Sat, 17 Jul 2021

Package agrmt updated to version 1.42.7 with previous version 1.42.4 dated 2020-08-31

Title: Calculate Concentration and Dispersion in Ordered Rating Scales
Description: Calculates concentration and dispersion in ordered rating scales. It implements various measures of concentration and dispersion to describe what researchers variably call agreement, concentration, consensus, dispersion, or polarization among respondents in ordered data. It also implements other related measures to classify distributions. In addition to a generic city-block based concentration measure and a generic dispersion measure, the package implements various measures, including van der Eijk's (2001) <DOI: 10.1023/A:1010374114305> measure of agreement A, measures of concentration by Leik, Tatsle and Wierman, Blair and Lacy, Kvalseth, Berry and Mielke, Reardon, and Garcia-Montalvo and Reynal-Querol. Furthermore, the package provides an implementation of Galtungs AJUS-system to classify distributions, as well as a function to identify the position of multiple modes.
Author: Didier Ruedin [aut, cre] Clem Aeppli [ctb]
Maintainer: Didier Ruedin <didier.ruedin@unine.ch>

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Package RIA updated to version 1.6.0 with previous version 1.5.1 dated 2021-06-30

Title: Radiomics Image Analysis Toolbox for Medial Images
Description: Radiomics image analysis toolbox for 2D and 3D radiological images. RIA supports DICOM, NIfTI, nrrd and npy (numpy array) file formats. RIA calculates first-order, gray level co-occurrence matrix, gray level run length matrix and geometry-based statistics. Almost all calculations are done using vectorized formulas to optimize run speeds. Calculation of several thousands of parameters only takes minutes on a single core of a conventional PC.
Author: Marton Kolossvary [aut, cre]
Maintainer: Marton Kolossvary <marton.kolossvary@gmail.com>

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Package patentr updated to version 0.1.2 with previous version 0.1.0 dated 2021-02-08

Title: Access USPTO Bulk Data in Tidy Rectangular Format
Description: Converts TXT and XML data curated by the United States Patent and Trademark Office (USPTO). Allows conversion of bulk data after downloading directly from the USPTO bulk data website, eliminating need for users to wrangle multiple data formats to get large patent databases in tidy, rectangular format. Data details can be found on the USPTO website <https://bulkdata.uspto.gov/>. Currently, all 3 formats: 1. TXT data (1976-2001); 2. XML format 1 data (2002-2004); and 3. XML format 2 data (2005-current) can be converted to rectangular, CSV format. Relevant literature that uses data from USPTO includes Wada (2020) <doi:10.1007/s11192-020-03674-4> and Plaza & Albert (2008) <doi:10.1007/s11192-007-1763-3>.
Author: Raoul Wadhwa [aut, cre] (<https://orcid.org/0000-0003-0503-9580>), James Yu [aut], Hayley Beltz [aut], Milind Desai [aut], Jacob Scott [aut], Peter Erdi [aut]
Maintainer: Raoul Wadhwa <raoulwadhwa@gmail.com>

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Package gpbStat updated to version 0.3.3 with previous version 0.3.2 dated 2021-06-16

Title: Comprehensive Statistical Analysis of Plant Breeding Experiments
Description: Performs statistical data analysis of various Plant Breeding experiments. Contains functions for Line by Tester analysis as per Arunachalam, V.(1974) <http://repository.ias.ac.in/89299/> and Diallel analysis as per Griffing, B. (1956) <https://www.publish.csiro.au/bi/pdf/BI9560463>.
Author: Nandan Patil [cre, aut] (<https://orcid.org/0000-0003-0100-9931>), Lakshmi R. Gangavati [aut, ctb]
Maintainer: Nandan Patil <tryanother609@gmail.com>

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Package adegenet updated to version 2.1.4 with previous version 2.1.3 dated 2020-05-10

Title: Exploratory Analysis of Genetic and Genomic Data
Description: Toolset for the exploration of genetic and genomic data. Adegenet provides formal (S4) classes for storing and handling various genetic data, including genetic markers with varying ploidy and hierarchical population structure ('genind' class), alleles counts by populations ('genpop'), and genome-wide SNP data ('genlight'). It also implements original multivariate methods (DAPC, sPCA), graphics, statistical tests, simulation tools, distance and similarity measures, and several spatial methods. A range of both empirical and simulated datasets is also provided to illustrate various methods.
Author: Thibaut Jombart [aut] (<https://orcid.org/0000-0003-2226-8692>), Zhian N. Kamvar [aut, cre] (<https://orcid.org/0000-0003-1458-7108>), Caitlin Collins [ctb], Roman Lustrik [ctb], Marie-Pauline Beugin [ctb], Brian J. Knaus [ctb], Peter Solymos [ctb], Vladimir Mikryukov [ctb], Klaus Schliep [ctb], Tiago Maié [ctb], Libor Morkovsky [ctb], Ismail Ahmed [ctb], Anne Cori [ctb], Federico Calboli [ctb], RJ Ewing [ctb], Frédéric Michaud [ctb], Rebecca DeCamp [ctb], Alexandre Courtiol [ctb] (<https://orcid.org/0000-0003-0637-2959>)
Maintainer: Zhian N. Kamvar <zkamvar@gmail.com>

