Mon, 26 Oct 2020

Package secuTrialR updated to version 1.0.6 with previous version 1.0.3 dated 2020-04-24

Title: Handling of Data from the Clinical Data Management System 'secuTrial'
Description: Seamless and standardized interaction with data exported from the clinical data management system (CDMS) 'secuTrial'<https://www.secutrial.com>. The primary data export the package works with is a standard non-rectangular export.
Author: Patrick R. Wright [cre, aut, cph], Alan G. Haynes [aut, cph], Milica Markovic [aut, cph], Gilles Dutilh [ctb], Armando Lenz [ctb], Pascal Benkert [com]
Maintainer: Patrick R. Wright <patrick.wright@usb.ch>

Diff between secuTrialR versions 1.0.3 dated 2020-04-24 and 1.0.6 dated 2020-10-26

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More information about secuTrialR at CRAN
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Package dosearch updated to version 1.0.6 with previous version 1.0.4 dated 2019-10-22

Title: Causal Effect Identification from Multiple Incomplete Data Sources
Description: Identification of causal effects from arbitrary observational and experimental probability distributions via do-calculus and standard probability manipulations using a search-based algorithm. Allows for the presence of mechanisms related to selection bias (Bareinboim, E. and Tian, J. (2015) <http://ftp.cs.ucla.edu/pub/stat_ser/r445.pdf>), transportability (Bareinboim, E. and Pearl, J. (2014) <http://ftp.cs.ucla.edu/pub/stat_ser/r443.pdf>), missing data (Mohan, K. and Pearl, J. and Tian., J. (2013) <http://ftp.cs.ucla.edu/pub/stat_ser/r410.pdf>) and arbitrary combinations of these. Also supports identification in the presence of context-specific independence (CSI) relations through labeled directed acyclic graphs (LDAG). For details on CSIs see Corander et al. (2019) <doi:10.1016/j.apal.2019.04.004>. For further information on the search-based approach see Tikka et al. (2019) <arXiv:1902.01073>.
Author: Santtu Tikka [aut, cre] (<https://orcid.org/0000-0003-4039-4342>), Antti Hyttinen [ctb] (<https://orcid.org/0000-0002-6649-3229>), Juha Karvanen [ctb] (<https://orcid.org/0000-0001-5530-769X>)
Maintainer: Santtu Tikka <santtuth@gmail.com>

Diff between dosearch versions 1.0.4 dated 2019-10-22 and 1.0.6 dated 2020-10-26

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Package equateMultiple updated to version 0.0.1 with previous version 0.0.0 dated 2017-11-02

Title: Equating of Multiple Forms
Description: Equating of multiple forms using Item Response Theory (IRT) methods (Battauz M. (2017) <doi:10.1007/s11336-016-9517-x> and Haberman S. J. (2009) <doi:10.1002/j.2333-8504.2009.tb02197.x>).
Author: Michela Battauz
Maintainer: Michela Battauz <michela.battauz@uniud.it>

Diff between equateMultiple versions 0.0.0 dated 2017-11-02 and 0.0.1 dated 2020-10-26

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Package AHMbook updated to version 0.2.2 with previous version 0.2.0 dated 2020-06-09

Title: Functions and Data for the Book 'Applied Hierarchical Modeling in Ecology' Vols 1 and 2
Description: Provides functions and data sets to accompany the two volume publication 'Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS' by Marc Kéry and Andy Royle: volume 1 (2016, ISBN: 978-0-12-801378-6) and volume 2 (2021, ISBN: 978-0-12-809585-0), <https://www.mbr-pwrc.usgs.gov/pubanalysis/keryroylebook>.
Author: Marc Kéry [aut], Andy Royle [aut], Mike Meredith [aut, cre], Urs Breitenmoser [dtc] (EurasianLynx), Richard Chandler [ctb], Bob Dorazio [ctb], Evan Grant [dtc] (duskySalamanders), John-Andren Henden [dtc] (Finnmark), Roland Kays [dtc] (MesoCarnivores), David King [dtc] (cswa), Xavier Lambin [dtc] (waterVoles), Jeremy Mizel [ctb, dtc] (treeSparrow), Anja Molinari-Jobin [dtc] (EurasianLynx), René-Jean Monneret [dtc] (FrenchPeregrines), Arielle Parsons [dtc] (MesoCarnivores), René Ruffinoni [dtc] (FrenchPeregrines), Michael Schaub [ctb], Rahel Solmann [ctb], Nicolas Strebel [dtc], Chris Sutherland [ctb, dtc] (waterVoles), Mathias Tobler [ctb], Fridolin Zimmermann [dtc] (EurasianLynx), Aargau Biodiversity Monitoring Program (LANAG) [dtc], British Ornithological Trust [dtc] (willowWarbler, UKmarbledWhite, <https://www.bto.org/>), Butterfly Conservation [dtc, cph] (UKmarbledWhite, <https://butterfly-conservation.org>), Centre for Ecology & Hydrology [dtc, cph] (UKmarbledWhite, <https://www.ceh.ac.uk>), Dutch Centre for Field Ornithology (Sovon) [dtc] (wagtail, <https://www.sovon.nl>), eMammal [dtc] (MesoCarnivores, <https://emammal.si.edu/>), Groupe Pèlerin Jura [dtc] (FrenchPeregrines), Hubbard Brook Ecosystem Study [dtc] (HubbardBrook, <http://data.hubbardbrook.org/data/dataset.php?id=178>), Joint Nature Conservation Committee (JNCC) [dtc, cph] (UKmarbledWhite, <https://jncc.gov.uk/>), North Carolina Museum of Natural Sciences [dtc] (mesoCarnivores), North Carolina State University [dtc] (mesoCarnivores), Progetto Lince Italia [dtc] (EurasianLynx, <https://www.progettolinceitalia.it>), Swiss Federal Statistical Office [dtc, cph] (BerneseOberland, <http://www.bfs.admin.ch>), Swiss Foundation KORA Carnivore Ecology and Wildlife Management (SCALP project) [dtc] (EurasianLynx, <https://www.kora.ch>), Swiss Ornithological Institute [dtc] (<https://www.vogelwarte.ch>), UK Butterfly Monitoring Scheme (UKBMS) [dtc, cph] (UKmarbledWhite, <https://www.ceh.ac.uk/our-science/projects/uk-butterfly-monitoring-scheme>)
Maintainer: Mike Meredith <mike@mmeredith.net>

Diff between AHMbook versions 0.2.0 dated 2020-06-09 and 0.2.2 dated 2020-10-26

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 R/simDSM.R                                                        |   33 -
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 R/simHDStr.R                                                      |   50 +
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 R/simSpatialHDS.R                                                 |   24 
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 inst/WORDLIST                                                     |  267 ++++------
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 man/ch2marray.Rd                                                  |    2 
 man/color_ramps.Rd                                                |    2 
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 man/data_EurasianLynx.Rd                                          |    4 
 man/data_Finnmark.Rd                                              |    2 
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 man/data_MHB2014.Rd                                               |    4 
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 man/data_SwissAtlasHa.Rd                                          |    4 
 man/data_SwissEagleOwls.Rd                                        |    4 
 man/data_SwissMarbledWhite.Rd                                     |   17 
 man/data_SwissSquirrels.Rd                                        |    4 
 man/data_SwissTits.Rd                                             |    8 
 man/data_UKmarbledWhite.Rd                                        |    4 
 man/data_crestedTit.Rd                                            |    4 
 man/data_crossbillAHM.Rd                                          |    8 
 man/data_cswa.Rd                                                  |    4 
 man/data_dragonflies.Rd                                           |    2 
 man/data_duskySalamanders.Rd                                      |    2 
 man/data_greenWoodpecker.Rd                                       |    4 
 man/data_spottedWoodpecker.Rd                                     |    2 
 man/data_treeSparrow.Rd                                           |    6 
 man/data_waterVoles.Rd                                            |    2 
 man/data_wigglyLine.Rd                                            |    4 
 man/data_willowWarbler.Rd                                         |   12 
 man/fitstats.Rd                                                   |    2 
 man/getLVcorrMat.Rd                                               |    4 
 man/graphSSM.Rd                                                   |    4 
 man/image_scale.Rd                                                |    6 
 man/modSelFP.Rd                                                   |    2 
 man/piFuns.Rd                                                     |    5 
 man/playRN.Rd                                                     |    2 
 man/sim3Occ.Rd                                                    |    2 
 man/simCJS.Rd                                                     |    2 
 man/simDCM.Rd                                                     |    6 
 man/simDM_simDM0.Rd                                               |    6 
 man/simDSM.Rd                                                     |   11 
 man/simData.fn.Rd                                                 |    2 
 man/simDataDK.Rd                                                  |    2 
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 man/simDynocc.Rd                                                  |   11 
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 man/simFn.Rd                                                      |    4 
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 man/simHDS.Rd                                                     |    2 
 man/simHDStr.Rd                                                   |    4 
 man/simIssj.sim.Rd                                                |    2 
 man/simLdata.Rd                                                   |    2 
 man/simMultMix.Rd                                                 |    4 
 man/simNmix.Rd                                                    |   10 
 man/simNmixSpatial.Rd                                             |    8 
 man/simNpC.Rd                                                     |    2 
 man/simOcc.Rd                                                     |    4 
 man/simOccSpatial.Rd                                              |   10 
 man/simOccttd.Rd                                                  |    8 
 man/simPH.Rd                                                      |    4 
 man/simPOP.Rd                                                     |    6 
 man/simPPe.Rd                                                     |    7 
 man/simSpatialDS.Rd                                               |    2 
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 man/simSpatialDSte.Rd                                             |    6 
 man/simWigglyOcc.Rd                                               |    2 
 man/simpleNmix.Rd                                                 |    2 
 man/standardize.Rd                                                |    2 
 man/valid_data.Rd                                                 |   12 
 man/zinit.Rd                                                      |    2 
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Package puniform updated to version 0.2.3 with previous version 0.2.2 dated 2020-06-20

Title: Meta-Analysis Methods Correcting for Publication Bias
Description: Provides meta-analysis methods that correct for publication bias and outcome reporting bias. Four methods and a visual tool are currently included in the package. The p-uniform method as described in van Assen, van Aert, and Wicherts (2015) <doi:10.1037/met0000025> can be used for estimating the average effect size, testing the null hypothesis of no effect, and testing for publication bias using only the statistically significant effect sizes of primary studies. The second method in the package is the p-uniform* method as described in van Aert and van Assen (2019) <doi:10.31222/osf.io/zqjr9>. This method is an extension of the p-uniform method that allows for estimation of the average effect size and the between-study variance in a meta-analysis, and uses both the statistically significant and nonsignificant effect sizes. The third method in the package is the hybrid method as described in van Aert and van Assen (2017) <doi:10.3758/s13428-017-0967-6>. The hybrid method is a meta-analysis method for combining an original study and replication and while taking into account statistical significance of the original study. The p-uniform and hybrid method are based on the statistical theory that the distribution of p-values is uniform conditional on the population effect size. The fourth method in the package is the Snapshot Bayesian Hybrid Meta-Analysis Method as described in van Aert and van Assen (2018) <doi:10.1371/journal.pone.0175302>. This method computes posterior probabilities for four true effect sizes (no, small, medium, and large) based on an original study and replication while taking into account publication bias in the original study. The method can also be used for computing the required sample size of the replication akin to power analysis in null hypothesis significance testing. The meta-plot is a visual tool for meta-analysis that provides information on the primary studies in the meta-analysis, the results of the meta-analysis, and characteristics of the research on the effect under study (van Assen and others, 2020). Helper functions to apply the Correcting for Outcome Reporting Bias (CORB) method to correct for outcome reporting bias in a meta-analysis (van Aert & Wicherts, 2020).
Author: Robbie C.M. van Aert
Maintainer: Robbie C.M. van Aert <R.C.M.vanAert@tilburguniversity.edu>

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Package packagefinder updated to version 0.3.2 with previous version 0.3.1 dated 2020-09-26

Title: Comfortable Search for R Packages on CRAN, Either Directly from the R Console or with an R Studio Add-in
Description: Search for R packages on CRAN directly from the R console, based on the packages' titles, short and long descriptions, or other fields. Combine multiple keywords with logical operators ('and', 'or'), view detailed information on any package and keep track of the latest package contributions to CRAN. If you don't want to search from the R console, use the comfortable R Studio add-in.
Author: Joachim Zuckarelli [aut, cre] (<https://orcid.org/0000-0002-9280-3016>)
Maintainer: Joachim Zuckarelli <joachim@zuckarelli.de>

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Package getCRUCLdata updated to version 0.3.2 with previous version 0.3.1 dated 2019-08-29

Title: 'CRU' 'CL' v. 2.0 Climatology Client
Description: Provides functions that automate downloading and importing University of East Anglia Climate Research Unit ('CRU') 'CL' v. 2.0 climatology data, facilitates the calculation of minimum temperature and maximum temperature and formats the data into a tidy data frame as a 'tibble' or a list of 'raster' 'stack' objects for use. 'CRU' 'CL' v. 2.0 data are a gridded climatology of 1961-1990 monthly means released in 2002 and cover all land areas (excluding Antarctica) at 10 arcminutes (0.1666667 degree) resolution. For more information see the description of the data provided by the University of East Anglia Climate Research Unit, <https://crudata.uea.ac.uk/cru/data/hrg/tmc/readme.txt>.
Author: Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>)
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

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Package tinyscholar updated to version 0.1.2 with previous version 0.1.1 dated 2020-09-19

Title: Get and Show Personal 'Google Scholar' Profile
Description: Provides functions to get personal 'Google Scholar' profile data from web API and show it in table or figure format.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>)
Maintainer: Shixiang Wang <w_shixiang@163.com>

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Package RegressionFactory updated to version 0.7.4 with previous version 0.7.2 dated 2016-09-08

Title: Expander Functions for Generating Full Gradient and Hessian from Single-Slot and Multi-Slot Base Distributions
Description: The expander functions rely on the mathematics developed for the Hessian-definiteness invariance theorem for linear projection transformations of variables, described in authors' paper, to generate the full, high-dimensional gradient and Hessian from the lower-dimensional derivative objects. This greatly relieves the computational burden of generating the regression-function derivatives, which in turn can be fed into any optimization routine that utilizes such derivatives. The theorem guarantees that Hessian definiteness is preserved, meaning that reasoning about this property can be performed in the low-dimensional space of the base distribution. This is often a much easier task than its equivalent in the full, high-dimensional space. Definiteness of Hessian can be useful in selecting optimization/sampling algorithms such as Newton-Raphson optimization or its sampling equivalent, the Stochastic Newton Sampler. Finally, in addition to being a computational tool, the regression expansion framework is of conceptual value by offering new opportunities to generate novel regression problems.
Author: Alireza S. Mahani, Mansour T.A. Sharabiani
Maintainer: Alireza S. Mahani <alireza.s.mahani@gmail.com>

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Package mpcmp updated to version 0.3.6 with previous version 0.3.5 dated 2020-10-19

Title: Mean-Parametrized Conway-Maxwell Poisson (COM-Poisson) Regression
Description: A collection of functions for estimation, testing and diagnostic checking for the mean-parametrized Conway-Maxwell-Poisson (COM-Poisson) regression model of Huang (2017) <doi:10.1177/1471082X17697749>.
Author: Thomas Fung [aut, cre] (<https://orcid.org/0000-0003-2601-0728>), Aya Alwan [aut], Justin Wishart [aut] (<https://orcid.org/0000-0002-8235-1845>), Alan Huang [aut]
Maintainer: Thomas Fung <thomas.fung.dr@gmail.com>

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Package DALEX updated to version 2.0.1 with previous version 2.0 dated 2020-09-04

Title: moDel Agnostic Language for Exploration and eXplanation
Description: Unverified black box model is the path to the failure. Opaqueness leads to distrust. Distrust leads to ignoration. Ignoration leads to rejection. DALEX package xrays any model and helps to explore and explain its behaviour. Machine Learning (ML) models are widely used and have various applications in classification or regression. Models created with boosting, bagging, stacking or similar techniques are often used due to their high performance. But such black-box models usually lack of direct interpretability. DALEX package contains various methods that help to understand the link between input variables and model output. Implemented methods help to explore model on the level of a single instance as well as a level of the whole dataset. All model explainers are model agnostic and can be compared across different models. DALEX package is the cornerstone for 'DrWhy.AI' universe of packages for visual model exploration. Find more details in (Biecek 2018) <arXiv:1806.08915>.
Author: Przemyslaw Biecek [aut, cre] (<https://orcid.org/0000-0001-8423-1823>), Szymon Maksymiuk [aut] (<https://orcid.org/0000-0002-3120-1601>), Hubert Baniecki [aut] (<https://orcid.org/0000-0001-6661-5364>)
Maintainer: Przemyslaw Biecek <przemyslaw.biecek@gmail.com>

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Package DFA updated to version 0.9.0 with previous version 0.1.0 dated 2020-07-01

Title: Detrended Fluctuation Analysis
Description: Contains the Detrended Fluctuation Analysis (DFA), Detrended Cross-Correlation Analysis (DCCA), Detrended Cross-Correlation Coefficient (rhoDCCA), Delta Amplitude Detrended Cross-Correlation Coefficient (DeltarhoDCCA), log amplitude Detrended Fluctuation Analysis (DeltalogDFA), two DFA automatic methods for identification of crossover points and a Deltalog automatic method for identification of reference channels.
Author: Victor Barreto Mesquita[aut,cre],Paulo Canas Rodrigues[ctb], Florencio Mendes Oliveira Filho[ctb]
Maintainer: Victor Barreto Mesquita <victormesquita40@hotmail.com>

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Package CHNCapitalStock updated to version 0.1.0 with previous version 0.0.2 dated 2020-06-25

Title: Compute Chinese Capital Stocks
Description: Compute Chinese capital stocks in provinces level, based on Zhang (2008) <DOI:10.1080/14765280802028302>.
Author: Pu Chen [aut, cre]
Maintainer: Pu Chen <shengnehs@qq.com>

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Sun, 25 Oct 2020

Package yap updated to version 0.1.1 with previous version 0.1.0 dated 2020-01-15

Title: Yet Another Probabilistic Neural Network
Description: Another implementation of probabilistic neural network in R based on Specht (1990) <DOI:10.1016/0893-6080(90)90049-Q>. It is applicable to the pattern recognition with a N-level response, where N > 2.
Author: WenSui Liu
Maintainer: WenSui Liu <liuwensui@gmail.com>

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Package rdbnomics updated to version 0.6.4 with previous version 0.6.3 dated 2020-09-22

Title: Download DBnomics Data
Description: R access to hundreds of millions data series from DBnomics API (<https://db.nomics.world/>).
Author: Sebastien Galais [cre, ctb], Thomas Brand [aut]
Maintainer: Sebastien Galais <s915.stem@gmail.com>

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Package yager updated to version 0.1.1 with previous version 0.1.0 dated 2020-01-14

Title: Yet Another General Regression Neural Network
Description: Another implementation of general regression neural network in R based on Specht (1991) <DOI:10.1109/72.97934>. It is applicable to the functional approximation or the classification.
Author: WenSui Liu
Maintainer: WenSui Liu <liuwensui@gmail.com>

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Package squashinformr updated to version 0.1.4 with previous version 0.1.2 dated 2020-05-01

Title: Politely Web Scrape Data from SquashInfo
Description: Scrape SquashInfo <http://www.squashinfo.com/> for data on the Professional Squash Association World Tour and other squash events. 'squashinformr' functions scrape, parse, and clean data associated with players, tournaments, and rankings.
Author: Hayden MacDonald [aut, cre]
Maintainer: Hayden MacDonald <hayden.macdonald.8778@gmail.com>

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Package ecespa updated to version 1.1-12 with previous version 1.1-11 dated 2020-02-13

Title: Functions for Spatial Point Pattern Analysis
Description: Some wrappers, functions and data sets for for spatial point pattern analysis (mainly based on 'spatstat'), used in the book "Introduccion al Analisis Espacial de Datos en Ecologia y Ciencias Ambientales: Metodos y Aplicaciones" and in the papers by De la Cruz et al. (2008) <doi:10.1111/j.0906-7590.2008.05299.x> and Olano et al. (2009) <doi:10.1051/forest:2008074>.
Author: Marcelino de la Cruz Rot, with contributions of Philip M. Dixon and Jose M. Blanco-Moreno
Maintainer: Marcelino de la Cruz Rot <marcelino.delacruz@urjc.es>

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Package unheadr updated to version 0.3.0 with previous version 0.2.1 dated 2020-03-03

Title: Handle Data with Messy Header Rows and Broken Values
Description: Verb-like functions to work with messy data, often derived from spreadsheets or parsed PDF tables. Includes functions for unwrapping values broken up across rows, relocating embedded grouping values, and to annotate meaningful formatting in spreadsheet files.
Author: Luis D. Verde Arregoitia [aut, cre] (<https://orcid.org/0000-0001-9520-6543>)
Maintainer: Luis D. Verde Arregoitia <luis@liomys.mx>

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Package Clustering updated to version 1.7 with previous version 1.6 dated 2020-04-23

Title: Execution of Multiple Clustering Algorithm
Description: The design of this package allows us to run different clustering packages and compare the results between them, to determine which algorithm behaves best from the data provided.
Author: Luis Alfonso Perez Martos [aut, cre]
Maintainer: Luis Alfonso Perez Martos <lapm0001@gmail.com>

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Package VineCopula updated to version 2.4.1 with previous version 2.4.0 dated 2020-10-03

Title: Statistical Inference of Vine Copulas
Description: Provides tools for the statistical analysis of vine copula models. The package includes tools for parameter estimation, model selection, simulation, goodness-of-fit tests, and visualization. Tools for estimation, selection and exploratory data analysis of bivariate copula models are also provided.
Author: Thomas Nagler [aut, cre], Ulf Schepsmeier [aut], Jakob Stoeber [aut], Eike Christian Brechmann [aut], Benedikt Graeler [aut], Tobias Erhardt [aut], Carlos Almeida [ctb], Aleksey Min [ctb, ths], Claudia Czado [ctb, ths], Mathias Hofmann [ctb], Matthias Killiches [ctb], Harry Joe [ctb], Thibault Vatter [ctb]
Maintainer: Thomas Nagler <mail@tnagler.com>

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Package sensitivity updated to version 1.22.2 with previous version 1.22.1 dated 2020-08-07

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

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Package PSSMCOOL updated to version 0.2.1 with previous version 0.2.0 dated 2020-08-07

