Fri, 12 Feb 2021

Package tidyseurat (with last version 0.1.17) was removed from CRAN

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

2020-11-23 0.1.17

Permanent link
Package ropenaq (with last version 0.2.11) was removed from CRAN

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

2020-11-10 0.2.11
2020-07-27 0.2.10
2020-03-26 0.2.9
2020-03-22 0.2.8
2019-01-31 0.2.7
2018-02-28 0.2.6
2018-01-03 0.2.5
2017-11-20 0.2.4
2017-08-01 0.2.2
2017-06-08 0.2.1
2017-04-28 0.2.0
2017-04-11 0.1.4
2016-09-14 0.1.3
2016-07-07 0.1.1
2016-07-05 0.1.0

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Package smerc updated to version 1.4.2 with previous version 1.4 dated 2021-02-06

Title: Statistical Methods for Regional Counts
Description: Implements statistical methods for analyzing the counts of areal data, with a focus on the detection of spatial clusters and clustering. The package has a heavy emphasis on spatial scan methods, which were first introduced by Kulldorff and Nagarwalla (1995) <doi:10.1002/sim.4780140809> and Kulldorff (1997) <doi:10.1080/03610929708831995>.
Author: Joshua French [aut, cre] (<https://orcid.org/0000-0002-9708-3353>), Mohammad Meysami [ctb] (<https://orcid.org/0000-0002-3322-5244>)
Maintainer: Joshua French <joshua.french@ucdenver.edu>

Diff between smerc versions 1.4 dated 2021-02-06 and 1.4.2 dated 2021-02-12

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Package mlt updated to version 1.2-2 with previous version 1.2-1 dated 2021-02-05

Title: Most Likely Transformations
Description: Likelihood-based estimation of conditional transformation models via the most likely transformation approach described in Hothorn et al. (2018) <DOI:10.1111/sjos.12291>.
Author: Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between mlt versions 1.2-1 dated 2021-02-05 and 1.2-2 dated 2021-02-12

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Package DiceDesign updated to version 1.9 with previous version 1.8-1 dated 2019-07-31

Title: Designs of Computer Experiments
Description: Space-Filling Designs and space-filling criteria (distance-based and uniformity-based), with emphasis to computer experiments; <doi:10.18637/jss.v065.i11>.
Author: Jessica Franco, Delphine Dupuy, Olivier Roustant, Patrice Kiener, Guillaume Damblin and Bertrand Iooss.
Maintainer: Celine Helbert <Celine.Helbert@ec-lyon.fr>

Diff between DiceDesign versions 1.8-1 dated 2019-07-31 and 1.9 dated 2021-02-12

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Package uGMAR updated to version 3.3.0 with previous version 3.2.6 dated 2020-12-17

Title: Estimate Univariate Gaussian or Student's t Mixture Autoregressive Model
Description: Maximum likelihood estimation of univariate Gaussian Mixture Autoregressive (GMAR), Student's t Mixture Autoregressive (StMAR), and Gaussian and Student's t Mixture Autoregressive (G-StMAR) models, quantile residual tests, graphical diagnostics, forecast and simulate from GMAR, StMAR and G-StMAR processes. Leena Kalliovirta, Mika Meitz, Pentti Saikkonen (2015) <doi:10.1111/jtsa.12108>, Mika Meitz, Daniel Preve, Pentti Saikkonen (2018) <arXiv:1805.04010>, Savi Virolainen (2020) <arXiv:2003.05221>.
Author: Savi Virolainen [aut, cre]
Maintainer: Savi Virolainen <savi.virolainen@helsinki.fi>

Diff between uGMAR versions 3.2.6 dated 2020-12-17 and 3.3.0 dated 2021-02-12

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Package SplitGLM updated to version 1.0.1 with previous version 1.0.0 dated 2021-02-09

Title: Split Generalized Linear Models
Description: Functions to compute split generalized linear models. The approach fits generalized linear models that split the covariates into groups. The optimal split of the variables into groups and the regularized estimation of the coefficients are performed by minimizing an objective function that encourages sparsity within each group and diversity among them.
Author: Anthony Christidis <anthony.christidis@stat.ubc.ca>, Stefan Van Aelst <stefan.vanaelst@kuleuven.be>, Ruben Zamar <ruben@stat.ubc.ca>
Maintainer: Anthony Christidis <anthony.christidis@stat.ubc.ca>

Diff between SplitGLM versions 1.0.0 dated 2021-02-09 and 1.0.1 dated 2021-02-12

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New package secsse with initial version 2.0.7
Package: secsse
Type: Package
Title: Several Examined and Concealed States-Dependent Speciation and Extinction
Version: 2.0.7
Date: 2021-02-10
License: GPL-3
Authors@R: c( person(given = "Leonel", family = "Herrera Alsina", email = "leonelhalsina@gmail.com", role = "aut"), person(given = "Paul", family = "van Els", email = "paulvanels@gmail.com", role = "aut"), person(given = "Rampal S.", family = "Etienne", email = "r.s.etienne@rug.nl", role = c("cre","aut"), comment = c(ORCID = "0000-0003-2142-7612")))
Description: Simultaneously infers state-dependent diversification across two or more states of a single or multiple traits while accounting for the role of a possible concealed trait. See Herrera-Alsina et al. 2019 Systematic Biology 68: 317-328 <DOI:10.1093/sysbio/syy057>.
Depends: R (>= 3.5.0)
Imports: utils, DDD (>= 4.0), ape, foreach, doParallel, apTreeshape, phylobase, geiger, deSolve
Suggests: diversitree, phytools, testthat, testit, knitr, rmarkdown
Enhances: doMC
NeedsCompilation: yes
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
RoxygenNote: 7.1.1
Packaged: 2021-02-11 16:05:16 UTC; rampa
Author: Leonel Herrera Alsina [aut], Paul van Els [aut], Rampal S. Etienne [cre, aut] (<https://orcid.org/0000-0003-2142-7612>)
Maintainer: Rampal S. Etienne <r.s.etienne@rug.nl>
Repository: CRAN
Date/Publication: 2021-02-12 16:50:09 UTC

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Package RcppSimdJson updated to version 0.1.4 with previous version 0.1.3 dated 2020-11-02