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Package comsimitv updated to version 0.1.5 with previous version 0.1.4 dated 2020-10-22

Title: Flexible Framework for Simulating Community Assembly
Description: Flexible framework for trait-based simulation of community assembly, where components could be replaced by user-defined function and that allows variation of traits within species.
Author: Zoltan Botta-Dukat
Maintainer: Zoltan Botta-Dukat <botta-dukat.zoltan@okologia.mta.hu>

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Package neatStats updated to version 1.7.2 with previous version 1.5.1 dated 2020-10-08

Title: Neat and Painless Statistical Reporting
Description: User-friendly, clear and simple statistics, primarily for publication in psychological science. The main functions are wrappers for other packages, but there are various additions as well. Every relevant step from data aggregation to reportable printed statistics is covered for basic experimental designs.
Author: Gáspár Lukács [aut, cre] (<https://orcid.org/0000-0001-9401-4830>), Bennett Kleinberg [ctb] (<https://orcid.org/0000-0003-1658-9086>), Johnny van Doorn [ctb] (<https://orcid.org/0000-0003-0270-096X>)
Maintainer: Gáspár Lukács <lkcsgaspar@gmail.com>

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Package kindisperse updated to version 0.10.1 with previous version 0.9.2 dated 2021-03-31

Title: Simulate and Estimate Close-Kin Dispersal Kernels
Description: Functions for simulating and estimating kinship-related dispersal. Based on the methods described in M. Jasper, T.L. Schmidt., N.W. Ahmad, S.P. Sinkins & A.A. Hoffmann (2019) <doi:10.1111/1755-0998.13043> "A genomic approach to inferring kinship reveals limited intergenerational dispersal in the yellow fever mosquito". Assumes an additive variance model of dispersal in two dimensions, compatible with Wright's neighbourhood area. Simple and composite dispersal simulations are supplied, as well as the functions needed to estimate parent-offspring dispersal for simulated or empirical data, and to undertake sampling design for future field studies of dispersal. For ease of use an integrated Shiny app is also included.
Author: Moshe-Elijah Jasper [aut, cre] (<https://orcid.org/0000-0003-4541-3223>)
Maintainer: Moshe-Elijah Jasper <moshe.jasper@unimelb.edu.au>

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Package FSA updated to version 0.9.1 with previous version 0.9.0 dated 2021-06-09

Title: Simple Fisheries Stock Assessment Methods
Description: A variety of simple fish stock assessment methods. Detailed vignettes are available on the fishR website <http://derekogle.com/fishR/>.
Author: Derek Ogle [aut, cre] (<https://orcid.org/0000-0002-0370-9299>), Jason Doll [aut], Powell Wheeler [aut], Alexis Dinno [aut] (Provided base functionality of dunnTest())
Maintainer: Derek Ogle <derek@derekogle.com>

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Package brglm2 updated to version 0.8.0 with previous version 0.7.1 dated 2021-01-22

Title: Bias Reduction in Generalized Linear Models
Description: Estimation and inference from generalized linear models based on various methods for bias reduction and maximum penalized likelihood with powers of the Jeffreys prior as penalty. The 'brglmFit' fitting method can achieve reduction of estimation bias by solving either the mean bias-reducing adjusted score equations in Firth (1993) <doi:10.1093/biomet/80.1.27> and Kosmidis and Firth (2009) <doi:10.1093/biomet/asp055>, or the median bias-reduction adjusted score equations in Kenne et al. (2017) <doi:10.1093/biomet/asx046>, or through the direct subtraction of an estimate of the bias of the maximum likelihood estimator from the maximum likelihood estimates as in Cordeiro and McCullagh (1991) <https://www.jstor.org/stable/2345592>. See Kosmidis et al (2020) <doi:10.1007/s11222-019-09860-6> for more details. Estimation in all cases takes place via a quasi Fisher scoring algorithm, and S3 methods for the construction of of confidence intervals for the reduced-bias estimates are provided. In the special case of generalized linear models for binomial and multinomial responses (both ordinal and nominal), the adjusted score approaches to mean and media bias reduction have been found to return estimates with improved frequentist properties, that are also always finite, even in cases where the maximum likelihood estimates are infinite (e.g. complete and quasi-complete separation; see Kosmidis and Firth, 2020 <doi:10.1093/biomet/asaa052>, for a proof for mean bias reduction in logistic regression).
Author: Ioannis Kosmidis [aut, cre] (<https://orcid.org/0000-0003-1556-0302>), Euloge Clovis Kenne Pagui [aut], Kjell Konis [ctb], Nicola Sartori [ctb]
Maintainer: Ioannis Kosmidis <ioannis.kosmidis@warwick.ac.uk>

