Fri, 25 Mar 2022

Package httk updated to version 2.1.0 with previous version 2.0.4 dated 2021-05-10

Title: High-Throughput Toxicokinetics
Description: Generic models and chemical-specific data for simulation and statistical analysis of chemical toxicokinetics ("TK") as described by Pearce et al. (2017) <doi:10.18637/jss.v079.i04>. Chemical-specific in vitro data have been obtained from relatively high-throughput experiments. Both physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models can be parameterized with the data provided for thousands of chemicals, multiple exposure routes, and various species. The models consist of systems of ordinary differential equations which are solved using compiled (C-based) code for speed. A Monte Carlo sampler is included, which allows for simulating human biological variability (Ring et al., 2017 <doi:10.1016/j.envint.2017.06.004>) and propagating parameter uncertainty. Calibrated methods are included for predicting tissue:plasma partition coefficients and volume of distribution (Pearce et al., 2017 <doi:10.1007/s10928-017-9548-7>). These functions and data provide a set of tools for in vitro-in vivo extrapolation ("IVIVE") of high-throughput screening data (for example, Tox21, ToxCast) to real-world exposures via reverse dosimetry (also known as "RTK") (Wetmore et al., 2015 <doi:10.1093/toxsci/kfv171>).
Author: John Wambaugh [aut, cre] , Sarah Davidson [aut] , Robert Pearce [aut] , Caroline Ring [aut] , Greg Honda [aut] , Mark Sfeir [aut], Matt Linakis [aut] , Dustin Kapraun [aut] , Miyuki Breen [ctb] , Shannon Bell [ctb] , Xiaoqing Chang [ctb] , Todor Anto [...truncated...]
Maintainer: John Wambaugh <wambaugh.john@epa.gov>

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More information about httk at CRAN
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Package wrMisc updated to version 1.9.0 with previous version 1.8.1 dated 2022-01-24

Title: Analyze Experimental High-Throughput (Omics) Data
Description: The efficient treatment and convenient analysis of experimental high-throughput (omics) data gets facilitated through this collection of diverse functions. Several functions address advanced object-conversions, like manipulating lists of lists or lists of arrays, reorganizing lists to arrays or into separate vectors, merging of multiple entries, etc. Another set of functions provides speed-optimized calculation of standard deviation (sd), coefficient of variance (CV) or standard error of the mean (SEM) for data in matrixes or means per line with respect to additional grouping (eg n groups of replicates). Other functions facilitate dealing with non-redundant information, by indexing unique, adding counters to redundant or eliminating lines with respect redundancy in a given reference-column, etc. Help is provided to identify very closely matching numeric values to generate (partial) distance matrixes for very big data in a memory efficient manner or to reduce the complexity of large data-sets by combining very close values. Many times large experimental datasets need some additional filtering, adequate functions are provided. Batch reading (or writing) of sets of files and combining data to arrays is supported, too. Convenient data normalization is supported in various different modes, parameter estimation via permutations or boot-strap as well as flexible testing of multiple pair-wise combinations using the framework of 'limma' is provided, too.
Author: Wolfgang Raffelsberger [aut, cre]
Maintainer: Wolfgang Raffelsberger <w.raffelsberger@gmail.com>

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Package worldfootballR updated to version 0.5.1 with previous version 0.5.0 dated 2022-03-21

Title: Functions to Extract and Clean World Football (Soccer) Data
Description: A set of functions to allow users to obtain clean and tidy football (soccer) game, team and player data. Data is collected from a number of popular sites, including 'FBref'<https://fbref.com/en/>, transfer and valuations data from 'Transfermarkt'<https://www.transfermarkt.com/> and shooting location and other match stats data from 'Understat'<https://understat.com/> and 'fotmob'<https://www.fotmob.com/>. It gives users the ability to access data more efficiently, rather than having to export data tables to files before being able to complete their analysis.
Author: Jason Zivkovic [aut, cre, cph], Tony ElHabr [ctb]
Maintainer: Jason Zivkovic <jaseziv83@gmail.com>

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New package wikiTools with initial version 0.0.6
Package: wikiTools
Version: 0.0.6
Date: 2022-03-18
Title: Tools for Wikidata and Wikipedia
Description: A set of wrappers intended to check, read and download information from the Wikimedia sources. It is specifically created to work with names of celebrities, in which case their information and statistics can be downloaded. Additionally, it also builds links and snippets to use in combination with the function gallery() in netCoin package.
License: GPL-3
Depends: R (>= 3.5.0)
Encoding: UTF-8
Imports: WikidataQueryServiceR (>= 1.0.0), WikidataR (>= 1.4.0), httr, jsonlite, ratelimitr
NeedsCompilation: no
Maintainer: Modesto Escobar <modesto@usal.es>
Packaged: 2022-03-23 18:25:19 UTC; Modesto
Author: Modesto Escobar [aut, cph, cre] , Ángel Zazo [aut], Carlos Prieto [aut] , David Barrios [aut], Cristina Calvo [aut]
Repository: CRAN
Date/Publication: 2022-03-24 08:40:02 UTC

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Package WeibullR updated to version 1.1.10 with previous version 1.1.5 dated 2022-03-05

Title: Weibull Analysis for Reliability Engineering
Description: Life data analysis in the graphical tradition of Waloddi Weibull. Methods derived from Robert B. Abernethy (2008, ISBN 0-965306-3-2), Wayne Nelson (1982, ISBN: 9780471094586), William Q. Meeker and Lois A. Escobar (1998, ISBN: 1-471-14328-6), John I. McCool, (2012, ISBN: 9781118217986).
Author: David Silkworth [aut], Jurgen Symynck [aut], Jacob Ormerod [cre], OpenReliability.org [cph]
Maintainer: Jacob Ormerod <jake@openreliability.org>

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Package visvow updated to version 1.3.4 with previous version 1.3.3 dated 2021-07-15

Title: Visible Vowels: Visualization of Vowel Variation
Description: Visualizes vowel variation in f0, F1, F2, F3 and duration.
Author: Wilbert Heeringa, Hans Van de Velde
Maintainer: Wilbert Heeringa <wjheeringa@gmail.com>

Diff between visvow versions 1.3.3 dated 2021-07-15 and 1.3.4 dated 2022-03-25

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Package versionsort updated to version 1.1.0 with previous version 1.0.0 dated 2021-12-15

Title: Sort and Order Version Codes
Description: A lightweight package for sorting version codes in various forms. No strong dependencies guaranteed.
Author: Laura Bakala [cre, aut, cph]
Maintainer: Laura Bakala <erdaradun.gaztea@gmail.com>

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Package validate updated to version 1.1.1 with previous version 1.1.0 dated 2021-10-07

Title: Data Validation Infrastructure
Description: Declare data validation rules and data quality indicators; confront data with them and analyze or visualize the results. The package supports rules that are per-field, in-record, cross-record or cross-dataset. Rules can be automatically analyzed for rule type and connectivity. Supports checks implied by an SDMX DSD file as well. See also Van der Loo and De Jonge (2018) <doi:10.1002/9781118897126>, Chapter 6 and the JSS paper (2021) <doi:10.18637/jss.v097.i10>.
Author: Mark van der Loo [cre, aut] , Edwin de Jonge [aut] , Paul Hsieh [ctb]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>

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Package unitizer updated to version 1.4.18 with previous version 1.4.17 dated 2022-01-09

Title: Interactive R Unit Tests
Description: Simplifies regression tests by comparing objects produced by test code with earlier versions of those same objects. If objects are unchanged the tests pass, otherwise execution stops with error details. If in interactive mode, tests can be reviewed through the provided interactive environment.
Author: Brodie Gaslam [aut, cre], R Core Team [cph]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

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Package uniset updated to version 0.3.0 with previous version 0.2.1 dated 2021-10-15

Title: Dynamic Settings File
Description: Any package (subsequently called 'target package') is enabled to provide its users an easily accessible, user-friendly and human readable text file where key=value pairs (used by functions defined in the target package) can be saved. This settings file lives in a location defined by the user of the target package, and its user-defined values remain unchanged even when the author of the target package is introducing or deleting keys, or when the target package is updated or re-installed.
Author: Bernhard Pollner [cre, aut], Zoltan Kovacs [aut]
Maintainer: Bernhard Pollner <bernhard.pollner@mac.com>

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Package umap updated to version 0.2.8.0 with previous version 0.2.7.0 dated 2020-11-04

Title: Uniform Manifold Approximation and Projection
Description: Uniform manifold approximation and projection is a technique for dimension reduction. The algorithm was described by McInnes and Healy (2018) in <arXiv:1802.03426>. This package provides an interface for two implementations. One is written from scratch, including components for nearest-neighbor search and for embedding. The second implementation is a wrapper for 'python' package 'umap-learn' (requires separate installation, see vignette for more details).
Author: Tomasz Konopka [aut, cre]
Maintainer: Tomasz Konopka <tokonopka@gmail.com>

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Package ukbabynames updated to version 0.3.0 with previous version 0.2.0 dated 2021-04-22

Title: UK Baby Names Data
Description: Full listing of UK baby names occurring more than three times per year between 1974 and 2020, and rankings of baby name popularity by decade from 1904 to 1994.
Author: Mine Çetinkaya-Rundel [aut, cre] , Thomas J. Leeper [aut], Nicholas Goguen-Compagnoni [aut], Sara Lemus [aut]
Maintainer: Mine Çetinkaya-Rundel <cetinkaya.mine@gmail.com>

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Package udpipe updated to version 0.8.9 with previous version 0.8.8 dated 2021-12-02

Title: Tokenization, Parts of Speech Tagging, Lemmatization and Dependency Parsing with the 'UDPipe' 'NLP' Toolkit
Description: This natural language processing toolkit provides language-agnostic 'tokenization', 'parts of speech tagging', 'lemmatization' and 'dependency parsing' of raw text. Next to text parsing, the package also allows you to train annotation models based on data of 'treebanks' in 'CoNLL-U' format as provided at <https://universaldependencies.org/format.html>. The techniques are explained in detail in the paper: 'Tokenizing, POS Tagging, Lemmatizing and Parsing UD 2.0 with UDPipe', available at <doi:10.18653/v1/K17-3009>. The toolkit also contains functionalities for commonly used data manipulations on texts which are enriched with the output of the parser. Namely functionalities and algorithms for collocations, token co-occurrence, document term matrix handling, term frequency inverse document frequency calculations, information retrieval metrics (Okapi BM25), handling of multi-word expressions, keyword detection (Rapid Automatic Keyword Extraction, noun phrase extraction, syntactical patterns) sentiment scoring and semantic similarity analysis.
Author: Jan Wijffels [aut, cre, cph], BNOSAC [cph], Institute of Formal and Applied Linguistics, Faculty of Mathematics and Physics, Charles University in Prague, Czech Republic [cph], Milan Straka [ctb, cph], Jana Strakova [ctb, cph]
Maintainer: Jan Wijffels <jwijffels@bnosac.be>

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Package TreeTools updated to version 1.7.1 with previous version 1.7.0 dated 2022-03-21

Title: Create, Modify and Analyse Phylogenetic Trees
Description: Efficient implementations of functions for the creation, modification and analysis of phylogenetic trees. Applications include: generation of trees with specified shapes; tree rearrangement; analysis of tree shape; rooting of trees and extraction of subtrees; calculation and depiction of split support; plotting the position of rogue taxa (Klopfstein & Spasojevic 2019) <doi:10.1371/journal.pone.0212942>; calculation of ancestor-descendant relationships, of 'stemwardness' (Asher & Smith, 2021) <doi:10.1093/sysbio/syab072>, and of tree balance (Mir et al. 2013) <doi:10.1016/j.mbs.2012.10.005>; artificial extinction (Asher & Smith, 2022) <doi:10.1093/sysbio/syab072>; import and export of trees from Newick, Nexus (Maddison et al. 1997) <doi:10.1093/sysbio/46.4.590>, and TNT <http://www.lillo.org.ar/phylogeny/tnt/> formats; and analysis of splits and cladistic information.
Author: Martin R. Smith [aut, cre, cph] , Emmanuel Paradis [cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package TOSTER updated to version 0.4.1 with previous version 0.4.0 dated 2022-02-04

Title: Two One-Sided Tests (TOST) Equivalence Testing
Description: Two one-sided tests (TOST) procedure to test equivalence for t-tests, correlations, differences between proportions, and meta-analyses, including power analysis for t-tests and correlations. Allows you to specify equivalence bounds in raw scale units or in terms of effect sizes. See: Lakens (2017) <doi:10.1177/1948550617697177>.
Author: Daniel Lakens [aut], Aaron Caldwell [aut, cre]
Maintainer: Aaron Caldwell <arcaldwell49@gmail.com>