Title: 'Rcpp' Bindings for the 'simdjson' Header-Only Library for 'JSON' Parsing
Description: The 'JSON' format is ubiquitous for data interchange, and the 'simdjson' library written by Daniel Lemire (and many contributors) provides a high-performance parser for these files which by relying on parallel 'SIMD' instruction manages to parse these files as faster than disk speed. See the <arXiv:1902.08318> paper for more details about 'simdjson'. This package parses 'JSON' from string, file, or remote URLs under a variety of settings.
Author: Dirk Eddelbuettel, Brendan Knapp
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RcppSimdJson versions 0.1.3 dated 2020-11-02 and 0.1.4 dated 2021-02-12

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New package norm2 with initial version 2.0.4
Package: norm2
Type: Package
Title: Analysis of Incomplete Multivariate Data under a Normal Model
Version: 2.0.4
Date: 2021-02-11
Author: Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Maintainer: Joseph L. Schafer <Joseph.L.Schafer@census.gov>
Description: Functions for parameter estimation, Bayesian posterior simulation and multiple imputation from incomplete multivariate data under a normal model.
Depends: R (>= 3.1.0)
Imports: stats
License: GPL-3
LazyLoad: yes
NeedsCompilation: yes
Packaged: 2021-02-11 20:22:16 UTC; schaf310
Repository: CRAN
Date/Publication: 2021-02-12 16:50:12 UTC

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New package dlookr with initial version 0.4.2
Package: dlookr
Type: Package
Title: Tools for Data Diagnosis, Exploration, Transformation
Version: 0.4.2
Authors@R: c( person("Choonghyun", "Ryu",, "choonghyun.ryu@gmail.com", role = c("aut", "cre")) )
Description: A collection of tools that support data diagnosis, exploration, and transformation. Data diagnostics provides information and visualization of missing values and outliers and unique and negative values to help you understand the distribution and quality of your data. Data exploration provides information and visualization of the descriptive statistics of univariate variables, normality tests and outliers, correlation of two variables, and relationship between target variable and predictor. Data transformation supports binning for categorizing continuous variables, imputates missing values and outliers, resolving skewness. And it creates automated reports that support these three tasks.
License: GPL-2 | file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.2.0)
Imports: cli, corrplot, dplyr (>= 0.7.6), extrafont, ggplot2 (>= 3.0.0), grid, gridExtra, hrbrthemes, kableExtra, knitr (>= 1.22), magrittr, methods, mice, partykit, prettydoc, purrr, RcmdrMisc, rlang, rmarkdown, tibble, tidyr, tidyselect, utils
Suggests: DBI, classInt, dbplyr, DMwR, forecast, ISLR, nycflights13, randomForest, rpart, RSQLite, stringr
Author: Choonghyun Ryu [aut, cre]
Maintainer: Choonghyun Ryu <choonghyun.ryu@gmail.com>
BugReports: https://github.com/choonghyunryu/dlookr/issues
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-12 06:40:57 UTC; choonghyunryu
Repository: CRAN
Date/Publication: 2021-02-12 16:50:16 UTC

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Package BAwiR updated to version 1.2.5 with previous version 1.2.4 dated 2020-05-11

Title: Analysis of Basketball Data
Description: Collection of tools to work with basketball data. Functions available are related to friendly web scraping and visualization. Data were obtained from <https://www.euroleague.net/>, <https://www.eurocupbasketball.com/> and <http://www.acb.com>, following the instructions of their respectives robots.txt files, when available. Tools for visualization include a population pyramid, 2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, team shooting plots, team four factors plots, cross-tables with the results of regular season games and maps of nationalities. Please see Vinue (2020) <doi:10.1089/big.2018.0124>.
Author: Guillermo Vinue
Maintainer: Guillermo Vinue <Guillermo.Vinue@uv.es>

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More information about BAwiR at CRAN
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Package matrixprofiler (with last version 0.1.1) was removed from CRAN

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

2021-02-11 0.1.1

Permanent link
Package ldsep updated to version 2.0.1 with previous version 1.1.0 dated 2020-11-14

Title: Linkage Disequilibrium Shrinkage Estimation for Polyploids
Description: Estimate haplotypic or composite pairwise linkage disequilibrium (LD) in polyploids, using either genotypes or genotype likelihoods. Support is provided to estimate the popular measures of LD: the LD coefficient D, the standardized LD coefficient D', and the Pearson correlation coefficient r. All estimates are returned with corresponding standard errors. These estimates and standard errors can then be used for shrinkage estimation. The main functions are ldfast(), ldest(), mldest(), sldest(), plot.lddf(), format_lddf(), and ldshrink(). Details of the methods are available in Gerard (2021a) <doi:10.1111/1755-0998.13349> and Gerard (2021b) <doi:10.1101/2021.02.08.430270>.
Author: David Gerard [aut, cre] (<https://orcid.org/0000-0001-9450-5023>)
Maintainer: David Gerard <gerard.1787@gmail.com>

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Package simsl updated to version 0.2.1 with previous version 0.2.0 dated 2021-02-08

Title: Single-Index Models with a Surface-Link
Description: An implementation of a single-index regression for optimizing individualized dose rules from an observational study. To model interaction effects between baseline covariates and a treatment variable defined on a continuum, we employ two-dimensional penalized spline regression on an index-treatment domain, where the index is defined as a linear combination of the covariates (a single-index). An unspecified main effect for the covariates is allowed, which can also be modeled through a parametric model. A unique contribution of this work is in the parsimonious single-index parametrization specifically defined for the interaction effect term. We refer to Park, Petkova, Tarpey, and Ogden (2020) <doi:10.1111/biom.13320> (for the case of a discrete treatment) and Park, Petkova, Tarpey, and Ogden (2021) "A single-index model with a surface-link for optimizing individualized dose rules" <arXiv:2006.00267v2> for detail of the method. The model can take a member of the exponential family as a response variable and can also take an ordinal categorical response. The main function of this package is simsl().
Author: Hyung Park, Eva Petkova, Thaddeus Tarpey, R. Todd Ogden
Maintainer: Hyung Park <parkh15@nyu.edu>

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Package resumer updated to version 0.0.5 with previous version 0.0.4 dated 2021-01-10