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Package clusternor (with last version 0.0-4) was removed from CRAN

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

2020-02-16 0.0-4
2019-03-29 0.0-3

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Package knor (with last version 0.0-7) was removed from CRAN

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

2020-01-16 0.0-7
2018-09-13 0.0-6
2018-08-05 0.0-5.1
2018-03-11 0.0-5

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Package ttdo updated to version 0.0.8 with previous version 0.0.7 dated 2021-07-06

Title: Extend 'tinytest' with 'diffobj'
Description: The 'tinytest' package offers a light-weight zero-dependency unit-testing framework to which this package adds support of the 'diffobj' package for 'diff'-style comparison of R objects.
Author: Dirk Eddelbuettel and Alton Barbehenn
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between ttdo versions 0.0.7 dated 2021-07-06 and 0.0.8 dated 2021-07-17

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Package influential updated to version 2.2.3 with previous version 2.2.2 dated 2021-04-30

Title: Identification and Classification of the Most Influential Nodes
Description: Contains functions for the classification and ranking of top candidate features, reconstruction of networks from adjacency matrices and data frames, analysis of the topology of the network and calculation of centrality measures, and identification of the most influential nodes. Also, a function is provided for running SIRIR model, which is the combination of leave-one-out cross validation technique and the conventional SIR model, on a network to unsupervisedly rank the true influence of vertices. Additionally, some functions have been provided for the assessment of dependence and correlation of two network centrality measures as well as the conditional probability of deviation from their corresponding means in opposite direction. Fred Viole and David Nawrocki (2013, ISBN:1490523995). Csardi G, Nepusz T (2006). "The igraph software package for complex network research." InterJournal, Complex Systems, 1695. Adopted algorithms and sources are referenced in function document.
Author: Adrian (Abbas) Salavaty [aut, cre], Mirana Ramialison [ths], Peter D. Currie [ths]
Maintainer: Adrian Salavaty <abbas.salavaty@gmail.com>

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New package RstoxData with initial version 1.2.1
Package: RstoxData
Version: 1.2.1
Date: 2021-07-13
Title: Tools to Read and Manipulate Fisheries Data
Authors@R: c( person(given = "Ibrahim", family = "Umar", role = c("cre", "aut"), email = "ibrahim.umar@hi.no"), person(given = "Sindre", family = "Vatnehol", role = "aut"), person(given = "Arne Johannes", family = "Holmin", role = "aut"), person(given = "Edvin", family = "Fuglebakk", role = "aut"), person(given = "Espen", family = "Johnsen", role = "aut"), person(given = "Norwegian Institute of Marine Research", role = c("cph", "fnd")))
Depends: R (>= 3.6)
Description: Set of tools to read and manipulate various data formats for fisheries. Mainly catered towards scientific trawl survey sampling ('biotic') data, acoustic trawl data, and commercial fishing catch ('landings') data. Among the supported data formats are the data products from the Norwegian Institute Marine Research ('IMR') and the International Council for the Exploration of the Sea (ICES).
URL: https://github.com/StoXProject/RstoxData
BugReports: https://github.com/StoXProject/RstoxData/issues
License: LGPL-3
LazyData: true
Encoding: UTF-8
Imports: Rcpp (>= 1.0.0), data.table (>= 1.12.6), xml2 (>= 1.2.2), xslt (>= 1.4), units (>= 0.7), stringi (>= 1.4.3)
Suggests: testthat
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2021-07-13 20:00:09 UTC; baim
Author: Ibrahim Umar [cre, aut], Sindre Vatnehol [aut], Arne Johannes Holmin [aut], Edvin Fuglebakk [aut], Espen Johnsen [aut], Norwegian Institute of Marine Research [cph, fnd]
Maintainer: Ibrahim Umar <ibrahim.umar@hi.no>
Repository: CRAN
Date/Publication: 2021-07-17 10:10:05 UTC

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Package plotmo updated to version 3.6.1 with previous version 3.6.0 dated 2020-09-13

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

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Package circletyper updated to version 1.0.1 with previous version 1.0.0 dated 2021-01-20

Title: Curve Text Elements in 'Shiny' Using 'CircleType.js'
Description: Enables curving text elements in 'Shiny' apps.
Author: Etienne Bacher [aut, cre, cph]
Maintainer: Etienne Bacher <etienne.bacher@protonmail.com>

Diff between circletyper versions 1.0.0 dated 2021-01-20 and 1.0.1 dated 2021-07-17