Diff between TOSTER versions 0.4.0 dated 2022-02-04 and 0.4.1 dated 2022-03-25

 DESCRIPTION                                   |   10 
 MD5                                           |  264 +--
 NAMESPACE                                     |  158 +-
 NEWS.md                                       |  161 +-
 R/TOSTmeta.R                                  |  230 +--
 R/TOSTone.R                                   |  230 +--
 R/TOSTone.raw.R                               |  222 +--
 R/TOSTpaired.R                                |  258 +--
 R/TOSTpaired.raw.R                            |  232 +--
 R/TOSTr.R                                     |  222 +--
 R/TOSTtwo.R                                   |  314 ++--
 R/TOSTtwo.prop.R                              |  290 ++--
 R/TOSTtwo.raw.R                               |  300 ++--
 R/anova_summary.R                             |  470 +++---
 R/boot_t_TOST.R                               |  988 +++++++-------
 R/cohend_calcs.R                              |  598 ++++----
 R/corr_calcs.R                                |  270 +--
 R/data.R                                      |   14 
 R/datatostone.b.R                             |  342 ++--
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 R/datatosttwoprop.b.R                         |  248 +--
 R/datatosttwoprop.h.R                         |  712 +++++-----
 R/equ_anova.R                                 |  170 +-
 R/equ_ftest.R                                 |  186 +-
 R/gg_curv_t.R                                 |  386 ++---
 R/globals.R                                   |   10 
 R/methods.TOSTnp.R                            |  104 -
 R/methods.TOSTt.R                             | 1102 +++++++--------
 R/pes_calc.R                                  |  440 +++---
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 R/rbs.R                                       |  288 ++--
 R/rbs_calcs.R                                 |  142 +-
 R/t_TOST.R                                    |  832 +++++------
 R/tsum_TOST.R                                 |  668 ++++-----
 R/tsum_funcs.R                                |  240 +--
 R/wilcox_TOST.R                               |  620 ++++----
 README.md                                     |   98 -
 build/vignette.rds                            |binary
 inst/CITATION                                 |    2 
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 man/rbs.Rd                                    |  144 +-
 man/t_TOST.Rd                                 |  184 +-
 man/tsum_TOST.Rd                              |  156 +-
 man/wilcox_TOST.Rd                            |  170 +-
 tests/testthat.R                              |    8 
 tests/testthat/test-NCSS1.R                   |  162 +-
 tests/testthat/test-bootTOST.R                |  428 +++---
 tests/testthat/test-data_summary_equivalent.R |  190 +-
 tests/testthat/test-ftests.R                  |  224 +--
 tests/testthat/test-jamovi.R                  | 1260 ++++++++---------
 tests/testthat/test-known_results.R           |  570 ++++----
 tests/testthat/test-old_errors.R              |  516 +++----
 tests/testthat/test-power_consistent.R        |  146 +-
 tests/testthat/test-power_t_TOST.R            |  684 ++++-----
 tests/testthat/test-powerraw.R                |  158 +-
 tests/testthat/test-tTOST.R                   | 1830 +++++++++++++-------------
 tests/testthat/test-wilcox.R                  |  260 +--
 vignettes/IntroTOSTt.Rmd                      |  641 ++++-----
 vignettes/IntroductionToTOSTER.Rmd            |  316 ++--
 vignettes/SMD_calcs.Rmd                       |  548 +++----
 vignettes/anovaTOSTER.R                       |   56 
 vignettes/anovaTOSTER.html                    |  976 ++++++-------
 vignettes/references.bib                      |  264 +--
 vignettes/robustTOST.Rmd                      |  256 +--
 vignettes/the_ftestTOSTER.Rmd                 |  232 +--
 133 files changed, 20243 insertions(+), 20237 deletions(-)

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Package TMB updated to version 1.8.1 with previous version 1.8.0 dated 2022-03-07

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

Diff between TMB versions 1.8.0 dated 2022-03-07 and 1.8.1 dated 2022-03-25

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 inst/include/cppad/local/optimize.hpp  |    2 +-
 inst/include/tmb_core.hpp              |    2 +-
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Package timeseriesdb updated to version 1.0.0-1.1.2 with previous version 0.4.1 dated 2018-08-06

Title: A Time Series Database for Official Statistics with R and PostgreSQL
Description: Archive and manage times series data from official statistics. The 'timeseriesdb' package was designed to manage a large catalog of time series from official statistics which are typically published on a monthly, quarterly or yearly basis. Thus timeseriesdb is optimized to handle updates caused by data revision as well as elaborate, multi-lingual meta information.
Author: Matthias Bannert [aut, cre], Severin Thoeni [aut], Ioan Gabriel Bucur [ctb]
Maintainer: Matthias Bannert <bannert@kof.ethz.ch>

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Package tiledb updated to version 0.11.1 with previous version 0.11.0 dated 2022-01-24

Title: Universal Storage Engine for Sparse and Dense Multidimensional Arrays
Description: The universal storage engine 'TileDB' introduces a powerful on-disk format for multi-dimensional arrays. It supports dense and sparse arrays, dataframes and key-values stores, cloud storage ('S3', 'GCS', 'Azure'), chunked arrays, multiple compression, encryption and checksum filters, uses a fully multi-threaded implementation, supports parallel I/O, data versioning ('time travel'), metadata and groups. It is implemented as an embeddable cross-platform C++ library with APIs from several languages, and integrations.
Author: TileDB, Inc. [aut, cph], Dirk Eddelbuettel [cre]
Maintainer: Dirk Eddelbuettel <dirk@tiledb.com>

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Package TesiproV updated to version 0.9.2 with previous version 0.9.1 dated 2022-01-17

Title: Calculation of Reliability and Failure Probability in Civil Engineering
Description: Calculate the failure probability of civil engineering problems with Level I up to Level III Methods. Have fun and enjoy. References: Spaethe (1991, ISBN:3-211-82348-4) "Die Sicherheit tragender Baukonstruktionen", AU,BECK (2001) "Estimation of small failure probabilities in high dimensions by subset simulation." <doi:10.1016/S0266-8920(01)00019-4>, Breitung (1989) "Asymptotic approximations for probability integrals." <doi:10.1016/0266-8920(89)90024-6>.
Author: Konstantin Nille-Hauf [aut, cre], Tania Feiri [aut], Marcus Ricker [aut]
Maintainer: Konstantin Nille-Hauf <konstantin.nillehauf@googlemail.com>

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Package taxonbridge updated to version 1.0.5 with previous version 1.0.4 dated 2022-03-08

Title: Create Custom Taxonomies Based on the NCBI Taxonomy and GBIF Backbone Taxonomy
Description: The NCBI taxonomy is a popular resource for taxonomic studies but it only contains data on species with sequence data whereas the GBIF has a more extensive coverage of extinct species. Taxonbridge is useful for the creation and analysis of custom taxonomies based on the NCBI taxonomy and GBIF backbone taxonomy.
Author: Werner Veldsman [aut, cre]
Maintainer: Werner Veldsman <wernerpieter.veldsman@unil.ch>

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Package survivalmodels updated to version 0.1.13 with previous version 0.1.12 dated 2022-03-11

Title: Models for Survival Analysis
Description: Implementations of classical and machine learning models for survival analysis, including deep neural networks via 'keras' and 'tensorflow'. Each model includes a separated fit and predict interface with consistent prediction types for predicting risk, survival probabilities, or survival distributions with 'distr6' <https://CRAN.R-project.org/package=distr6>. Models are either implemented from 'Python' via 'reticulate' <https://CRAN.R-project.org/package=reticulate>, from code in GitHub packages, or novel implementations using 'Rcpp' <https://CRAN.R-project.org/package=Rcpp>. Novel machine learning survival models wil be included in the package in near-future updates. Neural networks are implemented from the 'Python' package 'pycox' <https://github.com/havakv/pycox> and are detailed by Kvamme et al. (2019) <https://jmlr.org/papers/v20/18-424.html>. The 'Akritas' estimator is defined in Akritas (1994) <doi:10.1214/aos/1176325630>. 'DNNSurv' is defined in Zhao and Feng (2020) <arXiv:1908.02337>.
Author: Raphael Sonabend [aut, cre]
Maintainer: Raphael Sonabend <raphaelsonabend@gmail.com>

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Package SuperExactTest updated to version 1.1.0 with previous version 1.0.7 dated 2019-06-21

Title: Exact Test and Visualization of Multi-Set Intersections
Description: Identification of sets of objects with shared features is a common operation in all disciplines. Analysis of intersections among multiple sets is fundamental for in-depth understanding of their complex relationships. This package implements a theoretical framework for efficient computation of statistical distributions of multi-set intersections based upon combinatorial theory, and provides multiple scalable techniques for visualizing the intersection statistics. The statistical algorithm behind this package was published in Wang et al. (2015) <doi:10.1038/srep16923>.
Author: Minghui Wang, Yongzhong Zhao and Bin Zhang
Maintainer: Minghui Wang <minghui.wang@mssm.edu>

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Package sumFREGAT updated to version 1.2.4 with previous version 1.2.3 dated 2022-03-09

Title: Fast Region-Based Association Tests on Summary Statistics
Description: An adaptation of classical region/gene-based association analysis techniques to the use of summary statistics (P values and effect sizes) and correlations between genetic variants as input. It is a tool to perform the most popular and efficient gene-based tests using the results of genome-wide association (meta-)analyses without having the original genotypes and phenotypes at hand.
Author: Nadezhda M. Belonogova <belon@bionet.nsc.ru> and Gulnara R. Svishcheva <gulsvi@bionet.nsc.ru> with contributions from: Seunggeun Lee , Pierre Lafaye de Micheaux , Thomas Lumley , Minghui Wang, Yiyuan Liu, Shizhong Han , Yaowu Liu , James O. Ramsay , [...truncated...]
Maintainer: Nadezhda M. Belonogova <belon@bionet.nsc.ru>

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Package stevemisc updated to version 1.4.0 with previous version 1.3.0 dated 2021-10-22

Title: Steve's Miscellaneous Functions
Description: These are miscellaneous functions that I find useful for my research and teaching. The contents include themes for plots, functions for simulating quantities of interest from regression models, functions for simulating various forms of fake data for instructional/research purposes, and many more. All told, the functions provided here are broadly useful for data organization, data presentation, data recoding, and data simulation.
Author: Steve Miller [aut, cre], Ben Bolker [ctb], Dave Armstrong [ctb], John Fox [ctb], Winston Chang [ctb], Brian Ripley [ctb], Bill Venables [ctb], Pascal van Kooten [ctb], Gerko Vink [ctb], Paul Williamson [ctb], Andreas Beger [ctb] , Vincent Arel-Bundoc [...truncated...]
Maintainer: Steve Miller <steven.v.miller@gmail.com>

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Package spreval updated to version 1.1.0 with previous version 1.0.0 dated 2021-07-06

Title: Evaluation of Sprinkler Irrigation Uniformity and Efficiency
Description: Processing and analysis of field collected or simulated sprinkler system catch data (depths) to characterize irrigation uniformity and efficiency using standard and other measures. Standard measures include the Christiansen coefficient of uniformity (CU) as found in Christiansen, J.E.(1942, ISBN:0138779295, "Irrigation by Sprinkling"); and distribution uniformity (DU), potential efficiency of the low quarter (PELQ), and application efficiency of the low quarter (AELQ) that are implementations of measures of the same notation in Keller, J. and Merriam, J.L. (1978) "Farm Irrigation System Evaluation: A Guide for Management" <https://pdf.usaid.gov/pdf_docs/PNAAG745.pdf>. spreval::DU.lh is similar to spreval::DU but is the distribution uniformity of the low half instead of low quarter as in DU. spreval::PELQT is a version of spreval::PELQ adapted for traveling systems instead of lateral move or solid-set sprinkler systems. The function spreval::eff is analogous to the method used to compute application efficiency for furrow irrigation presented in Walker, W. and Skogerboe, G.V. (1987,ISBN:0138779295, "Surface Irrigation: Theory and Practice"),that uses piecewise integration of infiltrated depth compared against soil-moisture deficit (SMD), when the argument "target" is set equal to SMD. The other functions contained in the package provide graphical representation of sprinkler system uniformity, and other standard univariate parametric and non-parametric statistical measures as applied to sprinkler system catch depths. A sample data set of field test data spreval::catchcan (catch depths) is provided and is used in examples and vignettes. Agricultural systems emphasized, but this package can be used for landscape irrigation evaluation, and a landscape (turf) vignette is included as an example application.
Author: Garry Grabow [aut, cre, cph]
Maintainer: Garry Grabow <glgrabow@ncsu.edu>

Diff between spreval versions 1.0.0 dated 2021-07-06 and 1.1.0 dated 2022-03-25

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More information about spreval at CRAN
Permanent link

Package spaMM updated to version 3.11.3 with previous version 3.10.0 dated 2022-02-06

Title: Mixed-Effect Models, with or without Spatial Random Effects
Description: Inference based on models with or without spatially-correlated random effects, multivariate responses, or non-Gaussian random effects (e.g., Beta). Variation in residual variance (heteroscedasticity) can itself be represented by a mixed-effect model. Both classical geostatistical models (Rousset and Ferdy 2014 <doi:10.1111/ecog.00566>), and Markov random field models on irregular grids (as considered in the 'INLA' package, <https://www.r-inla.org>), can be fitted, with distinct computational procedures exploiting the sparse matrix representations for the latter case and other autoregressive models. Laplace approximations are used for likelihood or restricted likelihood. Penalized quasi-likelihood and other variants discussed in the h-likelihood literature (Lee and Nelder 2001 <doi:10.1093/biomet/88.4.987>) are also implemented.
Author: François Rousset [aut, cre, cph] , Jean-Baptiste Ferdy [aut, cph], Alexandre Courtiol [aut] , GSL authors [ctb]
Maintainer: François Rousset <francois.rousset@umontpellier.fr>