Title: Features Extracted from Position Specific Scoring Matrix (PSSM)
Description: Returns almost all features that has been extracted from Position Specific Scoring Matrix (PSSM) so far, which is a matrix of L rows (L is protein length) and 20 columns produced by 'PSI-BLAST' which is a program to produce PSSM Matrix from multiple sequence alignment of proteins see <https://www.ncbi.nlm.nih.gov/books/NBK2590/> for mor details. some of these features are described in Zahiri, J., et al.(2013) <DOI:10.1016/j.ygeno.2013.05.006>, Saini, H., et al.(2016) <DOI:10.17706/jsw.11.8.756-767>, Ding, S., et al.(2014) <DOI:10.1016/j.biochi.2013.09.013>, Cheng, C.W., et al.(2008) <DOI:10.1186/1471-2105-9-S12-S6>, Juan, E.Y., et al.(2009) <DOI:10.1109/CISIS.2009.194>.
Author: Javad zahiri [aut], Alireza mohammadi [aut, cre]
Maintainer: Alireza mohammadi <alireza691111@gmail.com>

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Package paws.common updated to version 0.3.5 with previous version 0.3.4 dated 2020-09-06

Title: Paws Low-Level Amazon Web Services API
Description: Functions for making low-level API requests to Amazon Web Services <https://aws.amazon.com>. The functions handle building, signing, and sending requests, and receiving responses. They are designed to help build higher-level interfaces to individual services, such as Simple Storage Service (S3).
Author: David Kretch [aut, cre], Adam Banker [aut], Amazon.com, Inc. [cph]
Maintainer: David Kretch <david.kretch@gmail.com>

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Package bcdata updated to version 0.2.1 with previous version 0.2.0 dated 2020-06-25

Title: Search and Retrieve Data from the BC Data Catalogue
Description: Search, query, and download tabular and 'geospatial' data from the British Columbia Data Catalogue (<https://catalogue.data.gov.bc.ca/>). Search catalogue data records based on keywords, data licence, sector, data format, and B.C. government organization. View metadata directly in R, download many data formats, and query 'geospatial' data available via the B.C. government Web Feature Service ('WFS') using 'dplyr' syntax.
Author: Andy Teucher [aut, cre] (<https://orcid.org/0000-0002-7840-692X>), Sam Albers [aut, ctb] (<https://orcid.org/0000-0002-9270-7884>), Stephanie Hazlitt [aut, ctb] (<https://orcid.org/0000-0002-3161-2304>), Province of British Columbia [cph]
Maintainer: Andy Teucher <andy.teucher@gov.bc.ca>

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Package phonfieldwork updated to version 0.0.8 with previous version 0.0.7 dated 2020-07-10

Title: Linguistic Phonetic Fieldwork Tools
Description: There are a lot of different typical tasks that have to be solved during phonetic research and experiments. This includes creating a presentation that will contain all stimuli, renaming and concatenating multiple sound files recorded during a session, automatic annotation in 'Praat' TextGrids (this is one of the sound annotation standards provided by 'Praat' software, see Boersma & Weenink 2020 <https://www.fon.hum.uva.nl/praat/>), creating an html table with annotations and spectrograms, and converting multiple formats ('Praat' TextGrid, 'ELAN', 'EXMARaLDA', 'Audacity', subtitles '.srt', and 'FLEx' flextext). All of these tasks can be solved by a mixture of different tools (any programming language has programs for automatic renaming, and Praat contains scripts for concatenating and renaming files, etc.). 'phonfieldwork' provides a functionality that will make it easier to solve those tasks independently of any additional tools. You can also compare the functionality with other packages: 'rPraat' <https://CRAN.R-project.org/package=rPraat>, 'textgRid' <https://CRAN.R-project.org/package=textgRid>.
Author: George Moroz [aut, cre] (<https://orcid.org/0000-0003-1990-6083>), Jonathan Keane [rev] (<https://orcid.org/0000-0001-7087-9776>), Niko Partanen [rev] (<https://orcid.org/0000-0001-8584-3880>)
Maintainer: George Moroz <agricolamz@gmail.com>

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Package ipmisc updated to version 4.1.0 with previous version 4.0.0 dated 2020-10-05

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

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Package effectsize updated to version 0.4.0 with previous version 0.3.3 dated 2020-09-17

Title: Indices of Effect Size and Standardized Parameters
Description: Provide utilities to work with indices of effect size and standardized parameters for a wide variety of models (see support list of insight; Lüdecke, Waggoner & Makowski (2019) <doi:10.21105/joss.01412>), allowing computation and conversion of indices such as Cohen's d, r, odds, etc.
Author: Mattan S. Ben-Shachar [aut, cre] (<https://orcid.org/0000-0002-4287-4801>), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Ken Kelley [ctb], David Stanley [ctb]
Maintainer: Mattan S. Ben-Shachar <matanshm@post.bgu.ac.il>

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Package ecp updated to version 3.1.3 with previous version 3.1.2 dated 2019-11-11

Title: Non-Parametric Multiple Change-Point Analysis of Multivariate Data
Description: Implements various procedures for finding multiple change-points from Matteson D. et al (2013) <doi:10.1080/01621459.2013.849605>, Zhang W. et al (2017) <doi:10.1109/ICDMW.2017.44>, Arlot S. et al (2019). Two methods make use of dynamic programming and pruning, with no distributional assumptions other than the existence of certain absolute moments in one method. Hierarchical and exact search methods are included. All methods return the set of estimated change- points as well as other summary information.
Author: Nicholas A. James, Wenyu Zhang and David S. Matteson
Maintainer: Wenyu Zhang <wz258@cornell.edu>

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Package dragon updated to version 1.0.4 with previous version 1.0.3 dated 2020-09-29

Title: Deep Time Redox Analysis of the Geobiology Ontology Network
Description: Create, visualize, manipulate, and analyze bipartite mineral-chemistry networks for set of focal element(s) across deep-time on Earth. The method is described in Spielman and Moore (2020) <doi:10.3389/feart.2020.585087>.
Author: Stephanie J. Spielman [aut, cre] (<https://orcid.org/0000-0002-9090-4788>)
Maintainer: Stephanie J. Spielman <spielman@rowan.edu>

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Package ppitables updated to version 0.5.4 with previous version 0.5.3 dated 2020-09-20

Title: Lookup Tables to Generate Poverty Likelihoods and Rates using the Poverty Probability Index (PPI)
Description: The Poverty Probability Index (PPI) is a poverty measurement tool for organizations and businesses with a mission to serve the poor. The PPI is statistically-sound, yet simple to use: the answers to 10 questions about a household’s characteristics and asset ownership are scored to compute the likelihood that the household is living below the poverty line – or above by only a narrow margin. This package contains country-specific lookup data tables used as reference to determine the poverty likelihood of a household based on their score from the country-specific PPI questionnaire. These lookup tables have been extracted from documentation of the PPI found at <https://www.povertyindex.org> and managed by Innovations for Poverty Action <https://www.poverty-action.org>.
Author: Ernest Guevarra [aut, cre] (<https://orcid.org/0000-0002-4887-4415>)
Maintainer: Ernest Guevarra <ernestgmd@gmail.com>

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Package GerminaR updated to version 2.0.1 with previous version 2.0.0 dated 2020-09-01

Title: Indices and Graphics for Assess Seed Germination Process
Description: A collection of different indices and visualization techniques for evaluate the seed germination process in ecophysiological studies (Lozano-Isla et al. 2019) <doi:10.1111/1440-1703.1275>.
Author: Flavio Lozano-Isla [aut, cre] (<https://orcid.org/0000-0002-0714-669X>), Omar Benites Alfaro [aut] (<https://orcid.org/0000-0002-6852-9598>), Denise Garcia de Santana [aut], Marli A. Ranal [aut], Marcelo F. Pompelli [aut, ths] (<https://orcid.org/0000-0002-4408-6374>), Federal University of Pernambuco [cph] (Register of application), Federal Rural University of Pernambuco [cph] (Post Graduate Program)
Maintainer: Flavio Lozano-Isla <flavjack@gmail.com>

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Package ProjectionBasedClustering updated to version 1.1.5 with previous version 1.1.2 dated 2020-08-25

Title: Projection Based Clustering
Description: A clustering approach applicable to every projection method is proposed here. The two-dimensional scatter plot of any projection method can construct a topographic map which displays unapparent data structures by using distance and density information of the data. The generalized U*-matrix renders this visualization in the form of a topographic map, which can be used to automatically define the clusters of high-dimensional data. The whole system is based on Thrun and Ultsch, "Using Projection based Clustering to Find Distance and Density based Clusters in High-Dimensional Data" <DOI:10.1007/s00357-020-09373-2>. Selecting the correct projection method will result in a visualization in which mountains surround each cluster. The number of clusters can be determined by counting valleys on the topographic map. Most projection methods are wrappers for already available methods in R. By contrast, the neighbor retrieval visualizer (NeRV) is based on C++ source code of the 'dredviz' software package, and the Curvilinear Component Analysis (CCA) is translated from 'MATLAB' ('SOM Toolbox' 2.0) to R.
Author: Michael Thrun [aut, cre, cph], Florian Lerch [aut], Felix Pape [aut], Tim Schreier [aut], Luis Winckelmann [aut], Kristian Nybo [cph], Jarkko Venna [cph]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package GeneralizedUmatrix updated to version 1.2.1 with previous version 1.2.0 dated 2020-08-24

Title: Credible Visualization for Two-Dimensional Projections of Data
Description: Projections are common dimensionality reduction methods, which represent high-dimensional data in a two-dimensional space. However, when restricting the output space to two dimensions, which results in a two dimensional scatter plot (projection) of the data, low dimensional similarities do not represent high dimensional distances coercively [Thrun, 2018] <DOI: 10.1007/978-3-658-20540-9>. This could lead to a misleading interpretation of the underlying structures [Thrun, 2018]. By means of the 3D topographic map the generalized Umatrix is able to depict errors of these two-dimensional scatter plots. The package is derived from the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9> and the main algorithm called simplified self-organizing map for dimensionality reduction methods is published in <DOI: 10.1016/j.mex.2020.101093>.
Author: Michael Thrun [aut, cre, cph] (<https://orcid.org/0000-0001-9542-5543>), Felix Pape [ctb, ctr], Tim Schreier [ctb, ctr], Luis Winckelman [ctb, ctr], Alfred Ultsch [ths]
Maintainer: Michael Thrun <m.thrun@gmx.net>

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Package RPEGLMEN updated to version 1.1.0 with previous version 1.0.1 dated 2020-01-13

Title: Gamma and Exponential Generalized Linear Models with Elastic Net Penalty
Description: Implements the fast iterative shrinkage-thresholding algorithm (FISTA) algorithm to fit a Gamma distribution with an elastic net penalty as described in Chen, Arakvin and Martin (2018) <arxiv:1804.07780>. An implementation for the case of the exponential distribution is also available, with details available in Chen and Martin (2018) <https://papers.ssrn.com/abstract_id=3085672>.
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Xin Chen <chenx26@uw.edu>, Daniel Hanson <hansondj@uw.edu>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

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Package traipse updated to version 0.2.0 with previous version 0.1.0 dated 2019-07-02

Title: Shared Tools for Tracking Data
Description: A collection of commonly used tools for animal movement and other tracking data. Variously distance, angle, bearing, distance-to, bearing-to and speed are provided for geographic data that can be used directly or within 'tidyverse' syntax. Distances and bearings are calculated using modern geodesic methods as provided by Charles F. F. Karney (2013) <doi:10.1007/s00190-012-0578-z> via the 'geodist' and 'geosphere' packages.
Author: Michael Sumner [aut, cre] (<https://orcid.org/0000-0002-2471-7511>)
Maintainer: Michael Sumner <mdsumner@gmail.com>

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Package reticulate updated to version 1.18 with previous version 1.17 dated 2020-10-21

Title: Interface to 'Python'
Description: Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types. When values are returned from 'Python' to R they are converted back to R types. Compatible with all versions of 'Python' >= 2.7.
Author: Kevin Ushey [aut, cre], JJ Allaire [aut], RStudio [cph, fnd], Yuan Tang [aut, cph] (<https://orcid.org/0000-0001-5243-233X>), Dirk Eddelbuettel [ctb, cph], Bryan Lewis [ctb, cph], Sigrid Keydana [ctb], Ryan Hafen [ctb, cph], Marcus Geelnard [ctb, cph] (TinyThread library, http://tinythreadpp.bitsnbites.eu/)
Maintainer: Kevin Ushey <kevin@rstudio.com>

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Package metR updated to version 0.8.0 with previous version 0.7.0 dated 2020-04-10

Title: Tools for Easier Analysis of Meteorological Fields
Description: Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
Author: Elio Campitelli [cre, aut] (<https://orcid.org/0000-0002-7742-9230>)
Maintainer: Elio Campitelli <elio.campitelli@cima.fcen.uba.ar>

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Package emmeans updated to version 1.5.2-1 with previous version 1.5.2 dated 2020-10-24

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Paul Buerkner [ctb], Maxime Herve [ctb], Jonathon Love [ctb], Hannes Riebl [ctb], Henrik Singmann [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

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Package ciTools updated to version 0.6.1 with previous version 0.6.0 dated 2020-09-04

Title: Confidence or Prediction Intervals, Quantiles, and Probabilities for Statistical Models
Description: Functions to append confidence intervals, prediction intervals, and other quantities of interest to data frames. All appended quantities are for the response variable, after conditioning on the model and covariates. This package has a data frame first syntax that allows for easy piping. Currently supported models include (log-) linear, (log-) linear mixed, generalized linear models, generalized linear mixed models, and accelerated failure time models.
Author: John Haman [cre, aut], Matthew Avery [aut], Institute for Defense Analyses [cph]
Maintainer: John Haman <jhaman@ida.org>

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Sat, 24 Oct 2020

Package modelsummary updated to version 0.6.3 with previous version 0.6.2 dated 2020-09-29

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

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Package florestal updated to version 0.1.3 with previous version 0.1.1 dated 2020-07-07

Title: Results for Forest Inventories
Description: The functions return sampling parameters for forest inventories with tables and graphics. Methods used in the package refers to Pellico e Brena (1997) <https://bit.ly/2BDbHJI>.
Author: Igor Cobelo Ferreira
Maintainer: Igor Cobelo Ferreira <cobelo.igor@gmail.com>

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Package digest updated to version 0.6.27 with previous version 0.6.26 dated 2020-10-17

Title: Create Compact Hash Digests of R Objects
Description: Implementation of a function 'digest()' for the creation of hash digests of arbitrary R objects (using the 'md5', 'sha-1', 'sha-256', 'crc32', 'xxhash', 'murmurhash', 'spookyhash' and 'blake3' algorithms) permitting easy comparison of R language objects, as well as functions such as'hmac()' to create hash-based message authentication code. Please note that this package is not meant to be deployed for cryptographic purposes for which more comprehensive (and widely tested) libraries such as 'OpenSSL' should be used.
Author: Dirk Eddelbuettel <edd@debian.org> with contributions by Antoine Lucas, Jarek Tuszynski, Henrik Bengtsson, Simon Urbanek, Mario Frasca, Bryan Lewis, Murray Stokely, Hannes Muehleisen, Duncan Murdoch, Jim Hester, Wush Wu, Qiang Kou, Thierry Onkelinx, Michel Lang, Viliam Simko, Kurt Hornik, Radford Neal, Kendon Bell, Matthew de Queljoe, Ion Suruceanu, Bill Denney, Dirk Schumacher, and Winston Chang.
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package V8 updated to version 3.3.0 with previous version 3.2.0 dated 2020-06-19

Title: Embedded JavaScript and WebAssembly Engine for R
Description: An R interface to V8: Google's open source JavaScript and WebAssembly engine. This package can be compiled either with V8 version 6 and up, a NodeJS shared library, or the legacy 3.14/3.15 branch of V8.
Author: Jeroen Ooms [aut, cre] (<https://orcid.org/0000-0002-4035-0289>)
Maintainer: Jeroen Ooms <jeroen@berkeley.edu>

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Package vasicek updated to version 0.0.2 with previous version 0.0.1 dated 2020-10-10

Title: Miscellaneous Functions for Vasicek Distribution
Description: Provide a collection of miscellaneous R functions related to the Vasicek distribution with the intent to make the lives of risk modelers easier.
Author: WenSui Liu
Maintainer: WenSui Liu <liuwensui@gmail.com>

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Package gemma2 updated to version 0.1.3 with previous version 0.1.1 dated 2019-10-01

Title: GEMMA Multivariate Linear Mixed Model
Description: Fits a multivariate linear mixed effects model that uses a polygenic term, after Zhou & Stephens (2014) (<https://www.nature.com/articles/nmeth.2848>). Of particular interest is the estimation of variance components with restricted maximum likelihood (REML) methods. Genome-wide efficient mixed-model association (GEMMA), as implemented in the package 'gemma2', uses an expectation-maximization algorithm for variance components inference for use in quantitative trait locus studies.
Author: Frederick Boehm [aut, cre] (<https://orcid.org/0000-0002-1644-5931>)
Maintainer: Frederick Boehm <frederick.boehm@gmail.com>

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Package syllabifyr updated to version 0.1.1 with previous version 0.1.0 dated 2018-07-10

Title: Syllabifier for CMU Dictionary Transcriptions
Description: Implements tidy syllabification of transcription. Based on @kylebgorman's 'python' implementation <https://github.com/kylebgorman/syllabify>.
Author: Josef Fruehwald
Maintainer: Josef Fruehwald <jofrhwld@gmail.com>

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Package mvSLOUCH updated to version 2.6 with previous version 2.5 dated 2020-06-03

Title: Multivariate Stochastic Linear Ornstein-Uhlenbeck Models for Phylogenetic Comparative Hypotheses
Description: Fits multivariate Ornstein-Uhlenbeck types of models to continues trait data from species related by a common evolutionary history. See K. Bartoszek, J, Pienaar, P. Mostad, S. Andersson, T. F.Hansen (2012) <doi:10.1016/j.jtbi.2012.08.005>. The suggested PCMBaseCpp package (which significantly speeds up the likelihood calculations) can be obtained from <https://github.com/venelin/PCMBaseCpp/>.
Author: Krzysztof Bartoszek <krzbar@protonmail.ch>
Maintainer: Krzysztof Bartoszek <krzbar@protonmail.ch>

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Package GET updated to version 0.2 with previous version 0.1-8 dated 2020-08-29

Title: Global Envelopes
Description: Implementation of global envelopes for a set of general d-dimensional vectors T in various applications. A 100(1-alpha)% global envelope is a band bounded by two vectors such that the probability that T falls outside this envelope in any of the d points is equal to alpha. Global means that the probability is controlled simultaneously for all the d elements of the vectors. The global envelopes can be used for graphical Monte Carlo and permutation tests where the test statistic is a multivariate vector or function (e.g. goodness-of-fit testing for point patterns and random sets, functional analysis of variance, functional general linear model, n-sample test of correspondence of distribution functions), for central regions of functional or multivariate data (e.g. outlier detection, functional boxplot) and for global confidence and prediction bands (e.g. confidence band in polynomial regression, Bayesian posterior prediction). See Myllymäki and Mrkvička (2020) <arXiv:1911.06583>, Myllymäki et al. (2017) <doi: 10.1111/rssb.12172>, Mrkvička et al. (2017) <doi: 10.1007/s11222-016-9683-9>, Mrkvička et al. (2020) <doi: 10.14736/kyb-2020-3-0432>, Mrkvička et al. (2019) <doi: 10.1007/s11009-019-09756-y>, Mrkvička et al. (2019) <arXiv:1902.04926>, Mrkvička et al. (2016) <doi: 10.1016/j.spasta.2016.04.005>, and Myllymäki et al. (2020) <doi: 10.1016/j.spasta.2020.100436>.
Author: Mari Myllymäki [aut, cre], Tomáš Mrkvička [aut], Pavel Grabarnik [ctb], Ute Hahn [ctb], Mikko Kuronen [ctb], Michael Rost [ctb], Henri Seijo [ctb]
Maintainer: Mari Myllymäki <mari.myllymaki@luke.fi>

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Package survivalMPLdc updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-13

Title: Penalised Likelihood for Survival Analysis with Dependent Censoring
Description: Fitting Cox proportional hazard model under dependent right censoring using copula and maximum penalised likelihood methods.
Author: Jing Xu [aut, cre], Jun Ma [aut], Thomas Fung [aut] (<https://orcid.org/0000-0003-2601-0728>)
Maintainer: Jing Xu <kenny.xu@duke-nus.edu.sg>

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Package rerddapXtracto updated to version 1.0.1 with previous version 1.0.0 dated 2020-07-29

Title: Extracts Environmental Data from 'ERDDAP' Web Services
Description: Contains three functions that access environmental data from any 'ERDDAP' data web service. The rxtracto() function extracts data along a trajectory for a given "radius" around the point. The rxtracto_3D() function extracts data in a box. The rxtractogon() function extracts data in a polygon. All of those three function use the 'rerddap' package to extract the data, and should work with any 'ERDDAP' server. There are also two functions, plotBBox() and plotTrack() that use the 'plotdap' package to simplify the creation of maps of the data.
Author: Roy Mendelssohn [aut, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>

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Package koRpus.lang.en updated to version 0.1-4 with previous version 0.1-3 dated 2019-05-13

Title: Language Support for 'koRpus' Package: English
Description: Adds support for the English language to the 'koRpus' package. To ask for help, report bugs, suggest feature improvements, or discuss the global development of the package, please consider subscribing to the koRpus-dev mailing list (<https://korpusml.reaktanz.de>).
Author: Meik Michalke [aut, cre], Elen Le Foll [ctb] (BNC tagset)
Maintainer: Meik Michalke <meik.michalke@hhu.de>

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Package fixest updated to version 0.7.0 with previous version 0.6.0 dated 2020-07-13

Title: Fast Fixed-Effects Estimations
Description: Fast and user-friendly estimation of econometric models with multiple fixed-effects. Includes ordinary least squares (OLS), generalized linear models (GLM) and the negative binomial. The core of the package is based on optimized parallel C++ code, scaling especially well for large data sets. The method to obtain the fixed-effects coefficients is based on Berge (2018) <https://wwwen.uni.lu/content/download/110162/1299525/file/2018_13>. Further provides tools to export and view the results of several estimations with intuitive design to cluster the standard-errors.
Author: Laurent Berge [aut, cre]
Maintainer: Laurent Berge <laurent.berge@uni.lu>