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New package BGVAR with initial version 2.2.3
Package: BGVAR
Title: Bayesian Global Vector Autoregressions
Version: 2.2.3
Author: Maximilian Boeck [aut, cre] (<https://orcid.org/0000-0001-6024-8305>), Martin Feldkircher [aut] (<https://orcid.org/0000-0002-5511-9215>), Florian Huber [aut] (<https://orcid.org/0000-0002-2896-7921>), Darjus Hosszejni [ctb] (<https://orcid.org/0000-0002-3803-691X>)
Authors@R: c(person("Maximilian","Boeck",role=c("aut","cre"),email="maximilian.boeck@wu.ac.at", comment = c(ORCID = "0000-0001-6024-8305")), person("Martin","Feldkircher", role="aut", comment = c(ORCID = "0000-0002-5511-9215")), person("Florian","Huber", role="aut", comment = c(ORCID = "0000-0002-2896-7921")), person("Darjus","Hosszejni", role="ctb", comment = c(ORCID = "0000-0002-3803-691X")))
Maintainer: Maximilian Boeck <maximilian.boeck@wu.ac.at>
Description: Estimation of Bayesian Global Vector Autoregressions (BGVAR) with different prior setups and the possibility to introduce stochastic volatility. Built-in priors include the Minnesota, the stochastic search variable selection and Normal-Gamma (NG) prior. For a reference see also Crespo Cuaresma, J., Feldkircher, M. and F. Huber (2016) "Forecasting with Global Vector Autoregressive Models: a Bayesian Approach", Journal of Applied Econometrics, Vol. 31(7), pp. 1371-1391 <doi:10.1002/jae.2504>. Post-processing functions allow for doing predictions, structurally identify the model with short-run or sign-restrictions and compute impulse response functions, historical decompositions and forecast error variance decompositions. Plotting functions are also available.
Encoding: UTF-8
License: GPL-3
Language: en-US
Depends: R (>= 3.5.0)
SystemRequirements: C++11, GNU make
Imports: abind, bayesm, coda, GIGrvg, graphics, knitr, MASS, Matrix, methods, parallel, Rcpp (>= 1.0.3), RcppParallel, stats, stochvol (>= 3.0.3), utils, xts, zoo
Suggests: rmarkdown, testthat (>= 2.1.0)
LazyData: true
LinkingTo: Rcpp, RcppArmadillo, RcppProgress, RcppParallel, stochvol, GIGrvg
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-07-14 14:13:09 UTC; mboeck
Repository: CRAN
Date/Publication: 2021-07-17 10:10:09 UTC

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Package UCSCXenaTools updated to version 1.4.6 with previous version 1.4.5 dated 2021-05-27

Title: Download and Explore Datasets from UCSC Xena Data Hubs
Description: Download and explore datasets from UCSC Xena data hubs, which are a collection of UCSC-hosted public databases such as TCGA, ICGC, TARGET, GTEx, CCLE, and others. Databases are normalized so they can be combined, linked, filtered, explored and downloaded.
Author: Shixiang Wang [aut, cre] (<https://orcid.org/0000-0001-9855-7357>), Xue-Song Liu [aut] (<https://orcid.org/0000-0002-7736-0077>), Martin Morgan [ctb], Christine Stawitz [rev] (Christine reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/315>), Carl Ganz [rev] (Carl reviewed the package for ropensci, see <https://github.com/ropensci/software-review/issues/315>)
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaTools versions 1.4.5 dated 2021-05-27 and 1.4.6 dated 2021-07-17

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New package nhdR with initial version 0.5.6
Package: nhdR
Title: Tools for Working with the National Hydrography Dataset
Version: 0.5.6
Authors@R: person("Jemma", "Stachelek", email = "stachel2@msu.edu", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-5924-2464"))
Description: Tools for working with the National Hydrography Dataset, with functions for querying, downloading, and networking both the NHD <https://www.usgs.gov/core-science-systems/ngp/national-hydrography> and NHDPlus <https://www.epa.gov/waterdata/nhdplus-national-hydrography-dataset-plus> datasets.
URL: https://github.com/jsta/nhdR
BugReports: https://github.com/jsta/nhdR/issues
Depends: R (>= 3.5.0), maps
License: GPL
Imports: rappdirs, rgdal, sf, httr, rvest, xml2, foreign, ggplot2, rlang, dplyr, curl, units, stringr, memoise, purrr
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, wikilake, sp, rgeos, testthat (>= 2.1.0), covr, crul, lwgeom, s2
VignetteBuilder: knitr
SystemRequirements: 7-zip command line tool (7z)
Language: en-US
NeedsCompilation: no
Packaged: 2021-07-13 15:38:40 UTC; jemma
Author: Jemma Stachelek [aut, cre] (<https://orcid.org/0000-0002-5924-2464>)
Maintainer: Jemma Stachelek <stachel2@msu.edu>
Repository: CRAN
Date/Publication: 2021-07-17 10:00:02 UTC

