lags / leads, and (lagged / leaded, iterated, quasi-, log-) differences and growth rates on (unordered) time series and panel data. Multivariate auto-, partial- and cross-correlation functions for panel data. Panel data to (ts-)array conversions. (5) List processing: (Recursive) list search / identification, extraction / subsetting, data-apply, and generalized row-binding / unlisting in 2D. (6) Advanced data exploration: Fast (grouped, weighted, panel-decomposed) summary statistics for complex multilevel / panel data.
Author: Sebastian Krantz [aut, cre], Matt Dowle [ctb], Arun Srinivasan [ctb], Simen Gaure [ctb], Dirk Eddelbuettel [ctb], R Core Team and contributors worldwide [ctb], Martyn Plummer [cph], 1999-2016 The R Core Team [cph]
Maintainer: Sebastian Krantz <sebastian.krantz@graduateinstitute.ch>

Diff between collapse versions 1.3.1 dated 2020-08-27 and 1.3.2 dated 2020-09-13

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Built and running on Debian GNU/Linux using R, littler and blosxom. Styled with Bootstrap.