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Package RPESE updated to version 1.1.0 with previous version 1.0.5 dated 2020-06-19

Title: Estimates of Standard Errors for Risk and Performance Measures
Description: Estimates of standard errors of popular risk and performance measures for asset or portfolio returns using methods as described in Chen and Martin (2018) <https://www.ssrn.com/abstract=3085672>.
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Xin Chen <chenx26@uw.edu>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

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Package nlme updated to version 3.1-150 with previous version 3.1-149 dated 2020-08-23

Title: Linear and Nonlinear Mixed Effects Models
Description: Fit and compare Gaussian linear and nonlinear mixed-effects models.
Author: José Pinheiro [aut] (S version), Douglas Bates [aut] (up to 2007), Saikat DebRoy [ctb] (up to 2002), Deepayan Sarkar [ctb] (up to 2005), EISPACK authors [ctb] (src/rs.f), Siem Heisterkamp [ctb] (Author fixed sigma), Bert Van Willigen [ctb] (Programmer fixed sigma), R-core [aut, cre]
Maintainer: R-core <R-core@R-project.org>

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Package HypergeoMat updated to version 3.1.0 with previous version 3.0.0 dated 2019-10-26

Title: Hypergeometric Function of a Matrix Argument
Description: Evaluates the hypergeometric functions of a matrix argument, which appear in random matrix theory. This is an implementation of Koev & Edelman's algorithm (2006) <doi:10.1090/S0025-5718-06-01824-2>.
Author: Stéphane Laurent
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package TraMineR updated to version 2.2-1 with previous version 2.2-0.1 dated 2020-04-29

Title: Trajectory Miner: a Toolbox for Exploring and Rendering Sequences
Description: Toolbox for the manipulation, description and rendering of sequences, and more generally the mining of sequence data in the field of social sciences. Although the toolbox is primarily intended for analyzing state or event sequences that describe life courses such as family formation histories or professional careers, its features also apply to many other kinds of categorical sequence data. It accepts many different sequence representations as input and provides tools for converting sequences from one format to another. It offers several functions for describing and rendering sequences, for computing distances between sequences with different metrics (among which optimal matching), original dissimilarity-based analysis tools, and simple functions for extracting the most frequent subsequences and identifying the most discriminating ones among them. A user's guide can be found on the TraMineR web page.
Author: Alexis Gabadinho [aut, cph], Matthias Studer [aut, cph] (<https://orcid.org/0000-0002-6269-1412>), Nicolas M"{u}ller [aut], Reto B"{u}rgin [aut], Pierre-Alexandre Fonta [aut], Gilbert Ritschard [aut, cre, cph] (<https://orcid.org/0000-0001-7776-0903>)
Maintainer: Gilbert Ritschard <gilbert.ritschard@unige.ch>

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Package tram updated to version 0.5-2 with previous version 0.5-1 dated 2020-09-04

Title: Transformation Models
Description: Formula-based user-interfaces to specific transformation models implemented in package 'mlt'. Available models include Cox models, some parametric survival models (Weibull, etc.), models for ordered categorical variables, normal and non-normal (Box-Cox type) linear models, and continuous outcome logistic regression (Lohse et al., 2017, <DOI:10.12688/f1000research.12934.1>). The underlying theory is described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>. An extension to transformation models for clustered data is provided (Hothorn, 2019, <arxiv:1910.09219>). Multivariate conditional transformation models (<arxiv:1906.03151>) can be fitted as well.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>), Luisa Barbanti [aut], Brian Ripley [ctb], Bill Venables [ctb], Douglas M. Bates [ctb], Nadja Klein [ctb]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

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Package nasapower updated to version 3.0.1 with previous version 3.0.0 dated 2020-10-10

Title: NASA POWER API Client
Description: Client for 'NASA' 'POWER' global meteorology, surface solar energy and climatology data 'API'. 'POWER' (Prediction Of Worldwide Energy Resource) data are freely available global meteorology and surface solar energy climatology data for download with a resolution of 1/2 by 1/2 arc degree longitude and latitude and are funded through the 'NASA' Earth Science Directorate Applied Science Program. For more on the data themselves, a web-based data viewer and web access, please see <https://power.larc.nasa.gov/>.
Author: Adam H. Sparks [aut, cre] (<https://orcid.org/0000-0002-0061-8359>), Scott Chamberlain [rev] (<https://orcid.org/0000-0003-1444-9135>, Scott Chamberlain reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Hazel Kavili [rev] (Hazel Kavili reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Alison Boyer [rev] (Alison Boyer reviewed nasapower for rOpenSci, see https://github.com/ropensci/software-review/issues/155), Fernando Miguez [ctb] (<https://orcid.org/0000-0002-4627-8329>, Fernando Miguez provided assistance in identifying improper missing value handling in the POWER data, see <https://github.com/femiguez/apsimx/pull/26>)
Maintainer: Adam H. Sparks <adamhsparks@gmail.com>

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Package emmeans updated to version 1.5.2 with previous version 1.5.1 dated 2020-09-18

Title: Estimated Marginal Means, aka Least-Squares Means
Description: Obtain estimated marginal means (EMMs) for many linear, generalized linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term "estimated marginal means" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means in the linear model: An alternative to least squares means, The American Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.
Author: Russell Lenth [aut, cre, cph], Paul Buerkner [ctb], Maxime Herve [ctb], Jonathon Love [ctb], Hannes Riebl [ctb], Henrik Singmann [ctb]
Maintainer: Russell Lenth <russell-lenth@uiowa.edu>

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Package Numero updated to version 1.7.2 with previous version 1.7.0 dated 2020-09-14

Title: Statistical Framework to Define Subgroups in Complex Datasets
Description: High-dimensional datasets that do not exhibit a clear intrinsic clustered structure pose a challenge to conventional clustering algorithms. For this reason, we developed an unsupervised framework that helps scientists to better subgroup their datasets based on visual cues, please see Gao S, Mutter S, Casey A, Makinen V-P (2019) Numero: a statistical framework to define multivariable subgroups in complex population-based datasets, Int J Epidemiology, 48:369-37, <doi:10.1093/ije/dyy113>. The framework includes the necessary functions to construct a self-organizing map of the data, to evaluate the statistical significance of the observed data patterns, and to visualize the results.
Author: Song Gao [aut], Stefan Mutter [aut], Aaron E. Casey [aut], Ville-Petteri Makinen [aut, cre]
Maintainer: Ville-Petteri Makinen <vpmakine@gmail.com>

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Package metan updated to version 1.10.0 with previous version 1.9.0 dated 2020-09-18

Title: Multi Environment Trials Analysis
Description: Performs stability analysis of multi-environment trial data using parametric and non-parametric methods. Parametric methods includes Additive Main Effects and Multiplicative Interaction (AMMI) analysis by Gauch (2013) <doi:10.2135/cropsci2013.04.0241>, Ecovalence by Wricke (1965), Genotype plus Genotype-Environment (GGE) biplot analysis by Yan & Kang (2003) <doi:10.1201/9781420040371>, geometric adaptability index by Mohammadi & Amri (2008) <doi:10.1007/s10681-007-9600-6>, joint regression analysis by Eberhart & Russel (1966) <doi:10.2135/cropsci1966.0011183X000600010011x>, genotypic confidence index by Annicchiarico (1992), Murakami & Cruz's (2004) method <doi:10.12702/1984-7033.v04n01a02>, power law residuals (POLAR) statistics by Doring et al. (2015) <doi:10.1016/j.fcr.2015.08.005>, scale-adjusted coefficient of variation by Doring & Reckling (2018) <doi:10.1016/j.eja.2018.06.007>, stability variance by Shukla (1972) <doi:10.1038/hdy.1972.87>, weighted average of absolute scores by Olivoto et al. (2019a) <doi:10.2134/agronj2019.03.0220>, and multi-trait stability index by Olivoto et al. (2019b) <doi:10.2134/agronj2019.03.0221>. Non-parametric methods includes superiority index by Lin & Binns (1988) <doi:10.4141/cjps88-018>, nonparametric measures of phenotypic stability by Huehn (1990) <https://link.springer.com/article/10.1007/BF00024241>, TOP third statistic by Fox et al. (1990) <doi:10.1007/BF00040364>. Functions for computing biometrical analysis such as path analysis, canonical correlation, partial correlation, clustering analysis, and tools for inspecting, manipulating, summarizing and plotting typical multi-environment trial data are also provided.
Author: Tiago Olivoto [aut, cre, cph] (<https://orcid.org/0000-0002-0241-9636>)
Maintainer: Tiago Olivoto <tiagoolivoto@gmail.com>

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Fri, 23 Oct 2020

Package ICON updated to version 0.4.0 with previous version 0.3.0 dated 2020-08-29

Title: Provides Easy Access to Complex Systems Datasets
Description: Provides easy-to-use and easy-to-access datasets from the Index of COmplex Networks (ICON) database available on the University of Colorado website. All datasets can be loaded with a single function call and new datasets are being slowly added from ICON at <https://icon.colorado.edu>. Specific ICON datasets of interest can be requested at the BugReports URL <https://github.com/rrrlw/ICON/issues>.
Author: Raoul Wadhwa [aut, cre] (<https://orcid.org/0000-0003-0503-9580>), Jacob Scott [aut] (<https://orcid.org/0000-0003-2971-7673>)
Maintainer: Raoul Wadhwa <raoulwadhwa@gmail.com>

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Package VC2copula updated to version 0.1.1 with previous version 0.1.0 dated 2019-12-15

Title: Extend the 'copula' Package with Families and Models from 'VineCopula'
Description: Provides new classes for (rotated) BB1, BB6, BB7, BB8, and Tawn copulas, extends the existing Gumbel and Clayton families with rotations, and allows to set up a vine copula model using the 'copula' API. Corresponding objects from the 'VineCopula' API can easily be converted.
Author: Thomas Nagler [aut, cre], Benedikt Graeler [ctb]
Maintainer: Thomas Nagler <mail@tnagler.com>

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Package knitrdata updated to version 0.5.2 with previous version 0.5.1 dated 2020-10-22

Title: Data Language Engine for 'knitr' / 'rmarkdown'
Description: Implements a data language engine for incorporating data directly in 'rmarkdown' documents so that they can be made completely standalone.
Author: David M. Kaplan [aut, cre, cph] (<https://orcid.org/0000-0001-6087-359X>, dmkaplan2000)
Maintainer: David M. Kaplan <dmkaplan2000@gmail.com>

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Package RcppSpdlog updated to version 0.0.3 with previous version 0.0.2 dated 2020-09-20

Title: 'spdlog' C++ Header Library for Logging
Description: The mature and widely-used C++ logging library 'spdlog' provides many desirable features. This package bundles these header files for easy use by R packages via a simple 'LinkingTo:' inclusion.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package rGEDI updated to version 0.1.9 with previous version 0.1.8 dated 2020-07-15

Title: NASA's Global Ecosystem Dynamics Investigation (GEDI) Data Visualization and Processing
Description: Set of tools for downloading, reading, visualizing and processing GEDI Level1B, Level2A and Level2B data.
Author: Carlos Alberto Silva [aut, cre, cph], Caio Hamamura [aut, cph], Ruben Valbuena [aut, ctb], Steven Hancock [aut, ctb], Adrian Cardil [aut, ctb], Eben North Broadbent [aut, ctb], Danilo Roberti Alves de Almeida [aut, ctb], Celso H. L. Silva Junior [aut, ctb], Carine Klauberg [aut, ctb], Burton Garbow [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Kenneth Hillstrom [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Jorge More [cph] (Is the author of the MINPACK-1 Least Squares Fitting Library), Craig Markwardt [cph] (Is the author of the enhanced MINPACK-1 Least Squares Fitting Library)
Maintainer: Carlos Alberto Silva <carlos_engflorestal@outlook.com>

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Package plotdap updated to version 0.0.8 with previous version 0.0.7 dated 2020-03-20

Title: Easily Visualize Data from 'ERDDAP' Servers via the 'rerddap' Package
Description: Easily visualize and animate 'tabledap' and 'griddap' objects obtained via the 'rerddap' package in a simple one-line command, using either base graphics or 'ggplot2' graphics. 'plotdap' handles extracting and reshaping the data, map projections and continental outlines. Optionally the data can be animated through time using the 'gganmiate' package.
Author: Carson Sievert [aut], Roy Mendelssohn [aut, ctb, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>

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Package graphicalVAR updated to version 0.2.4 with previous version 0.2.3 dated 2020-04-09

Title: Graphical VAR for Experience Sampling Data
Description: Estimates within and between time point interactions in experience sampling data, using the Graphical vector autoregression model in combination with regularization. See also Epskamp, Waldorp, Mottus & Borsboom (2018) <doi:10.1080/00273171.2018.1454823>.
Author: Sacha Epskamp
Maintainer: Sacha Epskamp <mail@sachaepskamp.com>

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Package fun updated to version 0.3 with previous version 0.2 dated 2018-12-05

Title: Use R for Fun
Description: This is a collection of R games and other funny stuff, such as the classic Mine sweeper and sliding puzzles.
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Yixuan Qiu [aut], Taiyun Wei [aut]
Maintainer: Yihui Xie <xie@yihui.name>

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Package mlrMBO updated to version 1.1.5 with previous version 1.1.4 dated 2020-02-28

Title: Bayesian Optimization and Model-Based Optimization of Expensive Black-Box Functions
Description: Flexible and comprehensive R toolbox for model-based optimization ('MBO'), also known as Bayesian optimization. It implements the Efficient Global Optimization Algorithm and is designed for both single- and multi- objective optimization with mixed continuous, categorical and conditional parameters. The machine learning toolbox 'mlr' provide dozens of regression learners to model the performance of the target algorithm with respect to the parameter settings. It provides many different infill criteria to guide the search process. Additional features include multi-point batch proposal, parallel execution as well as visualization and sophisticated logging mechanisms, which is especially useful for teaching and understanding of algorithm behavior. 'mlrMBO' is implemented in a modular fashion, such that single components can be easily replaced or adapted by the user for specific use cases.
Author: Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut, cre] (<https://orcid.org/0000-0003-4481-5554>), Jakob Bossek [aut] (<https://orcid.org/0000-0002-4121-4668>), Daniel Horn [aut], Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Janek Thomas [aut] (<https://orcid.org/0000-0003-4511-6245>)
Maintainer: Jakob Richter <code@jakob-r.de>

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Package findInFiles updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-22

Title: Find Pattern in Files
Description: Creates a HTML widget which displays the results of searching for a pattern in files in a given folder. The results can be viewed in the 'RStudio' viewer pane, included in a 'R Markdown' document or in a 'Shiny' app.
Author: Stéphane Laurent [aut, cre], Rob Burns [ctb, cph] ('ansi-to-html' library)
Maintainer: Stéphane Laurent <laurent_step@outlook.fr>

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Package epitweetr updated to version 0.1.24 with previous version 0.1.20 dated 2020-10-01

Title: Early Detection of Public Health Threats from Twitter Data
Description: It allows you to automatically monitor trends of tweets by time, place and topic aiming at detecting public health threats early through the detection of signals (e.g. an unusual increase in the number of tweets). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords.
Author: Francisco Orchard [aut, ctr] (<https://orcid.org/0000-0001-5793-3301>, Author of the package and original code), Laura Espinosa [aut, cre, fnd] (<https://orcid.org/0000-0003-0748-9657>, Project manager, author of the design and concept of the package, and package maintainer), Ariana Wijermans [ctb] (Contributor to the design and concept of the package), Thomas Mollet [ctb, fnd] (Business owner of the project, and contributor to the design and concept of the package), Adrian Prodan [ctb], Thomas Czernichow [ctb], Maria Prieto Gonzalez [ctb], Esther Kissling [ctb], Michael Höhle [ctb]
Maintainer: Laura Espinosa <laura.espinosa@ecdc.europa.eu>

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Package corto updated to version 1.1.3 with previous version 1.1.2 dated 2020-10-13

Title: Inference of Gene Regulatory Networks
Description: We present 'corto' (Correlation Tool), a simple package to infer gene regulatory networks and visualize master regulators from gene expression data using DPI (Data Processing Inequality) and bootstrapping to recover edges. An initial step is performed to calculate all significant edges between a list of source nodes (centroids) and target genes. Then all triplets containing two centroids and one target are tested in a DPI step which removes edges. A bootstrapping process then calculates the robustness of the network, eventually re-adding edges previously removed by DPI. The algorithm has been optimized to run outside a computing cluster, using a fast correlation implementation. The package finally provides functions to calculate network enrichment analysis from RNA-Seq and ATAC-Seq signatures as described in the article by Giorgi lab (2020) <doi:10.1093/bioinformatics/btaa223>.
Author: Federico M. Giorgi [aut, cre], Daniele Mercatelli [ctb], Gonzalo Lopez-Garcia [ctb]
Maintainer: Federico M. Giorgi <federico.giorgi@gmail.com>

Diff between corto versions 1.1.2 dated 2020-10-13 and 1.1.3 dated 2020-10-23

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Package prospectr updated to version 0.2.1 with previous version 0.2.0 dated 2020-03-14

Title: Miscellaneous Functions for Processing and Sample Selection of Spectroscopic Data
Description: Functions to preprocess spectroscopic data and conduct (representative) sample selection/calibration sampling.
Author: Antoine Stevens [aut, cre] (<https://orcid.org/0000-0002-1588-7519>), Leonardo Ramirez-Lopez [aut, cre] (<https://orcid.org/0000-0002-5369-5120>), Guillaume Hans [ctb] (<https://orcid.org/0000-0002-6503-5760>)
Maintainer: Leonardo Ramirez-Lopez <ramirez.lopez.leo@gmail.com>

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Package opentripplanner updated to version 0.3.0 with previous version 0.2.3.0 dated 2020-06-09

Title: Setup and connect to 'OpenTripPlanner'
Description: Setup and connect to 'OpenTripPlanner' (OTP) <http://www.opentripplanner.org/>. OTP is an open source platform for multi-modal and multi-agency journey planning written in 'Java'. The package allows you to manage a local version or connect to remote OTP server. This package has been peer-reviewed by rOpenSci (v. 0.2.0.0).
Author: Malcolm Morgan [aut, cre] (<https://orcid.org/0000-0002-9488-9183>), Marcus Young [aut] (<https://orcid.org/0000-0003-4627-1116>), Robin Lovelace [aut] (<https://orcid.org/0000-0001-5679-6536>), Layik Hama [ctb] (<https://orcid.org/0000-0003-1912-4890>)
Maintainer: Malcolm Morgan <m.morgan1@leeds.ac.uk>

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Package lmerTest updated to version 3.1-3 with previous version 3.1-2 dated 2020-04-08

Title: Tests in Linear Mixed Effects Models
Description: Provides p-values in type I, II or III anova and summary tables for lmer model fits (cf. lme4) via Satterthwaite's degrees of freedom method. A Kenward-Roger method is also available via the pbkrtest package. Model selection methods include step, drop1 and anova-like tables for random effects (ranova). Methods for Least-Square means (LS-means) and tests of linear contrasts of fixed effects are also available.
Author: Alexandra Kuznetsova [aut], Per Bruun Brockhoff [aut, ths], Rune Haubo Bojesen Christensen [aut, cre], Sofie Pødenphant Jensen [ctb]
Maintainer: Rune Haubo Bojesen Christensen <Rune.Haubo@gmail.com>

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Package RPEIF updated to version 1.1.0 with previous version 1.0.8 dated 2020-04-23

Title: Computation and Plots of Influence Functions for Risk and Performance Measures
Description: Computes the influence functions time series of the returns for the risk and performance measures as mentioned in Chen and Martin (2018) <https://www.ssrn.com/abstract=3085672>, as well as in Zhang et al. (2019) <https://www.ssrn.com/abstract=3415903>. Also evaluates estimators influence functions at a set of parameter values and plots them to display the shapes of the influence functions.
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Shengyu Zhang <syzhang@uw.edu>, Douglas Martin <doug@amath.washington.edu>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

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Package PowerTOST updated to version 1.5-1 with previous version 1.5-0 dated 2020-08-05

Title: Power and Sample Size for (Bio)Equivalence Studies
Description: Contains functions to calculate power and sample size for various study designs used in bioequivalence studies. Use known.designs() to see the designs supported. Power and sample size can be obtained based on different methods, amongst them prominently the TOST procedure (two one-sided t-tests). See README and NEWS for further information.
Author: Detlew Labes [aut, cre] (<https://orcid.org/0000-0003-2169-426X>), Helmut Schütz [aut] (<https://orcid.org/0000-0002-1167-7880>), Benjamin Lang [aut]
Maintainer: Detlew Labes <DetlewLabes@gmx.de>

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Package glca updated to version 1.1.0 with previous version 1.0.2 dated 2020-10-20

Title: An R Package for Estimating a Group-Effect in Latent Class Analysis
Description: Fits latent class analysis (LCA) including group variable and covariates. The group variable can be handled either by multilevel LCA described in Vermunt (2003) <DOI:10.1111/j.0081-1750.2003.t01-1-00131.x> or standard LCA at each level of group variable. The covariates can be incorporated in the form of logistic regression (Bandeen-Roche et al. (1997) <DOI:10.1080/01621459.1997.10473658>).
Author: Youngsun Kim [aut, cre], Hwan Chung [aut]
Maintainer: Youngsun Kim <kim0sun@korea.ac.kr>

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Package scam updated to version 1.2-8 with previous version 1.2-7 dated 2020-09-24

Title: Shape Constrained Additive Models
Description: Routines for generalized additive modelling under shape constraints on the component functions of the linear predictor (Pya and Wood, 2015) <doi:10.1007/s11222-013-9448-7>. Models can contain multiple shape constrained (univariate and/or bivariate) and unconstrained terms. The routines of gam() in package 'mgcv' are used for setting up the model matrix, printing and plotting the results. Penalized likelihood maximization based on Newton-Raphson method is used to fit a model with multiple smoothing parameter selection by GCV or UBRE/AIC.
Author: Natalya Pya <nat.pya@gmail.com>
Maintainer: Natalya Pya <nat.pya@gmail.com>

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Package lme4 updated to version 1.1-25 with previous version 1.1-23 dated 2020-04-07

