Mon, 22 Nov 2021

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

Title: R Templates from the University of Miami
Description: This holds some r markdown templates and a template to create a research project in RStudio.
Author: Raymond Balise [aut, cre] (<https://orcid.org/0000-0002-9856-5901>), Gabriel Odom [aut] (<https://orcid.org/0000-0003-1341-4555>)
Maintainer: Raymond Balise <balise@miami.edu>

Diff between rUM versions 0.3.0 dated 2021-07-26 and 0.3.1 dated 2021-11-22

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Package libr updated to version 1.2.2 with previous version 1.2.1 dated 2021-10-09

Title: Libraries, Data Dictionaries, and a Data Step for R
Description: Contains a set of functions to create data libraries, generate data dictionaries, and simulate a data step. The libname() function will load a directory of data into a library in one line of code. The dictionary() function will generate data dictionaries for individual data frames or an entire library. And the datestep() function will perform row-by-row data processing.
Author: David J. Bosak
Maintainer: David Bosak <dbosak01@gmail.com>

Diff between libr versions 1.2.1 dated 2021-10-09 and 1.2.2 dated 2021-11-22

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Package fedmatch updated to version 2.0.5 with previous version 2.0.4 dated 2021-10-28

Title: Fast, Flexible, and User-Friendly Record Linkage Methods
Description: Provides a flexible set of tools for matching two un-linked data sets. 'fedmatch' allows for three ways to match data: exact matches, fuzzy matches, and multi-variable matches. It also allows an easy combination of these three matches via the tier matching function.
Author: Melanie Friedrichs [aut], Chris Webster [aut, cre], Blake Marsh [aut], Jacob Dice [aut], Seung Lee [aut]
Maintainer: Chris Webster <chris0webster@gmail.com>

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Package fdapace updated to version 0.5.8 with previous version 0.5.7 dated 2021-05-24

Title: Functional Data Analysis and Empirical Dynamics
Description: A versatile package that provides implementation of various methods of Functional Data Analysis (FDA) and Empirical Dynamics. The core of this package is Functional Principal Component Analysis (FPCA), a key technique for functional data analysis, for sparsely or densely sampled random trajectories and time courses, via the Principal Analysis by Conditional Estimation (PACE) algorithm. This core algorithm yields covariance and mean functions, eigenfunctions and principal component (scores), for both functional data and derivatives, for both dense (functional) and sparse (longitudinal) sampling designs. For sparse designs, it provides fitted continuous trajectories with confidence bands, even for subjects with very few longitudinal observations. PACE is a viable and flexible alternative to random effects modeling of longitudinal data. There is also a Matlab version (PACE) that contains some methods not available on fdapace and vice versa. Updates to fdapace were supported by grants from NIH Echo and NSF DMS-1712864 and DMS-2014626. Please cite our package if you use it (You may run the command citation("fdapace") to get the citation format and bibtex entry). References: Wang, J.L., Chiou, J., Müller, H.G. (2016) <doi:10.1146/annurev-statistics-041715-033624>; Chen, K., Zhang, X., Petersen, A., Müller, H.G. (2017) <doi:10.1007/s12561-015-9137-5>.
Author: Alvaro Gajardo [aut, cre], Satarupa Bhattacharjee [aut], Cody Carroll [aut] (<https://orcid.org/0000-0003-3525-8653>), Yaqing Chen [aut], Xiongtao Dai [aut], Jianing Fan [aut], Pantelis Z. Hadjipantelis [aut], Kyunghee Han [aut], Hao Ji [aut], Changbo Zhu [aut], Shu-Chin Lin [ctb], Paromita Dubey [ctb], Hans-Georg Müller [cph, ths, aut], Jane-Ling Wang [cph, ths, aut]
Maintainer: Alvaro Gajardo <aegajardo@ucdavis.edu>

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Package yardstick updated to version 0.0.9 with previous version 0.0.8 dated 2021-03-28

Title: Tidy Characterizations of Model Performance
Description: Tidy tools for quantifying how well model fits to a data set such as confusion matrices, class probability curve summaries, and regression metrics (e.g., RMSE).
Author: Max Kuhn [aut], Davis Vaughan [aut, cre], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>

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Package qgam updated to version 1.3.4 with previous version 1.3.3 dated 2021-04-27

Title: Smooth Additive Quantile Regression Models
Description: Smooth additive quantile regression models, fitted using the methods of Fasiolo et al. (2020) <doi:10.1080/01621459.2020.1725521>. See Fasiolo at al. (2021) <doi:10.18637/jss.v100.i09> for an introduction to the package. Differently from 'quantreg', the smoothing parameters are estimated automatically by marginal loss minimization, while the regression coefficients are estimated using either PIRLS or Newton algorithm. The learning rate is determined so that the Bayesian credible intervals of the estimated effects have approximately the correct coverage. The main function is qgam() which is similar to gam() in 'mgcv', but fits non-parametric quantile regression models.
Author: Matteo Fasiolo [aut, cre], Simon N. Wood [ctb], Margaux Zaffran [ctb], Yannig Goude [ctb], Raphael Nedellec [ctb]
Maintainer: Matteo Fasiolo <matteo.fasiolo@gmail.com>

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Package onlineBcp updated to version 0.1.3 with previous version 0.1.2 dated 2021-11-18

Title: Online Bayesian Methods for Change Point Analysis
Description: It implements the online Bayesian methods for change point analysis. It can also perform missing data imputation with methods from 'VIM'. The reference is Yigiter A, Chen J, An L, Danacioglu N (2015) <doi:10.1080/02664763.2014.1001330>.
Author: Hongyan Xu [cre, aut], Ayten Yigiter [aut], Jie Chen [aut]
Maintainer: Hongyan Xu <hxu@augusta.edu>

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Package dalmatian updated to version 1.0.0 with previous version 0.6.3 dated 2021-11-03

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. For further information see Bonner, Kim, Westneat, Mutzel, Wright, and Schofield <doi:10.18637/jss.v100.i10>.
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 crul updated to version 1.2.0 with previous version 1.1.0 dated 2021-02-15

Title: HTTP Client
Description: A simple HTTP client, with tools for making HTTP requests, and mocking HTTP requests. The package is built on R6, and takes inspiration from Ruby's 'faraday' gem (<https://rubygems.org/gems/faraday>). The package name is a play on curl, the widely used command line tool for HTTP, and this package is built on top of the R package 'curl', an interface to 'libcurl' (<https://curl.se/libcurl/>).
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between crul versions 1.1.0 dated 2021-02-15 and 1.2.0 dated 2021-11-22

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Package brms updated to version 2.16.3 with previous version 2.16.1 dated 2021-08-23

Title: Bayesian Regression Models using 'Stan'
Description: Fit Bayesian generalized (non-)linear multivariate multilevel models using 'Stan' for full Bayesian inference. A wide range of distributions and link functions are supported, allowing users to fit -- among others -- linear, robust linear, count data, survival, response times, ordinal, zero-inflated, hurdle, and even self-defined mixture models all in a multilevel context. Further modeling options include non-linear and smooth terms, auto-correlation structures, censored data, meta-analytic standard errors, and quite a few more. In addition, all parameters of the response distribution can be predicted in order to perform distributional regression. Prior specifications are flexible and explicitly encourage users to apply prior distributions that actually reflect their beliefs. Model fit can easily be assessed and compared with posterior predictive checks and leave-one-out cross-validation. References: Bürkner (2017) <doi:10.18637/jss.v080.i01>; Bürkner (2018) <doi:10.32614/RJ-2018-017>; Bürkner (2021) <doi:10.18637/jss.v100.i05>; Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Author: Paul-Christian Bürkner [aut, cre], Jonah Gabry [ctb], Sebastian Weber [ctb], Andrew Johnson [ctb], Martin Modrak [ctb], Hamada S. Badr [ctb], Frank Weber [ctb], Mattan S. Ben-Shachar [ctb]
Maintainer: Paul-Christian Bürkner <paul.buerkner@gmail.com>

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Package gmvarkit updated to version 2.0.0 with previous version 1.5.0 dated 2021-09-17

Title: Estimate Gaussian or Student's t Mixture Vector Autoregressive Model
Description: Unconstrained and constrained maximum likelihood estimation of structural and reduced form Gaussian mixture vector autoregressive, Student's t mixture vector autoregressive, and Gaussian and Student's t mixture vector autoregressive models, quantile residual tests, graphical diagnostics, simulations, forecasting, and estimation of generalized impulse response function and generalized forecast error variance decomposition. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2016) <doi:10.1016/j.jeconom.2016.02.012>, Savi Virolainen (2020) <arXiv:2007.04713>, Savi Virolainen (2021) <arXiv:2109.13648>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>