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More information about spaMM at CRAN
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New package sistmr with initial version 0.1.1
Package: sistmr
Title: A Collection of Utility Function from the Inserm/Inria SISTM Team
Version: 0.1.1
Author: Boris Hejblum [aut], Mélanie Huchon [aut, cre]
Maintainer: Mélanie Huchon <melanie.huchon@u-bordeaux.fr>
Description: Functions common to members of the SISTM team.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: BlandAltmanLeh, dplyr, ggbeeswarm, ggplot2, ggrepel, rlang, scales, stats
NeedsCompilation: no
Packaged: 2022-03-23 16:14:49 UTC; mh8
Repository: CRAN
Date/Publication: 2022-03-24 08:30:02 UTC

More information about sistmr at CRAN
Permanent link

Package shinypanel updated to version 0.1.5 with previous version 0.1.4 dated 2021-01-07

Title: Shiny Control Panel
Description: Add shiny inputs with one or more inline buttons that grow and shrink with inputs. Also add tool tips to input buttons and styling and messages for input validation.
Author: Alex Pickering
Maintainer: Alex Pickering <alexvpickering@gmail.com>

Diff between shinypanel versions 0.1.4 dated 2021-01-07 and 0.1.5 dated 2022-03-25

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Package shiny.reglog updated to version 0.5.0 with previous version 0.4.1 dated 2021-10-28

Title: Optional Login and Registration Module System for ShinyApps
Description: RegLog system provides a set of shiny modules to handle register procedure for your users, alongside with login, edit credentials and password reset functionality. It provides support for popular SQL databases and optionally googlesheet-based database for easy setup. For email sending it provides support for 'emayili' and 'gmailr' backends. Architecture makes customizing usability pretty straightforward. The authentication system created with shiny.reglog is designed to be optional: user don't need to be logged-in to access your application, but when logged-in the user data can be used to read from and write to relational databases.
Author: Michal Kosinski [aut, cre]
Maintainer: Michal Kosinski <kosinski.mich@gmail.com>

Diff between shiny.reglog versions 0.4.1 dated 2021-10-28 and 0.5.0 dated 2022-03-25

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Package SEMgraph updated to version 1.1.0 with previous version 1.0.5 dated 2022-01-03

Title: Network Analysis and Causal Inference Through Structural Equation Modeling
Description: Estimate networks and causal relationships in complex systems through Structural Equation Modeling. This package also includes functions to import, weight, manipulate, and fit biological network models within the Structural Equation Modeling framework described in Palluzzi and Grassi (2021) <arXiv:2103.08332>.
Author: Mario Grassi [aut], Fernando Palluzzi [aut], Barbara Tarantino [aut, cre]
Maintainer: Barbara Tarantino <barbara.tarantino01@universitadipavia.it>

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Package segmented updated to version 1.4-1 with previous version 1.4-0 dated 2022-01-28

Title: Regression Models with Break-Points / Change-Points Estimation
Description: Given a regression model, segmented `updates' it by adding one or more segmented (i.e., piece-wise linear) relationships. Several variables with multiple breakpoints are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

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Package sdcSpatial updated to version 0.5.2 with previous version 0.1.1 dated 2019-07-19

Title: Statistical Disclosure Control for Spatial Data
Description: Privacy protected raster maps can be created from spatial point data. Protection methods include smoothing of dichotomous variables by de Jonge and de Wolf (2016) <doi:10.1007/978-3-319-45381-1_9>, continuous variables by de Wolf and de Jonge (2018) <doi:10.1007/978-3-319-99771-1_23>, suppressing revealing values and a generalization of the quad tree method by Suñé, Rovira, Ibáñez and Farré (2017) <doi:10.2901/EUROSTAT.C2017.001>.
Author: Edwin de Jonge [aut, cre] , Peter-Paul de Wolf [aut], Douwe Hut [ctb], Sapphire Han [ctb]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

Diff between sdcSpatial versions 0.1.1 dated 2019-07-19 and 0.5.2 dated 2022-03-25

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Package scpi updated to version 0.2.1 with previous version 0.1 dated 2022-02-23

Title: Prediction Intervals for Synthetic Control Methods
Description: Implementation of estimation and inference procedures for Synthetic Control methods using least square, lasso, ridge, or simplex-type constraints. Uncertainty is quantified with prediction intervals as developed in Cattaneo, Feng, and Titiunik (2021) <https://cattaneo.princeton.edu/papers/Cattaneo-Feng-Titiunik_2021_JASA.pdf>.
Author: Matias Cattaneo [aut], Yingjie Feng [aut], Filippo Palomba [aut, cre], Rocio Titiunik [aut]
Maintainer: Filippo Palomba <fpalomba@princeton.edu>

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Package scITD updated to version 1.0.2 with previous version 1.0.1 dated 2022-01-28

Title: Single-Cell Interpretable Tensor Decomposition
Description: Single-cell Interpretable Tensor Decomposition (scITD) employs the Tucker tensor decomposition to extract multicell-type gene expression patterns that vary across donors/individuals. This tool is geared for use with single-cell RNA-sequencing datasets consisting of many source donors. The method has a wide range of potential applications, including the study of inter-individual variation at the population-level, patient sub-grouping/stratification, and the analysis of sample-level batch effects. Each "multicellular process" that is extracted consists of (A) a multi cell type gene loadings matrix and (B) a corresponding donor scores vector indicating the level at which the corresponding loadings matrix is expressed in each donor. Additional methods are implemented to aid in selecting an appropriate number of factors and to evaluate stability of the decomposition. Additional tools are provided for downstream analysis, including integration of gene set enrichment analysis and ligand-receptor analysis. Tucker, L.R. (1966) <doi:10.1007/BF02289464>. Unkel, S., Hannachi, A., Trendafilov, N. T., & Jolliffe, I. T. (2011) <doi:10.1007/s13253-011-0055-9>. Zhou, G., & Cichocki, A. (2012) <doi:10.2478/v10175-012-0051-4>.
Author: Jonathan Mitchel [cre, aut], Evan Biederstedt [aut], Peter Kharchenko [aut]
Maintainer: Jonathan Mitchel <jonathan.mitchel3@gmail.com>

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Package scan updated to version 0.54 with previous version 0.53 dated 2021-09-22

Title: Single-Case Data Analyses for Single and Multiple Baseline Designs
Description: A collection of procedures for analysing, visualising, and managing single-case data. These include piecewise linear regression models, multilevel models, overlap indices (PND, PEM, PAND, PET, tauU, baseline corrected tau, CDC), and randomization tests. Data preparation functions support outlier detection, handling missing values, scaling, truncating, rank transformation, and smoothing. An exporting function helps to generate html and latex tables in a publication friendly style. More details can be found at <https://jazznbass.github.io/scan-Book/>.
Author: Juergen Wilbert [cre, aut] , Timo Lueke [aut]
Maintainer: Juergen Wilbert <juergen.wilbert@uni-potsdam.de>

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Package sass updated to version 0.4.1 with previous version 0.4.0 dated 2021-05-12

Title: Syntactically Awesome Style Sheets ('Sass')
Description: An 'SCSS' compiler, powered by the 'LibSass' library. With this, R developers can use variables, inheritance, and functions to generate dynamic style sheets. The package uses the 'Sass CSS' extension language, which is stable, powerful, and CSS compatible.
Author: Joe Cheng [aut], Timothy Mastny [aut], Richard Iannone [aut] , Barret Schloerke [aut] , Carson Sievert [aut, cre] , Christophe Dervieux [ctb] , RStudio [cph, fnd], Sass Open Source Foundation [ctb, cph] , Greter Marcel [ctb, cph] , Mifsud Michael [ct [...truncated...]
Maintainer: Carson Sievert <carson@rstudio.com>

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Package rsoi updated to version 0.5.5 with previous version 0.5.4 dated 2020-08-11

Title: Import Various Northern and Southern Hemisphere Climate Indices
Description: Downloads Southern Oscillation Index, Oceanic Nino Index, North Pacific Gyre Oscillation data, North Atlantic Oscillation and Arctic Oscillation. Data sources are described in the help files for each function.
Author: Sam Albers [aut, cre], Elio Campitelli [ctb]
Maintainer: Sam Albers <sam.albers@gmail.com>

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Permanent link

Package rscorecard updated to version 0.22.0 with previous version 0.21.0 dated 2022-02-08

Title: A Method to Download Department of Education College Scorecard Data
Description: A method to download Department of Education College Scorecard data using the public API <https://collegescorecard.ed.gov/data/documentation/>. It is based on the 'dplyr' model of piped commands to select and filter data in a single chained function call. An API key from the U.S. Department of Education is required.
Author: Benjamin Skinner [aut, cre]
Maintainer: Benjamin Skinner <btskinner@coe.ufl.edu>

Diff between rscorecard versions 0.21.0 dated 2022-02-08 and 0.22.0 dated 2022-03-25

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Permanent link

Package robcp updated to version 0.3.4 with previous version 0.3.3 dated 2021-10-29

Title: Robust Change-Point Tests
Description: Provides robust methods to detect change-points in uni- or multivariate time series. They can cope with corrupted data and heavy tails. Focus is on the detection of abrupt changes in location, but changes scale or dependence structure can be detected as well. This package provides tests for change detection in uni- and multivariate time series based on Huberized versions of CUSUM tests proposed in Duerre and Fried (2019) <arXiv:1905.06201>, and tests for change detection in univariate time series based on 2-sample U-statistics or 2-sample U-quantiles as proposed by Dehling et al. (2015) <DOI:10.1007/978-1-4939-3076-0_12> and Dehling, Fried and Wendler (2020) <DOI:10.1093/biomet/asaa004>. Furthermore, the packages provides tests on changes in the scale or the correlation as proposed in Gerstenberger, Vogel and Wendler (2020) <DOI:10.1080/01621459.2019.1629938>, Dehling et al. (2017) <DOI:10.1017/S026646661600044X>, and Wied et al. (2014) <DOI:10.1016/j.csda.2013.03.005>.
Author: Sheila Goerz [aut, cre], Alexander Duerre [aut]
Maintainer: Sheila Goerz <sheila.goerz@tu-dortmund.de>

Diff between robcp versions 0.3.3 dated 2021-10-29 and 0.3.4 dated 2022-03-25

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Package rmumps updated to version 5.2.1-15 with previous version 5.2.1-14 dated 2021-08-12

Title: Wrapper for MUMPS Library
Description: Some basic features of 'MUMPS' (Multifrontal Massively Parallel sparse direct Solver) are wrapped in a class whose methods can be used for sequentially solving a sparse linear system (symmetric or not) with one or many right hand sides (dense or sparse). There is a possibility to do separately symbolic analysis, LU (or LDL^t) factorization and system solving. Third part ordering libraries are included and can be used: 'PORD', 'METIS', 'SCOTCH'. 'MUMPS' method was first described in Amestoy et al. (2001) <doi:10.1137/S0895479899358194> and Amestoy et al. (2006) <doi:10.1016/j.parco.2005.07.004>.
Author: Serguei Sokol [aut, cre], Emmanuel Agullo [ctb], Patrick Amestoy [ctb, cph], Maurice Bremond [ctb], Alfredo Buttari [ctb], Philippe Combes [ctb], Marie Durand [ctb], Aurelia Fevre [ctb], Abdou Guermouche [ctb], Guillaume Joslin [ctb], Jacko Koster [c [...truncated...]
Maintainer: Serguei Sokol <sokol@insa-toulouse.fr>

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Package RJDemetra updated to version 0.2.0 with previous version 0.1.9 dated 2021-11-11

Title: Interface to 'JDemetra+' Seasonal Adjustment Software
Description: Interface around 'JDemetra+' (<https://github.com/jdemetra/jdemetra-app>), the seasonal adjustment software officially recommended to the members of the European Statistical System (ESS) and the European System of Central Banks. It offers full access to all options and outputs of 'JDemetra+', including the two leading seasonal adjustment methods TRAMO/SEATS+ and X-12ARIMA/X-13ARIMA-SEATS.
Author: Alain Quartier-la-Tente [aut, cre] , Anna Michalek [aut], Jean Palate [aut], Raf Baeyens [aut]
Maintainer: Alain Quartier-la-Tente <alain.quartier@yahoo.fr>

Diff between RJDemetra versions 0.1.9 dated 2021-11-11 and 0.2.0 dated 2022-03-25

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Package RJDBC updated to version 0.2-10 with previous version 0.2-8 dated 2020-03-10

Title: Provides Access to Databases Through the JDBC Interface
Description: The RJDBC package is an implementation of R's DBI interface using JDBC as a back-end. This allows R to connect to any DBMS that has a JDBC driver.
Author: Simon Urbanek <Simon.Urbanek@r-project.org>
Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org>

Diff between RJDBC versions 0.2-8 dated 2020-03-10 and 0.2-10 dated 2022-03-25

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Package restatapi updated to version 0.13.1 with previous version 0.12.8 dated 2022-01-26

Title: Search and Retrieve Data from Eurostat Database
Description: Eurostat is the statistical office of the European Union and provides high quality statistics for Europe. Large set of the data is disseminated through the Eurostat database (<https://ec.europa.eu/eurostat/data/database>). The tools are using the REST API with the Statistical Data and Metadata eXchange (SDMX) Web Services (<https://ec.europa.eu/eurostat/web/sdmx-web-services/about-this-service>) to search and download data from the Eurostat database using the SDMX standard.
Author: Matyas Mészaros [aut, cre]
Maintainer: Matyas Mészaros <matyas.meszaros@ec.europa.eu>