Title: Build Resumes with R
Description: Using a CSV, LaTeX and R to easily build attractive resumes.
Author: Jared Lander [aut, cre]
Maintainer: Jared Lander <packages@jaredlander.com>

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Package HEMDAG updated to version 2.7.4 with previous version 2.7.3 dated 2020-09-19

Title: Hierarchical Ensemble Methods for Directed Acyclic Graphs
Description: An implementation of several Hierarchical Ensemble Methods (HEMs) for Directed Acyclic Graphs (DAGs). 'HEMDAG' package: 1) reconciles flat predictions with the topology of the ontology; 2) can enhance the predictions of virtually any flat learning methods by taking into account the hierarchical relationships between ontology classes; 3) provides biologically meaningful predictions that always obey the true-path-rule, the biological and logical rule that governs the internal coherence of biomedical ontologies; 4) is specifically designed for exploiting the hierarchical relationships of DAG-structured taxonomies, such as the Human Phenotype Ontology (HPO) or the Gene Ontology (GO), but can be safely applied to tree-structured taxonomies as well (as FunCat), since trees are DAGs; 5) scales nicely both in terms of the complexity of the taxonomy and in the cardinality of the examples; 6) provides several utility functions to process and analyze graphs; 7) provides several performance metrics to evaluate HEMs algorithms. (Marco Notaro, Max Schubach, Peter N. Robinson and Giorgio Valentini (2017) <doi:10.1186/s12859-017-1854-y>).
Author: Marco Notaro [aut, cre] (<https://orcid.org/0000-0003-4309-2200>), Alessandro Petrini [ctb] (<https://orcid.org/0000-0002-0587-1484>), Giorgio Valentini [aut] (<https://orcid.org/0000-0002-5694-3919>)
Maintainer: Marco Notaro <marco.notaro@unimi.it>

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New package egor with initial version 0.21.02
Package: egor
Type: Package
Title: Import and Analyse Ego-Centered Network Data
Version: 0.21.02
Date: 2021-02-11
Authors@R: c( person("Till", "Krenz", email = "egor@tillt.net", role = c("aut", "cre")), person("Pavel N.", "Krivitsky", email="pavel@statnet.org", role=c("aut")), person("Raffaele", "Vacca", email = "r.vacca@ufl.edu", role = c("aut")), person(given = "Michal", family = "Bojanowski", role = "aut", email = "michal2992@gmail.com", comment = c(ORCID = "0000-0001-7503-852X")), person("Markus", "Gamper", email = "m.gamper@uni-koeln.de", role = c("ctb")), person("Andreas", "Herz", email = "herzand@uni-hildesheim.de", role = c("aut")), person("Christopher", "McCarty", email = "ufchris@ufl.edu", role = c("ctb")))
Description: Tools for importing, analyzing and visualizing ego-centered network data. Supports several data formats, including the export formats of 'EgoNet', 'EgoWeb 2.0' and 'openeddi'. An interactive (shiny) app for the intuitive visualization of ego-centered networks is provided. Also included are procedures for creating and visualizing Clustered Graphs (Lerner 2008 <DOI:10.1109/PACIFICVIS.2008.4475458>).
URL: https://github.com/tilltnet/egor, https://egor.tillt.net/
BugReports: https://github.com/tilltnet/egor/issues
License: AGPL-3
Depends: R (>= 3.5.0), dplyr, tibble
Imports: tidygraph, srvyr, tidyr, methods, utils, purrr, rlang
Suggests: knitr, testthat (>= 2.1.0), rmarkdown, survey, shiny, igraph, network, haven
VignetteBuilder: knitr
RoxygenNote: 7.1.1
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2021-02-11 17:57:14 UTC; till
Author: Till Krenz [aut, cre], Pavel N. Krivitsky [aut], Raffaele Vacca [aut], Michal Bojanowski [aut] (<https://orcid.org/0000-0001-7503-852X>), Markus Gamper [ctb], Andreas Herz [aut], Christopher McCarty [ctb]
Maintainer: Till Krenz <egor@tillt.net>
Repository: CRAN
Date/Publication: 2021-02-12 14:20:02 UTC

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New package ech with initial version 0.1.1.2
Package: ech
Title: Toolbox for ECH with R
Version: 0.1.1.2
Authors@R: c(person(given = "Gabriela", family = "Mathieu", role = c("aut", "cre"), email = "calcita@gmx.li", comment = c(ORCID = "0000-0003-3965-9024")), person(given = "Richard", family = "Detomasi", role = "aut", email = "richard.detomasi@gmail.com", comment = c(ORCID = "0000-0002-6725-0261")), person(given = "Tati", family = "Micheletti", role = "ctb", email = "tati.micheletti@gmail.com", comment = c(ORCID = "0000-0003-4838-8342")), person(family = "Instituto Nacional de Estadistica, Uruguay (INE)", role = "dtc"))
Maintainer: Gabriela Mathieu <calcita@gmx.li>
Description: R toolbox for the processing of the Encuesta Continua de Hogares (ECH) from Uruguay at <http://www.ine.gub.uy/encuesta-continua-de-hogares1> conducted by the Instituto Nacional de Estadistica (INE).
License: GPL-3
Depends: R (>= 3.5.0)
Imports: assertthat, curl, dplyr (>= 1.0.0), fs, geouy (>= 0.2.3), glue, haven (>= 2.3.0), janitor, labelled, laeken, purrr, readxl, rlang, srvyr (>= 0.4.0), statar, stringr, survey (>= 1.2.0), tidyr, utils
Suggests: knitr, rmarkdown, testthat (>= 2.1.0)
VignetteBuilder: knitr
ByteCompile: true
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
SystemRequirements: 'unrar' (Linux/macOS) or '7-Zip' (Windows) to work with '.rar' files, GDAL (>= 3.0.2), GEOS (>= 3.8.0), PROJ (>= 6.2.1)
NeedsCompilation: no
Packaged: 2021-01-27 17:16:52 UTC; calcita
Author: Gabriela Mathieu [aut, cre] (<https://orcid.org/0000-0003-3965-9024>), Richard Detomasi [aut] (<https://orcid.org/0000-0002-6725-0261>), Tati Micheletti [ctb] (<https://orcid.org/0000-0003-4838-8342>), Instituto Nacional de Estadistica, Uruguay (INE) [dtc]
Repository: CRAN
Date/Publication: 2021-02-12 14:30:02 UTC