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Package sitree updated to version 0.1-12 with previous version 0.1-11 dated 2021-11-11

Title: Single Tree Simulator
Description: Framework to build an individual tree simulator.
Author: Clara Anton Fernandez [aut, cre]
Maintainer: Clara Anton Fernandez <caf@nibio.no>

Diff between sitree versions 0.1-11 dated 2021-11-11 and 0.1-12 dated 2021-11-22

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Package string2path updated to version 0.0.4 with previous version 0.0.3 dated 2021-09-26

Title: Rendering Font into 'data.frame'
Description: Extract glyph information from a font file, and translate the outline curves to flattened paths or tessellated polygons. The converted data is returned as a 'data.frame' in easy-to-plot format.
Author: Hiroaki Yutani [aut, cre] (<https://orcid.org/0000-0002-3385-7233>)
Maintainer: Hiroaki Yutani <yutani.ini@gmail.com>

Diff between string2path versions 0.0.3 dated 2021-09-26 and 0.0.4 dated 2021-11-22

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Package duckdb updated to version 0.3.1-1 with previous version 0.3.1 dated 2021-11-16

Title: DBI Package for the DuckDB Database Management System
Description: The DuckDB project is an embedded analytical data management system with support for the Structured Query Language (SQL). This package includes all of DuckDB and a R Database Interface (DBI) connector.
Author: Hannes Mühleisen [aut, cre] (<https://orcid.org/0000-0001-8552-0029>), Mark Raasveldt [aut] (<https://orcid.org/0000-0001-5005-6844>), DuckDB Contributors [aut], Apache Software Foundation [cph], PostgreSQL Global Development Group [cph], The Regents of the University of California [cph], Cameron Desrochers [cph], Victor Zverovich [cph], RAD Game Tools [cph], Valve Software [cph], Rich Geldreich [cph], Tenacious Software LLC [cph], The RE2 Authors [cph], Google Inc. [cph], Facebook Inc. [cph], Steven G. Johnson [cph], Jiahao Chen [cph], Tony Kelman [cph], Jonas Fonseca [cph], Lukas Fittl [cph], Salvatore Sanfilippo [cph], Art.sy, Inc. [cph], Oran Agra [cph], Redis Labs, Inc. [cph], Melissa O'Neill [cph], PCG Project contributors [cph]
Maintainer: Hannes Mühleisen <hannes@cwi.nl>

Diff between duckdb versions 0.3.1 dated 2021-11-16 and 0.3.1-1 dated 2021-11-22

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 R/Connection.R                                                                      |    2 
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 src/include/typesr.hpp                                                              |    4 
 src/scan.cpp                                                                        |    8 -
 src/statement.cpp                                                                   |    9 +
 src/types.cpp                                                                       |    4 
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 tests/testthat/test_factor.R                                                        |   15 +-
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Package cpsR updated to version 0.4.5 with previous version 0.4.4 dated 2021-10-27

Title: Load CPS Microdata into R Using the 'Census Bureau Data' API
Description: Load Current Population Survey (CPS) microdata into R using the 'Census Bureau Data' API (<https://www.census.gov/data/developers/data-sets.html>), including basic monthly CPS and CPS ASEC microdata.
Author: Matt Saenz [aut, cre]
Maintainer: Matt Saenz <mattsaenz165@gmail.com>

Diff between cpsR versions 0.4.4 dated 2021-10-27 and 0.4.5 dated 2021-11-22

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Package sweater updated to version 0.1.1 with previous version 0.1.0 dated 2021-11-19

Title: Speedy Word Embedding Association Test and Extras Using R
Description: Conduct various tests for evaluating implicit biases in word embeddings: Word Embedding Association Test (Caliskan et al., 2017), <doi:10.1126/science.aal4230>, Relative Norm Distance (Garg et al., 2018), <doi:10.1073/pnas.1720347115>, Mean Average Cosine Similarity (Mazini et al., 2019) <arXiv:1904.04047>, SemAxis (An et al., 2018) <arXiv:1806.05521>, and Relative Negative Sentiment Bias (Sweeney & Najafian, 2019) <doi:10.18653/v1/P19-1162>.
Author: Chung-hong Chan [aut, cre] (<https://orcid.org/0000-0002-6232-7530>)
Maintainer: Chung-hong Chan <chainsawtiney@gmail.com>

Diff between sweater versions 0.1.0 dated 2021-11-19 and 0.1.1 dated 2021-11-22

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Package ltable updated to version 2.0.1 with previous version 1.0 dated 2018-08-13

Title: Easy to Make (Lazy) Tables
Description: Constructs tables of counts and proportions out of data sets. It has simplified syntax appealing for novice and even for advanced user under time pressure. It is particularly suitable for exploratory data analysis or presentation to single out most appropriate pieces of tabulated information. The other important feature is possibility to insert tables to Excel and Word documents. This version also features capacity of log-linear and power analyses (original by Oleksandr Ocheredko <doi:10.35566/isdsa2019c5>) for tabulated data with GSL.
Author: Ocheredko Oleksandr
Maintainer: Ocheredko Oleksandr <Ocheredko@yahoo.com>

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Package wnl updated to version 0.6.4 with previous version 0.6.3 dated 2021-09-06

Title: Minimization Tool for Pharmacokinetic-Pharmacodynamic Data Analysis
Description: This is a set of minimization tools (maximum likelihood estimation and least square fitting) to solve examples in the Johan Gabrielsson and Dan Weiner's book "Pharmacokinetic and Pharmacodynamic Data Analysis - Concepts and Applications" 5th ed. (ISBN:9198299107). Examples include linear and nonlinear compartmental model, turn-over model, single or multiple dosing bolus/infusion/oral models, allometry, toxicokinetics, reversible metabolism, in-vitro/in-vivo extrapolation, enterohepatic circulation, metabolite modeling, Emax model, inhibitory model, tolerance model, oscillating response model, enantiomer interaction model, effect compartment model, drug-drug interaction model, receptor occupancy model, and rebound phenomena model.
Author: Kyun-Seop Bae [aut]
Maintainer: Kyun-Seop Bae <k@acr.kr>

Diff between wnl versions 0.6.3 dated 2021-09-06 and 0.6.4 dated 2021-11-22

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New package tetragon with initial version 1.0.0
Package: tetragon
Title: Automatic Sequence Prediction by Expansion of the Distance Matrix
Version: 1.0.0
Author: Giancarlo Vercellino
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>
Description: Each sequence is predicted by expanding the distance matrix. The compact set of hyper-parameters is tuned via grid or random search.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.6)
Imports: purrr (>= 0.3.4), abind (>= 1.4-5), ggplot2 (>= 3.3.5), readr (>= 2.0.1), stringr (>= 1.4.0), lubridate (>= 1.7.10), narray (>= 0.4.1.1), imputeTS (>= 3.2), scales (>= 1.1.1), tictoc (>= 1.0.1), modeest (>= 2.4.0), moments (>= 0.14), greybox (>= 1.0.1), philentropy (>= 0.5.0)
URL: https://rpubs.com/giancarlo_vercellino/tetragon
NeedsCompilation: no
Packaged: 2021-11-22 07:37:37 UTC; gvercellino
Repository: CRAN
Date/Publication: 2021-11-22 09:50:05 UTC