Diff between restatapi versions 0.12.8 dated 2022-01-26 and 0.13.1 dated 2022-03-25

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Package rcbalance updated to version 1.8.8 with previous version 1.8.7 dated 2022-03-25

Title: Large, Sparse Optimal Matching with Refined Covariate Balance
Description: Tools for large, sparse optimal matching of treated units and control units in observational studies. Provisions are made for refined covariate balance constraints, which include fine and near-fine balance as special cases. Matches are optimal in the sense that they are computed as solutions to network optimization problems rather than greedy algorithms. See Pimentel, et al.(2015) <doi:10.1080/01621459.2014.997879> and Pimentel (2016), Obs. Studies 2(1):4-23. The rrelaxiv package, which provides an alternative solver for the underlying network flow problems, carries an academic license and is not available on CRAN, but may be downloaded from Github at <https://github.com/josherrickson/rrelaxiv/>.
Author: Samuel D. Pimentel
Maintainer: Samuel D. Pimentel <spi@berkeley.edu>

Diff between rcbalance versions 1.8.7 dated 2022-03-25 and 1.8.8 dated 2022-03-25

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New package rcbsubset with initial version 1.1.7
Package: rcbsubset
Title: Optimal Subset Matching with Refined Covariate Balance
Version: 1.1.7
Date: 2022-3-23
Author: Samuel D. Pimentel
Maintainer: Samuel D. Pimentel <spi@berkeley.edu>
Description: Tools for optimal subset matching of treated units and control units in observational studies, with support for refined covariate balance constraints, (including fine and near-fine balance as special cases). A close relative is the 'rcbalance' package. See Pimentel, et al.(2015) <doi:10.1080/01621459.2014.997879> and Pimentel and Kelz (2020) <doi:10.1080/01621459.2020.1720693>. The rrelaxiv package, which provides an alternative solver for the underlying network flow problems, carries an academic license and is not available on CRAN, but may be downloaded from Github at <https://github.com/josherrickson/rrelaxiv/>.
Depends: R (>= 3.2.0), MASS, plyr
Imports: rcbalance, rlemon
License: MIT + file LICENSE
Suggests: testthat, rrelaxiv, optmatch
Additional_repositories: https://errickson.net/rrelaxiv/
NeedsCompilation: no
Packaged: 2022-03-25 16:55:11 UTC; sdbpimentel
Repository: CRAN
Date/Publication: 2022-03-25 23:20:06 UTC

More information about rcbsubset at CRAN
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Package Nmix updated to version 2.0.0 with previous version 1.2.1 dated 2022-02-01

Title: Bayesian Inference on Univariate Normal Mixtures
Description: A program for Bayesian analysis of univariate normal mixtures with an unknown number of components, following the approach of Richardson and Green (1997) <doi:10.1111/1467-9868.00095>. This makes use of reversible jump Markov chain Monte Carlo methods that are capable of jumping between the parameter sub-spaces corresponding to different numbers of components in the mixture. A sample from the full joint distribution of all unknown variables is thereby generated, and this can be used as a basis for a thorough presentation of many aspects of the posterior distribution.
Author: Peter Green [aut, cre]
Maintainer: Peter Green <P.J.Green@bristol.ac.uk>

Diff between Nmix versions 1.2.1 dated 2022-02-01 and 2.0.0 dated 2022-03-25

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Package bucky updated to version 1.0.7 with previous version 1.0.6 dated 2019-12-17

Title: Bucky's Archive for Data Analysis in the Social Sciences
Description: Provides functions for various statistical techniques commonly used in the social sciences, including functions to compute clustered robust standard errors, combine results across multiply-imputed data sets, and simplify the addition of robust and clustered robust standard errors.
Author: Alexander Tahk [aut, cre]
Maintainer: Alexander Tahk <tahk@alum.mit.edu>

Diff between bucky versions 1.0.6 dated 2019-12-17 and 1.0.7 dated 2022-03-25

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New package respR with initial version 2.0.2
Package: respR
Title: Import, Process, Analyse, and Calculate Rates from Respirometry Data
Date: 2022-03-23
Version: 2.0.2
Maintainer: Nicholas Carey <nicholascarey@gmail.com>
Description: Provides a structural, reproducible workflow for the processing and analysis of respirometry data. It contains analytical functions and utilities for working with oxygen time-series to determine respiration or oxygen production rates, and to make it easier to report and share analyses.
URL: https://github.com/januarharianto/respr, https://doi.org/10.5281/zenodo.2548601, https://januarharianto.github.io/respR/
Depends: R (>= 3.3)
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: data.table, dplyr, glue, graphics, grDevices, lubridate, magrittr, marelac, purrr, readxl, roll, segmented, stats, stringr, utils, xml2
Suggests: knitr, rmarkdown, rMR, DiagrammeR, FishResp, respirometry, testthat, covr
NeedsCompilation: no
Packaged: 2022-03-23 14:22:02 UTC; nicholascarey
Author: Januar Harianto [aut], Nicholas Carey [aut, cre]
Repository: CRAN
Date/Publication: 2022-03-23 15:50:02 UTC

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Package rENA updated to version 0.2.4 with previous version 0.2.3 dated 2021-04-23

Title: Epistemic Network Analysis
Description: ENA (Shaffer, D. W. (2017) Quantitative Ethnography. ISBN: 0578191687) is a method used to identify meaningful and quantifiable patterns in discourse or reasoning. ENA moves beyond the traditional frequency-based assessments by examining the structure of the co-occurrence, or connections in coded data. Moreover, compared to other methodological approaches, ENA has the novelty of (1) modeling whole networks of connections and (2) affording both quantitative and qualitative comparisons between different network models. Shaffer, D.W., Collier, W., & Ruis, A.R. (2016).
Author: Cody L Marquart [aut, cre] , Zachari Swiecki [aut], Wesley Collier [aut], Brendan Eagan [aut], Roman Woodward [aut], David Williamson Shaffer [aut]
Maintainer: Cody L Marquart <cody.marquart@wisc.edu>

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Package RcppCNPy updated to version 0.2.11 with previous version 0.2.10 dated 2018-07-29

Title: Read-Write Support for 'NumPy' Files via 'Rcpp'
Description: The 'cnpy' library written by Carl Rogers provides read and write facilities for files created with (or for) the 'NumPy' extension for 'Python'. Vectors and matrices of numeric types can be read or written to and from files as well as compressed files. Support for integer files is available if the package has been built with -std=c++11 which should be the default on all platforms since the release of R 3.3.0.
Author: Dirk Eddelbuettel and Wush Wu
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppCNPy versions 0.2.10 dated 2018-07-29 and 0.2.11 dated 2022-03-25

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Package rcbalance updated to version 1.8.7 with previous version 1.8.6 dated 2022-03-02

Title: Large, Sparse Optimal Matching with Refined Covariate Balance
Description: Tools for large, sparse optimal matching of treated units and control units in observational studies. Provisions are made for refined covariate balance constraints, which include fine and near-fine balance as special cases. Matches are optimal in the sense that they are computed as solutions to network optimization problems rather than greedy algorithms. See Pimentel, et al.(2015) <doi:10.1080/01621459.2014.997879> and Pimentel (2016), Obs. Studies 2(1):4-23. The rrelaxiv package, which provides an alternative solver for the underlying network flow problems, carries an academic license and is not available on CRAN, but may be downloaded from Github at <https://github.com/josherrickson/rrelaxiv/>.
Author: Samuel D. Pimentel
Maintainer: Samuel D. Pimentel <spi@berkeley.edu>

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Package RandomFieldsUtils updated to version 1.2.2 with previous version 1.1.0 dated 2022-01-18

Title: Utilities for the Simulation and Analysis of Random Fields and Genetic Data
Description: Various utilities are provided that might be used in spatial statistics and elsewhere. It delivers a method for solving linear equations that checks the sparsity of the matrix before any algorithm is used.
Author: Martin Schlather [aut, cre], Alexander FreudenBerg [aut], Reinhard Furrer [ctb], Martin Kroll [ctb], Brian D. Ripley [ctb], John W. Ratcliff et al.
Maintainer: Martin Schlather <schlather@math.uni-mannheim.de>

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Package Radviz updated to version 0.9.3 with previous version 0.9.2 dated 2020-06-24

Title: Project Multidimensional Data in 2D Space
Description: An implementation of the radviz projection in R. It enables the visualization of multidimensional data while maintaining the relation to the original dimensions. This package provides functions to create and plot radviz projections, and a number of summary plots that enable comparison and analysis. For reference see Ankerst *et al.* (1996) (<https://citeseer.ist.psu.edu/viewdoc/summary?doi=10.1.1.68.1811>) for original implementation, see Di Caro *et al* (2012) (<https://link.springer.com/chapter/10.1007/978-3-642-13672-6_13>) for the original method for dimensional anchor arrangements, see Demsar *et al.* (2007) (<doi:10.1016/j.jbi.2007.03.010>) for the original Freeviz implementation.
Author: Yann Abraham [aut, cre], Nicolas Sauwen [aut]
Maintainer: Yann Abraham <yann.abraham@gmail.com>

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Package qqboxplot updated to version 0.2.0 with previous version 0.1.0 dated 2021-05-10

Title: Implementation of the Q-Q Boxplot
Description: A system to implement the Q-Q boxplot. It is implemented as an extension to 'ggplot2'. The Q-Q boxplot is an amalgam of the boxplot and the Q-Q plot and allows the user to rapidly examine summary statistics and tail behavior for multiple distributions in the same pane. As an extension of the 'ggplot2' implementation of the boxplot, possible modifications to the boxplot extend to the Q-Q boxplot.
Author: Jordan Rodu [aut, cre]
Maintainer: Jordan Rodu <jordan.rodu@gmail.com>

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Package psymetadata updated to version 1.0.1 with previous version 1.0.0 dated 2021-05-31

Title: Open Datasets from Meta-Analyses in Psychology Research
Description: Data and examples from meta-analyses in psychology research.
Author: Josue E. Rodriguez [aut, cre], Donald Williams [aut]
Maintainer: Josue E. Rodriguez <josue.rodriguez594@gmail.com>

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Package processx updated to version 3.5.3 with previous version 3.5.2 dated 2021-04-30

Title: Execute and Control System Processes
Description: Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes. It can read the standard output and error of the processes, using non-blocking connections. 'processx' can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
Author: Gabor Csardi [aut, cre, cph] , Winston Chang [aut], RStudio [cph, fnd], Mango Solutions [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package POFIBGE updated to version 0.1.6 with previous version 0.1.5 dated 2021-11-30

Title: Downloading, Reading and Analyzing POF Microdata - Package in Development
Description: Provides tools for downloading, reading and analyzing the POF, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package PNSIBGE updated to version 0.1.7 with previous version 0.1.6 dated 2021-11-30

Title: Downloading, Reading and Analyzing PNS Microdata
Description: Provides tools for downloading, reading and analyzing the PNS, a household survey from Brazilian Institute of Geography and Statistics - IBGE. The data must be downloaded from the official website <https://www.ibge.gov.br/>. Further analysis must be made using package 'survey'.
Author: Gabriel Assuncao [aut, cre], Luna Hidalgo [aut], Douglas Braga [ctb]
Maintainer: Gabriel Assuncao <pacotesipd@ibge.gov.br>

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Package plyr updated to version 1.8.7 with previous version 1.8.6 dated 2020-03-03

Title: Tools for Splitting, Applying and Combining Data
Description: A set of tools that solves a common set of problems: you need to break a big problem down into manageable pieces, operate on each piece and then put all the pieces back together. For example, you might want to fit a model to each spatial location or time point in your study, summarise data by panels or collapse high-dimensional arrays to simpler summary statistics. The development of 'plyr' has been generously supported by 'Becton Dickinson'.
Author: Hadley Wickham [aut, cre]
Maintainer: Hadley Wickham <hadley@rstudio.com>

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Package photobiology updated to version 0.10.10 with previous version 0.10.9 dated 2022-02-04

Title: Photobiological Calculations
Description: Definitions of classes, methods, operators and functions for use in photobiology and radiation meteorology and climatology. Calculation of effective (weighted) and not-weighted irradiances/doses, fluence rates, transmittance, reflectance, absorptance, absorbance and diverse ratios and other derived quantities from spectral data. Local maxima and minima: peaks, valleys and spikes. Conversion between energy-and photon-based units. Wavelength interpolation. Astronomical calculations related solar angles and day length. Colours and vision. This package is part of the 'r4photobiology' suite, Aphalo, P. J. (2015) <doi:10.19232/uv4pb.2015.1.14>.
Author: Pedro J. Aphalo [aut, cre] , Titta K. Kotilainen [ctb] , Glenn Davis [ctb], Agnese Fazio [ctb]
Maintainer: Pedro J. Aphalo <pedro.aphalo@helsinki.fi>

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Package peacesciencer updated to version 1.0.0 with previous version 0.7.0 dated 2021-11-11

Title: Tools and Data for Quantitative Peace Science Research
Description: These are useful tools and data sets for the study of quantitative peace science. The goal for this package is to include tools and data sets for doing original research that mimics well what a user would have to previously get from a software package that may not be well-sourced or well-supported. Those software bundles were useful the extent to which they encourage replications of long-standing analyses by starting the data-generating process from scratch. However, a lot of the functionality can be done relatively quickly and more transparently in the R programming language.
Author: Steve Miller [aut, cre]
Maintainer: Steve Miller <steven.v.miller@gmail.com>

