Mon, 20 Jun 2022

Package RFclust updated to version 0.1.2 with previous version 0.1.1 dated 2021-06-02

Title: Random Forest Cluster Analysis
Description: Tools to perform random forest consensus clustering of different data types. The package is designed to accept a list of matrices from different assays, typically from high-throughput molecular profiling so that class discovery may be jointly performed. For references, please see Tao Shi & Steve Horvath (2006) <doi:10.1198/106186006X94072> & Monti et al (2003) <doi:10.1023/A:1023949509487> .
Author: Ankur Chakravarthy, PhD
Maintainer: Ankur Chakravarthy <ankur.chakravarthy.10@ucl.ac.uk>

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Package rangeBuilder updated to version 1.6 with previous version 1.5 dated 2019-12-10

Title: Occurrence Filtering, Geographic and Taxonomic Standardization and Generation of Species Range Polygons
Description: Provides tools for filtering occurrence records, generating alpha-hull-derived range polygons and mapping species distributions.
Author: Pascal Title [aut, cre]
Maintainer: Pascal Title <ptitle@umich.edu>

Diff between rangeBuilder versions 1.5 dated 2019-12-10 and 1.6 dated 2022-06-20

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Package BiasCorrector updated to version 0.2.2 with previous version 0.2.1 dated 2022-02-16

Title: A GUI to Correct Measurement Bias in DNA Methylation Analyses
Description: A GUI to correct measurement bias in DNA methylation analyses. The 'BiasCorrector' package just wraps the functions implemented in the 'R' package 'rBiasCorrection' into a shiny web application in order to make them more easily accessible. Publication: Kapsner et al. (2021) <doi:10.1002/ijc.33681>.
Author: Lorenz A. Kapsner [cre, aut, cph] , Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package SpatialML updated to version 0.1.4 with previous version 0.1.3 dated 2019-05-09

Title: Spatial Machine Learning
Description: Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Allows for a geographically weighted random forest regression including a function to find the optical bandwidth.
Author: Stamatis Kalogirou [aut, cre], Stefanos Georganos [aut, ctb]
Maintainer: Stamatis Kalogirou <stamatis@lctools.science>

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Package mvpd updated to version 0.0.3 with previous version 0.0.2 dated 2022-03-30

Title: Multivariate Product Distributions for Elliptically Contoured Distributions
Description: Estimates multivariate subgaussian stable densities and probabilities as well as generates random variates using product distribution theory. A function for estimating the parameters from data to fit a distribution to data is also provided, using the method from Nolan (2013) <DOI:10.1007/s00180-013-0396-7>.
Author: Bruce Swihart [aut, cre]
Maintainer: Bruce Swihart <bruce.swihart@gmail.com>

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Package ucie updated to version 1.0.2 with previous version 1.0.1 dated 2022-03-01

Title: Mapping 3D Data into CIELab Color Space
Description: Returns a data frame with the names of the input data points and hex colors (or CIELab coordinates). Data can be mapped to colors for use in data visualization. It optimally maps data points into a polygon that represents the CIELab colour space. Since Euclidean distance approximates relative perceptual differences in CIELab color space, the result is a color encoding that aims to capture much of the structure of the original data.
Author: Mikaela Koutrouli [aut, cre], Lars Juhl Jensen [aut]
Maintainer: Mikaela Koutrouli <mikaela.koutrouli@cpr.ku.dk>

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Package deepgp updated to version 1.0.1 with previous version 1.0.0 dated 2022-04-08

Title: Deep Gaussian Processes using MCMC
Description: Performs posterior inference for deep Gaussian processes following Sauer, Gramacy, and Higdon (2020) <arXiv:2012.08015>. Models are trained through MCMC including elliptical slice sampling of latent Gaussian layers and Metropolis-Hastings sampling of kernel hyperparameters. Vecchia-approximation for faster computation is implemented following Sauer, Cooper, and Gramacy (2022) <arXiv:2204.02904>. Downstream tasks include sequential design through active learning Cohn/integrated mean squared error (ALC/IMSE; Sauer, Gramacy, and Higdon, 2020) and optimization through expected improvement (EI; Gramacy, Sauer, and Wycoff, 2021 <arXiv:2112.07457>). Models extend up to three layers deep; a one layer model is equivalent to typical Gaussian process regression. Covariance kernel options are matern (default) and squared exponential. Applicable to both noisy and deterministic functions. Incorporates SNOW parallelization and utilizes C and C++ under the hood.
Author: Annie Sauer <anniees@vt.edu>
Maintainer: Annie Sauer <anniees@vt.edu>

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Package vrtest (with last version 0.97) was removed from CRAN

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

2014-08-10 0.97
2014-04-22 0.96
2010-11-03 0.95
2009-06-24 0.94
2009-05-08 0.93
2009-04-14 0.91
2008-08-06 0.90
2008-04-20 0.86
2008-02-24 0.8
2007-06-16 0.7