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New package stan4bart with initial version 0.0-1
Package: stan4bart
Version: 0.0-1
Date: 2021-11-20
Title: Bayesian Additive Regression Trees with Stan-Sampled Parametric Extensions
Depends: R (>= 3.5-0), methods, dbarts (>= 0.9-20)
Imports: stats, Matrix, parallel, RcppParallel (>= 5.1.1)
LinkingTo: BH (>= 1.72.0.3), Rcpp (>= 1.0.5), RcppEigen (>= 0.3.3.7.0), RcppParallel (>= 5.1.1), dbarts (>= 0.9-20)
Suggests: testthat (>= 2.0-0), lme4
Description: Fits semiparametric linear and multilevel models with non-parametric additive Bayesian additive regression tree (BART; Chipman, George, and McCulloch (2010) <doi:10.1214/09-AOAS285>) components and Stan (Stan Development Team (2021) <https://mc-stan.org/>) sampled parametric ones. Multilevel models can be expressed using 'lme4' syntax (Bates, Maechler, Bolker, and Walker (2015) <doi:10.18637/jss.v067.i01>).
License: GPL (>= 3)
NeedsCompilation: yes
Biarch: true
UseLTO: true
URL: https://github.com/vdorie/stan4bart
BugReports: https://github.com/vdorie/stan4bart/issues
Packaged: 2021-11-21 21:56:32 UTC; vdorie
Author: Vincent Dorie [aut, cre] (<https://orcid.org/0000-0002-9576-3064>), Ben Goodrich [ctb] (rstanarm_functions.R, StanHeaders), Jonah Gabry [ctb] (rstanarm_functions.R, StanHeaders), Imad Ali [ctb] (rstanarm_functions.R), Sam Brilleman [ctb] (rstanarm_functions.R), Paul-Christian Burkner [ctb] (rstanarm_functions.R, <https://orcid.org/0000-0001-5765-8995>), Joshua Pritikin [ctb] (StanHeaders, <https://orcid.org/0000-0002-9862-5484>), Andrew Gelman [ctb] (StanHeaders, <https://orcid.org/0000-0002-6975-2601>), Bob Carpenter [ctb] (StanHeaders), Matt Hoffman [ctb] (StanHeaders), Daniel Lee [ctb] (StanHeaders), Michael Betancourt [ctb] (StanHeaders, <https://orcid.org/0000-0002-2900-0931>), Marcus Brubaker [ctb] (StanHeaders, <https://orcid.org/0000-0002-7892-9026>), Jiqiang Guo [ctb] (StanHeaders), Peter Li [ctb] (StanHeaders), Allen Riddell [ctb] (StanHeaders), Marco Inacio [ctb] (StanHeaders, <https://orcid.org/0000-0002-6865-5404>), Mitzi Morris [ctb] (StanHeaders), Jeffrey Arnold [ctb] (StanHeaders, <https://orcid.org/0000-0001-9953-3904>), Rob Goedman [ctb] (StanHeaders), Brian Lau [ctb] (StanHeaders), Rob Trangucci [ctb] (StanHeaders), Alp Kucukelbir [ctb] (StanHeaders), Robert Grant [ctb] (StanHeaders), Dustin Tran [ctb] (StanHeaders), Michael Malecki [ctb] (StanHeaders), Yuanjun Gao [ctb] (StanHeaders), Trustees of Columbia University [cph] (rstanarm_functions.R, StanHeaders), Lawrence Livermore National Security [cph] (CVODES), The Regents of the University of California [cph] (CVODES), Southern Methodist University [cph] (CVODES), Douglas Bates [ctb] (lme4_functions.R, <https://orcid.org/0000-0001-8316-9503>), Martin Maechler [ctb] (lme4_functions.R, <https://orcid.org/0000-0002-8685-9910>), Ben Bolker [ctb] (lme4_functions.R, <https://orcid.org/0000-0002-2127-0443>), Steve Walker [ctb] (lme4_functions.R, <https://orcid.org/0000-0002-4394-9078>), Armon Dadgar [ctb] (adaptive radix tree), Bothner Per [ctb] (config.guess), Elliston Ben [ctb] (config.guess), Free Software Foundation [cph] (config.sub), Guido U Draheim [ctb] (ax_check_compile_flag.m4), Maarten Bosmans [ctb] (ax_check_compile_flag.m4), Christophe Tournayre [ctb] (ax_ext.m4), Michael Petch [ctb] (ax_ext.m4, ax_gcc_x86_avx_xgetbv.m4, ax_gcc_x86_cpuid.m4), Rafael de Lucena Valle [ctb] (ax_ext.m4), Steven G. Johnson [ctb] (ax_gcc_x86_cpuid.m4, <https://orcid.org/0000-0001-7327-4967>), Matteo Frigo [ctb] (ax_gcc_x86_cpuid.m4), Scott Pakin [ctb] (ax_func_posix_memalign.m4, <https://orcid.org/0000-0002-5220-1985>)
Maintainer: Vincent Dorie <vdorie@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-22 09:50:07 UTC

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New package schtools with initial version 0.1.0
Package: schtools
Title: Schloss Lab Tools for Reproducible Microbiome Research
Version: 0.1.0
Description: A collection of useful functions and example code created and used by the Schloss Lab for reproducible microbiome research. Perform common tasks like read files created by mothur <https://mothur.org/>, tidy up your microbiome data, and format R Markdown documents for publication. See the website <http://www.schlosslab.org/schtools/> for more information, documentation, and examples.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, formatR, rlang, tidyr
Suggests: covr, knitr, purrr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-20 02:25:10 UTC; kelly
Author: Kelly Sovacool [aut, cre] (<https://orcid.org/0000-0003-3283-829X>), Nick Lesniak [aut] (<https://orcid.org/0000-0001-9359-5194>), Patrick Schloss [aut], Sarah Lucas [ctb] (<https://orcid.org/0000-0003-1676-5801>), Courtney Armour [ctb] (<https://orcid.org/0000-0002-5250-1224>), Jacqueline Moltzau [ctb] (<https://orcid.org/0000-0003-1398-5980>), Andrew Hannah [ctb], Nielson Baxter [ctb], Alyxandria Schubert [ctb], Kathryn Iverson [ctb]
Maintainer: Kelly Sovacool <sovacool@umich.edu>
Repository: CRAN
Date/Publication: 2021-11-22 09:30:02 UTC

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Package pmsampsize updated to version 1.1.1 with previous version 1.1.0 dated 2021-06-25

Title: Calculates the Minimum Sample Size Required for Developing a Multivariable Prediction Model
Description: Computes the minimum sample size required for the development of a new multivariable prediction model using the criteria proposed by Riley et al. (2018) <doi: 10.1002/sim.7992>. pmsampsize can be used to calculate the minimum sample size for the development of models with continuous, binary or survival (time-to-event) outcomes. Riley et al. (2018) <doi: 10.1002/sim.7992> lay out a series of criteria the sample size should meet. These aim to minimise the overfitting and to ensure precise estimation of key parameters in the prediction model.
Author: Joie Ensor [aut, cre], Emma C. Martin [aut], Richard D. Riley [aut]
Maintainer: Joie Ensor <j.ensor@keele.ac.uk>

Diff between pmsampsize versions 1.1.0 dated 2021-06-25 and 1.1.1 dated 2021-11-22

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 7 files changed, 86 insertions(+), 75 deletions(-)

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New package phylosamp with initial version 0.1.6
Package: phylosamp
Title: The Probability of Transmission Given Phylogenetic Linkage
Version: 0.1.6
Date: 2021-11-20
Maintainer: Justin Lessler <jlessler@unc.edu>
Description: Implements novel tools that estimate the probability of true transmission between two cases given phylogenetic linkage and the expected number of true transmission links in a sample. Methods described in Wohl, Giles, and Lessler (2021) <doi:10.1371/journal.pcbi.1009182>.
License: GPL-2
URL: https://github.com/HopkinsIDD/phylosamp
BugReports: https://github.com/HopkinsIDD/phylosamp/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10), stats
Imports: reshape2, ggplot2, cowplot, RColorBrewer
Suggests: knitr, rmarkdown, testthat
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-20 22:11:17 UTC; johngiles
Author: John R Giles [aut, ctb], Shirlee Wohl [aut, ctb], Justin Lessler [aut, cre]
Repository: CRAN
Date/Publication: 2021-11-22 09:40:02 UTC

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New package MorphoTools2 with initial version 0.9.0
Package: MorphoTools2
Title: Multivariate Morphometric Analysis
Version: 0.9.0
Date: 2021-11-05
Author: Marek Slenker [aut, cre] (https://orcid.org/0000-0002-5919-890X) Petr Koutecky [ctb] (https://orcid.org/0000-0002-3455-850X) Karol Marhold [ctb] (https://orcid.org/0000-0002-7658-0844)
Maintainer: Marek Slenker <marek.slenker@savba.sk>
Description: Tools for multivariate analyses of morphological data, wrapped in one package, to make the workflow convenient and fast. Statistical and graphical tools provide a comprehensive framework for checking and manipulating input data, statistical analyses, and visualization of results. Several methods are provided for the analysis of raw data, to make the dataset ready for downstream analyses. Integrated statistical methods include hierarchical classification, principal component analysis, principal coordinates analysis, non-metric multidimensional scaling, and multiple discriminant analyses: canonical, stepwise, and classificatory (linear, quadratic, and the non-parametric k nearest neighbours). The philosophy of the package will be described in Šlenker et al. (in prep).
URL: https://github.com/MarekSlenker/MorphoTools2
BugReports: https://github.com/MarekSlenker/MorphoTools2/issues
Depends: R (>= 2.10)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: ade4, candisc, car, class, ellipse, fpc, heplots, MASS, methods, plot3D, StatMatch, utils, vegan, stats
Suggests: testthat, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-21 20:18:07 UTC; HP
Repository: CRAN
Date/Publication: 2021-11-22 09:40:06 UTC