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Package fastrmodels updated to version 1.0.1 with previous version 1.0.0 dated 2021-02-11

Title: Models for the 'nflfastR' Package
Description: A data package that hosts all models for the 'nflfastR' package.
Author: Sebastian Carl [cre, aut], Ben Baldwin [aut]
Maintainer: Sebastian Carl <mrcaseb@gmail.com>

Diff between fastrmodels versions 1.0.0 dated 2021-02-11 and 1.0.1 dated 2021-02-12

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Package UComp updated to version 2.1.2 with previous version 2.1.1 dated 2021-02-02

Title: Automatic Unobserved Components Models
Description: Comprehensive analysis and forecasting of univariate time series using automatic unobserved components models and algorithms. Harvey, AC (1989) <doi:10.1017/CBO9781107049994>. Pedregal, DJ and Young PC (2002) <doi:10.1002/9780470996430>. Durbin J and Koopman SJ (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>.
Author: Diego J. Pedregal [aut, cre] (<https://orcid.org/0000-0003-4958-0969>)
Maintainer: Diego J. Pedregal <Diego.Pedregal@uclm.es>

Diff between UComp versions 2.1.1 dated 2021-02-02 and 2.1.2 dated 2021-02-12

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Package baRulho (with last version 1.0.3) was removed from CRAN

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

2021-02-11 1.0.3

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Package pubh (with last version 1.1.19) was removed from CRAN

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

2020-12-03 1.1.19
2020-11-10 1.1.18
2020-07-07 1.1.16

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Package Rraven (with last version 1.0.11) was removed from CRAN

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

2021-01-28 1.0.11

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Package warbleR (with last version 1.1.25) was removed from CRAN

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

2021-01-27 1.1.25

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Package pharmaRTF (with last version 0.1.1) was removed from CRAN

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

2020-06-17 0.1.1
2020-05-25 0.1.0

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New package visStatistics with initial version 0.1.1
Package: visStatistics
Type: Package
Title: Automated Visualization of Statistical Tests
Version: 0.1.1
Authors@R: c( person("Sabine", "Schilling", email = "sabineschilling@gmx.ch", role = c("cre","aut","cph")), person("Peter", "Kauf", email = "peter.kauf@zhaw.ch", role = "ctb"))
Maintainer: Sabine Schilling <sabineschilling@gmx.ch>
Description: Visualization of the most powerful statistical hypothesis test. The function vistat() visualizes the statistical hypothesis testing between the dependent variable (response) varsample and the independent variable (feature) varfactor. The statistical hypothesis test (including the eventual corresponding post-hoc analysis) with the highest statistical power fulfilling the assumptions of the corresponding test is chosen based on a decision tree. A graph displaying the raw data accordingly to the chosen test is generated, the test statistics including eventual post-hoc-analysis are returned. The automated workflow is especially suited for browser based interfaces to server-based deployments of R. Implemented tests: lm(), t.test(), wilcox.test(), aov(), kruskal.test(), fisher.test(), chisqu.test(). Implemented tests to check the normal distribution of standardized residuals: shapiro.test() and ad.test(). Implemented post-hoc tests: TukeyHSD() for aov() and pairwise.wilcox.test() for kruskal.test(). For the comparison of averages, the following algorithm is implemented: If the p-values of the standardized residuals of both shapiro.test() or ad.test() are smaller than 1-conf.level, kruskal.test() resp. wilcox.test() are performed, otherwise the oneway.test() and aov() resp. t.test() are performed and displayed. Exception: If the sample size is bigger than 100, t.test() is always performed and wilcox.test() is never executed (Lumley et al. (2002) <doi:10.1146/annurev.publhealth.23.100901.140546>). For the test of independence of count data, Cochran's rule (Cochran (1954) <doi:10.2307/3001666>) is implemented: If more than 20 percent of all cells have a count smaller than 5, fisher.test() is performed and displayed, otherwise chisqu.test(). In both cases case an additional mosaic plot is generated.
Imports: vcd, Cairo, graphics, grDevices, grid, multcompView, stats, utils, nortest
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-10 18:52:39 UTC; sschilli
Author: Sabine Schilling [cre, aut, cph], Peter Kauf [ctb]
Repository: CRAN
Date/Publication: 2021-02-12 11:10:02 UTC

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New package wiad with initial version 0.0.1.0
Package: wiad
Type: Package
Title: Wood Image Analysis and Dataset
Version: 0.0.1.0
Date: 2021-02-10
Authors@R: c(person("Bijan", "Seyednasrollah", role = c("aut", "cre","cph"), email = "bijan.s.nasr@gmail.com"), person("Tim", "Rademacher", role = c("aut", "cph", "wdc"), email = "rademacher.tim@gmail.com"), person("David", "Basler", role = c("aut", "cph", "wdc"), email = "david.j.basler@gmail.com"))
Description: Providing a user-friendly interface to digitize wood imagery such as tree ring scans. The package offers a web-based application that the user can run locally from their computers to analyze wood characteristics.
Encoding: UTF-8
LazyData: true
License: AGPL-3
RoxygenNote: 7.1.0
Imports: abind, data.table, shiny, dplyr, DT
Suggests: dplR, imager, jsonlite, jpeg, png, plotly, shinyFiles, shinyjs, shinythemes, raster, rgdal, readr, readxl, sp, testthat, tiff, tibble, tools, zoo
NeedsCompilation: no
Packaged: 2021-02-10 16:24:03 UTC; bijan
Author: Bijan Seyednasrollah [aut, cre, cph], Tim Rademacher [aut, cph, wdc], David Basler [aut, cph, wdc]
Maintainer: Bijan Seyednasrollah <bijan.s.nasr@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-12 10:30:02 UTC

More information about wiad at CRAN
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Package Mercator updated to version 1.0.0 with previous version 0.99.0 dated 2021-01-10

Title: Clustering and Visualizing Distance Matrices
Description: Defines the classes used to explore, cluster and visualize distance matrices, especially those arising from binary data. See Abrams et al., 2021, <doi:10.1093/bioinformatics/btab037>.
Author: Kevin R. Coombes, Caitlin E. Coombes
Maintainer: Kevin R. Coombes <krc@silicovore.com>