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New package CKMRpop with initial version 0.1.3
Package: CKMRpop
Title: Forward-in-Time Simulation and Tallying of Pairwise Relationships
Version: 0.1.3
Authors@R: c( person(given = c("Eric", "C."), "Anderson", , "eric.anderson@noaa.gov", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-1326-0840") ) )
Description: Provides an R wrapper around the program 'spip' (<https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1471-8286.2005.00884.x>), a C program for the simulation of pedigrees within age-structured populations with user-specified life histories. Also includes a variety of functions to parse 'spip' output to compile information about related pairs amongst simulated, sampled individuals, to assess the feasibility and potential accuracy of close-kin mark-recapture (CKMR). Full documentation and vignettes are mirrored at <https://eriqande.github.io/CKMRpop/index.html> and can be read online there.
License: CC0
Encoding: UTF-8
LazyData: true
LinkingTo: Rcpp
Depends: R (>= 3.5.0)
Imports: dplyr, ggforce, ggplot2, ggraph, igraph, magrittr, purrr, Rcpp (>= 1.0.4), readr, stats, stringr, tibble, tidygraph, tidyr, vroom
Suggests: knitr, rmarkdown, tidyverse
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-07-13 19:13:18 UTC; eriq
Author: Eric C. Anderson [aut, cre] (<https://orcid.org/0000-0003-1326-0840>)
Maintainer: Eric C. Anderson <eric.anderson@noaa.gov>
Repository: CRAN
Date/Publication: 2021-07-17 10:00:06 UTC

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Package rrlda (with last version 1.1) was removed from CRAN

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

2012-06-09 1.1
2011-09-20 1.0

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Package ToolsForCoDa (with last version 1.0.5) was removed from CRAN

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

2020-06-18 1.0.5
2017-11-13 1.0.2

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Package sROC (with last version 0.1-2) was removed from CRAN

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

2012-04-12 0.1-2

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Package mvoutlier (with last version 2.0.9) was removed from CRAN

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

2018-02-08 2.0.9
2017-01-16 2.0.8
2015-01-30 2.0.6
2014-06-23 2.0.5
2014-02-25 2.0.4
2013-08-23 2.0.3
2013-01-14 1.9.9
2012-08-31 1.9.8
2012-04-19 1.9.7
2011-11-07 1.9.4
2011-09-06 1.9.3
2011-06-02 1.9.1
2011-05-30 1.9
2011-04-06 1.8
2011-02-08 1.7
2011-01-14 1.6
2010-11-08 1.5
2009-01-22 1.4
2007-05-16 1.3

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Package robCompositions (with last version 2.3.0) was removed from CRAN

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

2020-11-18 2.3.0
2020-02-11 2.2.1
2020-01-14 2.2.0
2019-04-15 2.1.0
2019-02-19 2.0.10
2018-11-08 2.0.9
2018-05-29 2.0.8
2018-04-08 2.0.7
2017-08-14 2.0.6
2017-07-12 2.0.5
2017-01-11 2.0.3
2016-08-22 2.0.2
2016-02-08 2.0.0
2015-05-06 1.9.1
2014-08-18 1.9.0
2014-03-16 1.8.0
2014-02-07 1.7.0
2013-11-26 1.6.4
2013-02-27 1.6.3
2013-01-11 1.6.2
2012-05-15 1.6.0
2011-05-06 1.5.0
2011-01-11 1.4.4
2010-08-16 1.4.3
2010-07-05 1.4.2
2010-06-21 1.4.1
2010-04-06 1.4.0
2010-01-18 1.3.3
2009-11-29 1.3.2
2009-05-08 1.2.2
2009-03-06 1.2
2009-01-20 1.0.1

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Package groupedstats (with last version 2.1.0) was removed from CRAN

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

2021-05-28 2.1.0
2021-01-21 2.0.1

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Package cli updated to version 3.0.1 with previous version 3.0.0 dated 2021-06-30

Title: Helpers for Developing Command Line Interfaces
Description: A suite of tools to build attractive command line interfaces ('CLIs'), from semantic elements: headings, lists, alerts, paragraphs, etc. Supports custom themes via a 'CSS'-like language. It also contains a number of lower level 'CLI' elements: rules, boxes, trees, and 'Unicode' symbols with 'ASCII' alternatives. It support ANSI colors and text styles as well.
Author: Gábor Csárdi [aut, cre], Hadley Wickham [ctb], Kirill Müller [ctb], RStudio [cph]
Maintainer: Gábor Csárdi <csardi.gabor@gmail.com>

Diff between cli versions 3.0.0 dated 2021-06-30 and 3.0.1 dated 2021-07-17

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Package spatstat.linnet updated to version 2.3-0 with previous version 2.2-1 dated 2021-06-22