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Package pdynmc updated to version 0.9.7 with previous version 0.9.6 dated 2021-10-14

Title: Moment Condition Based Estimation of Linear Dynamic Panel Data Models
Description: Linear dynamic panel data modeling based on linear and nonlinear moment conditions as proposed by Holtz-Eakin, Newey, and Rosen (1988) <doi:10.2307/1913103>, Ahn and Schmidt (1995) <doi:10.1016/0304-4076(94)01641-C>, and Arellano and Bover (1995) <doi:10.1016/0304-4076(94)01642-D>. Estimation of the model parameters relies on the Generalized Method of Moments (GMM), numerical optimization (when nonlinear moment conditions are employed) and the computation of closed form solutions (when estimation is based on linear moment conditions). One-step, two-step and iterated estimation is available. For inference and specification testing, Windmeijer (2005) <doi:10.1016/j.jeconom.2004.02.005> and doubly corrected standard errors (Hwang, Kang, Lee, 2021 <doi:10.1016/j.jeconom.2020.09.010>) are available. Additionally, serial correlation tests, tests for overidentification, and Wald tests are provided. Functions for visualizing panel data structures and modeling results obtained from GMM estimation are also available. The plot methods include functions to plot unbalanced panel structure, coefficient ranges and coefficient paths across GMM iterations (the latter is implemented according to the plot shown in Hansen and Lee, 2021 <doi:10.3982/ECTA16274>). For a more detailed description of the functionality, please see Fritsch, Pua, Schnurbus (2021) <doi:10.32614/RJ-2021-035>.
Author: Markus Fritsch [aut, cre], Joachim Schnurbus [aut], Andrew Adrian Yu Pua [aut]
Maintainer: Markus Fritsch <Markus.Fritsch@uni-Passau.de>

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Package parsec updated to version 1.2.6 with previous version 1.2.4 dated 2021-05-14

Title: Partial Orders in Socio-Economics
Description: Implements tools for the analysis of partially ordered data, with a particular focus on the evaluation of multidimensional systems of indicators and on the analysis of poverty. References, Fattore M. (2016) <doi:10.1007/s11205-015-1059-6> Fattore M., Arcagni A. (2016) <doi:10.1007/s11205-016-1501-4> Arcagni A. (2017) <doi:10.1007/978-3-319-45421-4_19>.
Author: Alberto Arcagni [aut, cre], Marco Fattore [aut]
Maintainer: Alberto Arcagni <alberto.arcagni@uniroma1.it>

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Package ottr updated to version 1.1.4 with previous version 1.1.3 dated 2022-02-07

Title: An R Autograding Extension for Otter-Grader
Description: An R autograding extension for Otter-Grader (<https://otter-grader.readthedocs.io>). It supports grading R scripts, RMarkdown documents, and R Jupyter Notebooks.
Author: Christopher Pyles [aut, cre] , UC Berkeley Data Science Education Program [cph]
Maintainer: Christopher Pyles <cpyles@berkeley.edu>

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Package nlme updated to version 3.1-157 with previous version 3.1-155 dated 2022-01-13

Title: Linear and Nonlinear Mixed Effects Models
Description: Fit and compare Gaussian linear and nonlinear mixed-effects models.
Author: José Pinheiro [aut] , Douglas Bates [aut] , Saikat DebRoy [ctb] , Deepayan Sarkar [ctb] , EISPACK authors [ctb] , Siem Heisterkamp [ctb] , Bert Van Willigen [ctb] , Johannes Ranke [ctb] ), R Core Team [aut, cre]
Maintainer: R Core Team <R-core@R-project.org>

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Package MOSS updated to version 0.2.2 with previous version 0.2.0 dated 2021-07-16

Title: Multi-Omic Integration via Sparse Singular Value Decomposition
Description: High dimensionality, noise and heterogeneity among samples and features challenge the omic integration task. Here we present an omic integration method based on sparse singular value decomposition (SVD) to deal with these limitations, by: a. obtaining the main axes of variation of the combined omics, b. imposing sparsity constraints at both subjects (rows) and features (columns) levels using Elastic Net type of shrinkage, and c. allowing both linear and non-linear projections (via t-Stochastic Neighbor Embedding) of the omic data to detect clusters in very convoluted data (Gonzalez-Reymundez et. al, 2022) <doi:10.1093/bioinformatics/btac179>.
Author: Agustin Gonzalez-Reymundez [aut, cre, cph], Alexander Grueneberg [aut], Ana Vazquez [ctb, ths]
Maintainer: Agustin Gonzalez-Reymundez <agugonrey@gmail.com>

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Package moodleR updated to version 1.0.0 with previous version 0.3.2 dated 2021-04-20

Title: Helper Functions to Work with 'Moodle' Data
Description: A collection of functions to connect to a 'Moodle' database, cache relevant tables locally and generate learning analytics. 'Moodle' is an open source Learning Management System (LMS) developed by MoodleHQ. For more information about Moodle, visit <https://moodle.org>.
Author: Aleksander Dietrichson [aut, cre], Chi Square Laboratories [cph], Darko Miletic [ctb], Pablo Pagnone [ctb], Alex Ondrus [ctb]
Maintainer: Aleksander Dietrichson <dietrichson@gmail.com>

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Package MolgenisAuth updated to version 0.0.21 with previous version 0.0.18 dated 2021-10-12

Title: 'OpenID Connect' Discovery and Authentication
Description: Discover 'OpenID Connect' endpoints and authenticate using device flow. Used by 'MOLGENIS' packages.
Author: Fleur Kelpin [aut] , Tommy de Boer [aut] , Sido Haakma [aut] , Mariska Slofstra [aut, cre] , MOLGENIS org [cph, fnd]
Maintainer: Mariska Slofstra <m.k.slofstra@umcg.nl>

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Package mi4p updated to version 0.9 with previous version 0.8 dated 2022-03-14

Title: Multiple Imputation for Proteomics
Description: A framework for multiple imputation for proteomics is proposed by Marie Chion, Christine Carapito and Frederic Bertrand (2021) <arxiv:2108.07086>. It is dedicated to dealing with multiple imputation for proteomics.
Author: Marie Chion [aut] , Christine Carapito [aut] , Frederic Bertrand [cre, aut] , Gordon Smyth [ctb], Davis McCarthy [ctb], Hélène Borges [ctb], Thomas Burger [ctb], Quentin Giai-Gianetto [ctb], Samuel Wieczorek [ctb]
Maintainer: Frederic Bertrand <frederic.bertrand@utt.fr>

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Package Matrix updated to version 1.4-1 with previous version 1.4-0 dated 2021-12-08

Title: Sparse and Dense Matrix Classes and Methods
Description: A rich hierarchy of matrix classes, including triangular, symmetric, and diagonal matrices, both dense and sparse and with pattern, logical and numeric entries. Numerous methods for and operations on these matrices, using 'LAPACK' and 'SuiteSparse' libraries.
Author: Douglas Bates [aut], Martin Maechler [aut, cre] , Mikael Jagan [aut] , Timothy A. Davis [ctb] )), Jens Oehlschlägel [ctb] ), Jason Riedy [ctb] and onenormest for octave, Copyright: Regents of the University of California), R Core Team [ctb]
Maintainer: Martin Maechler <mmaechler+Matrix@gmail.com>

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Package loo updated to version 2.5.1 with previous version 2.5.0 dated 2022-03-16

Title: Efficient Leave-One-Out Cross-Validation and WAIC for Bayesian Models
Description: Efficient approximate leave-one-out cross-validation (LOO) for Bayesian models fit using Markov chain Monte Carlo, as described in Vehtari, Gelman, and Gabry (2017) <doi:10.1007/s11222-016-9696-4>. The approximation uses Pareto smoothed importance sampling (PSIS), a new procedure for regularizing importance weights. As a byproduct of the calculations, we also obtain approximate standard errors for estimated predictive errors and for the comparison of predictive errors between models. The package also provides methods for using stacking and other model weighting techniques to average Bayesian predictive distributions.
Author: Aki Vehtari [aut], Jonah Gabry [cre, aut], Mans Magnusson [aut], Yuling Yao [aut], Paul-Christian Buerkner [aut], Topi Paananen [aut], Andrew Gelman [aut], Ben Goodrich [ctb], Juho Piironen [ctb], Bruno Nicenboim [ctb]
Maintainer: Jonah Gabry <jsg2201@columbia.edu>

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New package LocKer with initial version 1.0
Package: LocKer
Title: Locally Sparse Estimator of Generalized Varying Coefficient Model for Asynchronous Longitudinal Data
Version: 1.0
Description: Locally sparse estimator of generalized varying coefficient model for asynchronous longitudinal data by kernel-weighted estimating equation.
License: GPL (>= 3)
Encoding: UTF-8
Imports: fda, Matrix, psych, splines, stats
NeedsCompilation: no
Packaged: 2022-03-24 02:19:33 UTC; 11013
Author: Rou Zhong [aut, cre], Jingxiao Zhang [aut]
Maintainer: Rou Zhong <zhong_rou@163.com>
Repository: CRAN
Date/Publication: 2022-03-24 08:50:05 UTC

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Package LMest updated to version 3.0.3 with previous version 3.0.2 dated 2021-10-09

Title: Generalized Latent Markov Models
Description: Latent Markov models for longitudinal continuous and categorical data. See Bartolucci, Pandolfi, Pennoni (2017)<doi:10.18637/jss.v081.i04>.
Author: Francesco Bartolucci [aut, cre], Silvia Pandolfi [aut], Fulvia Pennoni [aut], Alessio Farcomeni [ctb], Alessio Serafini [ctb]
Maintainer: Francesco Bartolucci <bart@stat.unipg.it>

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Package leaflet updated to version 2.1.1 with previous version 2.1.0 dated 2022-02-16

Title: Create Interactive Web Maps with the JavaScript 'Leaflet' Library
Description: Create and customize interactive maps using the 'Leaflet' JavaScript library and the 'htmlwidgets' package. These maps can be used directly from the R console, from 'RStudio', in Shiny applications and R Markdown documents.
Author: Joe Cheng [aut, cre], Bhaskar Karambelkar [aut], Yihui Xie [aut], Hadley Wickham [ctb], Kenton Russell [ctb], Kent Johnson [ctb], Barret Schloerke [ctb], jQuery Foundation and contributors [ctb, cph] , Vladimir Agafonkin [ctb, cph] , CloudMade [cph] [...truncated...]
Maintainer: Joe Cheng <joe@rstudio.com>

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Package lares updated to version 5.1.1 with previous version 5.1.0 dated 2022-02-22

Title: Analytics & Machine Learning Sidekick
Description: Auxiliary package for better/faster analytics, visualization, data mining, and machine learning tasks. With a wide variety of family functions, like Machine Learning, Data Wrangling, Exploratory, and Scrapper, it helps the analyst or data scientist to get quick and robust results, without the need of repetitive coding or extensive programming skills.
Author: Bernardo Lares [aut, cre]
Maintainer: Bernardo Lares <laresbernardo@gmail.com>

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Package kstMatrix updated to version 0.1-3 with previous version 0.1-2 dated 2019-06-09

Title: Basic Functions in Knowledge Space Theory Using Matrix Representation
Description: Knowledge space theory by Doignon and Falmagne (1999) <doi:10.1007/978-3-642-58625-5> is a set- and order-theoretical framework, which proposes mathematical formalisms to operationalize knowledge structures in a particular domain. The 'kstMatrix' package provides basic functionalities to generate, handle, and manipulate knowledge structures and knowledge spaces. Opposed to the 'kst' package, 'kstMatrix' uses matrix representations for knowledge structures. Furthermore, 'kstMatrix' contains several knowledge spaces developed by the research group around Cornelia Dowling through querying experts.
Author: Cord Hockemeyer [aut, cre], Wai Wong [aut]
Maintainer: Cord Hockemeyer <cord.hockemeyer@uni-graz.at>

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Package knitr updated to version 1.38 with previous version 1.37 dated 2021-12-16

Title: A General-Purpose Package for Dynamic Report Generation in R
Description: Provides a general-purpose tool for dynamic report generation in R using Literate Programming techniques.
Author: Yihui Xie [aut, cre] , Abhraneel Sarma [ctb], Adam Vogt [ctb], Alastair Andrew [ctb], Alex Zvoleff [ctb], Andre Simon [ctb] , Aron Atkins [ctb], Aaron Wolen [ctb], Ashley Manton [ctb], Atsushi Yasumoto [ctb] , Ben Baumer [ctb], Brian Diggs [ctb], Bri [...truncated...]
Maintainer: Yihui Xie <xie@yihui.name>

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Package kerastuneR updated to version 0.1.0.5 with previous version 0.1.0.4 dated 2022-01-10

Title: Interface to 'Keras Tuner'
Description: 'Keras Tuner' <https://keras-team.github.io/keras-tuner/> is a hypertuning framework made for humans. It aims at making the life of AI practitioners, hypertuner algorithm creators and model designers as simple as possible by providing them with a clean and easy to use API for hypertuning. 'Keras Tuner' makes moving from a base model to a hypertuned one quick and easy by only requiring you to change a few lines of code.
Author: Turgut Abdullayev [aut, cre], Google Inc. [cph]
Maintainer: Turgut Abdullayev <turqut.a.314@gmail.com>