Diff between Mercator versions 0.99.0 dated 2021-01-10 and 1.0.0 dated 2021-02-12

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Package MASS updated to version 7.3-53.1 with previous version 7.3-53 dated 2020-09-09

Title: Support Functions and Datasets for Venables and Ripley's MASS
Description: Functions and datasets to support Venables and Ripley, "Modern Applied Statistics with S" (4th edition, 2002).
Author: Brian Ripley [aut, cre, cph], Bill Venables [ctb], Douglas M. Bates [ctb], Kurt Hornik [trl] (partial port ca 1998), Albrecht Gebhardt [trl] (partial port ca 1998), David Firth [ctb]
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>

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New package lookout with initial version 0.1.0
Package: lookout
Type: Package
Title: Leave One Out Kernel Density Estimates for Outlier Detection
Version: 0.1.0
Authors@R: c( person("Sevvandi", "Kandanaarachchi", email = "sevvandik@gmail.com", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-0337-0395")), person("Rob", "Hyndman", email = "rob.hyndman@monash.edu", role = c("aut"), comment = c(ORCID = "0000-0002-2140-5352")) )
Maintainer: Sevvandi Kandanaarachchi <sevvandik@gmail.com>
Description: Outlier detection using leave-one-out kernel density estimates and extreme value theory. The bandwidth for kernel density estimates is computed using persistent homology, a technique in topological data analysis. Using peak-over-threshold method, a generalized Pareto distribution is fitted to the log of leave-one-out kde values to identify outliers.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Imports: TDAstats, evd, RANN, ggplot2, tidyr
Suggests: knitr, rmarkdown
URL: https://sevvandi.github.io/lookout/
NeedsCompilation: no
Packaged: 2021-02-10 04:10:14 UTC; Sevvandi
Author: Sevvandi Kandanaarachchi [aut, cre] (<https://orcid.org/0000-0002-0337-0395>), Rob Hyndman [aut] (<https://orcid.org/0000-0002-2140-5352>)
Repository: CRAN
Date/Publication: 2021-02-12 10:20:02 UTC

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Package highSCREEN updated to version 0.4 with previous version 0.3 dated 2018-08-22

Title: High-Throughput Screening for Plate Based Essays
Description: Can be used to carry out extraction, normalization, quality control (QC), candidate hits identification and visualization for plate based assays, in drug discovery. The package methods were applied in H. W. Choi et al. "Identification of Novel Mast Cell Activators Using Cell-Based High-Throughput Screening", SLAS Discovery 24(6), 2019. This project was funded by the Division of Allergy, Immunology, and Transplantation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services, under contract No. HHSN272201400054C entitled "Adjuvant Discovery For Vaccines Against West Nile Virus and Influenza", awarded to Duke University and lead by Drs. Herman Staats and Soman Abraham.
Author: Ivo D. Shterev [aut, cre], Cliburn Chan [aut], Gregory D. Sempowski [aut]
Maintainer: Ivo D. Shterev <i.shterev@gmail.com>

Diff between highSCREEN versions 0.3 dated 2018-08-22 and 0.4 dated 2021-02-12

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New package ggprism with initial version 1.0.1
Package: ggprism
Title: A 'ggplot2' Extension Inspired by 'GraphPad Prism'
Version: 1.0.1
Authors@R: person(given = "Charlotte", family = "Dawson", role = c("aut", "cre"), email = "csdaw@outlook.com", comment = c(ORCID = "0000-0002-7151-5971"))
Description: Provides various themes, palettes, and other functions that are used to customise ggplots to look like they were made in 'GraphPad Prism'. The 'Prism'-look is achieved with theme_prism() and scale_fill|colour_prism(), axes can be changed with custom guides like guide_prism_minor(), and significance indicators added with add_pvalue().
License: GPL (>= 3.0)
URL: https://csdaw.github.io/ggprism/, https://github.com/csdaw/ggprism
BugReports: https://github.com/csdaw/ggprism/issues
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.2)
Imports: digest, ggplot2 (>= 3.2.0), glue, grid, gtable (>= 0.1.1), rlang (>= 0.3.0), scales (>= 0.5.0), stats, tibble, utils
Suggests: covr, dplyr, ggbeeswarm, ggnewscale, knitr, magrittr, patchwork, rmarkdown, rstatix, tidyr, tinytest
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-10 15:35:59 UTC; csd51
Author: Charlotte Dawson [aut, cre] (<https://orcid.org/0000-0002-7151-5971>)
Maintainer: Charlotte Dawson <csdaw@outlook.com>
Repository: CRAN
Date/Publication: 2021-02-12 10:30:05 UTC

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Package gapfill updated to version 0.9.6-1 with previous version 0.9.6 dated 2018-04-06

Title: Fill Missing Values in Satellite Data
Description: Tools to fill missing values in satellite data and to develop new gap-fill algorithms. The methods are tailored to data (images) observed at equally-spaced points in time. The package is illustrated with MODIS NDVI data.
Author: Florian Gerber [aut, cre] (<https://orcid.org/0000-0001-8545-5263>)
Maintainer: Florian Gerber <flora.fauna.gerber@gmail.com>

Diff between gapfill versions 0.9.6 dated 2018-04-06 and 0.9.6-1 dated 2021-02-12

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New package folio with initial version 1.0.0
Package: folio
Title: Datasets for Teaching Archaeology and Paleontology
Version: 1.0.0
Authors@R: person(given = "Nicolas", family = "Frerebeau", role = c("aut", "cre"), email = "nicolas.frerebeau@u-bordeaux-montaigne.fr", comment = c(ORCID = "0000-0001-5759-4944"))
Maintainer: Nicolas Frerebeau <nicolas.frerebeau@u-bordeaux-montaigne.fr>
Description: Datasets for teaching quantitative approaches and modeling in archaeology and paleontology. This package provides several types of data related to broad topics (cultural evolution, radiocarbon dating, paleoenvironments, etc.), which can be used to illustrate statistical methods in the classroom (multivariate data analysis, compositional data analysis, diversity measurement, etc.).
License: GPL (>= 3)
URL: https://folio.tesselle.org, https://github.com/tesselle/folio
BugReports: https://github.com/tesselle/folio/issues
Depends: R (>= 2.10)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-10 09:51:39 UTC; nicolas
Author: Nicolas Frerebeau [aut, cre] (<https://orcid.org/0000-0001-5759-4944>)
Repository: CRAN
Date/Publication: 2021-02-12 10:30:09 UTC