Title: Linear Networks Functionality of the 'spatstat' Family
Description: Defines types of spatial data on a linear network and provides functionality for geometrical operations, data analysis and modelling of data on a linear network, in the 'spatstat' family of packages. Contains definitions and support for linear networks, including creation of networks, geometrical measurements, topological connectivity, geometrical operations such as inserting and deleting vertices, intersecting a network with another object, and interactive editing of networks. Data types defined on a network include point patterns, pixel images, functions, and tessellations. Exploratory methods include kernel estimation of intensity on a network, K-functions and pair correlation functions on a network, simulation envelopes, nearest neighbour distance and empty space distance, relative risk estimation with cross-validated bandwidth selection. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported. Parametric models can be fitted to point pattern data using the function lppm() similar to glm(). Only Poisson models are implemented so far. Models may involve dependence on covariates and dependence on marks. Models are fitted by maximum likelihood. Fitted point process models can be simulated, automatically. Formal hypothesis tests of a fitted model are supported (likelihood ratio test, analysis of deviance, Monte Carlo tests) along with basic tools for model selection (stepwise(), AIC()) and variable selection (sdr). Tools for validating the fitted model include simulation envelopes, residuals, residual plots and Q-Q plots, leverage and influence diagnostics, partial residuals, and added variable plots. Random point patterns on a network can be generated using a variety of models.
Author: Adrian Baddeley [aut, cre], Rolf Turner [aut], Ege Rubak [aut], Ottmar Cronie [ctb], Tilman Davies [ctb], Greg McSwiggan [ctb], Suman Rakshit [ctb]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package dotwhisker updated to version 0.7.0 with previous version 0.6.0 dated 2021-02-17

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

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Package distr6 updated to version 1.5.6 with previous version 1.5.4 dated 2021-07-14

Title: The Complete R6 Probability Distributions Interface
Description: An R6 object oriented distributions package. Unified interface for 42 probability distributions and 11 kernels including functionality for multiple scientific types. Additionally functionality for composite distributions and numerical imputation. Design patterns including wrappers and decorators are described in Gamma et al. (1994, ISBN:0-201-63361-2). For quick reference of probability distributions including d/p/q/r functions and results we refer to McLaughlin, M. P. (2001). Additionally Devroye (1986, ISBN:0-387-96305-7) for sampling the Dirichlet distribution, Gentle (2009) <doi:10.1007/978-0-387-98144-4> for sampling the Multivariate Normal distribution and Michael et al. (1976) <doi:10.2307/2683801> for sampling the Wald distribution.
Author: Raphael Sonabend [aut, cre] (<https://orcid.org/0000-0001-9225-4654>), Franz Kiraly [aut], Peter Ruckdeschel [ctb] (Author of distr), Matthias Kohl [ctb] (Author of distr), Nurul Ain Toha [ctb], Shen Chen [ctb], Jordan Deenichin [ctb], Chengyang Gao [ctb], Chloe Zhaoyuan Gu [ctb], Yunjie He [ctb], Xiaowen Huang [ctb], Shuhan Liu [ctb], Runlong Yu [ctb], Chijing Zeng [ctb], Qian Zhou [ctb]
Maintainer: Raphael Sonabend <raphaelsonabend@gmail.com>

Diff between distr6 versions 1.5.4 dated 2021-07-14 and 1.5.6 dated 2021-07-17

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New package spectre with initial version 1.0.2
Package: spectre
Title: Predict Regional Community Composition
Version: 1.0.2
Authors@R: c(person("Craig", "Simpkins", email = "simpkinscraig063@gmail.com", role = c("aut", "cre")), person("Sebastian", "Hanss", role = c("aut")), person("Maximilian", "Hesselbarth", role = c("aut")), person("Matthias", "Spangenberg", role = c("aut")), person("Jan", "Salecker", role = c("aut")))
Maintainer: Craig Simpkins <simpkinscraig063@gmail.com>
Description: Predict regional community composition at a fine spatial resolution using only sparse biological and environmental data. The package is based on the DynamicFOAM algorithm described in Mokany et al. (2011) <doi:10.1111/j.1461-0248.2011.01675.x>.
License: GPL-3
Depends: R (>= 3.5)
Imports: ggplot2, Rcpp (>= 1.0.1)
Suggests: dplyr, testthat (>= 3.0.2), knitr, rmarkdown, covr, RcppProgress
LinkingTo: Rcpp, RcppProgress, testthat
ByteCompile: true
Encoding: UTF-8
LazyData: true
SystemRequirements: C++11
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2021-07-16 00:37:13 UTC; simpk
Author: Craig Simpkins [aut, cre], Sebastian Hanss [aut], Maximilian Hesselbarth [aut], Matthias Spangenberg [aut], Jan Salecker [aut]
Repository: CRAN
Date/Publication: 2021-07-17 06:30:02 UTC

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Package isotree updated to version 0.2.10 with previous version 0.2.8 dated 2021-07-11

Title: Isolation-Based Outlier Detection
Description: Fast and multi-threaded implementation of isolation forest (Liu, Ting, Zhou (2008) <doi:10.1109/ICDM.2008.17>), extended isolation forest (Hariri, Kind, Brunner (2018) <arXiv:1811.02141>), SCiForest (Liu, Ting, Zhou (2010) <doi:10.1007/978-3-642-15883-4_18>), and fair-cut forest (Cortes (2019) <arXiv:1911.06646>), for isolation-based outlier detection, clustered outlier detection, distance or similarity approximation (Cortes (2019) <arXiv:1910.12362>), and imputation of missing values (Cortes (2019) <arXiv:1911.06646>), based on random or guided decision tree splitting. Provides simple heuristics for fitting the model to categorical columns and handling missing data, and offers options for varying between random and guided splits, and for using different splitting criteria.
Author: David Cortes
Maintainer: David Cortes <david.cortes.rivera@gmail.com>