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Package hsrecombi updated to version 0.4.1 with previous version 0.3.4 dated 2021-03-23

Title: Estimation of Recombination Rate and Maternal LD in Half-Sibs
Description: Paternal recombination rate and maternal linkage disequilibrium (LD) are estimated for pairs of biallelic markers such as single nucleotide polymorphisms (SNPs) from progeny genotypes and sire haplotypes. The implementation relies on paternal half-sib families. If maternal half-sib families are used, the roles of sire/dam are swapped. Multiple families can be considered. For parameter estimation, at least one sire has to be double heterozygous at the investigated pairs of SNPs. Based on recombination rates, genetic distances between markers can be estimated. Markers with unusually large recombination rate to markers in close proximity (i.e. putatively misplaced markers) shall be discarded in this derivation. A workflow description is attached as vignette. *A pipeline is available at GitHub* <https://github.com/wittenburg/hsrecombi> Hampel, Teuscher, Gomez-Raya, Doschoris, Wittenburg (2018) "Estimation of recombination rate and maternal linkage disequilibrium in half-sibs" <doi:10.3389/fgene.2018.00186>. Gomez-Raya (2012) "Maximum likelihood estimation of linkage disequilibrium in half-sib families" <doi:10.1534/genetics.111.137521>.
Author: Doerte Wittenburg [aut, cre]
Maintainer: Doerte Wittenburg <wittenburg@fbn-dummerstorf.de>

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Package HMM updated to version 1.0.1 with previous version 1.0 dated 2010-01-10

Title: Hidden Markov Models
Description: Easy to use library to setup, apply and make inference with discrete time and discrete space Hidden Markov Models.
Author: Scientific Software - Dr. Lin Himmelmann
Maintainer: Lin Himmelmann <hmm@linhi.de>

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Package GUILDS updated to version 1.4.5 with previous version 1.4.4 dated 2022-03-16

Title: Implementation of Sampling Formulas for the Unified Neutral Model of Biodiversity and Biogeography, with or without Guild Structure
Description: A collection of sampling formulas for the unified neutral model of biogeography and biodiversity. Alongside the sampling formulas, it includes methods to perform maximum likelihood optimization of the sampling formulas, methods to generate data given the neutral model, and methods to estimate the expected species abundance distribution. Sampling formulas included in the GUILDS package are the Etienne Sampling Formula (Etienne 2005), the guild sampling formula, where guilds are assumed to differ in dispersal ability (Janzen et al. 2015), and the guilds sampling formula conditioned on guild size (Janzen et al. 2015).
Author: Thijs Janzen [aut, cre], Bart Haegeman [ctb], Franck Jabot [ctb], Jerome Chave [ctb]
Maintainer: Thijs Janzen <thijsjanzen@gmail.com>

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Package greybox updated to version 1.0.5 with previous version 1.0.4 dated 2022-02-06

Title: Toolbox for Model Building and Forecasting
Description: Implements functions and instruments for regression model building and its application to forecasting. The main scope of the package is in variables selection and models specification for cases of time series data. This includes promotional modelling, selection between different dynamic regressions with non-standard distributions of errors, selection based on cross validation, solutions to the fat regression model problem and more. Models developed in the package are tailored specifically for forecasting purposes. So as a results there are several methods that allow producing forecasts from these models and visualising them.
Author: Ivan Svetunkov [aut, cre] , Yves R. Sagaert [ctb]
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

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Package grafify updated to version 2.2.0 with previous version 2.1.0 dated 2022-01-28

Title: Easy Graphs for Data Visualisation and Linear Models for ANOVA
Description: Easily explore data by generating different kinds of graphs with few lines of code. Use these ggplot() wrappers to quickly draw graphs of scatter/dots with box-whiskers, violins or SD error bars, data distributions, before-after graphs, factorial ANOVA and more. Customise graphs and choose from 8 colour-blind friendly discreet or 1 continuous colour scheme. Simple code for ANOVA as ordinary (lm()) or mixed-effects linear models (lmer()), including randomised-block or repeated-measures designs. Carry out post-hoc comparisons on fitted models (via emmeans() wrappers). Also includes small datasets for practicing code and teaching basics before users move on to more complex designs. See vignettes for details on usage <https://grafify-vignettes.netlify.app/>. Citation: <doi:10.5281/zenodo.5136508>.
Author: Avinash R Shenoy [cre, aut]
Maintainer: Avinash R Shenoy <a.shenoy@imperial.ac.uk>

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Package gpboost updated to version 0.7.3.1 with previous version 0.7.3 dated 2022-03-22

Title: Combining Tree-Boosting with Gaussian Process and Mixed Effects Models
Description: An R package that allows for combining tree-boosting with Gaussian process and mixed effects models. It also allows for independently doing tree-boosting as well as inference and prediction for Gaussian process and mixed effects models. See <https://github.com/fabsig/GPBoost> for more information on the software and Sigrist (2020) <arXiv:2004.02653> and Sigrist (2021) <arXiv:2105.08966> for more information on the methodology.
Author: Fabio Sigrist [aut, cre], Benoit Jacob [cph], Gael Guennebaud [cph], Nicolas Carre [cph], Pierre Zoppitelli [cph], Gauthier Brun [cph], Jean Ceccato [cph], Jitse Niesen [cph], Other authors of Eigen for the included version of Eigen [ctb, cph], Timot [...truncated...]
Maintainer: Fabio Sigrist <fabiosigrist@gmail.com>

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Package GOxploreR updated to version 1.2.5 with previous version 1.2.4 dated 2021-12-10

Title: Structural Exploration of the Gene Ontology (GO) Knowledge Base
Description: It provides an effective, efficient, and fast way to explore the Gene Ontology (GO). Given a set of genes, the package contains functions to assess the GO and obtain the terms associated with the genes and the levels of the GO terms. The package provides functions for the three different GO ontology. We discussed the methods explicitly in the following article <doi:10.1038/s41598-020-73326-3>.
Author: Kalifa Manjang, Frank Emmert-Streib, Shailesh Tripathi, Olli Yli-Harja, Matthias Dehmer
Maintainer: Kalifa Manjang <kalifamanjang1@gmail.com>

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Package ggnewscale updated to version 0.4.7 with previous version 0.4.6 dated 2022-02-15

Title: Multiple Fill and Colour Scales in 'ggplot2'
Description: Use multiple fill and colour scales in 'ggplot2'.
Author: Elio Campitelli [cre, aut]
Maintainer: Elio Campitelli <elio.campitelli@cima.fcen.uba.ar>

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Package ggExtra updated to version 0.10.0 with previous version 0.9 dated 2019-08-27

Title: Add Marginal Histograms to 'ggplot2', and More 'ggplot2' Enhancements
Description: Collection of functions and layers to enhance 'ggplot2'. The flagship function is 'ggMarginal()', which can be used to add marginal histograms/boxplots/density plots to 'ggplot2' scatterplots.
Author: Dean Attali [aut, cre], Christopher Baker [aut]
Maintainer: Dean Attali <daattali@gmail.com>

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 R/ggMarginal.R                                                                           |   28 
 R/ggMarginalGadget.R                                                                     |   16 
 R/runExample.R                                                                           |    2 
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Package GeneralisedCovarianceMeasure updated to version 0.2.0 with previous version 0.1.0 dated 2019-08-02

Title: Test for Conditional Independence Based on the Generalized Covariance Measure (GCM)
Description: A statistical hypothesis test for conditional independence. It performs nonlinear regressions on the conditioning variable and then tests for a vanishing covariance between the resulting residuals. It can be applied to both univariate random variables and multivariate random vectors. Details of the method can be found in Rajen D. Shah and Jonas Peters: The Hardness of Conditional Independence Testing and the Generalised Covariance Measure, Annals of Statistics 48(3), 1514--1538, 2020.
Author: Jonas Peters and Rajen D. Shah
Maintainer: Jonas Peters <jonas.peters@math.ku.dk>

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Package FRK updated to version 2.0.5 with previous version 2.0.4 dated 2022-02-18

Title: Fixed Rank Kriging
Description: Fixed Rank Kriging is a tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of r basis functions, where r is typically much smaller than the number of data points (or polygons) m. This low-rank basis-function representation facilitates the modelling of 'big' spatial/spatio-temporal data. The method naturally allows for non-stationary, anisotropic covariance functions. Discretisation of the spatial domain into so-called basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both point-referenced and areal supports, potentially simultaneously), and prediction over arbitrary user-specified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above of the package `FRK` also supports modelling of non-Gaussian data, by employing a spatial generalised linear mixed model (GLMM) framework to cater for Poisson, binomial, negative-binomial, gamma, and inverse-Gaussian distributions. Zammit-Mangion and Cressie <doi:10.18637/jss.v098.i04> describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs.
Author: Andrew Zammit-Mangion [aut, cre], Matthew Sainsbury-Dale [aut]
Maintainer: Andrew Zammit-Mangion <andrewzm@gmail.com>

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New package finetune with initial version 0.2.0
Package: finetune
Title: Additional Functions for Model Tuning
Version: 0.2.0
Description: The ability to tune models is important. 'finetune' enhances the 'tune' package by providing more specialized methods for finding reasonable values of model tuning parameters. Two racing methods described by Kuhn (2014) <arXiv:1405.6974> are included. An iterative search method using generalized simulated annealing (Bohachevsky, Johnson and Stein, 1986) <doi:10.1080/00401706.1986.10488128> is also included.
License: MIT + file LICENSE
URL: https://github.com/tidymodels/finetune, https://finetune.tidymodels.org
BugReports: https://github.com/tidymodels/finetune/issues
Depends: R (>= 3.4), tune (>= 0.2.0)
Imports: cli, dials (>= 0.1.0), dplyr, ggplot2, purrr, rlang, tibble, tidyr, tidyselect, utils, vctrs, workflows (>= 0.2.6)
Suggests: BradleyTerry2, covr, discrim, klaR, lme4, modeldata, parsnip (>= 0.2.1), ranger, recipes (>= 0.2.0), rpart, rsample, spelling, testthat, yardstick
Config/Needs/website: tidyverse/tidytemplate
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2022-03-24 14:40:58 UTC; maxkuhn
Author: Max Kuhn [aut, cre] , RStudio [cph, fnd]
Maintainer: Max Kuhn <max@rstudio.com>
Repository: CRAN
Date/Publication: 2022-03-24 18:30:02 UTC

More information about finetune at CRAN
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Package file2meco updated to version 0.2.2 with previous version 0.2.1 dated 2022-01-06

Title: Transform Files to 'microtable' Object with 'microeco' Package
Description: Transform output files of some tools to the 'microtable' object of 'microtable' class in 'microeco' package. The 'microtable' class is the basic class in 'microeco' package and is necessary for the downstream microbial community data analysis.
Author: Chi Liu [aut, cre]
Maintainer: Chi Liu <liuchi0426@126.com>

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Package ffp updated to version 0.2.1 with previous version 0.2.0 dated 2022-02-17

Title: Fully Flexible Probabilities for Stress Testing and Portfolio Construction
Description: Implements numerical entropy-pooling for scenario analysis as described in Meucci, Attilio (2010) <doi:10.2139/ssrn.1696802>.
Author: Bernardo Reckziegel [aut, cre, cph]
Maintainer: Bernardo Reckziegel <bernardo_cse@hotmail.com>

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Package fastRhockey updated to version 0.3.0 with previous version 0.1.0 dated 2021-12-10

Title: Functions to Access Premier Hockey Federation and National Hockey League Play by Play Data
Description: A utility to scrape and load play-by-play data and statistics from the Premier Hockey Federation (PHF)<https://www.premierhockeyfederation.com/>, formerly known as the National Women's Hockey League (NWHL). Additionally, allows access to the National Hockey League's stats API <https://www.nhl.com/>.
Author: Ben Howell [aut], Saiem Gilani [cre, aut], Alyssa Longmuir [ctb]
Maintainer: Saiem Gilani <saiem.gilani@gmail.com>

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Package fansi updated to version 1.0.3 with previous version 1.0.2 dated 2022-01-14

Title: ANSI Control Sequence Aware String Functions
Description: Counterparts to R string manipulation functions that account for the effects of ANSI text formatting control sequences.
Author: Brodie Gaslam [aut, cre], Elliott Sales De Andrade [ctb], R Core Team [cph]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

Diff between fansi versions 1.0.2 dated 2022-01-14 and 1.0.3 dated 2022-03-25

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Package exdex updated to version 1.1.1 with previous version 1.0.1 dated 2019-08-06

Title: Estimation of the Extremal Index
Description: Performs frequentist inference for the extremal index of a stationary time series. Two types of methodology are used. One type is based on a model that relates the distribution of block maxima to the marginal distribution of series and leads to the semiparametric maxima estimators described in Northrop (2015) <doi:10.1007/s10687-015-0221-5> and Berghaus and Bucher (2018) <doi:10.1214/17-AOS1621>. Sliding block maxima are used to increase precision of estimation. A graphical block size diagnostic is provided. The other type of methodology uses a model for the distribution of threshold inter-exceedance times (Ferro and Segers (2003) <doi:10.1111/1467-9868.00401>). Two versions of this type of approach are provided: the iterated weight least squares approach of Suveges (2007) <doi:10.1007/s10687-007-0034-2> and the K-gaps model of Suveges and Davison (2010) <doi:10.1214/09-AOAS292>. For the K-gaps model this package allows missing values in the data, can accommodate independent subsets of data, such as monthly or seasonal time series from different years, and can incorporate information from censored inter-exceedance times. A graphical diagnostic for the threshold level and the runs parameter K is provided.
Author: Paul J. Northrop [aut, cre, cph], Constantinos Christodoulides [aut, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