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New package CoOL with initial version 1.0
Package: CoOL
Type: Package
Title: Causes of Outcome Learning
Version: 1.0
Date: 2021-02-05
Authors@R: c( person("Andreas", "Rieckmann", role = c("aut","cre"), email = "aric@sund.ku.dk"), person("Piotr", "Dworzynski", role = "aut", email = "piotr@sund.ku.dk"), person("Leila", "Arras", role = "ctb", email = "leila.arras@hhi.fraunhofer.de"), person(c("Claus","Thorn"), "Ekstrom", role = "aut", email = "ekstrom@sund.ku.dk"))
Maintainer: Andreas Rieckmann <aric@sund.ku.dk>
Description: Implementing the computational phase of the Causes of Outcome Learning approach as described in Rieckmann, Dworzynski, Arras, Lapuschkin, Samek, Arah, Rod, Ekstrom. Causes of outcome learning: A causal inference-inspired machine learning approach to disentangling common combinations of potential causes of a health outcome. medRxiv (2020) <doi:10.1101/2020.12.10.20225243>. The optional 'ggtree' package can be obtained through Bioconductor.
URL: https://bioconductor.org
License: GPL-2
Imports: Rcpp, data.table, pROC, graphics, mltools, stats, plyr, ggplot2, ClustGeo, wesanderson
Suggests: ggtree, imager
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: yes
Packaged: 2021-02-10 14:27:27 UTC; lvb917
Author: Andreas Rieckmann [aut, cre], Piotr Dworzynski [aut], Leila Arras [ctb], Claus Thorn Ekstrom [aut]
Repository: CRAN
Date/Publication: 2021-02-12 10:10:12 UTC

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Package comf updated to version 0.1.10 with previous version 0.1.9 dated 2019-04-08

Title: Models and Equations for Human Comfort Research
Description: Calculation of various common and less common comfort indices such as predicted mean vote or the two node model. Converts physical variables such as relative to absolute humidity and evaluates the performance of comfort indices.
Author: Marcel Schweiker [aut, cre] (<https://orcid.org/0000-0003-3906-4688>), Sophia Mueller [aut], Michael Kleber [ctr], Boris Kingma [ctr] (<https://orcid.org/0000-0001-5961-0215>), Masanori Shukuya [ctr] (<https://orcid.org/0000-0003-2777-4375>), Shaomi Rahman [ctr], Shoaib Sarwar [ctr]
Maintainer: Marcel Schweiker <mschweiker@ukaachen.de>

Diff between comf versions 0.1.9 dated 2019-04-08 and 0.1.10 dated 2021-02-12

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Package vote updated to version 2.2-0 with previous version 2.1-0 dated 2021-01-06

Title: Election Vote Counting
Description: Counting election votes and determining election results by different methods, including the single transferable vote or ranked choice, approval, score, plurality, condorcet and two-round runoff methods (Raftery et al. (2021) <arXiv:2102.05801>).
Author: Hana Sevcikova, Bernard Silverman, Adrian Raftery
Maintainer: Hana Sevcikova<hanas@uw.edu>

Diff between vote versions 2.1-0 dated 2021-01-06 and 2.2-0 dated 2021-02-12

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New package VBsparsePCA with initial version 0.1.0
Package: VBsparsePCA
Type: Package
Title: The Variational Bayesian Method for Sparse PCA
Version: 0.1.0
Author: Bo (Yu-Chien) Ning
Maintainer: Bo (Yu-Chien) Ning <bo.ning@upmc.fr>
Description: Contains functions for a variational Bayesian method for sparse PCA proposed by Ning (2020) <arXiv:2102.00305>. There are two algorithms: the PX-CAVI algorithm (if assuming the loadings matrix is jointly row-sparse) and the batch PX-CAVI algorithm (if without this assumption). The outputs of the main function, VBsparsePCA(), include the mean and covariance of the loadings matrix, the score functions, the variable selection results, and the estimated variance of the random noise.
Depends: R (>= 3.6.0)
License: GPL-3
Imports: MASS, pracma, stats, utils
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-08 22:40:14 UTC; poning
Repository: CRAN
Date/Publication: 2021-02-12 09:50:16 UTC

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New package shutterplot with initial version 0.1.0
Package: shutterplot
Date: 2021-02-04
Type: Package
Title: The R Shutter Plot Package
Version: 0.1.0
Author: Siddhanta Phuyal <siddhantaphuyal7159@gmail.com> Jyotirmoy Sarkar <jsarkar@iupui.edu> Mamunur Rashid <mrashid@depauw.edu>
Maintainer: Siddhanta Phuyal <siddhantaphuyal7159@gmail.com>
Description: Shows the scatter plot along with the fitted regression lines. It depicts min, max, the three quartiles, mean, and sd for each variable. It also depicts sd-line, sd-box, r, r-square, prediction boundaries, and regression outliers.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
Depends: R (>= 3.1.0)
NeedsCompilation: no
Packaged: 2021-02-09 16:34:57 UTC; user
Repository: CRAN
Date/Publication: 2021-02-12 09:50:06 UTC

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Package phateR updated to version 1.0.7 with previous version 1.0.4 dated 2020-05-22

Title: PHATE - Potential of Heat-Diffusion for Affinity-Based Transition Embedding
Description: PHATE is a tool for visualizing high dimensional single-cell data with natural progressions or trajectories. PHATE uses a novel conceptual framework for learning and visualizing the manifold inherent to biological systems in which smooth transitions mark the progressions of cells from one state to another. To see how PHATE can be applied to single-cell RNA-seq datasets from hematopoietic stem cells, human embryonic stem cells, and bone marrow samples, check out our publication in Nature Biotechnology at <doi:10.1038/s41587-019-0336-3>.
Author: Krishnan Srinivasan [aut], Scott Gigante [cre] (<https://orcid.org/0000-0002-4544-2764>)
Maintainer: Scott Gigante <scott.gigante@yale.edu>