Title: Linear Mixed-Effects Models using 'Eigen' and S4
Description: Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".
Author: Douglas Bates [aut] (<https://orcid.org/0000-0001-8316-9503>), Martin Maechler [aut] (<https://orcid.org/0000-0002-8685-9910>), Ben Bolker [aut, cre] (<https://orcid.org/0000-0002-2127-0443>), Steven Walker [aut] (<https://orcid.org/0000-0002-4394-9078>), Rune Haubo Bojesen Christensen [ctb] (<https://orcid.org/0000-0002-4494-3399>), Henrik Singmann [ctb] (<https://orcid.org/0000-0002-4842-3657>), Bin Dai [ctb], Fabian Scheipl [ctb] (<https://orcid.org/0000-0001-8172-3603>), Gabor Grothendieck [ctb], Peter Green [ctb] (<https://orcid.org/0000-0002-0238-9852>), John Fox [ctb], Alexander Bauer [ctb], Pavel N. Krivitsky [ctb, cph] (<https://orcid.org/0000-0002-9101-3362>, shared copyright on simulate.formula)
Maintainer: Ben Bolker <bbolker+lme4@gmail.com>

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Package VGAM updated to version 1.1-4 with previous version 1.1-3 dated 2020-04-28

Title: Vector Generalized Linear and Additive Models
Description: An implementation of about 6 major classes of statistical regression models. The central algorithm is Fisher scoring and iterative reweighted least squares. At the heart of this package are the vector generalized linear and additive model (VGLM/VGAM) classes. VGLMs can be loosely thought of as multivariate GLMs. VGAMs are data-driven VGLMs that use smoothing. The book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7> gives details of the statistical framework and the package. Currently only fixed-effects models are implemented. Many (150+) models and distributions are estimated by maximum likelihood estimation (MLE) or penalized MLE. The other classes are RR-VGLMs (reduced-rank VGLMs), quadratic RR-VGLMs, reduced-rank VGAMs, RCIMs (row-column interaction models)---these classes perform constrained and unconstrained quadratic ordination (CQO/UQO) models in ecology, as well as constrained additive ordination (CAO). Hauck-Donner effect detection is implemented. Note that these functions are subject to change; see the NEWS and ChangeLog files for latest changes.
Author: Thomas Yee [aut, cre], Cleve Moler [ctb] (author of several LINPACK routines)
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

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Thu, 22 Oct 2020

Package Pijavski updated to version 1.0.3 with previous version 1.0 dated 2016-03-12

Title: Global Univariate Minimization
Description: Global univariate minimization of Lipschitz functions is performed by using Pijavski method, which was published in Pijavski (1972) <DOI:10.1016/0041-5553(72)90115-2>.
Author: Gleb Beliakov [aut, cre], Gita Das [aut], Jonathan Wells [ctb], Hewlett-Packard Company [ctb], Silicon Graphics Computer Systems Inc. [ctb]
Maintainer: Gleb Beliakov <gleb@deakin.edu.au>

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Package MNP updated to version 3.1-1 with previous version 3.1-0 dated 2017-09-27

Title: Fitting the Multinomial Probit Model
Description: Fits the Bayesian multinomial probit model via Markov chain Monte Carlo. The multinomial probit model is often used to analyze the discrete choices made by individuals recorded in survey data. Examples where the multinomial probit model may be useful include the analysis of product choice by consumers in market research and the analysis of candidate or party choice by voters in electoral studies. The MNP package can also fit the model with different choice sets for each individual, and complete or partial individual choice orderings of the available alternatives from the choice set. The estimation is based on the efficient marginal data augmentation algorithm that is developed by Imai and van Dyk (2005). "A Bayesian Analysis of the Multinomial Probit Model Using the Data Augmentation." Journal of Econometrics, Vol. 124, No. 2 (February), pp. 311-334. <doi:10.1016/j.jeconom.2004.02.002> Detailed examples are given in Imai and van Dyk (2005). "MNP: R Package for Fitting the Multinomial Probit Model." Journal of Statistical Software, Vol. 14, No. 3 (May), pp. 1-32. <doi:10.18637/jss.v014.i03>.
Author: Kosuke Imai [aut, cre], David van Dyk [aut], Hubert Jin [ctb]
Maintainer: Kosuke Imai <imai@harvard.edu>

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Package mlr3fselect updated to version 0.4.0 with previous version 0.3.0 dated 2020-09-22

Title: Feature Selection for 'mlr3'
Description: Implements methods for feature selection with 'mlr3', e.g. random search and sequential selection. Various termination criteria can be set and combined. The class 'AutoFSelector' provides a convenient way to perform nested resampling in combination with 'mlr3'.
Author: Marc Becker [aut, cre] (<https://orcid.org/0000-0002-8115-0400>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Michel Lang [aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>)
Maintainer: Marc Becker <marcbecker@posteo.de>

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Package merDeriv updated to version 0.2-2 with previous version 0.2-1 dated 2020-10-18

Title: Case-Wise and Cluster-Wise Derivatives for Mixed Effects Models
Description: Compute case-wise and cluster-wise derivative for mixed effects models with respect to fixed effects parameter, random effect (co)variances, and residual variance. This material is partially based on work supported by the National Science Foundation under Grant Number 1460719.
Author: Ting Wang [aut, cre], Edgar Merkle [aut] (<https://orcid.org/0000-0001-7158-0653>), Yves Rosseel [ctb]
Maintainer: Ting Wang <twb8d@mail.missouri.edu>

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Package kableExtra updated to version 1.3.1 with previous version 1.3.0 dated 2020-10-22

Title: Construct Complex Table with 'kable' and Pipe Syntax
Description: Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' and the piping syntax from 'magrittr'. Function 'kable()' is a light weight table generator coming from 'knitr'. This package simplifies the way to manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows users to construct complex tables and customize styles using a readable syntax.
Author: Hao Zhu [aut, cre] (<https://orcid.org/0000-0002-3386-6076>), Thomas Travison [ctb], Timothy Tsai [ctb], Will Beasley [ctb], Yihui Xie [ctb], GuangChuang Yu [ctb], Stéphane Laurent [ctb], Rob Shepherd [ctb], Yoni Sidi [ctb], Brian Salzer [ctb], George Gui [ctb], Yeliang Fan [ctb], Duncan Murdoch [ctb], Bill Evans [ctb]
Maintainer: Hao Zhu <haozhu233@gmail.com>

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Package mdatools updated to version 0.11.2 with previous version 0.11.1 dated 2020-07-23

Title: Multivariate Data Analysis for Chemometrics
Description: Projection based methods for preprocessing, exploring and analysis of multivariate data used in chemometrics. S. Kucheryavskiy (2020) <doi: 10.1016/j.chemolab.2020.103937>.
Author: Sergey Kucheryavskiy
Maintainer: Sergey Kucheryavskiy <svkucheryavski@gmail.com>

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Package MKinfer updated to version 0.6 with previous version 0.5 dated 2020-04-25

Title: Inferential Statistics
Description: Computation of various confidence intervals (Altman et al. (2000), ISBN:978-0-727-91375-3; Hedderich and Sachs (2018), ISBN:978-3-662-56657-2) including bootstrapped versions (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) as well as Hsu (Hedderich and Sachs (2018), ISBN:978-3-662-56657-2), permutation (Janssen (1997), <doi:10.1016/S0167-7152(97)00043-6>), bootstrap (Davison and Hinkley (1997), ISBN:978-0-511-80284-3) and multiple imputation (Barnard and Rubin (1999), <doi:10.1093/biomet/86.4.948>) t-test. Graphical visualization by volcano plots.
Author: Matthias Kohl [aut, cre] (<https://orcid.org/0000-0001-9514-8910>)
Maintainer: Matthias Kohl <Matthias.Kohl@stamats.de>

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Package modeldata updated to version 0.1.0 with previous version 0.0.2 dated 2020-06-22

Title: Data Sets Used Useful for Modeling Packages
Description: Data sets used for demonstrating or testing model-related packages are contained in this package.
Author: Max Kuhn [aut, cre], RStudio [cph]
Maintainer: Max Kuhn <max@rstudio.com>

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Package lazytrade updated to version 0.4.1 with previous version 0.4.0 dated 2020-09-16

Title: Learn Computer and Data Science using Algorithmic Trading
Description: Provide sets of functions and methods to learn and practice data science using idea of algorithmic trading. Main goal is to process information within "Decision Support System" to come up with analysis or predictions. There are several utilities such as dynamic and adaptive risk management using reinforcement learning and even functions to generate predictions of price changes using pattern recognition deep regression learning. Summary of Methods used: Awesome H2O tutorials: <https://github.com/h2oai/awesome-h2o>, Market Type research of Van Tharp Institute: <https://www.vantharp.com/>, Reinforcement Learning R package: <https://CRAN.R-project.org/package=ReinforcementLearning>.
Author: Vladimir Zhbanko
Maintainer: Vladimir Zhbanko <vladimir.zhbanko@gmail.com>

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Package nflfastR updated to version 3.1.1 with previous version 3.0.0 dated 2020-09-24

Title: Functions to Efficiently Access NFL Play by Play Data
Description: A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.
Author: Sebastian Carl [aut], Ben Baldwin [cre, aut], Lee Sharpe [ctb], Maksim Horowitz [ctb], Ron Yurko [ctb], Samuel Ventura [ctb]
Maintainer: Ben Baldwin <bbaldwin206@gmail.com>

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Permanent link

Package timetk updated to version 2.5.0 with previous version 2.4.0 dated 2020-10-08

Title: A Tool Kit for Working with Time Series in R
Description: Easy visualization, wrangling, and feature engineering of time series data for forecasting and machine learning prediction. Methods discussed herein are commonplace in machine learning, and have been cited in various literature. Refer to "Calendar Effects" in papers such as Taieb, Souhaib Ben. "Machine learning strategies for multi-step-ahead time series forecasting." Universit Libre de Bruxelles, Belgium (2014): 75-86. <http://souhaib-bentaieb.com/pdf/2014_phd.pdf>.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

Diff between timetk versions 2.4.0 dated 2020-10-08 and 2.5.0 dated 2020-10-22

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Package eoffice updated to version 0.2.0 with previous version 0.1.9 dated 2020-02-25

Title: Export or Graph and Tables to 'Microsoft' Office and Import Figures and Tables
Description: Provides wrap functions to export and import graphics and data frames in R to 'microsoft' office. And This package also provide write out figures with lots of different formats. Since people may work on the platform without GUI support, the package also provide function to easily write out figures to lots of different type of formats. Now this package provide function to extract colors from all types of figures and pdf files.
Author: Kai Guo [aut, cre]
Maintainer: Kai Guo <guokai8@gmail.com>

Diff between eoffice versions 0.1.9 dated 2020-02-25 and 0.2.0 dated 2020-10-22

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More information about eoffice at CRAN
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Package phenology updated to version 7.6 with previous version 7.3 dated 2019-01-04

Title: Tools to Manage a Parametric Function that Describes Phenology and More
Description: Functions used to fit and test the phenology of species based on counts.
Author: Marc Girondot
Maintainer: Marc Girondot <marc.girondot@universite-paris-saclay.fr>

Diff between phenology versions 7.3 dated 2019-01-04 and 7.6 dated 2020-10-22

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Package embryogrowth updated to version 8.0 with previous version 7.6 dated 2019-08-30

Title: Tools to Analyze the Thermal Reaction Norm of Embryo Growth
Description: Tools to analyze the embryo growth and the sexualisation thermal reaction norms.
Author: Marc Girondot <marc.girondot@universite-paris-saclay.fr>
Maintainer: Marc Girondot <marc.girondot@universite-paris-saclay.fr>

Diff between embryogrowth versions 7.6 dated 2019-08-30 and 8.0 dated 2020-10-22

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Package bayestestR updated to version 0.7.5 with previous version 0.7.2 dated 2020-07-20

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

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Package knitrdata updated to version 0.5.1 with previous version 0.5.0 dated 2020-07-15

Title: Data Language Engine for 'knitr' / 'rmarkdown'
Description: Implements a data language engine for incorporating data directly in 'rmarkdown' documents so that they can be made completely standalone.
Author: David M. Kaplan [aut, cre, cph] (<https://orcid.org/0000-0001-6087-359X>, dmkaplan2000)
Maintainer: David M. Kaplan <dmkaplan2000@gmail.com>

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Package simstandard updated to version 0.5.0 with previous version 0.3.0 dated 2019-01-07

Title: Generate Standardized Data
Description: Creates simulated data from structural equation models with standardized loading. Data generation methods are described in Schneider (2013) <doi:10.1177/0734282913478046>.
Author: W. Joel Schneider [aut, cre] (<https://orcid.org/0000-0002-8393-5316>)
Maintainer: W. Joel Schneider <w.joel.schneider@gmail.com>

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Package bbsBayes updated to version 2.3.4.2020 with previous version 2.3.3.2020 dated 2020-07-08

Title: Hierarchical Bayesian Analysis of North American BBS Data
Description: The North American Breeding Bird Survey (BBS) is a long-running program that seeks to monitor the status and trends of the breeding birds in North America. Since its start in 1966, the BBS has accumulated over 50 years of data for over 500 species of North American Birds. Given the temporal and spatial structure of the data, hierarchical Bayesian models are used to assess the status and trends of these 500+ species of birds. 'bbsBayes' allows you to perform hierarchical Bayesian analysis of BBS data. You can run a full model analysis for one or more species that you choose, or you can take more control and specify how the data should be stratified, prepared for 'JAGS', or modelled. The functions provided here allow you to replicate analyses performed by the United State Geological Survey (USGS, see Link and Sauer (2011) <doi:10.1525/auk.2010.09220>) and Canadian Wildlife Service (CWS, see Smith and Edwards (2020) <doi:10.1101/2020.03.26.010215>).
Author: Brandon P.M. Edwards [aut, cre], Adam C. Smith [aut]
Maintainer: Brandon P.M. Edwards <edwardsb@uoguelph.ca>

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Package xmeta updated to version 1.2-1 with previous version 1.1-5 dated 2019-11-01

Title: A Toolbox for Multivariate Meta-Analysis
Description: A toolbox for meta-analysis. This package includes a collection of functions for (1) implementing robust multivariate meta-analysis of continuous or binary outcomes; and (2) a bivariate Egger's test for detecting small study effects.
Author: Chuan Hong [aut], Chongliang Luo [aut], Rui Duan [aut], Jiayi Tong [aut, cre], Haitao Chu [ctb], Yulun Liu [ctb], Yong Chen [aut]
Maintainer: Jiayi Tong <Jiayi.Tong@pennmedicine.upenn.edu>

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Package neat updated to version 1.2.2 with previous version 1.2.1 dated 2020-01-09

Title: Efficient Network Enrichment Analysis Test
Description: Includes functions and examples to compute NEAT, the Network Enrichment Analysis Test described in Signorelli et al. (2016, <DOI:10.1186/s12859-016-1203-6>).
Author: Mirko Signorelli [aut, cre, cph] (<https://orcid.org/0000-0002-8102-3356>), Veronica Vinciotti [aut], Ernst Wit [aut]
Maintainer: Mirko Signorelli <msignorelli.rpackages@gmail.com>

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Package metaboGSE updated to version 1.2.5 with previous version 1.2.4 dated 2020-05-07

Title: Gene Set Enrichment Analysis via Integration of Metabolic Networks and RNA-Seq Data
Description: Integrates metabolic networks and RNA-seq data to construct condition-specific series of metabolic sub-networks and applies to gene set enrichment analysis (Tran et al. (2018) <doi:10.1093/bioinformatics/bty929>).
Author: Van Du T. Tran [aut, cre], Marco Pagni [aut]
Maintainer: Van Du T. Tran <thuong.tran@sib.swiss>

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Package rotl updated to version 3.0.11 with previous version 3.0.10 dated 2019-09-28

Title: Interface to the 'Open Tree of Life' API
Description: An interface to the 'Open Tree of Life' API to retrieve phylogenetic trees, information about studies used to assemble the synthetic tree, and utilities to match taxonomic names to 'Open Tree identifiers'. The 'Open Tree of Life' aims at assembling a comprehensive phylogenetic tree for all named species.
Author: Francois Michonneau [aut, cre] (<https://orcid.org/0000-0002-9092-966X>), Joseph Brown [aut] (<https://orcid.org/0000-0002-3835-8062>), David Winter [aut] (<https://orcid.org/0000-0002-6165-0029>), Scott Chamberlain [rev] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Francois Michonneau <francois.michonneau@gmail.com>

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Package czso updated to version 0.3.2 with previous version 0.2.3 dated 2020-04-07

Title: Use Open Data from the Czech Statistical Office in R
Description: Get programmatic access to the open data provided by the Czech Statistical Office (CZSO, <https://czso.cz>).
Author: Petr Bouchal [aut, cre] (<https://orcid.org/0000-0002-0471-716X>), Jindra Lacko [ctb]
Maintainer: Petr Bouchal <pbouchal@gmail.com>

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Package wru updated to version 0.1-10 with previous version 0.1-9 dated 2019-02-21

Title: Who are You? Bayesian Prediction of Racial Category Using Surname and Geolocation
Description: Predicts individual race/ethnicity using surname, geolocation, and other attributes, such as gender and age. The method utilizes the Bayes' Rule to compute the posterior probability of each racial category for any given individual. The package implements methods described in Imai and Khanna (2015) "Improving Ecological Inference by Predicting Individual Ethnicity from Voter Registration Records" <DOI:10.1093/pan/mpw001>.
Author: Kabir Khanna [aut, cre], Kosuke Imai [aut]
Maintainer: Kabir Khanna <kabirkhanna@gmail.com>

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Package vectools updated to version 0.2.0 with previous version 0.1.1 dated 2020-01-09

Title: Advanced Vector Toolkit
Description: Block matrices and object arrays, as general purpose S4 data structures, with automatic formatting. Matrix arrays (that is, arrays of matrices), with binary operators for succinct/convenient matrix array multiplication. Set/sequence related functions, including index/interval finding functions. Also, SQL-like select functions, analytic geometry functions, head/tail generalizations and prototype pooling/convolution functions.
Author: Abby Spurdle
Maintainer: Abby Spurdle <spurdle.a@gmail.com>

Diff between vectools versions 0.1.1 dated 2020-01-09 and 0.2.0 dated 2020-10-22

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Package kableExtra updated to version 1.3.0 with previous version 1.2.1 dated 2020-08-27

Title: Construct Complex Table with 'kable' and Pipe Syntax
Description: Build complex HTML or 'LaTeX' tables using 'kable()' from 'knitr' and the piping syntax from 'magrittr'. Function 'kable()' is a light weight table generator coming from 'knitr'. This package simplifies the way to manipulate the HTML or 'LaTeX' codes generated by 'kable()' and allows users to construct complex tables and customize styles using a readable syntax.
Author: Hao Zhu [aut, cre] (<https://orcid.org/0000-0002-3386-6076>), Thomas Travison [ctb], Timothy Tsai [ctb], Will Beasley [ctb], Yihui Xie [ctb], GuangChuang Yu [ctb], Stéphane Laurent [ctb], Rob Shepherd [ctb], Yoni Sidi [ctb], Brian Salzer [ctb], George Gui [ctb], Yeliang Fan [ctb], Duncan Murdoch [ctb], Bill Evans [ctb]
Maintainer: Hao Zhu <haozhu233@gmail.com>

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Package insight updated to version 0.10.0 with previous version 0.9.6 dated 2020-09-20

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

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Package distill updated to version 1.0 with previous version 0.8 dated 2020-06-04

Title: 'R Markdown' Format for Scientific and Technical Writing
Description: Scientific and technical article format for the web. 'Distill' articles feature attractive, reader-friendly typography, flexible layout options for visualizations, and full support for footnotes and citations.
Author: JJ Allaire [aut, cre] (<https://orcid.org/0000-0003-0174-9868>), Rich Iannone [aut], Alison Presmanes Hill [aut] (<https://orcid.org/0000-0002-8082-1890>), Yihui Xie [aut] (<https://orcid.org/0000-0003-0645-5666>), RStudio, Inc. [cph], Google LLC [ctb, cph] (https://distill.pub/guide/), Nick Williams [ctb, cph] (https://wicky.nillia.ms/headroom.js/), Denis Demchenko [ctb, cph] (https://github.com/lancedikson/bowser), The Polymer Authors [ctb, cph] (https://www.webcomponents.org/polyfills/), Gábor Csárdi [ctb, cph] (whoami), JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>)
Maintainer: JJ Allaire <jj@rstudio.com>

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Package anyflights updated to version 0.3.1 with previous version 0.3.0 dated 2020-08-10

Title: Query 'nycflights13'-Like Air Travel Data for Given Years and Airports
Description: Supplies a set of functions to query air travel data for user- specified years and airports. Datasets include on-time flights, airlines, airports, planes, and weather.
Author: Simon P. Couch [aut, cre], Hadley Wickham [ctb], Jay Lee [ctb], Dennis Irorere [ctb]
Maintainer: Simon P. Couch <simonpatrickcouch@gmail.com>

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Wed, 21 Oct 2020

Package spatsoc updated to version 0.1.15 with previous version 0.1.14 dated 2020-07-05

Title: Group Animal Relocation Data by Spatial and Temporal Relationship
Description: Detects spatial and temporal groups in GPS relocations (Robitaille et al. (2020) <doi:10.1111/2041-210X.13215>). It can be used to convert GPS relocations to gambit-of-the-group format to build proximity-based social networks In addition, the randomizations function provides data-stream randomization methods suitable for GPS data.
Author: Alec L. Robitaille [aut, cre] (<https://orcid.org/0000-0002-4706-1762>), Quinn Webber [aut] (<https://orcid.org/0000-0002-0434-9360>), Eric Vander Wal [aut] (<https://orcid.org/0000-0002-8534-4317>)
Maintainer: Alec L. Robitaille <robit.alec@gmail.com>

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Package signnet updated to version 0.7.0 with previous version 0.6.0 dated 2020-08-13

Title: Methods to Analyse Signed Networks
Description: Methods for the analysis of signed networks. This includes several measures for structural balance as introduced by Cartwright and Harary (1956) <doi:10.1037/h0046049>, blockmodeling algorithms from Doreian (2008) <doi:10.1016/j.socnet.2008.03.005>, various centrality indices, and projections of signed two-mode networks introduced by Schoch (2020) <doi:10.1080/0022250X.2019.1711376>.
Author: David Schoch [aut, cre]
Maintainer: David Schoch <david.schoch@manchester.ac.uk>

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Package StempCens updated to version 1.1.0 with previous version 0.1.0 dated 2019-02-08