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Package swissdd updated to version 1.1.4 with previous version 1.1.3 dated 2021-06-29

Title: Get Swiss Federal and Cantonal Vote Results from Opendata.swiss
Description: Builds upon the real time data service as well as the archive for national votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-eidgenoessischen-abstimmungsvorlagen> and cantonal votes <https://opendata.swiss/api/3/action/package_show?id=echtzeitdaten-am-abstimmungstag-zu-kantonalen-abstimmungsvorlagen>. It brings the results of Swiss popular votes, aggregated at the geographical level of choice, into R. Additionally, it allows to retrieve data from the Swissvotes-Database, one of the most comprehensive data platforms on Swiss referendums and initiatives <https://swissvotes.ch/page/dataset/swissvotes_dataset.csv>.
Author: Thomas Lo Russo [cre, aut], Thomas Willi [aut]
Maintainer: Thomas Lo Russo <th.lorusso@gmail.com>

Diff between swissdd versions 1.1.3 dated 2021-06-29 and 1.1.4 dated 2021-07-17

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Package SDMtune updated to version 1.1.5 with previous version 1.1.4 dated 2021-03-14

Title: Species Distribution Model Selection
Description: User-friendly framework that enables the training and the evaluation of species distribution models (SDMs). The package implements functions for data driven variable selection and model tuning and includes numerous utilities to display the results. All the functions used to select variables or to tune model hyperparameters have an interactive real-time chart displayed in the 'RStudio' viewer pane during their execution.
Author: Sergio Vignali [aut, cre] (<https://orcid.org/0000-0002-3390-5442>), Arnaud Barras [aut] (<https://orcid.org/0000-0003-0850-6965>), Veronika Braunisch [aut] (<https://orcid.org/0000-0001-7035-4662>), Conservation Biology - University of Bern [fnd]
Maintainer: Sergio Vignali <sergio.vignali@iee.unibe.ch>

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Package penfa updated to version 0.1.1 with previous version 0.1.0 dated 2021-07-12

Title: Single- And Multiple-Group Penalized Factor Analysis
Description: Fits single- and multiple-group penalized factor analysis models via a trust-region algorithm with integrated automatic multiple tuning parameter selection (Geminiani et al., 2021 <doi:10.1007/s11336-021-09751-8>). Available penalties include lasso, adaptive lasso, scad, mcp, and ridge.
Author: Elena Geminiani [aut, cre] (<https://orcid.org/0000-0001-5992-9728>), Giampiero Marra [aut] (<https://orcid.org/0000-0002-9010-2646>), Irini Moustaki [aut] (<https://orcid.org/0000-0001-8371-1251>)
Maintainer: Elena Geminiani <geminianielena@gmail.com>

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Package liGP updated to version 1.0.1 with previous version 1.0.0 dated 2021-07-01

Title: Locally Induced Gaussian Process Regression
Description: Performs locally induced approximate GP regression for large computer experiments and spatial datasets following Cole D.A., Christianson, R., Gramacy, R.B. (2021) Statistics and Computing, 31(3), 1-21, <arXiv:2008.12857>. The approximation is based on small local designs combined with a set of inducing points (latent design points) for predictions at particular inputs. Parallelization is supported for generating predictions over an immense out-of-sample testing set. Local optimization of the inducing points design is provided based on variance-based criteria. Inducing point template schemes, including scaling of space-filling designs, are also provided.
Author: D. Austin Cole [aut, cre], Ryan B Christianson [cph], Robert B. Gramacy [cph]
Maintainer: D. Austin Cole <austin.cole8@vt.edu>

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

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

2021-07-16 0.1.0

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Package kittyR (with last version 1.1.0) was removed from CRAN

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

2021-04-03 1.1.0
2021-01-18 1.0.0

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Package phase updated to version 1.1.2 with previous version 1.1.1 dated 2021-07-02