Diff between phateR versions 1.0.4 dated 2020-05-22 and 1.0.7 dated 2021-02-12

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New package pagoo with initial version 0.3.8
Package: pagoo
Version: 0.3.8
Title: Analyze Bacterial Pangenomes in R with 'Pagoo'
Description: Provides an encapsulated, object-oriented class system for analyzing bacterial pangenomes. For a definition of this concept, see Tettelin, et al. (2005) <doi:10.1073/pnas.0506758102>. It uses the R6 package as backend. It was designed in order to facilitate and speed-up the comparative analysis of multiple bacterial genomes, standardizing and optimizing routine tasks performed everyday. There are a handful of things done everyday when working with bacterial pangenomes: subset, summarize, extract, visualize and store data. So, 'pagoo' is intended to facilitate these tasks as much as possible. For a description of the implemented data structure and methods, see Ferres & Iraola (2020), <doi:10.1101/2020.07.29.226951>.
Authors@R: c( person("Ignacio", "Ferres", , "iferres@pasteur.edu.uy", role = c("aut", "cre"), comment = c(ORCID = "0000-0003-0910-6568") ), person("Gregorio", "Iraola", , "iferres@pasteur.edu.uy", role = c("aut"), comment = c(ORCID = "0000-0002-6516-3404") ), person("Institut Pasteur de Montevideo", role = c("fnd") ) )
Maintainer: Ignacio Ferres <iferres@pasteur.edu.uy>
URL: https://iferres.github.io/pagoo/, https://github.com/iferres/pagoo
BugReports: https://github.com/iferres/pagoo/issues
Depends: R (>= 3.5.0), S4Vectors, Biostrings, ggplot2
biocViews:
Imports: R6, reshape2, vegan, GenomicRanges, BiocGenerics, shinyWidgets, shinydashboard, DT, plotly, magrittr, heatmaply, dendextend, ggfortify, shiny
Suggests: micropan, patchwork, ape, phangorn, pegas, DECIPHER, rhierbaps, knitr, rmarkdown, testthat, covr
License: GPL-3
Encoding: UTF-8
LazyData: true
ByteCompile: true
RoxygenNote: 7.1.1
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2021-02-09 17:54:38 UTC; iferres
Author: Ignacio Ferres [aut, cre] (<https://orcid.org/0000-0003-0910-6568>), Gregorio Iraola [aut] (<https://orcid.org/0000-0002-6516-3404>), Institut Pasteur de Montevideo [fnd]
Repository: CRAN
Date/Publication: 2021-02-12 09:50:08 UTC

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New package httpproblems with initial version 1.0.0
Package: httpproblems
Title: Report Errors in Web Applications with 'Problem Details' (RFC 7807)
Version: 1.0.0
Authors@R: c(person(given = "Aaron", family = "Jacobs", role = c("aut", "cre"), email = "atheriel@gmail.com"))
Description: Tools for emitting the 'Problem Details' structure defined in 'RFC' 7807 <https://tools.ietf.org/html/rfc7807> for reporting errors from 'HTTP' servers in a standard way.
License: Apache License (>= 2)
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-09 20:43:44 UTC; aaronj
Author: Aaron Jacobs [aut, cre]
Maintainer: Aaron Jacobs <atheriel@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-12 10:00:06 UTC

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New package enerscape with initial version 0.1.0
Package: enerscape
Type: Package
Title: Compute Energy Landscapes
Version: 0.1.0
Author: Emilio Berti
Maintainer: Emilio Berti <emilio.berti@idiv.de>
Description: Compute energy landscapes using a digital elevation model (DEM) raster and body mass (kg) of animals.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: raster, gdistance, rgdal, sp, Matrix
Suggests: knitr, rmarkdown
RoxygenNote: 7.1.1
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2021-02-09 15:38:40 UTC; eb97ziwi
Repository: CRAN
Date/Publication: 2021-02-12 09:40:02 UTC

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New package cfda with initial version 0.9.9
Package: cfda
Type: Package
Title: Categorical Functional Data Analysis
Version: 0.9.9
Date: 2021-02-05
Authors@R: c(person("Cristian", "Preda", role = "aut", email = "cristian.preda@inria.fr"), person("Quentin", "Grimonprez", role = c("aut", "cre"), email = "quentingrim@yahoo.fr"), person("Vincent", "Vandewalle", role = "ctb", email = "vincent.vandewalle@inria.fr"))
Copyright: Inria - Université de Lille
Description: Package for the analysis of categorical functional data. The main purpose is to compute an encoding (real functional variable) for each state <https://hal.inria.fr/hal-02973094>. It also provides functions to perform basic statistical analysis on categorical functional data.
BugReports: https://github.com/modal-inria/cfda/issues
License: AGPL-3
Imports: msm, diagram, ggplot2, mgcv, parallel, pbapply
Depends: fda, R (>= 3.5.0)
Suggests: testthat, covr, knitr, rmarkdown
Encoding: UTF-8
VignetteBuilder: knitr
RoxygenNote: 7.1.1
NeedsCompilation: no
Packaged: 2021-02-10 13:11:28 UTC; quentin
Author: Cristian Preda [aut], Quentin Grimonprez [aut, cre], Vincent Vandewalle [ctb]
Maintainer: Quentin Grimonprez <quentingrim@yahoo.fr>
Repository: CRAN
Date/Publication: 2021-02-12 10:00:09 UTC