Title: Spatio-Temporal Estimation and Prediction for Censored/Missing Responses
Description: It estimates the parameters of a censored or missing data in spatio-temporal models using the SAEM algorithm (Delyon et al., 1999). This algorithm is a stochastic approximation of the widely used EM algorithm and an important tool for models in which the E-step does not have an analytic form. Besides the expressions obtained to estimate the parameters to the proposed model, we include the calculations for the observed information matrix using the method developed by Louis (1982). To examine the performance of the fitted model, case-deletion measure are provided.
Author: Larissa A. Matos [aut, cre] (<https://orcid.org/0000-0002-2635-0901>), Katherine L. Valeriano [aut] (<https://orcid.org/0000-0001-6388-4753>), Victor H. Lachos [ctb] (<https://orcid.org/0000-0002-7239-2459>)
Maintainer: Larissa A. Matos <larissa.amatos@gmail.com>

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Package SQUAREM updated to version 2020.5 with previous version 2020.4 dated 2020-08-26

Title: Squared Extrapolation Methods for Accelerating EM-Like Monotone Algorithms
Description: Algorithms for accelerating the convergence of slow, monotone sequences from smooth, contraction mapping such as the EM algorithm. It can be used to accelerate any smooth, linearly convergent acceleration scheme. A tutorial style introduction to this package is available in a vignette on the CRAN download page or, when the package is loaded in an R session, with vignette("SQUAREM"). Refer to the J Stat Software article: <doi:10.18637/jss.v092.i07>.
Author: Ravi Varadhan
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

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Package SDAR updated to version 0.9-55 with previous version 0.9-5 dated 2020-10-20

Title: Stratigraphic Data Analysis
Description: A fast, consistent tool for plotting and facilitating the analysis of stratigraphic and sedimentological data. Taking advantage of the flexible plotting tools available in R, 'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness, lithology, samples, sedimentary structures, colors, fossil content, bioturbation index, gamma ray logs) (Johnson, 1992, <ISSN 0037-0738>).
Author: John R. Ortiz [aut, cre], Carlos Jaramillo [aut], Carlos Moreno [ctb]
Maintainer: John R. Ortiz <jrortizt@unal.edu.co>

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Package Quartet updated to version 1.2.0 with previous version 1.1.0 dated 2020-01-28

Title: Comparison of Phylogenetic Trees Using Quartet and Split Measures
Description: Calculates the number of four-taxon subtrees consistent with a pair of cladograms, calculating the symmetric quartet distance of Bandelt & Dress (1986), Reconstructing the shape of a tree from observed dissimilarity data, Advances in Applied Mathematics, 7, 309-343 <doi:10.1016/0196-8858(86)90038-2>, and using the tqDist algorithm of Sand et al. (2014), tqDist: a library for computing the quartet and triplet distances between binary or general trees, Bioinformatics, 30, 2079–2080 <doi:10.1093/bioinformatics/btu157> for pairs of binary trees.
Author: Martin R. Smith [aut, cre, cph] (<https://orcid.org/0000-0001-5660-1727>), Andreas Sand [ant], Gerth Stølting Brodal [ant], Rolf Fagerberg [ant], Thomas Mailund [ant], Christian N. S. Pedersen [ant], Jens Johansen [ant], Morten K. Holt [ant]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

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Package QCA updated to version 3.10 with previous version 3.9 dated 2020-09-01

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

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Package paradox updated to version 0.5.0 with previous version 0.4.0 dated 2020-07-21

Title: Define and Work with Parameter Spaces for Complex Algorithms
Description: Define parameter spaces, constraints and dependencies for arbitrary algorithms, to program on such spaces. Also includes statistical designs and random samplers. Objects are implemented as 'R6' classes.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Xudong Sun [aut] (<https://orcid.org/0000-0003-3269-2307>), Martin Binder [aut], Marc Becker [ctb] (<https://orcid.org/0000-0002-8115-0400>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package nonmemica updated to version 0.9.6 with previous version 0.9.4 dated 2020-10-02

Title: Create and Evaluate NONMEM Models in a Project Context
Description: Systematically creates and modifies NONMEM(R) control streams. Harvests NONMEM output, builds run logs, creates derivative data, generates diagnostics. NONMEM (ICON Development Solutions <http://www.iconplc.com/>) is software for nonlinear mixed effects modeling. See 'package?nonmemica'.
Author: Tim Bergsma
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package lefko3 updated to version 3.0.0 with previous version 2.4.2 dated 2020-09-17

Title: Historical and Ahistorical Population Projection Matrix Analysis
Description: Creates matrix population models for use in population ecological analyses. Specializes on the construction of historical matrices, which are 2d matrices comprising 3 time intervals of demographic information. Estimates both raw and function-based forms of historical and standard ahistorical matrices. Methodology based on Ehrlen (2000) <doi:10.1890/0012-9658(2000)081[1675:TDOPPD]2.0.CO;2>.
Author: Richard P. Shefferson [aut, cre] (<https://orcid.org/0000-0002-5234-3131>), Johan Ehrlen [aut] (<https://orcid.org/0000-0001-8539-8967>)
Maintainer: Richard P. Shefferson <cdorm@g.ecc.u-tokyo.ac.jp>

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Package ghypernet updated to version 1.0.1 with previous version 1.0.0 dated 2020-05-20

Title: Fit and Simulate Generalised Hypergeometric Ensembles of Graphs
Description: Provides functions for model fitting and selection of generalised hypergeometric ensembles of random graphs (gHypEG). To learn how to use it, check the vignettes for a quick tutorial. Please reference its use as Casiraghi, G., Nanumyan, V. (2019) <doi:10.5281/zenodo.2555300> together with those relevant references from the one listed below. The package is based on the research developed at the Chair of Systems Design, ETH Zurich. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2016) <arXiv:1607.02441>. Casiraghi, G., Nanumyan, V., Scholtes, I., Schweitzer, F. (2017) <doi:10.1007/978-3-319-67256-4_11>. Casiraghi, G., (2017) <arxiv:1702.02048> Casiraghi, G., Nanumyan, V. (2018) <arXiv:1810.06495>. Brandenberger, L., Casiraghi, G., Nanumyan, V., Schweitzer, F. (2019) <doi:10.1145/3341161.3342926> Casiraghi, G. (2019) <doi:10.1007/s41109-019-0241-1>.
Author: Giona Casiraghi [aut, cre] (<https://orcid.org/0000-0003-0233-5747>), Vahan Nanumyan [aut] (<https://orcid.org/0000-0001-9054-3217>), Laurence Brandenberger [aut], Giacomo Vaccario [ctb]
Maintainer: Giona Casiraghi <giona@ethz.ch>

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Package behaviorchange updated to version 0.2.4 with previous version 0.2.2 dated 2020-03-01

Title: Tools for Behavior Change Researchers and Professionals
Description: Contains specialised analyses and visualisation tools for behavior change science. These facilitate conducting determinant studies (for example, using confidence interval-based estimation of relevance, CIBER, or CIBERlite plots, see Crutzen, Noijen & Peters (2017) <doi:10.3389/fpubh.2017.00165>), systematically developing, reporting, and analysing interventions (for example, using Acyclic Behavior Change Diagrams), and reporting about intervention effectiveness (for example, using the Numbers Needed for Change, see Gruijters & Peters (2017) <doi:10.31234/osf.io/2bau7>), and computing the required sample size (using the Meaningful Change Definition, see Gruijters & Peters (2019) <doi:10.31234/osf.io/jc295>). This package is especially useful for researchers in the field of behavior change or health psychology and to behavior change professionals such as intervention developers and prevention workers.
Author: Gjalt-Jorn Peters [aut, cre] (<https://orcid.org/0000-0002-0336-9589>), Rik Crutzen [ctb] (<https://orcid.org/0000-0002-3731-6610>), Stefan Gruijters [ctb] (<https://orcid.org/0000-0003-0141-0071>)
Maintainer: Gjalt-Jorn Peters <gjalt-jorn@a-bc.eu>

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Package batchtools updated to version 0.9.14 with previous version 0.9.13 dated 2020-03-19

Title: Tools for Computation on Batch Systems
Description: As a successor of the packages 'BatchJobs' and 'BatchExperiments', this package provides a parallel implementation of the Map function for high performance computing systems managed by schedulers 'IBM Spectrum LSF' (<https://www.ibm.com/products/hpc-workload-management>), 'OpenLava' (<https://www.openlava.org/>), 'Univa Grid Engine'/'Oracle Grid Engine' (<https://www.univa.com/>), 'Slurm' (<https://slurm.schedmd.com/>), 'TORQUE/PBS' (<https://adaptivecomputing.com/cherry-services/torque-resource-manager/>), or 'Docker Swarm' (<https://docs.docker.com/engine/swarm/>). A multicore and socket mode allow the parallelization on a local machines, and multiple machines can be hooked up via SSH to create a makeshift cluster. Moreover, the package provides an abstraction mechanism to define large-scale computer experiments in a well-organized and reproducible way.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut], Dirk Surmann [ctb] (<https://orcid.org/0000-0003-0873-137X>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package Arothron updated to version 2.0.1 with previous version 1.1.1 dated 2019-12-05

Title: Geometric Morphometric Methods and Virtual Anthropology Tools
Description: Tools for geometric morphometric analysis. The package includes tools of virtual anthropology to align two not articulated parts belonging to the same specimen, to build virtual cavities as endocast (Profico et al, 2018 <doi:10.1002/ajpa.23493>).
Author: Antonio Profico, Costantino Buzi, Silvia Castiglione, Marina Melchionna, Paolo Piras, Pasquale Raia, Alessio Veneziano
Maintainer: Antonio Profico <antonio.profico@york.ac.uk>

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Package ACEt updated to version 1.8.1 with previous version 1.8.0 dated 2017-05-07

Title: Estimation of Dynamic Heritability and Comparison of Twin Models
Description: Estimate the dynamic behaviour of the variance components in the classical twin models with respect to age using B-splines and P-splines.
Author: Liang He [aut, cre]
Maintainer: Liang He <liang.he@duke.edu>

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Package redland updated to version 1.0.17-14 with previous version 1.0.17-13 dated 2020-10-09

Title: RDF Library Bindings in R
Description: Provides methods to parse, query and serialize information stored in the Resource Description Framework (RDF). RDF is described at <https://www.w3.org/TR/rdf-primer/>. This package supports RDF by implementing an R interface to the Redland RDF C library, described at <http://librdf.org/docs/api/index.html>. In brief, RDF provides a structured graph consisting of Statements composed of Subject, Predicate, and Object Nodes.
Author: Matthew B. Jones [aut, cre], Peter Slaughter [aut], Jeroen Ooms [aut], Carl Boettiger [aut], Scott Chamberlain [aut], David Beckett [cph], University of Bristol [cph], Regents of the University of California [cph]
Maintainer: Matthew B. Jones <jones@nceas.ucsb.edu>

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Package waterquality updated to version 0.2.6 with previous version 0.2.5 dated 2020-10-02

Title: Satellite Derived Water Quality Detection Algorithms
Description: The main purpose of waterquality is to quickly and easily convert satellite-based reflectance imagery into one or many well-known water quality algorithms designed for the detection of harmful algal blooms or the following pigment proxies: chlorophyll-a, blue-green algae (phycocyanin), and turbidity. Johansen et al. (2019) <doi:10.21079/11681/35053>.
Author: Richard Johansen [aut, cre] (<https://orcid.org/0000-0003-4287-9677>), Jakub Nowosad [aut] (<https://orcid.org/0000-0002-1057-3721>), Molly Reif [aut] (<https://orcid.org/0000-0003-4207-1459>), Erich Emery [aut], U.S. Army Corps of Engineers [fnd]
Maintainer: Richard Johansen <richard.a.johansen@erdc.dren.mil>

Diff between waterquality versions 0.2.5 dated 2020-10-02 and 0.2.6 dated 2020-10-21

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Package warp updated to version 0.2.0 with previous version 0.1.0 dated 2020-01-14

Title: Group Dates
Description: Tooling to group dates by a variety of periods including: yearly, monthly, by second, by week of the month, and more. The groups are defined in such a way that they also represent the distance between dates in terms of the period. This extracts valuable information that can be used in further calculations that rely on a specific temporal spacing between observations.
Author: Davis Vaughan [aut, cre], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>

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Package reticulate updated to version 1.17 with previous version 1.16 dated 2020-05-27

Title: Interface to 'Python'
Description: Interface to 'Python' modules, classes, and functions. When calling into 'Python', R data types are automatically converted to their equivalent 'Python' types. When values are returned from 'Python' to R they are converted back to R types. Compatible with all versions of 'Python' >= 2.7.
Author: Kevin Ushey [aut, cre], JJ Allaire [aut], RStudio [cph, fnd], Yuan Tang [aut, cph] (<https://orcid.org/0000-0001-5243-233X>), Dirk Eddelbuettel [ctb, cph], Bryan Lewis [ctb, cph], Sigrid Keydana [ctb], Ryan Hafen [ctb, cph], Marcus Geelnard [ctb, cph] (TinyThread library, http://tinythreadpp.bitsnbites.eu/)
Maintainer: Kevin Ushey <kevin@rstudio.com>

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Package PMCMRplus updated to version 1.6.1 with previous version 1.6.0 dated 2020-10-14

Title: Calculate Pairwise Multiple Comparisons of Mean Rank Sums Extended
Description: For one-way layout experiments the one-way ANOVA can be performed as an omnibus test. All-pairs multiple comparisons tests (Tukey-Kramer test, Scheffe test, LSD-test) and many-to-one tests (Dunnett test) for normally distributed residuals and equal within variance are available. Furthermore, all-pairs tests (Games-Howell test, Tamhane's T2 test, Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one (Tamhane-Dunnett Test) for normally distributed residuals and heterogeneous variances are provided. Van der Waerden's normal scores test for omnibus, all-pairs and many-to-one tests is provided for non-normally distributed residuals and homogeneous variances. The Kruskal-Wallis, BWS and Anderson-Darling omnibus test and all-pairs tests (Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow- Fligner test) as well as many-to-one (Nemenyi test, Dunn test, U-test) are given for the analysis of variance by ranks. Non-parametric trend tests (Jonckheere test, Cuzick test, Johnson-Mehrotra test, Spearman test) are included. In addition, a Friedman-test for one-way ANOVA with repeated measures on ranks (CRBD) and Skillings-Mack test for unbalanced CRBD is provided with consequent all-pairs tests (Nemenyi test, Siegel test, Miller test, Conover test, Exact test) and many-to-one tests (Nemenyi test, Demsar test, Exact test). A trend can be tested with Pages's test. Durbin's test for a two-way balanced incomplete block design (BIBD) is given in this package as well as Gore's test for CRBD with multiple observations per cell is given. Outlier tests, Mandel's k- and h statistic as well as functions for Type I error and Power analysis as well as generic summary, print and plot methods are provided.
Author: Thorsten Pohlert [aut, cre] (<https://orcid.org/0000-0003-3855-3025>)
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

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Package furrr updated to version 0.2.1 with previous version 0.2.0 dated 2020-10-12

Title: Apply Mapping Functions in Parallel using Futures
Description: Implementations of the family of map() functions from 'purrr' that can be resolved using any 'future'-supported backend, e.g. parallel on the local machine or distributed on a compute cluster.
Author: Davis Vaughan [aut, cre], Matt Dancho [aut], RStudio [cph]
Maintainer: Davis Vaughan <davis@rstudio.com>

Diff between furrr versions 0.2.0 dated 2020-10-12 and 0.2.1 dated 2020-10-21

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Package gausscov updated to version 0.0.8 with previous version 0.0.7 dated 2020-09-14

Title: The Gaussian Covariate Method for Variable Selection
Description: Given the standard linear model the traditional way of deciding whether to include the jth covariate is to apply the F-test to decide whether the corresponding beta coefficient is zero. The Gaussian covariate method is completely different. The question as to whether the beta coefficient is or is not zero is replaced by the question as to whether the covariate is better or worse than i.i.d. Gaussian noise. The P-value for the covariate is the probability that Gaussian noise is better. Surprisingly this can be given exactly and it is the same a the P-value for the classical model based on the F-distribution. The Gaussian covariate P-value is model free, it is the same for any data set. Using the idea it is possible to do covariate selection for a small number of covariates 25 by considering all subsets. Post selection inference causes no problems as the P-values hold whatever the data. The idea extends to stepwise regression again with exact probabilities. In the simplest version the only parameter is a specified cut-off P-value which can be interpreted as the probability of a false positive being included in the final selection. For more information see the website below and the accompanying papers: L. Davies and L. Duembgen, "Covariate Selection Based on a Model-free Approach to Linear Regression with Exact Probabilities", 2020, <arXiv:1906.01990>. L. Davies, "Lasso, Knockoff and Gaussian covariates: A comparison", 2018, <arXiv:1807.09633>.
Author: Laurie Davies [aut, cre]
Maintainer: Laurie Davies <laurie.davies@uni-due.de>

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Package tidyquant updated to version 1.0.2 with previous version 1.0.1 dated 2020-07-02

Title: Tidy Quantitative Financial Analysis
Description: Bringing business and financial analysis to the 'tidyverse'. The 'tidyquant' package provides a convenient wrapper to various 'xts', 'zoo', 'quantmod', 'TTR' and 'PerformanceAnalytics' package functions and returns the objects in the tidy 'tibble' format. The main advantage is being able to use quantitative functions with the 'tidyverse' functions including 'purrr', 'dplyr', 'tidyr', 'ggplot2', 'lubridate', etc. See the 'tidyquant' website for more information, documentation and examples.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package occCite updated to version 0.4.0 with previous version 0.3.0 dated 2020-10-06

Title: Querying and Managing Large Biodiversity Occurrence Datasets
Description: Facilitates the gathering of biodiversity occurrence data from disparate sources. Metadata is managed throughout the process to facilitate reporting and enhanced ability to repeat analyses.
Author: Hannah L. Owens [aut, cre] (<https://orcid.org/0000-0003-0071-1745>), Cory Merow [aut] (<https://orcid.org/0000-0003-0561-053X>), Brian Maitner [aut] (<https://orcid.org/0000-0002-2118-9880>), Jamie M. Kass [aut] (<https://orcid.org/0000-0002-9432-895X>), Vijay Barve [aut] (<https://orcid.org/0000-0002-4852-2567>), Robert P. Guralnick [aut] (<https://orcid.org/0000-0001-6682-1504>)
Maintainer: Hannah L. Owens <hannah.owens@gmail.com>

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Package netgwas updated to version 1.12 with previous version 1.11 dated 2019-10-15

Title: Network-Based Genome Wide Association Studies
Description: A multi-core R package that contains a set of tools based on copula graphical models for accomplishing the three interrelated goals in genetics and genomics in an unified way: (1) linkage map construction, (2) constructing linkage disequilibrium networks, and (3) exploring high-dimensional genotype-phenotype network and genotype- phenotype-environment interactions networks. The netgwas package can deal with biparental inbreeding and outbreeding species with any ploidy level, namely diploid (2 sets of chromosomes), triploid (3 sets of chromosomes), tetraploid (4 sets of chromosomes) and so on. We target on high-dimensional data where number of variables p is considerably larger than number of sample sizes (p >> n). The computations is memory-optimized using the sparse matrix output. The package is implemented the recent methodological developments in Behrouzi and Wit (2017) <doi:10.1111/rssc.12287> and Behrouzi and Wit (2017) <doi:10.1093/bioinformatics/bty777>. NOTICE proper functionality of 'netgwas' requires that the 'RBGL' package is installed from 'bioconductor'; for installation instruction please refer to the 'RBGL' web page given below.
Author: Pariya Behrouzi <https://orcid.org/0000-0001-6762-5433> and Ernst C. Wit
Maintainer: Pariya Behrouzi <pariya.behrouzi@gmail.com>

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Package mlr3 updated to version 0.8.0 with previous version 0.7.0 dated 2020-10-07

Title: Machine Learning in R - Next Generation
Description: Efficient, object-oriented programming on the building blocks of machine learning. Provides 'R6' objects for tasks, learners, resamplings, and measures. The package is geared towards scalability and larger datasets by supporting parallelization and out-of-memory data-backends like databases. While 'mlr3' focuses on the core computational operations, add-on packages provide additional functionality.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>), Bernd Bischl [aut] (<https://orcid.org/0000-0001-6002-6980>), Jakob Richter [aut] (<https://orcid.org/0000-0003-4481-5554>), Patrick Schratz [aut] (<https://orcid.org/0000-0003-0748-6624>), Giuseppe Casalicchio [ctb] (<https://orcid.org/0000-0001-5324-5966>), Stefan Coors [ctb] (<https://orcid.org/0000-0002-7465-2146>), Quay Au [ctb] (<https://orcid.org/0000-0002-5252-8902>), Martin Binder [aut], Marc Becker [ctb] (<https://orcid.org/0000-0002-8115-0400>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package traitdataform updated to version 0.6.0 with previous version 0.5.7 dated 2020-04-05

Title: Formatting and Harmonizing Ecological Trait-Data
Description: Assistance for handling ecological trait data and applying the Ecological Trait-Data Standard terminology (Schneider et al. 2019 <doi:10.1111/2041-210X.13288>). There are two major use cases: (1) preparation of own trait datasets for upload into public data bases, and (2) harmonizing trait datasets from different sources by re-formatting them into a unified format. See 'traitdataform' website for full documentation.
Author: Florian D. Schneider [aut, cre] (<https://orcid.org/0000-0002-1494-5684>), Caterina Penone [ctb] (<https://orcid.org/0000-0002-8170-6659>), Andreas Ostrowski [ctb] (<https://orcid.org/0000-0002-2033-779X>), Dennis Heimann [ctb], Felix Neff [ctb], Markus J. Ankenbrand [ctb], Jessica Burnett [ctb]
Maintainer: Florian D. Schneider <florian.dirk.schneider@gmail.com>

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Package mixl updated to version 1.2.3 with previous version 1.2.2 dated 2020-07-13

Title: Simulated Maximum Likelihood Estimation of Mixed Logit Models for Large Datasets
Description: Specification and estimation of multinomial logit models. Large datasets and complex models are supported, with an intuitive syntax. Multinomial Logit Models, Mixed models, random coefficients and Hybrid Choice are all supported. For more information, see Molloy et al. (2019) <doi:10.3929/ethz-b-000334289>.
Author: Joseph Molloy [aut, cre]
Maintainer: Joseph Molloy <joseph.molloy@ivt.baug.ethz.ch>

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Package cplm updated to version 0.7-9 with previous version 0.7-8 dated 2019-03-05