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New package innsight with initial version 0.1.0
Package: innsight
Title: Get the Insights of your Neural Network
Version: 0.1.0
Description: Interpretability methods to analyze the behavior and individual predictions of modern neural networks. Implemented methods are: 'Connection Weights' described by Olden et al. (2004) <doi:10.1016/j.ecolmodel.2004.03.013>, Layer-wise Relevance Propagation ('LRP') described by Bach et al. (2015) <doi:10.1371/journal.pone.0130140>, Deep Learning Important Features ('DeepLIFT') described by Shrikumar et al. (2017) <arXiv:1704.02685> and gradient-based methods like 'SmoothGrad' described by Smilkov et al. (2017) <arXiv:1706.03825>, 'Gradient x Input' described by Baehrens et al. (2009) <arXiv:0912.1128> or 'Vanilla Gradient'.
License: MIT + file LICENSE
URL: https://bips-hb.github.io/innsight/, https://github.com/bips-hb/innsight/
BugReports: https://github.com/bips-hb/innsight/issues/
Depends: R (>= 3.5.0)
Imports: checkmate, ggplot2, R6, torch
Suggests: keras, knitr, neuralnet, plotly, rmarkdown, tensorflow, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-11-22 07:25:28 UTC; niklas
Author: Niklas Koenen [aut, cre] (<https://orcid.org/0000-0002-4623-8271>), Raphael Baudeu [ctb]
Maintainer: Niklas Koenen <niklas.koenen@gmail.com>
Repository: CRAN
Date/Publication: 2021-11-22 09:50:14 UTC

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Package Bestie updated to version 0.1.3 with previous version 0.1.2 dated 2021-02-26

Title: Bayesian Estimation of Intervention Effects
Description: An implementation of intervention effect estimation for DAGs (directed acyclic graphs) learned from binary or continuous data. First, parameters are estimated or sampled for the DAG and then interventions on each node (variable) are propagated through the network (do-calculus). Both exact computation (for continuous data or for binary data up to around 20 variables) and Monte Carlo schemes (for larger binary networks) are implemented.
Author: Jack Kuipers [aut,cre] and Giusi Moffa [aut]
Maintainer: Jack Kuipers <jack.kuipers@bsse.ethz.ch>

Diff between Bestie versions 0.1.2 dated 2021-02-26 and 0.1.3 dated 2021-11-22

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 8 files changed, 226 insertions(+), 86 deletions(-)

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Package radiant updated to version 1.4.1 with previous version 1.4.0 dated 2021-06-08

Title: Business Analytics using R and Shiny
Description: A platform-independent browser-based interface for business analytics in R, based on the shiny package. The application combines the functionality of 'radiant.data', 'radiant.design', 'radiant.basics', 'radiant.model', and 'radiant.multivariate'.
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

Diff between radiant versions 1.4.0 dated 2021-06-08 and 1.4.1 dated 2021-11-22

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 6 files changed, 33 insertions(+), 30 deletions(-)

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New package PEkit with initial version 1.0.0.1000
Package: PEkit
Title: Partition Exchangeability Toolkit
Version: 1.0.0.1000
Description: Bayesian supervised predictive classifiers, hypothesis testing, and parametric estimation under Partition Exchangeability are implemented. The two classifiers presented are the marginal classifier (that assumes test data is i.i.d.) next to a more computationally costly but accurate simultaneous classifier (that finds a labelling for the entire test dataset at once based on simultanous use of all the test data to predict each label). We also provide the Maximum Likelihood Estimation (MLE) of the only underlying parameter of the partition exchangeability generative model as well as hypothesis testing statistics for equality of this parameter with a single value, alternative, or multiple samples. We present functions to simulate the sequences from Ewens Sampling Formula as the realisation of the Poisson-Dirichlet distribution and their respective probabilities.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
Imports: stats (>= 4.1.0)
NeedsCompilation: no
Packaged: 2021-11-19 13:16:51 UTC; villekin
Author: Ville Kinnula [aut], Jing Tang [ctb] (<https://orcid.org/0000-0001-7480-7710>), Ali Amiryousefi [aut, cre] (<https://orcid.org/0000-0002-6317-3860>)
Maintainer: Ali Amiryousefi <ali.amiryousefi@helsinki.fi>
Repository: CRAN
Date/Publication: 2021-11-22 08:50:02 UTC

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Package openair updated to version 2.8-6 with previous version 2.8-5 dated 2021-10-22

Title: Tools for the Analysis of Air Pollution Data
Description: Tools to analyse, interpret and understand air pollution data. Data are typically hourly time series and both monitoring data and dispersion model output can be analysed. Many functions can also be applied to other data, including meteorological and traffic data.
Author: David Carslaw [aut, cre], Karl Ropkins [aut]
Maintainer: David Carslaw <david.carslaw@york.ac.uk>

Diff between openair versions 2.8-5 dated 2021-10-22 and 2.8-6 dated 2021-11-22

 DESCRIPTION       |    8 ++--
 MD5               |   14 ++++----
 R/calendarPlot.R  |    4 ++
 R/cutData.R       |    2 -
 R/importAURN.R    |   92 ++++++++++++++++++++++++++++++++++++++++++++++++++++--
 R/importUKAQ.R    |   36 +++++++++++++++++----
 R/zzz.R           |    3 +
 man/importAURN.Rd |   14 +++++++-
 8 files changed, 149 insertions(+), 24 deletions(-)

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New package groupTesting with initial version 1.0.0
Package: groupTesting
Title: Simulating and Modeling Group (Pooled) Testing Data
Version: 1.0.0
Date: 2021-11-19
Author: Md S. Warasi
Maintainer: Md S. Warasi <msarker@radford.edu>
Description: Provides an expectation-maximization (EM) algorithm using the approach introduced in Xie (2001) <doi:10.1002/sim.817>. The EM algorithm can be used to estimate the prevalence (overall proportion) of a disease and to estimate a binary regression model from among the class of generalized linear models based on group testing data. The estimation framework we consider offers a flexible and general approach; i.e., its application is not limited to any specific group testing protocol. Consequently, the EM algorithm can model data arising from simple pooling as well as advanced pooling such as hierarchical testing, array testing, and quality control pooling. Also, provided are functions that can be used to conduct the Wald tests described in Buse (1982) <doi:10.1080/00031305.1982.10482817> and to simulate the group testing data described in Kim et al. (2007) <doi:10.1111/j.1541-0420.2007.00817.x>.
License: GPL-3
Depends: R(>= 3.5.0)
Imports: pracma
NeedsCompilation: yes
Encoding: UTF-8
Packaged: 2021-11-19 18:49:25 UTC; msarker
Repository: CRAN
Date/Publication: 2021-11-22 09:00:02 UTC

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New package gggrid with initial version 0.1-1
Package: gggrid
Title: Draw with 'grid' in 'ggplot2'
Version: 0.1-1
Maintainer: Paul Murrell <paul@stat.auckland.ac.nz>
Description: An extension of 'ggplot2' that makes it easy to add raw 'grid' output, such as customised annotations, to a 'ggplot2' plot.
Depends: grid, ggplot2
Suggests: knitr, rmarkdown, vwline
URL: https://github.com/pmur002/gggrid,https://stattech.wordpress.fos.auckland.ac.nz/2021/05/31/2021-01-accessing-grid-from-ggplot2/
VignetteBuilder: knitr
License: GPL-3
NeedsCompilation: no
Packaged: 2021-11-21 23:41:04 UTC; pmur002
Author: Paul Murrell [aut, cre]
Repository: CRAN
Date/Publication: 2021-11-22 09:00:05 UTC

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Package dlookr updated to version 0.5.2 with previous version 0.5.1 dated 2021-09-02