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New package box with initial version 1.0.0
Package: box
Title: Write Reusable, Composable and Modular R Code
Version: 1.0.0
Authors@R: c( person( 'Konrad', 'Rudolph', email = 'konrad.rudolph@gmail.com', role = c('aut', 'cre'), comment = c(ORCID = '0000-0002-9866-7051') ), person( 'Michael', 'Schubert', email = 'mschu.dev@gmail.com', role = 'ctb', comment = c(ORCID = '0000-0002-6862-5221') ) )
URL: https://klmr.me/box/, https://github.com/klmr/box
BugReports: https://github.com/klmr/box/issues
Description: A modern module system for R. Organise code into hierarchical, composable, reusable modules, and use it effortlessly across projects via a flexible, declarative dependency loading syntax.
Depends: R (>= 3.5.0)
Imports: tools
License: MIT + file LICENSE
LazyData: true
Encoding: UTF-8
Suggests: devtools, knitr, rmarkdown, R6, rlang, roxygen2 (>= 7.0.2), shiny, testthat (>= 2.0.0)
VignetteBuilder: knitr
RoxygenNote: 7.1.0
NeedsCompilation: yes
Packaged: 2021-02-08 18:52:24 UTC; konrad
Author: Konrad Rudolph [aut, cre] (<https://orcid.org/0000-0002-9866-7051>), Michael Schubert [ctb] (<https://orcid.org/0000-0002-6862-5221>)
Maintainer: Konrad Rudolph <konrad.rudolph@gmail.com>
Repository: CRAN
Date/Publication: 2021-02-12 09:30:03 UTC

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Package bnpsd updated to version 1.2.3 with previous version 1.2.1 dated 2020-01-10

Title: Simulate Genotypes from the BN-PSD Admixture Model
Description: The Pritchard-Stephens-Donnelly (PSD) admixture model has k intermediate subpopulations from which n individuals draw their alleles dictated by their individual-specific admixture proportions. The BN-PSD model additionally imposes the Balding-Nichols (BN) allele frequency model to the intermediate populations, which therefore evolved independently from a common ancestral population T with subpopulation-specific FST (Wright's fixation index) parameters. The BN-PSD model can be used to yield complex population structures. Method described in Ochoa and Storey (2021) <doi:10.1371/journal.pgen.1009241>.
Author: Alejandro Ochoa [aut, cre] (<https://orcid.org/0000-0003-4928-3403>), John D. Storey [aut] (<https://orcid.org/0000-0001-5992-402X>)
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>

Diff between bnpsd versions 1.2.1 dated 2020-01-10 and 1.2.3 dated 2021-02-12

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Package klassR (with last version 0.1.3) was removed from CRAN

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

2020-10-30 0.1.3
2019-10-09 0.1.2

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Package huxtable (with last version 5.1.1) was removed from CRAN

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

2020-10-27 5.1.1
2020-09-18 5.1.0
2020-06-15 5.0.0

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Package correlation updated to version 0.6.0 with previous version 0.5.0 dated 2020-12-02

Title: Methods for Correlation Analysis
Description: Lightweight package for computing different kinds of correlations, such as partial correlations, Bayesian correlations, multilevel correlations, polychoric correlations, biweight correlations, distance correlations and more. Part of the 'easystats' ecosystem.
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>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>, @patilindrajeets)
Maintainer: Dominique Makowski <dom.makowski@gmail.com>

Diff between correlation versions 0.5.0 dated 2020-12-02 and 0.6.0 dated 2021-02-12

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Package boot updated to version 1.3-27 with previous version 1.3-26 dated 2021-01-25

Title: Bootstrap Functions (Originally by Angelo Canty for S)
Description: Functions and datasets for bootstrapping from the book "Bootstrap Methods and Their Application" by A. C. Davison and D. V. Hinkley (1997, CUP), originally written by Angelo Canty for S.
Author: Angelo Canty [aut], Brian Ripley [aut, trl, cre] (author of parallel support)
Maintainer: Brian Ripley <ripley@stats.ox.ac.uk>

Diff between boot versions 1.3-26 dated 2021-01-25 and 1.3-27 dated 2021-02-12

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Package stormwindmodel (with last version 0.1.4) was removed from CRAN

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

2020-07-27 0.1.4
2020-04-01 0.1.3

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Package partitions updated to version 1.10-1 with previous version 1.9-22 dated 2019-10-21

Title: Additive Partitions of Integers
Description: Additive partitions of integers. Enumerates the partitions, unequal partitions, and restricted partitions of an integer; the three corresponding partition functions are also given. Set partitions and now compositions are included.
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>), Paul Egeler [ctb] (<https://orcid.org/0000-0001-6948-9498>)
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

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Package OCA updated to version 0.4 with previous version 0.3 dated 2021-01-27

Title: Optimal Capital Allocations
Description: Computes optimal capital allocations based on some standard principles such as Haircut, Overbeck type II and the Covariance Allocation Principle. It also provides some shortcuts for obtaining the Value at Risk and the Expectation Shortfall, using both the normal and the t-student distribution, see Urbina and Guillén (2014)<doi:10.1016/j.eswa.2014.05.017> and Urbina (2013)<http://hdl.handle.net/2099.1/19443>.
Author: Jilber Urbina
Maintainer: Jilber Urbina <jurbina@cipadla.com>

Diff between OCA versions 0.3 dated 2021-01-27 and 0.4 dated 2021-02-12

 OCA-0.3/OCA/man/OCA-package.Rd |only
 OCA-0.4/OCA/DESCRIPTION        |    9 +-
 OCA-0.4/OCA/MD5                |   29 ++++----
 OCA-0.4/OCA/NAMESPACE          |   16 ++++
 OCA-0.4/OCA/R/ES.R             |  126 +++++++++++++++++++++++++++++--------
 OCA-0.4/OCA/R/Overbeck2.R      |   75 +++++++++++++++++++---
 OCA-0.4/OCA/R/Risk.R           |   70 +++++++++++++++++---
 OCA-0.4/OCA/R/VaR.R            |   74 ++++++++++++++++++---
 OCA-0.4/OCA/R/cap.R            |   46 +++++++++++++
 OCA-0.4/OCA/R/hap.R            |   76 +++++++++++++++++++---
 OCA-0.4/OCA/man/ES.Rd          |  138 ++++++++++++++++-------------------------
 OCA-0.4/OCA/man/Overbeck2.Rd   |   99 +++++++++++++----------------
 OCA-0.4/OCA/man/Risk.Rd        |  116 ++++++++++++++--------------------
 OCA-0.4/OCA/man/VaR.Rd         |  101 +++++++++++++-----------------
 OCA-0.4/OCA/man/cap.Rd         |   75 ++++++++--------------
 OCA-0.4/OCA/man/hap.Rd         |   93 +++++++++++----------------
 16 files changed, 697 insertions(+), 446 deletions(-)

More information about OCA at CRAN
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