Title: Compound Poisson Linear Models
Description: Likelihood-based and Bayesian methods for various compound Poisson linear models based on Zhang, Yanwei (2013) <https://link.springer.com/article/10.1007/s11222-012-9343-7>.
Author: Yanwei (Wayne) Zhang
Maintainer: Yanwei (Wayne) Zhang <actuary_zhang@hotmail.com>

Diff between cplm versions 0.7-8 dated 2019-03-05 and 0.7-9 dated 2020-10-21

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Package soilDB updated to version 2.5.8 with previous version 2.5 dated 2020-01-28

Title: Soil Database Interface
Description: A collection of functions for reading data from USDA-NCSS soil databases.
Author: Dylan Beaudette [aut], Jay Skovlin [aut], Stephen Roecker [aut], Andrew Brown [aut, cre]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

Diff between soilDB versions 2.5 dated 2020-01-28 and 2.5.8 dated 2020-10-21

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Package EnvStats updated to version 2.4.0 with previous version 2.3.1 dated 2018-07-15

Title: Package for Environmental Statistics, Including US EPA Guidance
Description: Graphical and statistical analyses of environmental data, with focus on analyzing chemical concentrations and physical parameters, usually in the context of mandated environmental monitoring. Major environmental statistical methods found in the literature and regulatory guidance documents, with extensive help that explains what these methods do, how to use them, and where to find them in the literature. Numerous built-in data sets from regulatory guidance documents and environmental statistics literature. Includes scripts reproducing analyses presented in the book "EnvStats: An R Package for Environmental Statistics" (Millard, 2013, Springer, ISBN 978-1-4614-8455-4, <https://www.springer.com/book/9781461484554>).
Author: Steven P. Millard [aut], Alexander Kowarik [ctb, cre] (<https://orcid.org/0000-0001-8598-4130>)
Maintainer: Alexander Kowarik <alexander.kowarik@statistik.gv.at>

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Package desplot updated to version 1.8 with previous version 1.7 dated 2020-07-20

Title: Plotting Field Plans for Agricultural Experiments
Description: A function for plotting maps of agricultural field experiments that are laid out in grids.
Author: Kevin Wright [aut, cre] (<https://orcid.org/0000-0002-0617-8673>)
Maintainer: Kevin Wright <kw.stat@gmail.com>

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Package xaringan updated to version 0.18 with previous version 0.17 dated 2020-09-24

Title: Presentation Ninja
Description: Create HTML5 slides with R Markdown and the JavaScript library 'remark.js' (<https://remarkjs.com>).
Author: Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Alessandro Gasparini [ctb] (<https://orcid.org/0000-0002-8319-7624>), Benjie Gillam [ctb], Claus Thorn Ekstrøm [ctb], Daniel Anderson [ctb], Dawei Lang [ctb], Emi Tanaka [ctb], Garrick Aden-Buie [ctb] (<https://orcid.org/0000-0002-7111-0077>), Iñaki Ucar [ctb] (<https://orcid.org/0000-0001-6403-5550>), John Little [ctb], Joselyn Chávez [ctb] (<https://orcid.org/0000-0002-4974-4591>), Joseph Casillas [ctb], Lucy D'Agostino McGowan [ctb] (<https://orcid.org/0000-0001-7297-9359>), Malcolm Barrett [ctb] (<https://orcid.org/0000-0003-0299-5825>), Matthew Mark Strasiotto [ctb] (mstr3336), Michael Wayne Kearney [ctb], Nan-Hung Hsieh [ctb], Ole Petter Bang [ctb] (CSS in rmarkdown/templates/xaringan/resources/default.css), Patrick Schratz [ctb], Paul Klemm [ctb] (<https://orcid.org/0000-0002-5985-1737>), Paul Lemmens [ctb], Sean Lopp [ctb], Susan VanderPlas [ctb] (<https://orcid.org/0000-0002-3803-0972>), Waldir Leoncio [ctb], Yongfu Liao [ctb], Yue Jiang [ctb] (<https://orcid.org/0000-0002-9798-5517>)
Maintainer: Yihui Xie <xie@yihui.name>

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Package SuessR updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-09

Title: Suess and Laws Corrections for Marine Stable Carbon Isotope Data
Description: Generates region-specific Suess and Laws corrections for stable carbon isotope data from marine organisms collected between 1850 and 2019. Version 0.1.1 of 'SuessR' contains four built-in regions: the Bering Sea ('Bering Sea'), the Aleutian archipelago ('Aleutians Islands'), the Gulf of Alaska ('Gulf of Alaska'), and the subpolar North Atlantic ('Subpolar North Atlantic'). Users can supply their own environmental data for regions currently not built into the package to generate corrections for those regions.
Author: Casey Clark [cre, aut], Mattias Cape [aut], Mark Shapley [aut], Franz Mueter [aut], Bruce Finney [aut], Nicole Misarti [aut]
Maintainer: Casey Clark <casey.t.clark@gmail.com>

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Package rmarkdown updated to version 2.5 with previous version 2.4 dated 2020-09-30

Title: Dynamic Documents for R
Description: Convert R Markdown documents into a variety of formats.
Author: JJ Allaire [aut], Yihui Xie [aut, cre] (<https://orcid.org/0000-0003-0645-5666>), Jonathan McPherson [aut], Javier Luraschi [aut], Kevin Ushey [aut], Aron Atkins [aut], Hadley Wickham [aut], Joe Cheng [aut], Winston Chang [aut], Richard Iannone [aut] (<https://orcid.org/0000-0003-3925-190X>), Andrew Dunning [ctb] (<https://orcid.org/0000-0003-0464-5036>), Atsushi Yasumoto [ctb, cph] (<https://orcid.org/0000-0002-8335-495X>, Number sections Lua filter), Barret Schloerke [ctb], Christophe Dervieux [ctb], Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Jeff Allen [ctb], JooYoung Seo [ctb] (<https://orcid.org/0000-0002-4064-6012>), Malcolm Barrett [ctb], Rob Hyndman [ctb], Romain Lesur [ctb], Roy Storey [ctb], Ruben Arslan [ctb], Sergio Oller [ctb], RStudio, PBC [cph], jQuery Foundation [cph] (jQuery library), jQuery contributors [ctb, cph] (jQuery library; authors listed in inst/rmd/h/jquery-AUTHORS.txt), jQuery UI contributors [ctb, cph] (jQuery UI library; authors listed in inst/rmd/h/jqueryui-AUTHORS.txt), Mark Otto [ctb] (Bootstrap library), Jacob Thornton [ctb] (Bootstrap library), Bootstrap contributors [ctb] (Bootstrap library), Twitter, Inc [cph] (Bootstrap library), Alexander Farkas [ctb, cph] (html5shiv library), Scott Jehl [ctb, cph] (Respond.js library), Ivan Sagalaev [ctb, cph] (highlight.js library), Greg Franko [ctb, cph] (tocify library), John MacFarlane [ctb, cph] (Pandoc templates), Google, Inc. [ctb, cph] (ioslides library), Dave Raggett [ctb] (slidy library), W3C [cph] (slidy library), Dave Gandy [ctb, cph] (Font-Awesome), Ben Sperry [ctb] (Ionicons), Drifty [cph] (Ionicons), Aidan Lister [ctb, cph] (jQuery StickyTabs), Benct Philip Jonsson [ctb, cph] (pagebreak Lua filter), Albert Krewinkel [ctb, cph] (pagebreak Lua filter)
Maintainer: Yihui Xie <xie@yihui.name>

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Package RaSEn updated to version 1.1.0 with previous version 1.0.0 dated 2020-06-12

Title: Random Subspace Ensemble Classification
Description: We propose a flexible ensemble classification framework, RaSE algorithm, for the sparse classification problem. In RaSE algorithm, for each weak learner, some random subspaces are generated and the optimal one is chosen to train the model on the basis of some criterion. To be adapted to the problem, a novel criterion, ratio information criterion (RIC) is put up with based on Kullback-Leibler divergence. Besides minimizing RIC, multiple criteria can be applied, for instance, minimizing extended Bayesian information criterion (eBIC), minimizing training error, minimizing the validation error, minimizing the cross-validation error, minimizing leave-one-out error. And the choices of base classifiers are also various, for instance, linear discriminant analysis, quadratic discriminant analysis, k-nearest neighbor, logistic regression, decision trees, random forest, support vector machines. RaSE algorithm can also be applied to do feature ranking, providing us the importance of each feature based on the selected percentage in multiple subspaces. In addition, to relax the requirement of the number of random subspaces to be generated, we propose an iterative version of RaSE, which is shown to be effective under many sparse binary classification settings.
Author: Ye Tian [aut, cre] and Yang Feng [aut]
Maintainer: Ye Tian <ye.t@columbia.edu>

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Package PRISM.forecast updated to version 0.2.1 with previous version 0.2.0 dated 2020-04-22

Title: Penalized Regression with Inferred Seasonality Module - Forecasting Unemployment Initial Claims using 'Google Trends' Data
Description: Implements Penalized Regression with Inferred Seasonality Module (PRISM) to generate forecast estimation of weekly unemployment initial claims using 'Google Trends' data. It includes required data and tools for backtesting the performance in 2007-2020.
Author: Dingdong Yi [aut, cre], Samuel Kou [aut], Shaoyang Ning [aut]
Maintainer: Dingdong Yi <ryan.ddyi@gmail.com>

Diff between PRISM.forecast versions 0.2.0 dated 2020-04-22 and 0.2.1 dated 2020-10-21

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Package mvrsquared updated to version 0.1.1 with previous version 0.1.0 dated 2020-06-25

Title: Compute the Coefficient of Determination for Vector or Matrix Outcomes
Description: Compute the coefficient of determination for outcomes in n-dimensions. May be useful for multidimensional predictions (such as a multinomial model) or calculating goodness of fit from latent variable models such as probabilistic topic models like latent Dirichlet allocation or deterministic topic models like latent semantic analysis. Based on Jones (2019) <arXiv:1911.11061>.
Author: Tommy Jones [aut, cre]
Maintainer: Tommy Jones <jones.thos.w@gmail.com>

Diff between mvrsquared versions 0.1.0 dated 2020-06-25 and 0.1.1 dated 2020-10-21

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Package MARSS updated to version 3.11.3 with previous version 3.11.1 dated 2020-08-27

Title: Multivariate Autoregressive State-Space Modeling
Description: The MARSS package provides maximum-likelihood parameter estimation for constrained and unconstrained linear multivariate autoregressive state-space (MARSS) models fit to multivariate time-series data. Fitting is primarily via an Expectation-Maximization (EM) algorithm, although fitting via the BFGS algorithm (using the optim function) is also provided. MARSS models are a class of dynamic linear model (DLM) and vector autoregressive model (VAR) model. Functions are provided for parametric and innovations bootstrapping, Kalman filtering and smoothing, bootstrap model selection criteria (AICb), confidences intervals via the Hessian approximation and via bootstrapping and calculation of auxiliary residuals for detecting outliers and shocks. The user guide shows examples of using MARSS for parameter estimation for a variety of applications, model selection, dynamic factor analysis, outlier and shock detection, and addition of covariates. Type RShowDoc("UserGuide", package="MARSS") at the R command line to open the MARSS user guide. Online workshops (lectures and computer labs) at <https://nwfsc-timeseries.github.io/> See the NEWS file for update information.
Author: Eli Holmes, Eric Ward, Mark Scheuerell, and Kellie Wills, NOAA, Seattle, USA
Maintainer: Elizabeth Holmes - NOAA Federal <eli.holmes@noaa.gov>

Diff between MARSS versions 3.11.1 dated 2020-08-27 and 3.11.3 dated 2020-10-21

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Tue, 20 Oct 2020

Package torch updated to version 0.1.1 with previous version 0.1.0 dated 2020-09-28

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

Diff between torch versions 0.1.0 dated 2020-09-28 and 0.1.1 dated 2020-10-20

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More information about torch at CRAN
Permanent link

Package pkgmaker updated to version 0.32.2 with previous version 0.31.1 dated 2020-03-19

Title: Development Utilities for R Packages
Description: Provides some low-level utilities to use for package development. It currently provides managers for multiple package specific options and registries, vignette, unit test and bibtex related utilities. It serves as a base package for packages like NMF, RcppOctave, doRNG, and as an incubator package for other general purposes utilities, that will eventually be packaged separately. It is still under heavy development and changes in the interface(s) are more than likely to happen.
Author: Renaud Gaujoux [aut, cre]
Maintainer: Renaud Gaujoux <renozao@protonmail.com>

Diff between pkgmaker versions 0.31.1 dated 2020-03-19 and 0.32.2 dated 2020-10-20

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Package wellknown updated to version 0.7.0 with previous version 0.6.0 dated 2020-01-10

Title: Convert Between 'WKT' and 'GeoJSON'
Description: Convert 'WKT' to 'GeoJSON' and 'GeoJSON' to 'WKT'. Functions included for converting between 'GeoJSON' to 'WKT', creating both 'GeoJSON' features, and non-features, creating 'WKT' from R objects (e.g., lists, data.frames, vectors), and linting 'WKT'.
Author: Scott Chamberlain [aut, cre] (<https://orcid.org/0000-0003-1444-9135>)
Maintainer: Scott Chamberlain <myrmecocystus@gmail.com>

Diff between wellknown versions 0.6.0 dated 2020-01-10 and 0.7.0 dated 2020-10-20

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Package VGAMdata updated to version 1.1-4 with previous version 1.0-3 dated 2017-01-10

Title: Data Supporting the 'VGAM' Package
Description: Mainly data sets to accompany the VGAM package and the book "Vector Generalized Linear and Additive Models: With an Implementation in R" (Yee, 2015) <DOI:10.1007/978-1-4939-2818-7>. These are used to illustrate vector generalized linear and additive models (VGLMs/VGAMs), and associated models (Reduced-Rank VGLMs, Quadratic RR-VGLMs, Row-Column Interaction Models, and constrained and unconstrained ordination models in ecology). This package now contains some old VGAM family functions which have been replaced by newer ones (often because they are now special cases).
Author: Thomas Yee [aut, cre, cph], James Gray [dtc]
Maintainer: Thomas Yee <t.yee@auckland.ac.nz>

Diff between VGAMdata versions 1.0-3 dated 2017-01-10 and 1.1-4 dated 2020-10-20

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Package representr updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-17

Title: Create Representative Records After Entity Resolution
Description: An implementation of Kaplan, Betancourt, Steorts (2020) <arXiv:1810.01538> that creates representative records for use in downstream tasks after entity resolution is performed. Multiple methods for creating the representative records (data sets) are provided.
Author: Andee Kaplan [aut, cre], Brenda Betancourt [aut], Rebecca C. Steorts [aut]
Maintainer: Andee Kaplan <andee.kaplan@colostate.edu>

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Package arrow updated to version 2.0.0 with previous version 1.0.1 dated 2020-08-28

Title: Integration to 'Apache' 'Arrow'
Description: 'Apache' 'Arrow' <https://arrow.apache.org/> is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an interface to the 'Arrow C++' library.
Author: Romain François [aut] (<https://orcid.org/0000-0002-2444-4226>), Jeroen Ooms [aut], Neal Richardson [aut, cre], Javier Luraschi [ctb], Jeffrey Wong [ctb], Apache Arrow [aut, cph]
Maintainer: Neal Richardson <neal@ursalabs.org>

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Package sharpshootR updated to version 1.6.5 with previous version 1.6 dated 2020-01-30

Title: A Soil Survey Toolkit
Description: Miscellaneous soil data management, summary, visualization, and conversion utilities to support soil survey.
Author: Dylan Beaudette [cre], Jay Skovlin [aut], Stephen Roecker [aut], USDA-NRCS Soil Survey Staff [ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

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Package lgr updated to version 0.4.1 with previous version 0.3.4 dated 2020-03-20

Title: A Fully Featured Logging Framework
Description: A flexible, feature-rich yet light-weight logging framework based on 'R6' classes. It supports hierarchical loggers, custom log levels, arbitrary data fields in log events, logging to plaintext, 'JSON', (rotating) files, memory buffers. For extra appenders that support logging to databases, email and push notifications see the the package lgr.app.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

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Package hisse updated to version 1.9.9 with previous version 1.9.8 dated 2020-06-15

Title: Hidden State Speciation and Extinction
Description: Sets up and executes a HiSSE model (Hidden State Speciation and Extinction) on a phylogeny and character sets to test for hidden shifts in trait dependent rates of diversification. Beaulieu and O'Meara (2016) <doi:10.1093/sysbio/syw022>.
Author: Jeremy Beaulieu [aut, cre], Brian O'Meara [aut], Daniel Caetano [aut], James Boyko [aut]
Maintainer: Jeremy Beaulieu <jmbeauli@uark.edu>

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Package fdaACF updated to version 1.0.0 with previous version 0.2.0 dated 2020-08-11

Title: Autocorrelation Function for Functional Time Series
Description: Quantify the serial correlation across lags of a given functional time series using the autocorrelation function and a partial autocorrelation function for functional time series proposed in Mestre et al. (2021) <doi:10.1016/j.csda.2020.107108>. The autocorrelation functions are based on the L2 norm of the lagged covariance operators of the series. Functions are available for estimating the distribution of the autocorrelation functions under the assumption of strong functional white noise.
Author: Guillermo Mestre Marcos [aut, cre], José Portela González [aut], Gregory Rice [aut], Antonio Muñoz San Roque [ctb], Estrella Alonso Pérez [ctb]
Maintainer: Guillermo Mestre Marcos <guillermo.mestre@comillas.edu>

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Package adoptr updated to version 0.4.1 with previous version 0.3.2 dated 2020-01-09

Title: Adaptive Optimal Two-Stage Designs in R
Description: Optimize one or two-arm, two-stage designs for clinical trials with respect to several pre-implemented objective criteria or implement custom objectives. Optimization under uncertainty and conditional (given stage-one outcome) constraints are supported. See Pilz M, Kunzmann K, Herrmann C, Rauch G, Kieser M. A variational approach to optimal two-stage designs. Statistics in Medicine. 2019;38(21):4159–4171. <doi:10.1002/sim.8291> for details.
Author: Kevin Kunzmann [aut, cre], Maximilian Pilz [aut]
Maintainer: Kevin Kunzmann <kevin.kunzmann@mrc-bsu.cam.ac.uk>

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Package OUwie updated to version 2.5 with previous version 2.4 dated 2020-08-04

Title: Analysis of Evolutionary Rates in an OU Framework
Description: Estimates rates for continuous character evolution under Brownian motion and a new set of Ornstein-Uhlenbeck based Hansen models that allow both the strength of the pull and stochastic motion to vary across selective regimes. Beaulieu et al (2012) <doi:10.1111/j.1558-5646.2012.01619.x>.
Author: Jeremy M. Beaulieu <jmbeauli@uark.edu>, Brian O'Meara <bomeara@utk.edu>
Maintainer: Jeremy Beaulieu <jmbeauli@uark.edu>

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Package NMOF updated to version 2.2-2 with previous version 2.1-0 dated 2020-04-06

Title: Numerical Methods and Optimization in Finance
Description: Functions, examples and data from the first and the second edition of "Numerical Methods and Optimization in Finance" by M. Gilli, D. Maringer and E. Schumann (2019, ISBN:978-0128150658). The package provides implementations of optimisation heuristics (Differential Evolution, Genetic Algorithms, Particle Swarm Optimisation, Simulated Annealing and Threshold Accepting), and other optimisation tools, such as grid search and greedy search. There are also functions for the valuation of financial instruments such as bonds and options, for portfolio selection and functions that help with stochastic simulations.
Author: Enrico Schumann [aut, cre] (<https://orcid.org/0000-0001-7601-6576>)
Maintainer: Enrico Schumann <es@enricoschumann.net>

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Package miRNAss updated to version 1.5 with previous version 1.4 dated 2018-01-02

Title: Genome-Wide Discovery of Pre-miRNAs with few Labeled Examples
Description: Machine learning method specifically designed for pre-miRNA prediction. It takes advantage of unlabeled sequences to improve the prediction rates even when there are just a few positive examples, when the negative examples are unreliable or are not good representatives of its class. Furthermore, the method can automatically search for negative examples if the user is unable to provide them. MiRNAss can find a good boundary to divide the pre-miRNAs from other groups of sequences; it automatically optimizes the threshold that defines the classes boundaries, and thus, it is robust to high class imbalance. Each step of the method is scalable and can handle large volumes of data.
Author: Cristian Yones
Maintainer: Cristian Yones <cyones@sinc.unl.edu.ar>

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Package anomalize updated to version 0.2.2 with previous version 0.2.1 dated 2020-06-19

Title: Tidy Anomaly Detection
Description: The 'anomalize' package enables a "tidy" workflow for detecting anomalies in data. The main functions are time_decompose(), anomalize(), and time_recompose(). When combined, it's quite simple to decompose time series, detect anomalies, and create bands separating the "normal" data from the anomalous data at scale (i.e. for multiple time series). Time series decomposition is used to remove trend and seasonal components via the time_decompose() function and methods include seasonal decomposition of time series by Loess ("stl") and seasonal decomposition by piecewise medians ("twitter"). The anomalize() function implements two methods for anomaly detection of residuals including using an inner quartile range ("iqr") and generalized extreme studentized deviation ("gesd"). These methods are based on those used in the 'forecast' package and the Twitter 'AnomalyDetection' package. Refer to the associated functions for specific references for these methods.
Author: Matt Dancho [aut, cre], Davis Vaughan [aut]
Maintainer: Matt Dancho <mdancho@business-science.io>

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Package streambugs updated to version 1.2 with previous version 1.1 dated 2019-09-19

Title: Parametric Ordinary Differential Equations Model of Growth, Death, and Respiration of Macroinvertebrate and Algae Taxa
Description: Numerically solve and plot solutions of a parametric ordinary differential equations model of growth, death, and respiration of macroinvertebrate and algae taxa dependent on pre-defined environmental factors. The model (version 1.0) is introduced in Schuwirth, N. and Reichert, P., (2013) <DOI:10.1890/12-0591.1>. This package includes model extensions and the core functions introduced and used in Schuwirth, N. et al. (2016) <DOI:10.1111/1365-2435.12605>, Kattwinkel, M. et al. (2016) <DOI:10.1021/acs.est.5b04068>, Mondy, C. P., and Schuwirth, N. (2017) <DOI:10.1002/eap.1530>, and Paillex, A. et al. (2017) <DOI:10.1111/fwb.12927>.
Author: Nele Schuwirth, Peter Reichert, Mikolaj Rybinski
Maintainer: Nele Schuwirth <nele.schuwirth@eawag.ch>