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 0.5.1 dated 2021-09-02 and 0.5.2 dated 2021-11-22

 dlookr-0.5.1/dlookr/man/import_liberation.Rd                  |only
 dlookr-0.5.2/dlookr/DESCRIPTION                               |   19 
 dlookr-0.5.2/dlookr/MD5                                       |  212 ++--
 dlookr-0.5.2/dlookr/NAMESPACE                                 |    9 
 dlookr-0.5.2/dlookr/NEWS                                      |   90 ++
 dlookr-0.5.2/dlookr/R/EDA.R                                   |   28 
 dlookr-0.5.2/dlookr/R/aggregate.R                             |  207 +++-
 dlookr-0.5.2/dlookr/R/binning.R                               |  115 +-
 dlookr-0.5.2/dlookr/R/combination.R                           |    8 
 dlookr-0.5.2/dlookr/R/compare.R                               |   61 -
 dlookr-0.5.2/dlookr/R/correlate.R                             |   85 +
 dlookr-0.5.2/dlookr/R/diagnose.R                              |  161 ++-
 dlookr-0.5.2/dlookr/R/discribe.R                              |   18 
 dlookr-0.5.2/dlookr/R/dlookr.R                                |  123 --
 dlookr-0.5.2/dlookr/R/graphics.R                              |   65 -
 dlookr-0.5.2/dlookr/R/html_diagnose.R                         |   41 
 dlookr-0.5.2/dlookr/R/html_eda.R                              |  320 ++++---
 dlookr-0.5.2/dlookr/R/html_transformation.R                   |   83 +
 dlookr-0.5.2/dlookr/R/imputation.R                            |   50 -
 dlookr-0.5.2/dlookr/R/missing.R                               |   69 +
 dlookr-0.5.2/dlookr/R/normality.R                             |  144 +--
 dlookr-0.5.2/dlookr/R/overview.R                              |   24 
 dlookr-0.5.2/dlookr/R/report.R                                |   60 +
 dlookr-0.5.2/dlookr/R/stats.R                                 |   27 
 dlookr-0.5.2/dlookr/R/target_by.R                             |   38 
 dlookr-0.5.2/dlookr/R/tbl_dbi.R                               |  426 +++++-----
 dlookr-0.5.2/dlookr/R/transform.R                             |   52 -
 dlookr-0.5.2/dlookr/R/univariate.R                            |   64 +
 dlookr-0.5.2/dlookr/R/zzz.R                                   |only
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 dlookr-0.5.2/dlookr/inst/doc/diagonosis.html                  |   12 
 dlookr-0.5.2/dlookr/inst/doc/introduce.Rmd                    |    2 
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 dlookr-0.5.2/dlookr/inst/report/eda_paged_temp.Rmd            |   24 
 dlookr-0.5.2/dlookr/inst/report/eda_temp.Rmd                  |   21 
 dlookr-0.5.2/dlookr/inst/report/transformation_paged_temp.Rmd |    5 
 dlookr-0.5.2/dlookr/inst/report/transformation_temp.Rmd       |   17 
 dlookr-0.5.2/dlookr/man/binning.Rd                            |   38 
 dlookr-0.5.2/dlookr/man/binning_by.Rd                         |    4 
 dlookr-0.5.2/dlookr/man/correlate.data.frame.Rd               |   18 
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 dlookr-0.5.2/dlookr/man/describe.data.frame.Rd                |   18 
 dlookr-0.5.2/dlookr/man/describe.tbl_dbi.Rd                   |   10 
 dlookr-0.5.2/dlookr/man/diagnose.data.frame.Rd                |   18 
 dlookr-0.5.2/dlookr/man/diagnose.tbl_dbi.Rd                   |   24 
 dlookr-0.5.2/dlookr/man/diagnose_category.data.frame.Rd       |    4 
 dlookr-0.5.2/dlookr/man/diagnose_category.tbl_dbi.Rd          |   52 -
 dlookr-0.5.2/dlookr/man/diagnose_numeric.data.frame.Rd        |   12 
 dlookr-0.5.2/dlookr/man/diagnose_numeric.tbl_dbi.Rd           |   26 
 dlookr-0.5.2/dlookr/man/diagnose_outlier.data.frame.Rd        |   22 
 dlookr-0.5.2/dlookr/man/diagnose_outlier.tbl_dbi.Rd           |   26 
 dlookr-0.5.2/dlookr/man/diagnose_paged_report.data.frame.Rd   |    8 
 dlookr-0.5.2/dlookr/man/diagnose_report.data.frame.Rd         |    6 
 dlookr-0.5.2/dlookr/man/diagnose_report.tbl_dbi.Rd            |   30 
 dlookr-0.5.2/dlookr/man/diagnose_sparese.data.frame.Rd        |    8 
 dlookr-0.5.2/dlookr/man/diagnose_web_report.data.frame.Rd     |    8 
 dlookr-0.5.2/dlookr/man/dlookr-package.Rd                     |    2 
 dlookr-0.5.2/dlookr/man/eda_paged_report.data.frame.Rd        |    8 
 dlookr-0.5.2/dlookr/man/eda_report.data.frame.Rd              |   26 
 dlookr-0.5.2/dlookr/man/eda_report.tbl_dbi.Rd                 |   78 -
 dlookr-0.5.2/dlookr/man/eda_web_report.data.frame.Rd          |    8 
 dlookr-0.5.2/dlookr/man/get_column_info.Rd                    |   12 
 dlookr-0.5.2/dlookr/man/get_transform.Rd                      |    2 
 dlookr-0.5.2/dlookr/man/import_google_font.Rd                 |only
 dlookr-0.5.2/dlookr/man/imputate_na.Rd                        |   12 
 dlookr-0.5.2/dlookr/man/imputate_outlier.Rd                   |    4 
 dlookr-0.5.2/dlookr/man/normality.data.frame.Rd               |   14 
 dlookr-0.5.2/dlookr/man/normality.tbl_dbi.Rd                  |   28 
 dlookr-0.5.2/dlookr/man/performance_bin.Rd                    |    6 
 dlookr-0.5.2/dlookr/man/plot.bins.Rd                          |   24 
 dlookr-0.5.2/dlookr/man/plot.compare_category.Rd              |   25 
 dlookr-0.5.2/dlookr/man/plot.compare_numeric.Rd               |   12 
 dlookr-0.5.2/dlookr/man/plot.imputation.Rd                    |   18 
 dlookr-0.5.2/dlookr/man/plot.optimal_bins.Rd                  |    9 
 dlookr-0.5.2/dlookr/man/plot.overview.Rd                      |   21 
 dlookr-0.5.2/dlookr/man/plot.performance_bin.Rd               |   18 
 dlookr-0.5.2/dlookr/man/plot.relate.Rd                        |    9 
 dlookr-0.5.2/dlookr/man/plot.transform.Rd                     |   20 
 dlookr-0.5.2/dlookr/man/plot.univar_category.Rd               |   17 
 dlookr-0.5.2/dlookr/man/plot.univar_numeric.Rd                |    9 
 dlookr-0.5.2/dlookr/man/plot_bar_category.data.frame.Rd       |   13 
 dlookr-0.5.2/dlookr/man/plot_box_numeric.data.frame.Rd        |   13 
 dlookr-0.5.2/dlookr/man/plot_correlate.data.frame.Rd          |   46 -
 dlookr-0.5.2/dlookr/man/plot_correlate.tbl_dbi.Rd             |   40 
 dlookr-0.5.2/dlookr/man/plot_hist_numeric.data.frame.Rd       |   13 
 dlookr-0.5.2/dlookr/man/plot_na_hclust.Rd                     |   14 
 dlookr-0.5.2/dlookr/man/plot_na_intersect.Rd                  |   12 
 dlookr-0.5.2/dlookr/man/plot_na_pareto.Rd                     |   23 
 dlookr-0.5.2/dlookr/man/plot_normality.data.frame.Rd          |   31 
 dlookr-0.5.2/dlookr/man/plot_normality.tbl_dbi.Rd             |   38 
 dlookr-0.5.2/dlookr/man/plot_outlier.data.frame.Rd            |   17 
 dlookr-0.5.2/dlookr/man/plot_outlier.target_df.Rd             |   13 
 dlookr-0.5.2/dlookr/man/plot_outlier.tbl_dbi.Rd               |   10 
 dlookr-0.5.2/dlookr/man/plot_qq_numeric.data.frame.Rd         |   13 
 dlookr-0.5.2/dlookr/man/summary.bins.Rd                       |    2 
 dlookr-0.5.2/dlookr/man/summary.imputation.Rd                 |    6 
 dlookr-0.5.2/dlookr/man/summary.performance_bin.Rd            |    6 
 dlookr-0.5.2/dlookr/man/summary.transform.Rd                  |    6 
 dlookr-0.5.2/dlookr/man/summary.univar_numeric.Rd             |    2 
 dlookr-0.5.2/dlookr/man/target_by.tbl_dbi.Rd                  |   18 
 dlookr-0.5.2/dlookr/man/transform.Rd                          |    6 
 dlookr-0.5.2/dlookr/man/transformation_paged_report.Rd        |    8 
 dlookr-0.5.2/dlookr/man/transformation_report.Rd              |   12 
 dlookr-0.5.2/dlookr/man/transformation_web_report.Rd          |    8 
 dlookr-0.5.2/dlookr/vignettes/introduce.Rmd                   |    2 
 109 files changed, 2332 insertions(+), 1564 deletions(-)