Diff between exdex versions 1.0.1 dated 2019-08-06 and 1.1.1 dated 2022-03-25

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Package envi updated to version 0.1.13 with previous version 0.1.11 dated 2022-02-04

Title: Environmental Interpolation using Spatial Kernel Density Estimation
Description: Estimates an ecological niche using occurrence data, covariates, and kernel density-based estimation methods. For a single species with presence and absence data, the 'envi' package uses the spatial relative risk function that is estimated using the 'sparr' package. Details about the 'sparr' package methods can be found in the tutorial: Davies et al. (2018) <doi:10.1002/sim.7577>. Details about kernel density estimation can be found in J. F. Bithell (1990) <doi:10.1002/sim.4780090616>. More information about relative risk functions using kernel density estimation can be found in J. F. Bithell (1991) <doi:10.1002/sim.4780101112>.
Author: Ian D. Buller [aut, cre, cph] , Lance A. Waller [ctb, ths] , Emory University [cph]
Maintainer: Ian D. Buller <ian.buller@alumni.emory.edu>

Diff between envi versions 0.1.11 dated 2022-02-04 and 0.1.13 dated 2022-03-25

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Package dtgiw updated to version 0.1.1 with previous version 0.1.0 dated 2022-03-09

Title: Discrete Transmuted Generalized Inverse Weibull Distribution
Description: The Discrete Transmuted Generalized Inverse Weibull (DTGIW) distribution is a new distribution for count data analysis. The DTGIW is discrete distribution based on Atchanut and Sirinapa (2021). <DOI: 10.14456/sjst-psu.2021.149>.
Author: Atchanut Rattanalertnusorn [cre, aut], Sirinapa Aryuyuen [aut]
Maintainer: Atchanut Rattanalertnusorn <atchanut_r@rmutt.ac.th>

Diff between dtgiw versions 0.1.0 dated 2022-03-09 and 0.1.1 dated 2022-03-25

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Package DSMolgenisArmadillo updated to version 1.4.1 with previous version 1.4.0 dated 2021-10-25

Title: 'DataSHIELD' Client for 'MOLGENIS Armadillo'
Description: 'DataSHIELD' is an infrastructure and series of R packages that enables the remote and 'non-disclosive' analysis of sensitive research data. This package is the 'DataSHIELD' interface implementation to analyze data shared on a 'MOLGENIS Armadillo' server. 'MOLGENIS Armadillo' is a light-weight 'DataSHIELD' server using a file store and an 'RServe' server.
Author: Mariska Slofstra [aut, cre] , Sido Haakma [aut] , Tommy de Boer [aut] , Fleur Kelpin [aut] , MOLGENIS org [cph, fnd]
Maintainer: Mariska Slofstra <m.k.slofstra@umcg.nl>

Diff between DSMolgenisArmadillo versions 1.4.0 dated 2021-10-25 and 1.4.1 dated 2022-03-25

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Package DRaWR updated to version 1.0.3 with previous version 1.0.1 dated 2016-02-04

Title: Discriminative Random Walk with Restart
Description: We present DRaWR, a network-based method for ranking genes or properties related to a given gene set. Such related genes or properties are identified from among the nodes of a large, heterogeneous network of biological information. Our method involves a random walk with restarts, performed on an initial network with multiple node and edge types, preserving more of the original, specific property information than current methods that operate on homogeneous networks. In this first stage of our algorithm, we find the properties that are the most relevant to the given gene set and extract a subnetwork of the original network, comprising only the relevant properties. We then rerank genes by their similarity to the given gene set, based on a second random walk with restarts, performed on the above subnetwork.
Author: Charles Blatti [aut, cre]
Maintainer: Charles Blatti <blatti@illinois.edu>

Diff between DRaWR versions 1.0.1 dated 2016-02-04 and 1.0.3 dated 2022-03-25

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Package DGEobj updated to version 1.1.0 with previous version 1.0.3 dated 2021-04-09

Title: Differential Gene Expression (DGE) Analysis Results Data Object
Description: Provides a flexible container to manage and annotate Differential Gene Expression (DGE) analysis results (Smythe et. al (2015) <doi:10.1093/nar/gkv007>). The DGEobj has data slots for row (gene), col (samples), assays (matrix n-rows by m-samples dimensions) and metadata (not keyed to row, col, or assays). A set of accessory functions to deposit, query and retrieve subsets of a data workflow has been provided. Attributes are used to capture metadata such as species and gene model, including reproducibility information such that a 3rd party can access a DGEobj history to see how each data object was created or modified. Since the DGEobj is customizable and extensible it is not limited to RNA-seq analysis types of workflows -- it can accommodate nearly any data analysis workflow that starts from a matrix of assays (rows) by samples (columns).
Author: John Thompson [aut], Connie Brett [aut, cre], Isaac Neuhaus [aut], Ryan Thompson [aut]
Maintainer: Connie Brett <connie@aggregate-genius.com>

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New package dmdScheme with initial version 1.3.1
Package: dmdScheme
Title: Domain Specific MetaData Scheme
Description: Forms the core for developing own domain specific metadata schemes. It contains the basic functionality needed for all metadata schemes based on the 'dmdScheme'. See R.M. Krug and O.L. Petchey (2019) <DOI:10.5281/zenodo.3581970>.
Version: 1.3.1
Date: 2022-03-23
URL: https://UZH-PEG.github.io/dmdScheme/, https://github.com/UZH-PEG/dmdScheme/
BugReports: https://github.com/UZH-PEG/dmdScheme/issues/
Depends: R (>= 3.5.0)
Imports: tools, methods, utils, magrittr (>= 1.5), readxl (>= 1.2.0), xml2, rlang (>= 0.3.1), rmarkdown, knitr, digest (>= 0.6), writexl, rappdirs, yaml, EML, stringr
License: MIT + file LICENSE
Encoding: UTF-8
StagedInstall: true
Suggests: covr (>= 3.2.1), testthat (>= 2.0.1), here (>= 0.1), kableExtra (>= 0.9.0), shiny, openxlsx, xfun
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2022-03-23 10:38:42 UTC; rainerkrug
Author: Rainer M. Krug [aut, cre] , Owen L. Petchey [ctb]
Maintainer: Rainer M. Krug <Rainer.Krug@uzh.ch>
Repository: CRAN
Date/Publication: 2022-03-23 13:30:02 UTC

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Package desctable updated to version 0.3.0 with previous version 0.1.9 dated 2020-10-16

Title: Produce Descriptive and Comparative Tables Easily
Description: Easily create descriptive and comparative tables. It makes use and integrates directly with the tidyverse family of packages, and pipes. Tables are produced as (nested) dataframes for easy manipulation.
Author: Maxime Wack [aut, cre], Adrien Boukobza [aut], Yihui Xie [ctb]
Maintainer: Maxime Wack <maximewack@free.fr>

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Package DBR updated to version 1.2.3 with previous version 1.2.2 dated 2022-03-23

Title: Discrete Beta Regression
Description: Bayesian Beta Regression, adapted for bounded discrete responses, commonly seen in survey responses. Estimation is done via Markov Chain Monte Carlo sampling, using a Gibbs wrapper around univariate slice sampler (Neal (2003) <DOI:10.1214/aos/1056562461>), as implemented in the R package MfUSampler (Mahani and Sharabiani (2017) <DOI: 10.18637/jss.v078.c01>).
Author: Alireza Mahani [cre, aut], Mansour Sharabiani [aut]
Maintainer: Alireza Mahani <alireza.s.mahani@gmail.com>

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New package cplots with initial version 0.5-0
Package: cplots
Title: Plots for Circular Data
Version: 0.5-0
Date: 2022-03-18
Imports: circular, grDevices, graphics, stats
Description: Provides functions to produce some circular plots for circular data, in a height- or area-proportional manner. They include bar plots, smooth density plots, stacked dot plots, histograms, multi-class stacked smooth density plots, and multi-class stacked histograms.
License: GPL (>= 2)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2022-03-24 02:02:55 UTC; ywan076
Author: Danli Xu [aut], Yong Wang [aut, cre]
Maintainer: Yong Wang <yongwang@auckland.ac.nz>
Repository: CRAN
Date/Publication: 2022-03-24 08:50:02 UTC

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Package covid19us updated to version 0.1.8 with previous version 0.1.7 dated 2020-09-07

Title: Cases of COVID-19 in the United States
Description: A wrapper around the 'COVID Tracking Project API' <https://covidtracking.com/api/> providing data on cases of COVID-19 in the US.
Author: Amanda Dobbyn [aut, cre]
Maintainer: Amanda Dobbyn <amanda.e.dobbyn@gmail.com>

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Package contribution updated to version 0.2.2 with previous version 0.2.1 dated 2022-02-28

Title: A Tiny Contribution Table Generator Based on 'ggplot2'
Description: Contribution table for credit assignment based on 'ggplot2'. This can improve the author contribution information in academic journals and personal CV.
Author: Shixiang Wang [aut, cre]
Maintainer: Shixiang Wang <w_shixiang@163.com>

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Package Compositional updated to version 5.5 with previous version 5.4 dated 2022-02-07

Title: Compositional Data Analysis
Description: Regression, classification, contour plots, hypothesis testing and fitting of distributions for compositional data are some of the functions included. The standard textbook for such data is John Aitchison's (1986) "The statistical analysis of compositional data". Relevant papers include: a) Tsagris M.T., Preston S. and Wood A.T.A. (2011). A data-based power transformation for compositional data. Fourth International International Workshop on Compositional Data Analysis. b) Tsagris M. (2014). The k-NN algorithm for compositional data: a revised approach with and without zero values present. Journal of Data Science, 12(3):519--534. c) Tsagris M. (2015). A novel, divergence based, regression for compositional data. Proceedings of the 28th Panhellenic Statistics Conference, 15-18 April 2015, Athens, Greece, 430--444. d) Tsagris M. (2015). Regression analysis with compositional data containing zero values. Chilean Journal of Statistics, 6(2):47--57. e) Tsagris M., Preston S. and Wood A.T.A. (2016). Improved supervised classification for compositional data using the alpha-transformation. Journal of Classification, 33(2):243--261. <doi:10.1007/s00357-016-9207-5>. f) Tsagris M., Preston S. and Wood A.T.A. (2017). Nonparametric hypothesis testing for equality of means on the simplex. Journal of Statistical Computation and Simulation, 87(2): 406--422. <doi:10.1080/00949655.2016.1216554>. g) Tsagris M. and Stewart C. (2018). A Dirichlet regression model for compositional data with zeros. Lobachevskii Journal of Mathematics, 39(3): 398--412. <doi:10.1134/S1995080218030198>. h) Alenazi A. (2019). Regression for compositional data with compositional data as predictor variables with or without zero values. Journal of Data Science, 17(1): 219--238. <doi:10.6339/JDS.201901_17(1).0010>. i) Tsagris M. and Stewart C. (2020). A folded model for compositional data analysis. Australian and New Zealand Journal of Statistics, 62(2):249--277. <doi:10.1111/anzs.12289>. j) Tsagris M., Alenazi A. and Stewart C. (2021). Non-parametric regression models for compositional data. <arXiv:2002.05137>. k) Alenazi A. (2021). Alenazi, A. (2021). A review of compositional data analysis and recent advances. Communications in Statistics-Theory and Methods (Accepted for publication). <doi:10.1080/03610926.2021.2014890>. We further include functions for percentages (or proportions).
Author: Michail Tsagris [aut, cre], Giorgos Athineou [aut], Abdulaziz Alenazi [ctb], Christos Adam [ctb]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

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Package clordr updated to version 1.7.0 with previous version 1.6.0 dated 2020-11-17

Title: Composite Likelihood Inference and Diagnostics for Replicated Spatial Ordinal Data
Description: Composite likelihood parameter estimate and asymptotic covariance matrix are calculated for the spatial ordinal data with replications, where spatial ordinal response with covariate and both spatial exponential covariance within subject and independent and identically distributed measurement error. Parameter estimation can be performed by either solving the gradient function or maximizing composite log-likelihood. Parametric bootstrapping is used to estimate the Godambe information matrix and hence the asymptotic standard error and covariance matrix with parallel processing option. Moreover, the proposed surrogate residual, which extends the results of Liu and Zhang (2017) <doi: 10.1080/01621459.2017.1292915>, can act as a useful tool for model diagnostics.
Author: Ting Fung Ma [cre, aut], Pingping Wang [aut], Jun Zhu [aut], Dipankar Bandyopadhyay [ctb], Yincai Tang [ctb]
Maintainer: Ting Fung (Ralph) Ma <tingfung.ma@wisc.edu>

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Package causaloptim updated to version 0.9.2 with previous version 0.9.1 dated 2021-12-10