Diff between streambugs versions 1.1 dated 2019-09-19 and 1.2 dated 2020-10-20

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Package dfoptim updated to version 2020.10-1 with previous version 2018.2-1 dated 2018-04-02

Title: Derivative-Free Optimization
Description: Derivative-Free optimization algorithms. These algorithms do not require gradient information. More importantly, they can be used to solve non-smooth optimization problems.
Author: Ravi Varadhan[aut, cre], Johns Hopkins University, Hans W. Borchers[aut], ABB Corporate Research, and Vincent Bechard[aut], HEC Montreal (Montreal University)
Maintainer: Ravi Varadhan <ravi.varadhan@jhu.edu>

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Package mrf2d updated to version 0.4.1 with previous version 0.4.0 dated 2020-06-30

Title: Markov Random Field Models for Image Analysis
Description: Model fitting, sampling and visualization for the (Hidden) Markov Random Field model with pairwise interactions and general interaction structure from Freguglia, Garcia & Bicas (2020) <doi:10.1002/env.2613>, which has many popular models used in 2-dimensional lattices as particular cases, like the Ising Model and Potts Model.
Author: Victor Freguglia [aut, cre] (<https://orcid.org/0000-0002-6189-4453>)
Maintainer: Victor Freguglia <victorfreguglia@gmail.com>

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Package leaflet.extras2 updated to version 1.1.0 with previous version 1.0.0 dated 2020-05-18

Title: Extra Functionality for 'leaflet' Package
Description: Several 'leaflet' plugins are integrated, which are available as extension to the 'leaflet' package.
Author: Gatscha Sebastian [aut, cre]
Maintainer: Gatscha Sebastian <sebastian_gatscha@gmx.at>

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Package windfarmGA updated to version 2.3.0 with previous version 2.2.3 dated 2019-12-16

Title: Genetic Algorithm for Wind Farm Layout Optimization
Description: The genetic algorithm is designed to optimize wind farms of any shape. It requires a predefined amount of turbines, a unified rotor radius and an average wind speed value for each incoming wind direction. A terrain effect model can be included that downloads an 'SRTM' elevation model and loads a Corine Land Cover raster to approximate surface roughness.
Author: Sebastian Gatscha [aut, cre]
Maintainer: Sebastian Gatscha <sebastian_gatscha@gmx.at>

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Permanent link

Package rotor updated to version 0.3.2 with previous version 0.3.1 dated 2020-10-18

Title: Log Rotation and Conditional Backups
Description: Conditionally rotate or back-up files based on their size or the date of the last backup; inspired by the 'Linux' utility 'logrotate'.
Author: Stefan Fleck [aut, cre] (<https://orcid.org/0000-0003-3344-9851>)
Maintainer: Stefan Fleck <stefan.b.fleck@gmail.com>

Diff between rotor versions 0.3.1 dated 2020-10-18 and 0.3.2 dated 2020-10-20

 DESCRIPTION                 |    6 +++---
 MD5                         |    6 +++---
 R/Cache.R                   |    3 ++-
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More information about rotor at CRAN
Permanent link

Package rEDM updated to version 1.6.1 with previous version 1.5.0 dated 2020-07-06

Title: Empirical Dynamic Modeling ('EDM')
Description: An implementation of 'EDM' algorithms based on research software developed for internal use at the Sugihara Lab ('UCSD/SIO'). The package is implemented with 'Rcpp' wrappers around the 'cppEDM' library. It implements the 'simplex' projection method from Sugihara & May (1990) <doi:10.1038/344734a0>, the 'S-map' algorithm from Sugihara (1994) <doi:10.1098/rsta.1994.0106>, convergent cross mapping described in Sugihara et al. (2012) <doi:10.1126/science.1227079>, and, 'multiview embedding' described in Ye & Sugihara (2016) <doi:10.1126/science.aag0863>.
Author: Joseph Park [aut, cre] (<https://orcid.org/0000-0001-5411-1409>), Cameron Smith [aut], George Sugihara [aut, ccp] (<https://orcid.org/0000-0002-2863-6946>), Ethan Deyle [aut] (<https://orcid.org/0000-0001-8704-8434>), Erik Saberski [ctb] (<https://orcid.org/0000-0002-6475-6187>), Hao Ye [ctb] (<https://orcid.org/0000-0002-8630-1458>), The Regents of the University of California [cph]
Maintainer: Joseph Park <JosephPark@IEEE.org>

Diff between rEDM versions 1.5.0 dated 2020-07-06 and 1.6.1 dated 2020-10-20

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Package QRIpkg updated to version 0.2.1 with previous version 0.2.0 dated 2020-09-20

Title: Quantile Regression Index Score
Description: The QRI_func() function performs quantile regression analysis using age and sex as predictors to calculate the Quantile Regression Index (QRI) score for each individual’s regional brain imaging metrics and then averages across the regional scores to generate an average tissue specific score for each subject. The QRI_plot() is used to plot QRI and generate the normative curves for individual measurements.
Author: Peter Kochunov [aut], Si Gao [aut, cre], Meghann Ryan [aut]
Maintainer: Si Gao <sgao@som.umaryland.edu>

Diff between QRIpkg versions 0.2.0 dated 2020-09-20 and 0.2.1 dated 2020-10-20

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More information about QRIpkg at CRAN
Permanent link

Package EpiNow2 updated to version 1.2.1 with previous version 1.1.0 dated 2020-09-01

Title: Estimate Real-Time Case Counts and Time-Varying Epidemiological Parameters
Description: Estimates the time-varying reproduction number, rate of spread, and doubling time using a range of open-source tools (Abbott et al. (2020) <doi:10.12688/wellcomeopenres.16006.1>), and current best practices (Gostic et al. (2020) <doi:10.1101/2020.06.18.20134858>). It aims to help users avoid some of the limitations of naive implementations in a framework that is informed by community feedback and is under active development.
Author: Sam Abbott [aut, cre] (<https://orcid.org/0000-0001-8057-8037>), Joel Hellewell [aut] (<https://orcid.org/0000-0003-2683-0849>), Robin Thompson [aut], Katelyn Gostic [aut], Katharine Sherratt [aut], Sophie Meakin [aut], James Munday [aut], Nikos Bosse [aut], Joe Hickson [aut], Paul Mee [ctb], Peter Ellis [ctb], Hamada S. Badr [ctb] (<https://orcid.org/0000-0002-9808-2344>), Michael DeWitt [ctb] (<https://orcid.org/0000-0001-8940-1967>), EpiForecasts [aut], Sebastian Funk [aut]
Maintainer: Sam Abbott <sam.abbott@lshtm.ac.uk>

Diff between EpiNow2 versions 1.1.0 dated 2020-09-01 and 1.2.1 dated 2020-10-20

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Permanent link

Package bootcluster updated to version 0.2.0 with previous version 0.1.0 dated 2017-11-13

Title: Bootstrapping Estimates of Clustering Stability
Description: Implementation of the bootstrapping approach for the estimation of clustering stability and its application in estimating the number of clusters, as introduced by Yu et al<doi:10.1142/9789814749411_0007>. Implementation of the non-parametric bootstrap approach to assessing the stability of module detection in a graph, the extension for the selection of a parameter set that defines a graph from data in a way that optimizes stability and the corresponding visualization functions, as introduced by Tian et al.
Author: Han Yu, Mingmei Tian
Maintainer: Mingmei Tian <mingmeit@buffalo.edu>

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Package BIOMASS updated to version 2.1.4 with previous version 2.1.3 dated 2020-06-25

Title: Estimating Aboveground Biomass and Its Uncertainty in Tropical Forests
Description: Contains functions to estimate aboveground biomass/carbon and its uncertainty in tropical forests. These functions allow to (1) retrieve and to correct taxonomy, (2) estimate wood density and its uncertainty, (3) construct height-diameter models, (4) manage tree and plot coordinates, (5) estimate the aboveground biomass/carbon at the stand level with associated uncertainty. To cite BIOMASS, please use citation("BIOMASS"). See more in the article of Réjou-Méchain et al. (2017) <doi:10.1111/2041-210X.12753>.
Author: Maxime Réjou-Méchain [aut, cre, dtc], Arthur Pere [aut], Guillaume Cornu [aut] (<https://orcid.org/0000-0002-7523-5176>), Ariane Tanguy [aut], Camille Piponiot [aut], Jerome Chave [dtc], Bruno Hérault [aut], Ted Feldpausch [dtc], Philippe Verley [ctb]
Maintainer: Maxime Réjou-Méchain <maxime.rejou@gmail.com>

Diff between BIOMASS versions 2.1.3 dated 2020-06-25 and 2.1.4 dated 2020-10-20

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Package GofKmt updated to version 2.2.0 with previous version 2.1.1 dated 2020-02-21

Title: Khmaladze Martingale Transformation Goodness-of-Fit Test
Description: Consider a goodness-of-fit (GOF) problem of testing whether a random sample comes from one sample location-scale model where location and scale parameters are unknown. It is well known that Khmaladze martingale transformation method - which was proposed by Khmaladze (1981) <DOI:10.1137/1126027> - provides asymptotic distribution free test for the GOF problem. This package contains one function: KhmaladzeTrans(). In this version, KhmaladzeTrans() provides test statistic and critical value of GOF test for normal, Cauchy, and logistic distributions. This package used the main algorithm proposed by Kim (2020) <DOI:10.1007/s00180-020-00971-7> and tests for other distributions will be available at the later version.
Author: Jiwoong Kim <jwboys26 at gmail.com>
Maintainer: Jiwoong Kim <jwboys26@gmail.com>

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Package tm1r updated to version 1.1.5 with previous version 1.1.4 dated 2020-03-19

Title: The Integration Between 'IBM COGNOS TM1' and R
Description: Useful functions to connect to 'TM1' <https://www.ibm.com/uk-en/products/planning-and-analytics> instance from R via REST API. With the functions in the package, data can be imported from 'TM1' via mdx view or native view, data can be sent to 'TM1', processes and chores can be executed, and cube and dimension metadata information can be taken.
Author: Muhammed Ali Onder
Maintainer: Muhammed Ali Onder <muhammedalionder@gmail.com>

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Package SKAT updated to version 2.0.1 with previous version 2.0.0 dated 2020-03-09

Title: SNP-Set (Sequence) Kernel Association Test
Description: Functions for kernel-regression-based association tests including Burden test, SKAT and SKAT-O. These methods aggregate individual SNP score statistics in a SNP set and efficiently compute SNP-set level p-values.
Author: Seunggeun (Shawn) Lee and Zhangchen Zhao, with contributions from Larisa Miropolsky and Michael Wu
Maintainer: Seunggeun (Shawn) Lee <lee7801@snu.ac.kr>

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Package mlr3oml updated to version 0.4.0 with previous version 0.3.0 dated 2020-10-05

Title: Connector Between 'mlr3' and 'OpenML'
Description: Provides an interface to 'OpenML.org' to list and download machine learning data and tasks. Data and tasks can be automatically converted to 'mlr3' tasks. For a more sophisticated interface which also allows uploading experiments, see the 'OpenML' package.
Author: Michel Lang [cre, aut] (<https://orcid.org/0000-0001-9754-0393>)
Maintainer: Michel Lang <michellang@gmail.com>

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Package chronosphere updated to version 0.4.0 with previous version 0.3.1 dated 2020-08-10

Title: Earth System History Variables
Description: The purpose of the 'chronosphere' project is to facilitate spatially explicit analyses of (paleo)environmental/ecological research. The package serves as a gateway to plate tectonic reconstructions, deep time global climate model results as well as fossil occurrence datasets such as the Paleobiology Database <https://paleobiodb.org/> and the PaleoReefs Database <https://www.paleo-reefs.pal.uni-erlangen.de/>. Environmental data stored on a remote server can be downloaded and imported directly to the R environment. Query functions to the GPlates <https://www.gplates.org/> desktop application or the GPlates Web Service <https://gws.gplates.org/> allow users to reconstruct coordinates, static plates, and Spatial objects. A wrapper class 'RasterArray' is implemented around the 'RasterLayer' class, allowing the organization of spatially explicit raster data in n-dimensional arrays. The project is developed under the umbrella of the DFG (Deutsche Forschungsgemeinschaft) Research Unit TERSANE2 (For 2332, TEmperature Related Stressors in ANcient Extinctions).
Author: Adam T. Kocsis, Nussaibah B. Raja
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>

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Package SDAR updated to version 0.9-5 with previous version 0.9-3 dated 2019-10-24

Title: Stratigraphic Data Analysis
Description: A fast, consistent tool for plotting and facilitating the analysis of stratigraphic and sedimentological data. Taking advantage of the flexible plotting tools available in R, 'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness, lithology, samples, sedimentary structures, colors, fossil content, bioturbation index, gamma ray logs) (Johnson, 1992, <ISSN 0037-0738>).
Author: John R. Ortiz [aut, cre], Carlos Jaramillo [aut], Carlos Moreno [ctb]
Maintainer: John R. Ortiz <jrortizt@unal.edu.co>

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 SDAR-0.9-5/SDAR/man/strata-class.Rd                      |    8 
 SDAR-0.9-5/SDAR/man/summary.Rd                           |    4 
 SDAR-0.9-5/SDAR/vignettes/SDAR_data_model.Rmd            |only
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 SDAR-0.9-5/SDAR/vignettes/introduction_to_SDAR.Rmd       |only
 46 files changed, 2348 insertions(+), 877 deletions(-)

More information about SDAR at CRAN
Permanent link

Package RcppZiggurat updated to version 0.1.6 with previous version 0.1.5 dated 2018-06-10

Title: 'Rcpp' Integration of Different "Ziggurat" Normal RNG Implementations
Description: The Ziggurat generator for normally distributed random numbers, originally proposed by Marsaglia and Tsang (2000, <doi:10.18637/jss.v005.i08>) has been improved upon a few times starting with Leong et al (2005, <doi:10.18637/jss.v012.i07>). This package provides an aggregation in order to compare different implementations in order to provide an 'faster but good enough' alternative for use with R and C++ code.
Author: Dirk Eddelbuettel
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppZiggurat versions 0.1.5 dated 2018-06-10 and 0.1.6 dated 2020-10-20

 RcppZiggurat-0.1.5/RcppZiggurat/src/init.c                  |only
 RcppZiggurat-0.1.6/RcppZiggurat/ChangeLog                   |   52 +++++++++++
 RcppZiggurat-0.1.6/RcppZiggurat/DESCRIPTION                 |   10 +-
 RcppZiggurat-0.1.6/RcppZiggurat/MD5                         |   33 +++----
 RcppZiggurat-0.1.6/RcppZiggurat/R/RcppExports.R             |    8 +
 RcppZiggurat-0.1.6/RcppZiggurat/README.md                   |    9 +
 RcppZiggurat-0.1.6/RcppZiggurat/build/vignette.rds          |binary
 RcppZiggurat-0.1.6/RcppZiggurat/cleanup                     |    2 
 RcppZiggurat-0.1.6/RcppZiggurat/inst/NEWS.Rd                |   10 ++
 RcppZiggurat-0.1.6/RcppZiggurat/inst/doc/RcppZiggurat.R     |   16 +--
 RcppZiggurat-0.1.6/RcppZiggurat/inst/doc/RcppZiggurat.Rmd   |   28 ++----
 RcppZiggurat-0.1.6/RcppZiggurat/inst/doc/RcppZiggurat.pdf   |binary
 RcppZiggurat-0.1.6/RcppZiggurat/inst/include/Ziggurat.h     |   17 +++
 RcppZiggurat-0.1.6/RcppZiggurat/man/RcppZiggurat-package.Rd |    8 -
 RcppZiggurat-0.1.6/RcppZiggurat/man/ziggurat.Rd             |   19 +++-
 RcppZiggurat-0.1.6/RcppZiggurat/src/RcppExports.cpp         |   56 ++++++++++++
 RcppZiggurat-0.1.6/RcppZiggurat/src/ziggurat.cpp            |   14 +++
 RcppZiggurat-0.1.6/RcppZiggurat/vignettes/RcppZiggurat.Rmd  |   28 ++----
 18 files changed, 235 insertions(+), 75 deletions(-)

More information about RcppZiggurat at CRAN
Permanent link

Package RcppArmadillo updated to version 0.10.1.0.0 with previous version 0.9.900.3.0 dated 2020-09-03

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library (by Conrad Sanderson) that aims towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matrix decompositions are provided through optional integration with LAPACK and ATLAS libraries. The 'RcppArmadillo' package includes the header files from the templated 'Armadillo' library. Thus users do not need to install 'Armadillo' itself in order to use 'RcppArmadillo'. From release 7.800.0 on, 'Armadillo' is licensed under Apache License 2; previous releases were under licensed as MPL 2.0 from version 3.800.0 onwards and LGPL-3 prior to that; 'RcppArmadillo' (the 'Rcpp' bindings/bridge to Armadillo) is licensed under the GNU GPL version 2 or later, as is the rest of 'Rcpp'. Note that Armadillo requires a fairly recent compiler; for the g++ family at least version 4.6.* is required.
Author: Dirk Eddelbuettel, Romain Francois, Doug Bates and Binxiang Ni
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppArmadillo versions 0.9.900.3.0 dated 2020-09-03 and 0.10.1.0.0 dated 2020-10-20

 RcppArmadillo-0.10.1.0.0/RcppArmadillo/ChangeLog                                                 |   24 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/DESCRIPTION                                               |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/MD5                                                       |  517 ++---
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/README.md                                                 |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/configure                                                 |   18 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/NEWS.Rd                                              |   39 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/doc/RcppArmadillo-intro.pdf                          |binary
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/doc/RcppArmadillo-sparseMatrix.pdf                   |binary
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/RcppArmadillo/Mat_meat.h                     |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo                                    |   56 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Base_bones.hpp                |    3 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Base_meat.hpp                 |   26 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Col_bones.hpp                 |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Col_meat.hpp                  |  214 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/CubeToMatOp_bones.hpp         |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Cube_bones.hpp                |   39 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Cube_meat.hpp                 |  433 ++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/GenCube_bones.hpp             |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Gen_bones.hpp                 |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/GlueCube_bones.hpp            |    5 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Glue_bones.hpp                |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/MapMat_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/MapMat_meat.hpp               |  142 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Mat_bones.hpp                 |   85 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Mat_meat.hpp                  |  888 +++++-----
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/OpCube_bones.hpp              |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Op_bones.hpp                  |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Proxy.hpp                     |  780 ++++----
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/ProxyCube.hpp                 |   90 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Row_bones.hpp                 |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/Row_meat.hpp                  |  214 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpCol_bones.hpp               |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpCol_meat.hpp                |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpGlue_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpMat_bones.hpp               |   67 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpMat_iterators_meat.hpp      |  263 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpMat_meat.hpp                |  487 +++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpOp_bones.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpProxy.hpp                   |  173 +
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpRow_bones.hpp               |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpRow_meat.hpp                |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpSubview_bones.hpp           |  195 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpSubview_col_list_bones.hpp  |only
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpSubview_col_list_meat.hpp   |only
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpSubview_iterators_meat.hpp  |   81 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpSubview_meat.hpp            |  202 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpToDOp_bones.hpp             |   17 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpValProxy_bones.hpp          |    5 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/SpValProxy_meat.hpp           |   52 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/access.hpp                    |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_cmath.hpp                |  596 ------
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_config.hpp               |   91 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_forward.hpp              |   90 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_ostream_bones.hpp        |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_rng.hpp                  |   76 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_rng_cxx11.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_rng_cxx98.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_static_check.hpp         |   46 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_str.hpp                  |   54 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arma_version.hpp              |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/arrayops_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/auxlib_bones.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/auxlib_meat.hpp               |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/compiler_check.hpp            |only
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/compiler_setup.hpp            |  163 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/config.hpp                    |   45 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/constants.hpp                 |   89 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/constants_old.hpp             |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/debug.hpp                     |   13 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/def_superlu.hpp               |   15 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/diagmat_proxy.hpp             |   44 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/diagview_bones.hpp            |   18 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/diskio_bones.hpp              |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/diskio_meat.hpp               |  325 +--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eGlueCube_bones.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eGlue_bones.hpp               |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eOpCube_bones.hpp             |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eOp_bones.hpp                 |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eglue_core_meat.hpp           |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eop_aux.hpp                   |   93 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eop_core_bones.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/eop_core_meat.hpp             |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fft_engine.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/field_bones.hpp               |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/field_meat.hpp                |  401 ++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_approx_equal.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_as_scalar.hpp              |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_chi2rnd.hpp                |   32 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_chol.hpp                   |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_clamp.hpp                  |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_conv.hpp                   |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_conv_to.hpp                |   44 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_det.hpp                    |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eig_gen.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eig_sym.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eigs_gen.hpp               |  361 +++-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eigs_sym.hpp               |  210 ++
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_elem.hpp                   |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eps.hpp                    |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_eye.hpp                    |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_find.hpp                   |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_hess.hpp                   |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_inplace_strans.hpp         |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_inplace_trans.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_interp1.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_interp2.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_inv.hpp                    |  204 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_log_det.hpp                |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_log_normpdf.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_lu.hpp                     |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_misc.hpp                   |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_norm.hpp                   |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_normalise.hpp              |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_normcdf.hpp                |  128 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_normpdf.hpp                |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_ones.hpp                   |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_pinv.hpp                   |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_princomp.hpp               |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_qr.hpp                     |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_qz.hpp                     |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randg.hpp                  |  189 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randi.hpp                  |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randn.hpp                  |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_randu.hpp                  |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_rank.hpp                   |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_reshape.hpp                |   52 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_schur.hpp                  |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_solve.hpp                  |  192 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sort.hpp                   |   82 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sort_index.hpp             |   48 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_speye.hpp                  |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sprandn.hpp                |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_sprandu.hpp                |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_spsolve.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_strans.hpp                 |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_svd.hpp                    |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_svds.hpp                   |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_syl_lyap.hpp               |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_trans.hpp                  |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/fn_zeros.hpp                  |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_affmul_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_atan2_meat.hpp           |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_conv_bones.hpp           |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_cor_bones.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_cov_bones.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_cross_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_hist_bones.hpp           |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_histc_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_intersect_bones.hpp      |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_join_bones.hpp           |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_kron_bones.hpp           |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_mixed_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_mvnrnd_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_polyfit_bones.hpp        |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_polyval_bones.hpp        |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_quantile_bones.hpp       |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_solve_bones.hpp          |   42 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_times_bones.hpp          |   16 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/glue_trapz_bones.hpp          |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_diag_bones.hpp            |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_diag_meat.hpp             |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_full_bones.hpp            |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/gmm_full_meat.hpp             |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/hdf5_misc.hpp                 |  238 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/injector_bones.hpp            |   30 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/injector_meat.hpp             |   23 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/memory.hpp                    |   66 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtGlueCube_bones.hpp          |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtGlue_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtOpCube_bones.hpp            |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtOp_bones.hpp                |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtSpGlue_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mtSpOp_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mul_gemm.hpp                  |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mul_gemv.hpp                  |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/mul_herk.hpp                  |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_all_bones.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_any_bones.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_chi2rnd_bones.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_chi2rnd_meat.hpp           |  101 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_diagmat_bones.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_diagvec_bones.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_expmat_meat.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_find_bones.hpp             |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_htrans_bones.hpp           |   37 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_htrans_meat.hpp            |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_index_max_bones.hpp        |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_index_min_bones.hpp        |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_logmat_meat.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_max_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_median_bones.hpp           |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_min_bones.hpp              |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_norm_bones.hpp             |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_reshape_bones.hpp          |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_reshape_meat.hpp           |  213 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_sort_meat.hpp              |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_sp_minus_meat.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_strans_bones.hpp           |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_trimat_bones.hpp           |   11 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_trimat_meat.hpp            |  232 --
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/op_wishrnd_meat.hpp           |  126 -
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/operator_div.hpp              |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/operator_relational.hpp       |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/podarray_bones.hpp            |    2 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/podarray_meat.hpp             |   29 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/promote_type.hpp              |   72 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/restrictors.hpp               |   20 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/running_stat_bones.hpp        |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/running_stat_vec_bones.hpp    |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/sp_auxlib_bones.hpp           |   87 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/sp_auxlib_meat.hpp            |  721 ++++++--
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/span.hpp                      |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spdiagview_bones.hpp          |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_join_bones.hpp         |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_kron_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_max_meat.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_merge_meat.hpp         |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_min_meat.hpp           |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_minus_meat.hpp         |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_plus_meat.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_relational_bones.hpp   |   28 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_relational_meat.hpp    |  263 ++
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_schur_meat.hpp         |   55 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_times_bones.hpp        |   18 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spglue_times_meat.hpp         |    9 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_htrans_bones.hpp         |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_max_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_max_meat.hpp             |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_mean_meat.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_min_bones.hpp            |    8 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_min_meat.hpp             |   40 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_strans_bones.hpp         |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_var_bones.hpp            |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/spop_var_meat.hpp             |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/strip.hpp                     |   24 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_bones.hpp             |   65 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_bones.hpp        |    9 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_each_bones.hpp   |   12 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_meat.hpp         |   86 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_cube_slices_bones.hpp |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_each_bones.hpp        |   13 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_elem1_bones.hpp       |   14 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_elem2_bones.hpp       |   23 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_elem2_meat.hpp        |  112 +
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_field_bones.hpp       |    7 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/subview_meat.hpp              |  224 +-
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/traits.hpp                    |  494 ++---
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/translate_arpack.hpp          |    4 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/translate_superlu.hpp         |  113 +
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/typedef_elem.hpp              |   28 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/typedef_elem_check.hpp        |   30 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/typedef_mat.hpp               |   22 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/unwrap.hpp                    |  704 +++----
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/unwrap_cube.hpp               |    6 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/unwrap_spmat.hpp              |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/wall_clock_bones.hpp          |   11 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/wall_clock_meat.hpp           |   62 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/xtrans_mat_bones.hpp          |   10 
 RcppArmadillo-0.10.1.0.0/RcppArmadillo/inst/include/armadillo_bits/xvec_htrans_bones.hpp         |    8 
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/compiler_extra.hpp           |only
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/config.hpp.cmake             |only
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/spglue_elem_helper_bones.hpp |only
 RcppArmadillo-0.9.900.3.0/RcppArmadillo/inst/include/armadillo_bits/spglue_elem_helper_meat.hpp  |only
 263 files changed, 7174 insertions(+), 7486 deletions(-)