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New package clustra with initial version 0.1.5
Package: clustra
Version: 0.1.5
Date: 2021-11-19
Title: Clustering Trajectories Anchored at Intervention Time
Depends: R (>= 3.5.0)
Imports: data.table, graphics, grDevices, methods, mgcv, MixSim, parallel, stats
Suggests: ggplot2, knitr, rmarkdown
Description: Clusters medical trajectories (unequally spaced and unequal length time series) aligned by an intervention time. Performs k-means clustering, where each mean is a thin plate spline fit to all points in a cluster. Distance is MSE across trajectory points to cluster spline. Provides silhouette plots and Adjusted Rand Index evaluations of the number of clusters. Scales well to large data with multicore parallelism available to speed computation.
LazyLoad: yes
License: BSD 2-clause License + file LICENSE
Encoding: UTF-8
Maintainer: George Ostrouchov <ostrouchovg@ornl.gov>
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-11-22 00:34:34 UTC; ost
Author: George Ostrouchov [aut, cre], David Gagnon [aut], Hanna Gerlovin [aut], Chen Wei-Chen [ctb], Schmidt Drew [ctb], Oak Ridge National Laboratory [cph], U.S. Department of Veteran's Affairs [fnd] (Project: Million Veteran Program Data Core)
Repository: CRAN
Date/Publication: 2021-11-22 09:00:08 UTC

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Package abtest updated to version 1.0.1 with previous version 0.2.2 dated 2020-11-12

Title: Bayesian A/B Testing
Description: Provides functions for Bayesian A/B testing including prior elicitation options based on Kass and Vaidyanathan (1992) <doi:10.1111/j.2517-6161.1992.tb01868.x>. Gronau, Raj K. N., & Wagenmakers (2021) <doi:10.18637/jss.v100.i17>.
Author: Quentin F. Gronau [aut, cre], Akash Raj [ctb], Eric-Jan Wagenmakers [ths]
Maintainer: Quentin F. Gronau <Quentin.F.Gronau@gmail.com>

Diff between abtest versions 0.2.2 dated 2020-11-12 and 1.0.1 dated 2021-11-22

 DESCRIPTION            |   11 ++++++-----
 MD5                    |   32 +++++++++++++++++---------------
 NEWS                   |    8 ++++++++
 R/ab_test.R            |    6 +++++-
 R/elicit_prior.R       |    7 ++++++-
 build                  |only
 inst                   |only
 man/ab_test.Rd         |   19 +++++++++++++++----
 man/dprior.Rd          |    9 +++++++--
 man/elicit_prior.Rd    |   17 ++++++++++++++---
 man/plot_posterior.Rd  |   13 +++++++++++--
 man/plot_prior.Rd      |    9 +++++++--
 man/plot_robustness.Rd |   14 +++++++++++---
 man/pprior.Rd          |    8 ++++++--
 man/qprior.Rd          |    8 ++++++--
 man/seqdata.Rd         |    4 +++-
 man/simulate_priors.Rd |    7 +++++--
 src/RcppExports.cpp    |    5 +++++
 18 files changed, 132 insertions(+), 45 deletions(-)

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Package fastshap (with last version 0.0.5) was removed from CRAN

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

2020-02-02 0.0.5
2020-01-26 0.0.4
2019-12-03 0.0.3
2019-11-22 0.0.2

Permanent link
Package OutlierDC (with last version 0.3-0) was removed from CRAN

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

2014-03-24 0.3-0
2013-06-21 0.2.5
2013-03-18 0.2.1
2013-03-18 0.2.1

Permanent link
New package stacomiR with initial version 0.6.0
Package: stacomiR
Version: 0.6.0
Date: 2021-11-16
Title: Fish Migration Monitoring
Description: Graphical outputs and treatment for a database of fish pass monitoring. It is a part of the 'STACOMI' open source project developed in France by the French Office for Biodiversity institute to centralize data obtained by fish pass monitoring. This version is available in French and English. See <http://stacomir.r-forge.r-project.org/> for more information on 'STACOMI'.
License: GPL (>= 2)
URL: http://stacomir.r-forge.r-project.org/
BugReports: https://github.com/MarionLegrandLogrami/stacomiR/issues
LazyLoad: yes
LazyData: true
Depends: R (>= 4.0.0), methods, stacomirtools (>= 0.6.0)
Imports: magrittr, intervals, RColorBrewer, stringr, RPostgres, ggplot2, reshape2, graphics, utils, stats, lattice, grDevices, Hmisc (>= 4.1-1), lubridate, dplyr, xtable, mgcv, rlang, pool, withr
Suggests: testthat, viridis, knitr, rmarkdown
Author: Cedric Briand [aut, cre], Marion Legrand [aut], Beaulaton Laurent [ctb], Boulenger Clarisse [ctb], Lafage Denis [ctb], Grall Sebastien [ctb]
Maintainer: Cedric Briand <cedric.briand00@gmail.com>
NeedsCompilation: no
VignetteBuilder: knitr
Packaged: 2021-11-19 21:17:56 UTC; cedric.briand
Repository: CRAN
Date/Publication: 2021-11-22 08:00:02 UTC

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Package rio updated to version 0.5.29 with previous version 0.5.27 dated 2021-06-21

Title: A Swiss-Army Knife for Data I/O
Description: Streamlined data import and export by making assumptions that the user is probably willing to make: 'import()' and 'export()' determine the data structure from the file extension, reasonable defaults are used for data import and export (e.g., 'stringsAsFactors=FALSE'), web-based import is natively supported (including from SSL/HTTPS), compressed files can be read directly without explicit decompression, and fast import packages are used where appropriate. An additional convenience function, 'convert()', provides a simple method for converting between file types.
Author: Jason Becker [ctb], Chung-hong Chan [aut] (<https://orcid.org/0000-0002-6232-7530>), Geoffrey CH Chan [ctb], Thomas J. Leeper [aut, cre] (<https://orcid.org/0000-0003-4097-6326>), Christopher Gandrud [ctb], Andrew MacDonald [ctb], Ista Zahn [ctb], Stanislaus Stadlmann [ctb], Ruaridh Williamson [ctb], Patrick Kennedy [ctb], Ryan Price [ctb], Trevor L Davis [ctb], Nathan Day [ctb], Bill Denney [ctb] (<https://orcid.org/0000-0002-5759-428X>), Alex Bokov [ctb] (<https://orcid.org/0000-0002-0511-9815>)
Maintainer: Thomas J. Leeper <thosjleeper@gmail.com>

Diff between rio versions 0.5.27 dated 2021-06-21 and 0.5.29 dated 2021-11-22

 DESCRIPTION                         |   10 ++---
 MD5                                 |   52 +++++++++++++++---------------
 NEWS.md                             |    7 +++-
 R/characterize.R                    |    6 +--
 R/convert.R                         |   23 ++++++-------
 R/export.R                          |   62 ++++++++++++++++++++----------------
 R/export_list.R                     |   18 +++++-----
 R/export_methods.R                  |    4 +-
 R/import.R                          |   28 ++++++++--------
 R/import_list.R                     |   24 ++++++++-----
 R/import_methods.R                  |    2 -
 R/is_file_text.R                    |   12 +++---
 R/rio.R                             |   18 +++++-----
 inst/doc/rio.html                   |    4 +-
 man/characterize.Rd                 |    6 +--
 man/convert.Rd                      |   23 ++++++-------
 man/export.Rd                       |   60 +++++++++++++++++++---------------
 man/export_list.Rd                  |   18 +++++-----
 man/import.Rd                       |   28 ++++++++--------
 man/import_list.Rd                  |   24 ++++++++-----
 man/is_file_text.Rd                 |   12 +++---
 man/rio.Rd                          |   18 +++++-----
 tests/testthat/test_format_fwf.R    |    2 -
 tests/testthat/test_format_matlab.R |    6 ++-
 tests/testthat/test_format_pzfx.R   |    1 
 tests/testthat/test_format_xml.R    |    3 +
 tests/testthat/test_is_file_text.R  |    6 ++-
 27 files changed, 260 insertions(+), 217 deletions(-)