Title: Analyse Biological Time-Series Data
Description: Compiles functions to trim, bin, visualise, and analyse activity/sleep time-series data collected from the Drosophila Activity Monitor (DAM) system (Trikinetics, USA). The following methods were used to compute periodograms - Chi-square periodogram: Sokolove and Bushell (1978) <doi:10.1016/0022-5193(78)90022-X>, Lomb-Scargle periodogram: Lomb (1976) <doi:10.1007/BF00648343>, Scargle (1982) <doi:10.1086/160554> and Ruf (1999) <doi:10.1076/brhm.30.2.178.1422>, and Autocorrelation: Eijzenbach et al. (1986) <doi:10.1111/j.1440-1681.1986.tb00943.x>. Identification of activity peaks is done after using a Savitzky-Golay filter (Savitzky and Golay (1964) <doi:10.1021/ac60214a047>) to smooth raw activity data. Three methods to estimate anticipation of activity are used based on the following papers - Slope method: Fernandez et al. (2020) <doi:10.1016/j.cub.2020.04.025>, Harrisingh method: Harrisingh et al. (2007) <doi:10.1523/JNEUROSCI.3680-07.2007>, and Stoleru method: Stoleru et al. (2004) <doi:10.1038/nature02926>. Rose plots and circular analysis are based on methods from - Batschelet (1981) <ISBN:0120810506> and Zar (2010) <ISBN:0321656865>.
Author: Lakshman Abhilash [aut, cre] (<https://orcid.org/0000-0002-9933-8989>)
Maintainer: Lakshman Abhilash <labhilash@gc.cuny.edu>

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Package orders updated to version 0.1.6 with previous version 0.1.5 dated 2021-03-29

Title: Sampling from k-th Order Statistics of New Families of Distributions
Description: Set of tools to generate samples of k-th order statistics and others quantities of interest from new families of distributions. The main references for this package are: C. Kleiber and S. Kotz (2003) Statistical size distributions in economics and actuarial sciences; Gentle, J. (2009), Computational Statistics, Springer-Verlag; Naradajah, S. and Rocha, R. (2016), <DOI:10.18637/jss.v069.i10> and Stasinopoulos, M. and Rigby, R. (2015), <DOI:10.1111/j.1467-9876.2005.00510.x>. The families of distributions are: Burr distributions, Feller-Pareto distributions, Generalized Pareto Distributions, The Inverse Paralogistic Distributions, Marshall-Olkin G distributions, exponentiated G distributions, beta G distributions, gamma G distributions, Kumaraswamy G distributions, generalized beta G distributions, beta extended G distributions, gamma G distributions, gamma uniform G distributions, beta exponential G distributions, Weibull G distributions, log gamma G I distributions, log gamma G II distributions, exponentiated generalized G distributions, exponentiated Kumaraswamy G distributions, geometric exponential Poisson G distributions, truncated-exponential skew-symmetric G distributions, modified beta G distributions, exponentiated exponential Poisson G distributions, Poisson-inverse gaussian distribution, Skew normal type 1 distributions, Skew student t distribution, Sinh-Arcsinh distribution, Sichel distribution, Zero inflated Poisson.
Author: Carlos Alberto Cardozo Delgado
Maintainer: Carlos Alberto Cardozo Delgado <cardozorpackages@gmail.com>

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Package jmv updated to version 2.0 with previous version 1.2.23 dated 2020-06-26

Title: The 'jamovi' Analyses
Description: A suite of common statistical methods such as descriptives, t-tests, ANOVAs, regression, correlation matrices, proportion tests, contingency tables, and factor analysis. This package is also useable from the 'jamovi' statistical spreadsheet (see <https://www.jamovi.org> for more information).
Author: Ravi Selker, Jonathon Love, Damian Dropmann, Victor Moreno
Maintainer: Jonathon Love <jon@thon.cc>

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 91 files changed, 4853 insertions(+), 2871 deletions(-)

More information about jmv at CRAN
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Package gridpattern updated to version 0.2.1 with previous version 0.1.2 dated 2021-06-17

Title: 'grid' Pattern Grobs
Description: Provides 'grid' grobs that fill in a user-defined area with various patterns. Includes enhanced versions of the geometric and image-based patterns originally contained in the 'ggpattern' package as well as original 'pch', 'polygon_tiling', 'regular_polygon', 'rose', 'text', 'wave', and 'weave' patterns plus support for custom user-defined patterns.
Author: Mike FC [aut] (Patterns extracted from ggpattern), Trevor L Davis [aut, cre], Thomas Lin Pedersen [ctb] (new_data_frame() copied from ggplot2)
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>

Diff between gridpattern versions 0.1.2 dated 2021-06-17 and 0.2.1 dated 2021-07-17

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 gridpattern-0.2.1/gridpattern/tests/testthat/test_tiling.R         |    3 
 gridpattern-0.2.1/gridpattern/tests/testthat/test_utils.R          |   19 +
 47 files changed, 498 insertions(+), 145 deletions(-)

More information about gridpattern at CRAN
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Package fasano.franceschini.test updated to version 1.0.1 with previous version 1.0.0 dated 2021-06-22

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

Diff between fasano.franceschini.test versions 1.0.0 dated 2021-06-22 and 1.0.1 dated 2021-07-17

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 R/interal_functions_FasFran.R                  |   32 +++++++++------
 README.md                                      |   39 +++++++++----------
 build/partial.rdb                              |binary
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 tests/testthat/test-fasano_franceschini_test.R |   13 ++++--
 10 files changed, 95 insertions(+), 88 deletions(-)

More information about fasano.franceschini.test at CRAN
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