Title: An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects
Description: When causal quantities are not identifiable from the observed data, it still may be possible to bound these quantities using the observed data. We outline a class of problems for which the derivation of tight bounds is always a linear programming problem and can therefore, at least theoretically, be solved using a symbolic linear optimizer. We extend and generalize the approach of Balke and Pearl (1994) <doi:10.1016/B978-1-55860-332-5.50011-0> and we provide a user friendly graphical interface for setting up such problems via directed acyclic graphs (DAG), which only allow for problems within this class to be depicted. The user can then define linear constraints to further refine their assumptions to meet their specific problem, and then specify a causal query using a text interface. The program converts this user defined DAG, query, and constraints, and returns tight bounds. The bounds can be converted to R functions to evaluate them for specific datasets, and to latex code for publication. The methods and proofs of tightness and validity of the bounds are described in a preprint by Sachs, Gabriel, and Sjölander (2021) <https://sachsmc.github.io/causaloptim/articles/CausalBoundsMethods.pdf>.
Author: Michael C Sachs [aut, cre], Erin E Gabriel [aut], Arvid Sjölander [aut], Gustav Jonzon [ctb] ), Alexander A Balke [ctb] ), Colorado Reed [ctb] )
Maintainer: Michael C Sachs <sachsmc@gmail.com>

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Package catlearn updated to version 0.9.1 with previous version 0.9 dated 2022-03-23

Title: Formal Psychological Models of Categorization and Learning
Description: Formal psychological models of categorization and learning, independently-replicated data sets against which to test them, and simulation archives.
Author: Andy Wills, Lenard Dome, Charlotte Edmunds, Garrett Honke, Angus Inkster, René Schlegelmilch, Stuart Spicer
Maintainer: Andy Wills <andy@willslab.co.uk>

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Package BRACoD.R updated to version 0.0.2.0 with previous version 0.0.1.2 dated 2021-05-17

Title: BRACoD: Bayesian Regression Analysis of Compositional Data
Description: The goal of this method is to identify associations between bacteria and an environmental variable in 16S or other compositional data. The environmental variable is any variable which is measure for each microbiome sample, for example, a butyrate measurement paired with every sample in the data. Microbiome data is compositional, meaning that the total abundance of each sample sums to 1, and this introduces severe statistical distortions. This method takes a Bayesian approach to correcting for these statistical distortions, in which the total abundance is treated as an unknown variable. This package runs the python implementation using reticulate.
Author: Adrian Verster [aut, cre]
Maintainer: Adrian Verster <adrian.verster@hc-sc.gc.ca>

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Package bibliometrixData updated to version 0.2.0 with previous version 0.1.0 dated 2020-12-10

Title: Bibliometrix Example Datasets
Description: It contains some example datasets used in 'bibliometrix'. The data are bibliographic datasets exported from the 'SCOPUS' (<https://scopus.com>) and 'Clarivate Analytics Web of Science' (<https://www.webofscience.com/>) databases. They can be used to test the different features of the package 'bibliometrix' (<https://bibliometrix.org>).
Author: Massimo Aria [aut, cre]
Maintainer: Massimo Aria <massimo.aria@gmail.com>

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Package betapart updated to version 1.5.5 with previous version 1.5.4 dated 2021-04-11

Title: Partitioning Beta Diversity into Turnover and Nestedness Components
Description: Functions to compute pair-wise dissimilarities (distance matrices) and multiple-site dissimilarities, separating the turnover and nestedness-resultant components of taxonomic (incidence and abundance based), functional and phylogenetic beta diversity.
Author: Andres Baselga [aut, cre], David Orme [aut], Sebastien Villeger [aut], Julien De Bortoli [aut], Fabien Leprieur [aut], Maxime Logez [aut], Renato Henriques-Silva [ctb]
Maintainer: Andres Baselga <andres.baselga@usc.es>

Diff between betapart versions 1.5.4 dated 2021-04-11 and 1.5.5 dated 2022-03-25

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More information about betapart at CRAN
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Package BASiNETEntropy updated to version 0.99.2 with previous version 0.99.1 dated 2022-01-12

Title: Classification of RNA Sequences using Complex Network and Information Theory
Description: It makes the creation of networks from sequences of RNA, with this is done the abstraction of characteristics of these networks with a methodology of maximum entropy for the purpose of making a classification between the classes of the sequences. There are two data present in the 'BASiNET' package, "mRNA", and "ncRNA" with 100 sequences. These sequences were taken from the data set used in the article (LI, Aimin; ZHANG, Junying; ZHOU, Zhongyin, 2014) <doi:10.1186/1471-2105-15-311>, these sequences are used to run examples.
Author: Murilo Montanini Breve [aut] , Matheus Henrique Pimenta-Zanon [aut] , Fabricio Martins Lopes [aut, cre]
Maintainer: Fabricio Martins Lopes <fabricio@utfpr.edu.br>

Diff between BASiNETEntropy versions 0.99.1 dated 2022-01-12 and 0.99.2 dated 2022-03-25

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Package AvInertia updated to version 0.0.2 with previous version 0.0.1 dated 2021-07-22

Title: Calculate the Inertial Properties of a Flying Bird
Description: Tools to compute the center of gravity and moment of inertia tensor of any flying bird. The tools function by modeling a bird as a composite structure of simple geometric objects. This requires detailed morphological measurements of bird specimens although those obtained for the associated paper have been included in the package for use. Refer to the vignettes and supplementary material for detailed information on the package function.
Author: Christina Harvey [aut, cre] , Vikram B. Baliga [aut] , Jasmin C.M. Wong [aut]
Maintainer: Christina Harvey <harveyca@umich.edu>

Diff between AvInertia versions 0.0.1 dated 2021-07-22 and 0.0.2 dated 2022-03-25

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Package ANTs updated to version 0.0.14 with previous version 0.0.13 dated 2021-11-19

Title: Animal Network Toolkit Software
Description: How animals interact and develop social relationships in face of sociodemographic and ecological pressures is of great interest. New methodologies, in particular Social Network Analysis (SNA), allow us to elucidate these types of questions. However, the different methodologies developed to that end and the speed at which they emerge make their use difficult. Moreover, the lack of communication between the different software developed to provide an answer to the same/different research questions is a source of confusion. The R package Animal Network Toolkit 'ANTs' was developed with the aim of implementing in one package the different social network analysis techniques currently used in the study of animal social networks. Hence, ANT is a toolkit for animal research allowing among other things to: 1) measure global, dyadic and nodal networks metrics; 2) perform data randomization: pre- and post-network (node and link permutations); 3) perform statistical permutation tests as correlation test (<doi:10.2307/2332226>), t-test (<doi:10.1037/h0041412>), General Linear Model (<doi:10.2307/2346786>), General Linear Mixed Model (<doi:10.2307/2346786>), deletion simulation (<doi:10.1098/rsbl.2003.0057>), 'Matrix TauKr correlations' (<doi:10.1016/S0022-5193(05)80036-0>). The package is partially coded in C++ using the R package 'Rcpp' for an optimal coding speed. The package gives researchers a workflow from the raw data to the achievement of statistical analyses, allowing for a multilevel approach (<doi:10.1007/978-3-319-47829-6_1882-1>): from the individual's position and role within the network, to the identification of interaction patterns, and the study of the overall network properties. Furthermore, ANT also provides a guideline on the SNA techniques used: 1) from the appropriate randomization technique according to the data collected; 2) to the choice, the meaning, the limitations and advantages of the network metrics to apply, 3) and the type of statistical tests to run. The ANT project is multi-collaborative, aiming to provide access to advanced social network analysis techniques and to create new ones that meet researchers' needs in future versions. The ANT project is multi-collaborative, aiming to provide access to advanced social network analysis techniques and to create new ones that meet researchers' needs in future versions.
Author: Sosa Sebastian [aut, cre], Puga-Gonzalez Ivan [aut], Hu Feng He [aut], Pansanel Jerome [aut], Xiaohua Xie [aut], Sueur Cedric [aut]
Maintainer: Sosa Sebastian <s.sosa@live.fr>

Diff between ANTs versions 0.0.13 dated 2021-11-19 and 0.0.14 dated 2022-03-25

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Package AMR updated to version 1.8.1 with previous version 1.8.0 dated 2022-01-07

Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR) data analysis and to work with microbial and antimicrobial properties by using evidence-based methods and reliable reference data such as LPSN <doi:10.1099/ijsem.0.004332>.
Author: Matthijs S. Berends [aut, cre] , Christian F. Luz [aut, ctb] , Dennis Souverein [aut, ctb] , Erwin E. A. Hassing [aut, ctb], Casper J. Albers [ths] , Judith M. Fonville [ctb], Alex W. Friedrich [ths] , Corinna Glasner [ths] , Eric H. L. C. M. Hazenbe [...truncated...]
Maintainer: Matthijs S. Berends <m.berends@certe.nl>

Diff between AMR versions 1.8.0 dated 2022-01-07 and 1.8.1 dated 2022-03-25

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Package amanida updated to version 0.2.2 with previous version 0.2.1 dated 2022-03-11

Title: Meta-Analysis for Non-Integral Data
Description: Combination of results for meta-analysis using significance and effect size only. P-values and fold-change are combined to obtain a global significance on each metabolite. Produces a volcano plot summarising the relevant results from meta-analysis. Vote-counting reports for metabolites. And explore plot to detect discrepancies between studies at a first glance. Methodology is described in the Llambrich et al. (2021) <doi:10.1093/bioinformatics/btab591>.
Author: Maria Llambrich [aut, cre] , Eudald Correig [aut], Raquel Cumeras [aut]
Maintainer: Maria Llambrich <maria.llambrich@urv.cat>

Diff between amanida versions 0.2.1 dated 2022-03-11 and 0.2.2 dated 2022-03-25

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Package akc updated to version 0.9.7 with previous version 0.9.6 dated 2022-01-09

Title: Automatic Knowledge Classification
Description: A tidy framework for automatic knowledge classification and visualization. Currently, the core functionality of the framework is mainly supported by modularity-based clustering (community detection) in keyword co-occurrence network, and focuses on co-word analysis of bibliometric research. However, the designed functions in 'akc' are general, and could be extended to solve other tasks in text mining as well.
Author: Tian-Yuan Huang [aut, cre]
Maintainer: Tian-Yuan Huang <huang.tian-yuan@qq.com>

Diff between akc versions 0.9.6 dated 2022-01-09 and 0.9.7 dated 2022-03-25

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New package ag5Tools with initial version 0.0.1
Package: ag5Tools
Title: Toolbox for Downloading and Extracting Copernicus AgERA5 Data
Version: 0.0.1
Description: Tools for downloading and extracting data from the Copernicus "Agrometeorological indicators from 1979 to present derived from reanalysis" <https://cds.climate.copernicus.eu/cdsapp#!/dataset/sis-agrometeorological-indicators?tab=overview> (AgERA5).
Config/reticulate: list( packages = list( list(package = "cdsapi", pip = TRUE) ) )
Depends: R (>= 3.5.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: terra, reticulate, fs
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
URL: https://agrdatasci.github.io/ag5Tools/
NeedsCompilation: no
Packaged: 2022-03-24 14:12:50 UTC; David
Author: David Brown [aut, cre] , Kaue de Sousa [aut] , Jacob van Etten [ths] , Sytze de Bruin [ths]
Maintainer: David Brown <d.brown@cgiar.org>
Repository: CRAN
Date/Publication: 2022-03-24 18:20:02 UTC

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Package admix updated to version 0.4.0 with previous version 0.3.2 dated 2021-06-14

Title: Package Admix for Admixture (aka Contamination) Models
Description: Implements several methods to estimate the unknown quantities related to two-component admixture models, where the two components can belong to any distribution (note that in the case of multinomial mixtures, the two components must belong to the same family). Estimation methods depend on the assumptions made on the unknown component density (see Bordes and Vandekerkhove (2010) <doi:10.3103/S1066530710010023>; Patra and Sen (2016) <doi:10.1111/rssb.12148>); Milhaud, Pommeret, Salhi and Vandekerkhove (2021) <doi:10.1016/j.jspi.2021.05.010>). In practice, one can estimate both the mixture weight and the unknown component density in a wide variety of frameworks. On top of that, hypothesis tests can be performed in one and two-samples contexts to test the unknown component density. Finally, clustering of unknown mixture components is also feasible in a K-samples setting.
Author: Xavier Milhaud [aut, cre], Pierre Vandekerkhove [ctb], Denys Pommeret [ctb], Yahia Salhi [ctb]
Maintainer: Xavier Milhaud <xavier.milhaud.research@gmail.com>

Diff between admix versions 0.3.2 dated 2021-06-14 and 0.4.0 dated 2022-03-25

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Package adjROC updated to version 0.2.0 with previous version 0.1.0 dated 2022-03-21

Title: Computing Sensitivity at a Fix Value of Specificity and Vice Versa
Description: For a binary classification the adjusted sensitivity and specificity are measured for a given fixed threshold. If the threshold for either sensitivity or specificity is not given, the crossing point between the sensitivity and specificity curves are returned.
Author: E. F. Haghish
Maintainer: E. F. Haghish <haghish@uio.no>

Diff between adjROC versions 0.1.0 dated 2022-03-21 and 0.2.0 dated 2022-03-25

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Permanent link

Package oxcgrt (with last version 0.1.0) was removed from CRAN

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

2020-11-27 0.1.0

Permanent link
Package FlywayNet (with last version 0.1.0) was removed from CRAN

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

2022-03-09 0.1.0

Permanent link
Package elfgen (with last version 2.2.3) was removed from CRAN

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

2022-02-08 2.2.3

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