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Package Rcplex updated to version 0.3-4 with previous version 0.3-3 dated 2016-06-13

Title: R Interface to CPLEX
Description: R interface to CPLEX solvers for linear, quadratic, and (linear and quadratic) mixed integer programs. Support for quadratically constrained programming is available. See the file "INSTALL" for details on how to install the Rcplex package in Linux/Unix-like and Windows systems. Support for sparse matrices is provided by an S3-style class "simple_triplet_matrix" from package slam and by objects from the Matrix package class hierarchy.
Author: Hector Corrada Bravo [aut], Kurt Hornik [ctb], Stefan Theussl [aut, cre]
Maintainer: Stefan Theussl <Stefan.Theussl@R-project.org>

Diff between Rcplex versions 0.3-3 dated 2016-06-13 and 0.3-4 dated 2021-11-22

 DESCRIPTION      |   10 +++++-----
 MD5              |   13 +++++++------
 NAMESPACE        |    2 +-
 R/Rcplex.R       |    4 ++--
 configure.ac     |    5 +++--
 src/Rcplex.c     |    3 ++-
 src/Rcplex_QCP.c |    3 ++-
 src/init.c       |only
 8 files changed, 22 insertions(+), 18 deletions(-)

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New package nimbleAPT with initial version 1.0.4
Package: nimbleAPT
Title: Adaptive Parallel Tempering for 'NIMBLE'
Version: 1.0.4
Encoding: UTF-8
Date: 2021-11-10
Maintainer: David Pleydell <david.pleydell@inrae.fr>
URL: https://github.com/DRJP/nimbleAPT
Description: Functions for adaptive parallel tempering (APT) with NIMBLE models. Adapted from 'Lacki' & 'Miasojedow' (2016) <DOI:10.1007/s11222-015-9579-0> and 'Miasojedow, Moulines and Vihola' (2013) <DOI:10.1080/10618600.2013.778779>.
License: BSD_3_clause + file LICENSE
Copyright: See COPYRIGHTS file.
Depends: R (>= 3.1.2), nimble
Imports: methods
Suggests: knitr, rmarkdown, coda
VignetteBuilder: knitr
Note: The APT samplers within this package were adapted from MCMC samplers provided in the NIMBLE package (https://github.com/nimble-dev/nimble) and developed by the cited members of the NIMBLE Development Team. The adaptations for APT included in this package were the work of the package developer. Many thanks to the NIMBLE Development Team for their support during the development of this package.
NeedsCompilation: no
Packaged: 2021-11-19 13:00:40 UTC; pleydell
Author: David Pleydell [aut, cre, cph] (Package developer, <https://orcid.org/0000-0002-6450-1475>), Daniel Turek [cph] (Member of the NIMBLE Developent Team), Perry de Valpine [cph] (Member of the NIMBLE Developent Team), Christopher Paciorek [cph] (Member of the NIMBLE Developent Team), Nick Michaud [cph] (Member of the NIMBLE Developent Team)
Repository: CRAN
Date/Publication: 2021-11-22 07:50:02 UTC

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Package monobinShiny updated to version 0.1.0 with previous version 0.0.9 dated 2021-08-23

Title: Shiny User Interface for 'monobin' Package
Description: This is an add-on package to the 'monobin' package that simplifies its use. It provides shiny-based user interface (UI) that is especially handy for less experienced 'R' users as well as for those who intend to perform quick scanning of numeric risk factors when building credit rating models. The additional functions implemented in 'monobinShiny' that do no exist in 'monobin' package are: descriptive statistics, special case and outliers imputation. The function descriptive statistics is exported and can be used in 'R' sessions independently from the user interface, while special case and outlier imputation functions are written to be used with shiny UI.
Author: Andrija Djurovic [aut, cre]
Maintainer: Andrija Djurovic <djandrija@gmail.com>

Diff between monobinShiny versions 0.0.9 dated 2021-08-23 and 0.1.0 dated 2021-11-22

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Package monobin updated to version 0.2.1 with previous version 0.2.0 dated 2021-10-21

Title: Monotonic Binning for Credit Rating Models
Description: Performs monotonic binning of numeric risk factor in credit rating models (PD, LGD, EAD) development. All functions handle both binary and continuous target variable. Functions that use isotonic regression in the first stage of binning process have an additional feature for correction of minimum percentage of observations and minimum target rate per bin. Additionally, monotonic trend can be identified based on raw data or, if known in advance, forced by functions' argument. Missing values and other possible special values are treated separately from so-called complete cases.
Author: Andrija Djurovic [aut, cre]
Maintainer: Andrija Djurovic <djandrija@gmail.com>

Diff between monobin versions 0.2.0 dated 2021-10-21 and 0.2.1 dated 2021-11-22

 DESCRIPTION        |    6 +++---
 MD5                |    8 ++++----
 NEWS.md            |    9 +++++++--
 R/07_MDT_BINNING.R |    9 +++++++--
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More information about monobin at CRAN
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Package mindr updated to version 1.3.2 with previous version 1.3.1 dated 2021-11-19

Title: Generate Mind Maps with R
Description: Convert Markdown ('.md') or R Markdown ('.Rmd') texts, R scripts, and directory structures, into mind map widgets or files ('.mm'), and vice versa. "FreeMind" mind map ('.mm') files can be opened by or imported to common mindmap software such as 'FreeMind' (<http://freemind.sourceforge.net/wiki/index.php/Main_Page>).
Author: Peng Zhao
Maintainer: Peng Zhao <pzhao@pzhao.net>

Diff between mindr versions 1.3.1 dated 2021-11-19 and 1.3.2 dated 2021-11-22

 DESCRIPTION          |    8 ++---
 MD5                  |   12 +++----
 R/individual.R       |    6 +++
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Package MethodCompare updated to version 0.1.1 with previous version 0.1.0 dated 2016-10-11

Title: Bias and Precision Plots
Description: Implementation of the methodology from the paper entitled "Effective plots to assess bias and precision in method comparison studies" published in Statistical Methods in Medical Research, P. Taffé (2018) <doi:10.1177/0962280218759693>.
Author: Mingkai Peng, Patrick Taffé, Tyler Williamson
Maintainer: Patrick Taffé <patrick.taffe@unisante.ch>

Diff between MethodCompare versions 0.1.0 dated 2016-10-11 and 0.1.1 dated 2021-11-22

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Package git2r updated to version 0.29.0 with previous version 0.28.0 dated 2021-01-10

Title: Provides Access to Git Repositories
Description: Interface to the 'libgit2' library, which is a pure C implementation of the 'Git' core methods. Provides access to 'Git' repositories to extract data and running some basic 'Git' commands.
Author: See AUTHORS file.
Maintainer: Stefan Widgren <stefan.widgren@gmail.com>

Diff between git2r versions 0.28.0 dated 2021-01-10 and 0.29.0 dated 2021-11-22

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Package FuzzyResampling updated to version 0.3.0 with previous version 0.1.0 dated 2021-09-15

Title: Resampling Methods for Triangular and Trapezoidal Fuzzy Numbers
Description: The classical (i.e. Efron's, see Efron and Tibshirani (1994, ISBN:978-0412042317) "An Introduction to the Bootstrap") bootstrap is widely used for both the real (i.e. "crisp") and fuzzy data. The main aim of the algorithms implemented in this package is to overcome a problem with repetition of a few distinct values and to create fuzzy numbers, which are "similar" (but not the same) to values from the initial sample. To do this, different characteristics of triangular/trapezoidal numbers are kept (like the value, the ambiguity, etc., see Grzegorzewski et al. <doi:10.2991/eusflat-19.2019.68>, Grzegorzewski et al. (2020) <doi:10.2991/ijcis.d.201012.003>, Grzegorzewski et al. (2020) <doi:10.34768/amcs-2020-0022>, Romaniuk and Hryniewicz (2019) <doi:10.1007/s00500-018-3251-5>). Some additional procedures related to these resampling methods are also provided, like calculation of the Bertoluzza et al.'s distance (aka the mid/spread distance, see Bertoluzza et al. (1995) "On a new class of distances between fuzzy numbers") and estimation of the p-value of the one-sample bootstrapped test for the mean (see Lubiano et al. (2016, <doi:10.1016/j.ejor.2015.11.016>)). Additionally, there are procedures which randomly generate trapezoidal fuzzy numbers using some well-known statistical distributions.
Author: Maciej Romaniuk [cre], Przemyslaw Grzegorzewski [aut], Olgierd Hryniewicz [aut]
Maintainer: Maciej Romaniuk <mroman@ibspan.waw.pl>