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Package glca updated to version 1.0.2 with previous version 1.0.1 dated 2020-09-08

Title: An R Package for Estimating a Group-Effect in Latent Class Analysis
Description: Fits latent class analysis (LCA) including group variable and covariates. The group variable can be handled either by multilevel LCA described in Vermunt (2003) <DOI:10.1111/j.0081-1750.2003.t01-1-00131.x> or standard LCA at each level of group variable. The covariates can be incorporated in the form of logistic regression (Bandeen-Roche et al. (1997) <DOI:10.1080/01621459.1997.10473658>).
Author: Youngsun Kim [aut, cre], Hwan Chung [aut]
Maintainer: Youngsun Kim <kim0sun@korea.ac.kr>

Diff between glca versions 1.0.1 dated 2020-09-08 and 1.0.2 dated 2020-10-20

 DESCRIPTION       |   15 +++++++++------
 MD5               |   22 +++++++++++++---------
 NEWS.md           |only
 R/dataset.r       |    3 ++-
 R/glca.gof.R      |    1 +
 R/glca_encode.R   |    4 ++--
 R/print.glca.R    |    6 +++---
 R/summary.glca.R  |   10 +++++-----
 build/partial.rdb |binary
 data/nyts18.rda   |binary
 inst              |only
 man/nyts18.Rd     |    6 ++----
 tests             |only
 13 files changed, 37 insertions(+), 30 deletions(-)

More information about glca at CRAN
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Package BoSSA updated to version 3.7 with previous version 3.6 dated 2018-11-06

Title: A Bunch of Structure and Sequence Analysis
Description: Reads and plots phylogenetic placements.
Author: Pierre Lefeuvre
Maintainer: Pierre Lefeuvre <pierre.lefeuvre@cirad.fr>

Diff between BoSSA versions 3.6 dated 2018-11-06 and 3.7 dated 2020-10-20

 DESCRIPTION                  |    8 +-
 MD5                          |   30 +++----
 build/partial.rdb            |binary
 build/vignette.rds           |binary
 inst/doc/bossa-analysis.R    |   46 ++++++------
 inst/doc/bossa-analysis.Rmd  |   10 +-
 inst/doc/bossa-analysis.html |  164 +++++++++++++++++++++++++------------------
 inst/doc/bossa-refpkg.R      |  154 ++++++++++++++++++++--------------------
 inst/doc/bossa-refpkg.Rmd    |   44 +++++++----
 inst/doc/bossa-refpkg.html   |   87 ++++++++++++++++------
 inst/doc/bossa-tree.R        |   12 +--
 inst/doc/bossa-tree.html     |   54 +++++++++++---
 man/refpkg.Rd                |    3 
 man/write_jplace.Rd          |    3 
 vignettes/bossa-analysis.Rmd |   10 +-
 vignettes/bossa-refpkg.Rmd   |   44 +++++++----
 16 files changed, 402 insertions(+), 267 deletions(-)

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Package survivalmodels updated to version 0.1.1 with previous version 0.1.0 dated 2020-10-15

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] (<https://orcid.org/0000-0001-9225-4654>)
Maintainer: Raphael Sonabend <raphael.sonabend.15@ucl.ac.uk>

Diff between survivalmodels versions 0.1.0 dated 2020-10-15 and 0.1.1 dated 2020-10-20

 DESCRIPTION       |    8 ++++----
 MD5               |    8 ++++----
 NEWS.md           |    4 ++++
 build/partial.rdb |binary
 src/C_akritas.cpp |   13 +++++--------
 5 files changed, 17 insertions(+), 16 deletions(-)

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Package sos updated to version 2.0-2 with previous version 2.0-0 dated 2017-07-03

Title: Search Contributed R Packages, Sort by Package
Description: Search contributed R packages, sort by package.
Author: Spencer Graves [cre, aut, cph], Sundar Dorai-Raj [aut], and Romain Francois [ctb]
Maintainer: Spencer Graves <spencer.graves@prodsyse.com>

Diff between sos versions 2.0-0 dated 2017-07-03 and 2.0-2 dated 2020-10-20

 DESCRIPTION              |   16 +-
 MD5                      |   47 ++++----
 NEWS                     |    6 -
 R/PackageSum2.R          |    2 
 R/findFn.R               |    2 
 R/packageSum.R           |    4 
 R/writeFindFn2xls.R      |   69 +++++++-----
 build/vignette.rds       |binary
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 inst/doc/sos.pdf         |binary
 man/Extract.findFn.Rd    |   36 +++---
 man/PackageSum2.Rd       |   27 ++---
 man/PackageSummary.Rd    |   75 +++++++------
 man/back2ForwardSlash.Rd |  153 ++++++++++++++--------------
 man/findFn.Rd            |  253 ++++++++++++++++++++++++++---------------------
 man/hits.Rd              |   20 ++-
 man/packageSum.Rd        |   69 +++++++-----
 man/print.findFn.Rd      |   38 +++----
 man/print.packageSum.Rd  |   34 +++---
 man/sortFindFn.Rd        |   22 ++--
 man/summary.findFn.Rd    |  100 ++++++++++--------
 man/unionFindFn.Rd       |   44 ++++----
 man/writeFindFn2xls.Rd   |   34 +++---
 vignettes/sos.Rnw        |   10 -
 25 files changed, 591 insertions(+), 480 deletions(-)

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Package labeling updated to version 0.4.2 with previous version 0.3 dated 2014-08-23

Title: Axis Labeling
Description: Functions which provide a range of axis labeling algorithms.
Author: Justin Talbot,
Maintainer: Nuno Sempere <nuno.semperelh@gmail.com>

Diff between labeling versions 0.3 dated 2014-08-23 and 0.4.2 dated 2020-10-20

 DESCRIPTION       |   21 +++++++++------------
 LICENSE           |    2 +-
 MD5               |   10 +++++-----
 NAMESPACE         |    2 ++
 R/labeling.R      |    6 ++++++
 man/matplotlib.Rd |    2 +-
 6 files changed, 24 insertions(+), 19 deletions(-)

More information about labeling at CRAN
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Package hutilscpp updated to version 0.5.2 with previous version 0.5.1 dated 2020-10-13

Title: Miscellaneous Functions in C++
Description: Provides utility functions that are simply, frequently used, but may require higher performance that what can be obtained from base R. Incidentally provides support for 'reverse geocoding', such as matching a point with its nearest neighbour in another array. Used as a complement to package 'hutils' by sacrificing compilation or installation time for higher running speeds. The name is a portmanteau of the author and 'Rcpp'.
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between hutilscpp versions 0.5.1 dated 2020-10-13 and 0.5.2 dated 2020-10-20

 DESCRIPTION                       |    6 
 MD5                               |   20 
 NEWS.md                           |  379 ++---
 R/RcppExports.R                   |    8 
 R/which_first.R                   |  973 +++++++-------
 src/RcppExports.cpp               |   22 
 src/allocate.cpp                  |   15 
 src/do_which_first.cpp            |   14 
 src/do_which_last.cpp             |   14 
 tests/testthat/test-which_first.R | 2567 +++++++++++++++++++-------------------
 tests/testthat/test-which_last.R  | 1392 ++++++++++----------
 11 files changed, 2732 insertions(+), 2678 deletions(-)

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Package greybox updated to version 0.6.3 with previous version 0.6.2 dated 2020-09-02

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] (Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK), Yves R. Sagaert [ctb] (Visiting Research at Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.ru>

Diff between greybox versions 0.6.2 dated 2020-09-02 and 0.6.3 dated 2020-10-20

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Package broom updated to version 0.7.2 with previous version 0.7.1 dated 2020-10-01

Title: Convert Statistical Objects into Tidy Tibbles
Description: Summarizes key information about statistical objects in tidy tibbles. This makes it easy to report results, create plots and consistently work with large numbers of models at once. Broom provides three verbs that each provide different types of information about a model. tidy() summarizes information about model components such as coefficients of a regression. glance() reports information about an entire model, such as goodness of fit measures like AIC and BIC. augment() adds information about individual observations to a dataset, such as fitted values or influence measures.
Author: David Robinson [aut], Alex Hayes [aut, cre] (<https://orcid.org/0000-0002-4985-5160>), Simon Couch [aut], Indrajeet Patil [ctb] (<https://orcid.org/0000-0003-1995-6531>), Derek Chiu [ctb], Matthieu Gomez [ctb], Boris Demeshev [ctb], Dieter Menne [ctb], Benjamin Nutter [ctb], Luke Johnston [ctb], Ben Bolker [ctb], Francois Briatte [ctb], Jeffrey Arnold [ctb], Jonah Gabry [ctb], Luciano Selzer [ctb], Gavin Simpson [ctb], Jens Preussner [ctb], Jay Hesselberth [ctb], Hadley Wickham [ctb], Matthew Lincoln [ctb], Alessandro Gasparini [ctb], Lukasz Komsta [ctb], Frederick Novometsky [ctb], Wilson Freitas [ctb], Michelle Evans [ctb], Jason Cory Brunson [ctb], Simon Jackson [ctb], Ben Whalley [ctb], Karissa Whiting [ctb], Yves Rosseel [ctb], Michael Kuehn [ctb], Jorge Cimentada [ctb], Erle Holgersen [ctb], Karl Dunkle Werner [ctb] (<https://orcid.org/0000-0003-0523-7309>), Ethan Christensen [ctb], Steven Pav [ctb], Paul PJ [ctb], Ben Schneider [ctb], Patrick Kennedy [ctb], Lily Medina [ctb], Brian Fannin [ctb], Jason Muhlenkamp [ctb], Matt Lehman [ctb], Bill Denney [ctb] (<https://orcid.org/0000-0002-5759-428X>), Nic Crane [ctb], Andrew Bates [ctb], Vincent Arel-Bundock [ctb] (<https://orcid.org/0000-0003-2042-7063>), Hideaki Hayashi [ctb], Luis Tobalina [ctb], Annie Wang [ctb], Wei Yang Tham [ctb], Clara Wang [ctb], Abby Smith [ctb] (<https://orcid.org/0000-0002-3207-0375>), Jasper Cooper [ctb] (<https://orcid.org/0000-0002-8639-3188>), E Auden Krauska [ctb] (<https://orcid.org/0000-0002-1466-5850>), Alex Wang [ctb], Malcolm Barrett [ctb] (<https://orcid.org/0000-0003-0299-5825>), Charles Gray [ctb] (<https://orcid.org/0000-0002-9978-011X>), Jared Wilber [ctb], Vilmantas Gegzna [ctb] (<https://orcid.org/0000-0002-9500-5167>), Eduard Szoecs [ctb], Frederik Aust [ctb] (<https://orcid.org/0000-0003-4900-788X>), Angus Moore [ctb], Nick Williams [ctb], Marius Barth [ctb] (<https://orcid.org/0000-0002-3421-6665>), Bruna Wundervald [ctb] (<https://orcid.org/0000-0001-8163-220X>), Joyce Cahoon [ctb] (<https://orcid.org/0000-0001-7217-4702>), Grant McDermott [ctb] (<https://orcid.org/0000-0001-7883-8573>), Kevin Zarca [ctb], Shiro Kuriwaki [ctb] (<https://orcid.org/0000-0002-5687-2647>), Lukas Wallrich [ctb] (<https://orcid.org/0000-0003-2121-5177>), James Martherus [ctb] (<https://orcid.org/0000-0002-8285-3300>), Chuliang Xiao [ctb] (<https://orcid.org/0000-0002-8466-9398>), Joseph Larmarange [ctb], Max Kuhn [ctb], Michal Bojanowski [ctb], Hakon Malmedal [ctb], Clara Wang [ctb], Sergio Oller [ctb], Luke Sonnet [ctb], Jim Hester [ctb], Cory Brunson [ctb], Ben Schneider [ctb], Bernie Gray [ctb] (<https://orcid.org/0000-0001-9190-6032>), Mara Averick [ctb], Aaron Jacobs [ctb], Andreas Bender [ctb], Sven Templer [ctb], Paul-Christian Buerkner [ctb], Matthew Kay [ctb], Erwan Le Pennec [ctb], Johan Junkka [ctb], Hao Zhu [ctb], Benjamin Soltoff [ctb], Zoe Wilkinson Saldana [ctb], Tyler Littlefield [ctb], Charles T. Gray [ctb], Shabbh E. Banks [ctb], Serina Robinson [ctb], Roger Bivand [ctb], Riinu Ots [ctb], Nicholas Williams [ctb], Nina Jakobsen [ctb], Michael Weylandt [ctb], Lisa Lendway [ctb], Karl Hailperin [ctb], Josue Rodriguez [ctb], Jenny Bryan [ctb], Chris Jarvis [ctb], Greg Macfarlane [ctb], Brian Mannakee [ctb], Drew Tyre [ctb], Shreyas Singh [ctb], Laurens Geffert [ctb], Hong Ooi [ctb], Henrik Bengtsson [ctb], Eduard Szocs [ctb], David Hugh-Jones [ctb], Matthieu Stigler [ctb], Hugo Tavares [ctb] (<https://orcid.org/0000-0001-9373-2726>), R. Willem Vervoort [ctb], Brenton M. Wiernik [ctb]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

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Package SSDforR updated to version 1.5.19 with previous version 1.5.18 dated 2020-09-16

Title: Functions to Analyze Single System Data
Description: Functions to visually and statistically analyze single system data.
Author: Charles Auerbach [aut, cre], Wendy Zeitlin [aut]
Maintainer: Charles Auerbach <auerbach@yu.edu>

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Package deepgmm updated to version 0.1.62 with previous version 0.1.59 dated 2019-12-16

Title: Deep Gaussian Mixture Models
Description: Deep Gaussian mixture models as proposed by Viroli and McLachlan (2019) <doi:10.1007/s11222-017-9793-z> provide a generalization of classical Gaussian mixtures to multiple layers. Each layer contains a set of latent variables that follow a mixture of Gaussian distributions. To avoid overparameterized solutions, dimension reduction is applied at each layer by way of factor models.
Author: Cinzia Viroli, Geoffrey J. McLachlan
Maintainer: Suren Rathnayake <surenr@gmail.com>

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Package hereR updated to version 0.5.1 with previous version 0.5.0 dated 2020-09-18

Title: 'sf'-Based Interface to the 'HERE' REST APIs
Description: Interface to the 'HERE' REST APIs <https://developer.here.com/develop/rest-apis>: (1) geocode and autosuggest addresses or reverse geocode POIs using the 'Geocoder' API; (2) route directions, travel distance or time matrices and isolines using the 'Routing' API; (3) request real-time traffic flow and incident information from the 'Traffic' API; (4) find request public transport connections and nearby stations from the 'Public Transit' API; (5) request intermodal routes using the 'Intermodal Routing' API; (6) get weather forecasts, reports on current weather conditions, astronomical information and alerts at a specific location from the 'Destination Weather' API. Locations, routes and isolines are returned as 'sf' objects.
Author: Merlin Unterfinger [aut, cre] (<https://orcid.org/0000-0003-2020-2366>), Daniel Possenriede [ctb] (<https://orcid.org/0000-0002-6738-9845>)
Maintainer: Merlin Unterfinger <info@munterfinger.ch>

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Mon, 19 Oct 2020

Package BayesFM updated to version 0.1.4 with previous version 0.1.3 dated 2019-12-05

Title: Bayesian Inference for Factor Modeling
Description: Collection of procedures to perform Bayesian analysis on a variety of factor models. Currently, it includes: Bayesian Exploratory Factor Analysis (befa), an approach to dedicated factor analysis with stochastic search on the structure of the factor loading matrix. The number of latent factors, as well as the allocation of the manifest variables to the factors, are not fixed a priori but determined during MCMC sampling. More approaches will be included in future releases of this package.
Author: Rémi Piatek [aut, cre] (<https://orcid.org/0000-0002-3474-1304>)
Maintainer: Rémi Piatek <remi.piatek@gmail.com>

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Package aqp updated to version 1.25 with previous version 1.19 dated 2020-01-24

Title: Algorithms for Quantitative Pedology
Description: The Algorithms for Quantitative Pedology (AQP) project was started in 2009 to organize a loosely-related set of concepts and source code on the topic of soil profile visualization, aggregation, and classification into this package (aqp). Over the past 8 years, the project has grown into a suite of related R packages that enhance and simplify the quantitative analysis of soil profile data. Central to the AQP project is a new vocabulary of specialized functions and data structures that can accommodate the inherent complexity of soil profile information; freeing the scientist to focus on ideas rather than boilerplate data processing tasks <doi:10.1016/j.cageo.2012.10.020>. These functions and data structures have been extensively tested and documented, applied to projects involving hundreds of thousands of soil profiles, and deeply integrated into widely used tools such as SoilWeb <https://casoilresource.lawr.ucdavis.edu/soilweb-apps/>. Components of the AQP project (aqp, soilDB, sharpshootR, soilReports packages) serve an important role in routine data analysis within the USDA-NRCS Soil Science Division. The AQP suite of R packages offer a convenient platform for bridging the gap between pedometric theory and practice.
Author: Dylan Beaudette [aut, cre], Pierre Roudier [aut, ctb], Andrew Brown [aut, ctb]
Maintainer: Dylan Beaudette <dylan.beaudette@usda.gov>

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Package windex updated to version 2.0 with previous version 1.0 dated 2014-10-15

Title: Analysing Convergent Evolution using the Wheatsheaf Index
Description: Analysing convergent evolution using the Wheatsheaf index, described in Arbuckle et al. (2014) <doi: 10.1111/2041-210X.12195>, and some other random but perhaps useful functions).
Author: Kevin Arbuckle and Amanda Minter
Maintainer: Kevin Arbuckle <kevin.arbuckle@swansea.ac.uk>

Diff between windex versions 1.0 dated 2014-10-15 and 2.0 dated 2020-10-19

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Package Rfast2 updated to version 0.0.7 with previous version 0.0.6 dated 2020-10-12

Title: A Collection of Efficient and Extremely Fast R Functions II
Description: A collection of fast statistical and utility functions for data analysis. Functions for regression, maximum likelihood, column-wise statistics and many more have been included. C++ has been utilized to speed up the functions.
Author: Manos Papadakis, Michail Tsagris, Stefanos Fafalios and Marios Dimitriadis.
Maintainer: Manos Papadakis <rfastofficial@gmail.com>

Diff between Rfast2 versions 0.0.6 dated 2020-10-12 and 0.0.7 dated 2020-10-19

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