Diff between FuzzyResampling versions 0.1.0 dated 2021-09-15 and 0.3.0 dated 2021-11-22

 DESCRIPTION                    |   10 +-
 MD5                            |   49 ++++++----
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 man/wmethod.Rd                 |   16 +--
 32 files changed, 333 insertions(+), 87 deletions(-)

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New package cgrcusum with initial version 0.1.0
Package: cgrcusum
Title: Continuous Time Generalized Rapid Response CUSUM
Version: 0.1.0
Description: Allows users to construct the Continuous Time Generalized Rapid Response CUSUM (CGR-CUSUM), Biswas & Kalbfleisch (2008) <doi:10.1002/sim.3296> CUSUM, Binary CUSUM and risk-adjusted funnel plot for survival data. These procedures can be used to monitor survival processes and detect problems in their quality.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0)
Imports: ggplot2, survival
Depends: R (>= 3.5.0)
Maintainer: Daniel Gomon <d.gomon@math.leidenuniv.nl>
URL: https://github.com/d-gomon/cgrcusum
NeedsCompilation: no
Packaged: 2021-11-19 15:07:48 UTC; danie
Author: Daniel Gomon [aut, cre] (<https://orcid.org/0000-0001-9011-3743>)
Repository: CRAN
Date/Publication: 2021-11-22 08:00:09 UTC

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Package radiant.model updated to version 1.4.2 with previous version 1.4.1 dated 2021-10-10

Title: Model Menu for Radiant: Business Analytics using R and Shiny
Description: The Radiant Model menu includes interfaces for linear and logistic regression, naive Bayes, neural networks, classification and regression trees, model evaluation, collaborative filtering, decision analysis, and simulation. The application extends the functionality in 'radiant.data'.
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

Diff between radiant.model versions 1.4.1 dated 2021-10-10 and 1.4.2 dated 2021-11-22

 DESCRIPTION                             |   16 +++---
 MD5                                     |   60 +++++++++++------------
 NEWS.md                                 |    5 +
 R/crs.R                                 |    2 
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Package RcppEnsmallen updated to version 0.2.18.1.1 with previous version 0.2.18.0.1 dated 2021-10-22

Title: Header-Only C++ Mathematical Optimization Library for 'Armadillo'
Description: 'Ensmallen' is a templated C++ mathematical optimization library (by the 'MLPACK' team) that provides a simple set of abstractions for writing an objective function to optimize. Provided within are various standard and cutting-edge optimizers that include full-batch gradient descent techniques, small-batch techniques, gradient-free optimizers, and constrained optimization. The 'RcppEnsmallen' package includes the header files from the 'Ensmallen' library and pairs the appropriate header files from 'armadillo' through the 'RcppArmadillo' package. Therefore, users do not need to install 'Ensmallen' nor 'Armadillo' to use 'RcppEnsmallen'. Note that 'Ensmallen' is licensed under 3-Clause BSD, 'Armadillo' starting from 7.800.0 is licensed under Apache License 2, 'RcppArmadillo' (the 'Rcpp' bindings/bridge to 'Armadillo') is licensed under the GNU GPL version 2 or later. Thus, 'RcppEnsmallen' is also licensed under similar terms. Note that 'Ensmallen' requires a compiler that supports 'C++11' and 'Armadillo' 9.800 or later.
Author: James Joseph Balamuta [aut, cre, cph] (<https://orcid.org/0000-0003-2826-8458>), Dirk Eddelbuettel [aut, cph] (<https://orcid.org/0000-0001-6419-907X>)
Maintainer: James Joseph Balamuta <balamut2@illinois.edu>

Diff between RcppEnsmallen versions 0.2.18.0.1 dated 2021-10-22 and 0.2.18.1.1 dated 2021-11-22

 ChangeLog                                        |    7 +++++++
 DESCRIPTION                                      |    6 +++---
 MD5                                              |   14 +++++++-------
 NEWS.md                                          |   10 ++++++++++
 build/vignette.rds                               |binary
 inst/doc/using-rcppensmallen.html                |   20 ++++++++++----------
 inst/include/ensmallen_bits/cmaes/cmaes_impl.hpp |    2 +-
 inst/include/ensmallen_bits/ens_version.hpp      |    6 +++---
 8 files changed, 41 insertions(+), 24 deletions(-)

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Package radiant.multivariate updated to version 1.4.1 with previous version 1.3.5 dated 2020-03-25

Title: Multivariate Menu for Radiant: Business Analytics using R and Shiny
Description: The Radiant Multivariate menu includes interfaces for perceptual mapping, factor analysis, cluster analysis, and conjoint analysis. The application extends the functionality in 'radiant.data'.
Author: Vincent Nijs [aut, cre]
Maintainer: Vincent Nijs <radiant@rady.ucsd.edu>

Diff between radiant.multivariate versions 1.3.5 dated 2020-03-25 and 1.4.1 dated 2021-11-22

 DESCRIPTION                              |   26 +++++++-------
 MD5                                      |   54 +++++++++++++++----------------
 NEWS.md                                  |    9 +++++
 R/conjoint.R                             |   16 ++++-----
 R/full_factor.R                          |    6 +--
 R/hclus.R                                |    8 ++--
 R/kclus.R                                |   10 ++---
 R/mds.R                                  |    8 ++--
 R/pre_factor.R                           |   35 ++++++++++----------
 R/prmap.R                                |   16 ++++-----
 R/radiant.R                              |    6 +--
 README.md                                |   20 ++++++-----
 inst/app/tools/analysis/conjoint_ui.R    |   50 ++++++++++++++--------------
 inst/app/tools/analysis/full_factor_ui.R |    4 +-
 inst/app/tools/analysis/hclus_ui.R       |   10 ++---
 inst/app/tools/analysis/kclus_ui.R       |   13 ++++---
 inst/app/tools/analysis/prmap_ui.R       |    8 ++--
 man/plot.conjoint.Rd                     |    2 -
 man/plot.full_factor.Rd                  |    2 -
 man/plot.hclus.Rd                        |    2 -
 man/plot.kclus.Rd                        |    2 -
 man/plot.mds.Rd                          |    2 -
 man/plot.pre_factor.Rd                   |    3 -
 man/plot.prmap.Rd                        |    2 -
 man/radiant.multivariate.Rd              |    2 -
 man/radiant.multivariate_viewer.Rd       |    2 -
 man/radiant.multivariate_window.Rd       |    2 -
 man/summary.pre_factor.Rd                |    1 
 28 files changed, 167 insertions(+), 154 deletions(-)

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Package polyreg updated to version 0.7.0 with previous version 0.6.9 dated 2021-09-08

Title: Polynomial Regression
Description: Automate formation and evaluation of polynomial regression models. The motivation for this package is described in 'Polynomial Regression As an Alternative to Neural Nets' by Xi Cheng, Bohdan Khomtchouk, Norman Matloff, and Pete Mohanty (<arXiv:1806.06850>).
Author: Norm Matloff [aut, cre] (<https://orcid.org/0000-0001-9179-6785>), Xi Cheng [aut], Pete Mohanty [aut] (<https://orcid.org/0000-0001-8531-3345>), Bohdan Khomtchouk [aut], Matthew Kotila [aut], Robin Yancey [aut], Robert Tucker [aut], Allan Zhao [aut], Tiffany Jiang [aut]
Maintainer: Norm Matloff <matloff@cs.ucdavis.edu>

Diff between polyreg versions 0.6.9 dated 2021-09-08 and 0.7.0 dated 2021-11-22

 DESCRIPTION          |   11 ++++--
 MD5                  |   19 +++++++----
 NAMESPACE            |    4 --
 R/S3methods.R        |   44 --------------------------
 R/helper_functions.R |   36 ---------------------
 R/polyFit.R          |   84 ++++++++++-----------------------------------------
 build                |only
 data                 |only
 inst                 |only
 man/pef.Rd           |only
 man/polyFit.Rd       |   45 ++++++++++++---------------
 man/weatherTS.Rd     |only
 vignettes            |only
 13 files changed, 60 insertions(+), 183 deletions(-)

More information about polyreg at CRAN
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