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Package wahc (with last version 1.0) was removed from CRAN

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

2015-02-23 1.0

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Package rBiasCorrection updated to version 0.3.4 with previous version 0.3.3 dated 2022-02-16

Title: Correct Bias in DNA Methylation Analyses
Description: Implementation of the algorithms (with minor modifications) to correct bias in quantitative DNA methylation analyses as described by Moskalev et al. (2011) <doi:10.1093/nar/gkr213>. Publication: Kapsner et al. (2021) <doi:10.1002/ijc.33681>.
Author: Lorenz A. Kapsner [cre, aut, cph] , Evgeny A. Moskalev [aut]
Maintainer: Lorenz A. Kapsner <lorenz.kapsner@gmail.com>

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Package raveio updated to version 0.0.7 with previous version 0.0.6 dated 2022-05-30

Title: File-System Toolbox for RAVE Project
Description: Includes multiple cross-platform read/write interfaces for 'RAVE' project. 'RAVE' stands for "R analysis and visualization of human intracranial electroencephalography data". The whole project aims at providing powerful free-source package that analyze brain recordings from patients with electrodes placed on the cortical surface or inserted into the brain. 'raveio' as part of this project provides tools to read/write neurophysiology data from/to 'RAVE' file structure, as well as several popular formats including 'EDF(+)', 'Matlab', 'BIDS-iEEG', and 'HDF5', etc. Documentation and examples about 'RAVE' project are provided at <https://openwetware.org/wiki/RAVE>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see 'citation("raveio")' for details.
Author: Zhengjia Wang [aut, cre], Beauchamp lab [cph, fnd]
Maintainer: Zhengjia Wang <dipterix.wang@gmail.com>

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Package itsdm updated to version 0.1.2 with previous version 0.1.1 dated 2022-01-11

Title: Isolation Forest-Based Presence-Only Species Distribution Modeling
Description: Collection of R functions to do purely presence-only species distribution modeling with isolation forest (iForest) and its variations such as Extended isolation forest and SCiForest. See the details of these methods in references: Liu, F.T., Ting, K.M. and Zhou, Z.H. (2008) <doi:10.1109/ICDM.2008.17>, Hariri, S., Kind, M.C. and Brunner, R.J. (2019) <doi:10.1109/TKDE.2019.2947676>, Liu, F.T., Ting, K.M. and Zhou, Z.H. (2010) <doi:10.1007/978-3-642-15883-4_18>, Guha, S., Mishra, N., Roy, G. and Schrijvers, O. (2016) <https://proceedings.mlr.press/v48/guha16.html>, Cortes, D. (2021) <arXiv:2110.13402>. Additionally, Shapley values are used to explain model inputs and outputs. See details in references: Shapley, L.S. (1953) <doi:10.1515/9781400881970-018>, Lundberg, S.M. and Lee, S.I. (2017) <https://dl.acm.org/doi/abs/10.5555/3295222.3295230>, Molnar, C. (2020) <ISBN:978-0-244-76852-2>, Å trumbelj, E. and Kononenko, I. (2014) <doi:10.1007/s10115-013-0679-x>. itsdm also provides functions to diagnose variable response, analyze variable importance, draw spatial dependence of variables and examine variable contribution. As utilities, the package includes a few functions to download bioclimatic variables including 'WorldClim' version 2.0 (see Fick, S.E. and Hijmans, R.J. (2017) <doi:10.1002/joc.5086>) and 'CMCC-BioClimInd' (see Noce, S., Caporaso, L. and Santini, M. (2020) <doi:10.1038/s41597-020-00726-5>.
Author: Lei Song [aut, cre] , Lyndon Estes [ths]
Maintainer: Lei Song <lsong@clarku.edu>

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 itsdm-0.1.2/itsdm/vignettes/itsdm_example.Rmd                     |  265 ++++-----
 itsdm-0.1.2/itsdm/vignettes/itsdm_example.Rmd.orig                |   15 
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Package DeclareDesign updated to version 1.0.0 with previous version 0.30.0 dated 2022-01-28

Title: Declare and Diagnose Research Designs
Description: Researchers can characterize and learn about the properties of research designs before implementation using `DeclareDesign`. Ex ante declaration and diagnosis of designs can help researchers clarify the strengths and limitations of their designs and to improve their properties, and can help readers evaluate a research strategy prior to implementation and without access to results. It can also make it easier for designs to be shared, replicated, and critiqued.
Author: Graeme Blair [aut, cre] , Jasper Cooper [aut] , Alexander Coppock [aut] , Macartan Humphreys [aut] , Neal Fultz [aut]
Maintainer: Graeme Blair <graeme.blair@gmail.com>

Diff between DeclareDesign versions 0.30.0 dated 2022-01-28 and 1.0.0 dated 2022-06-20

 DeclareDesign-0.30.0/DeclareDesign/R/deprecated.R                                        |only
 DeclareDesign-0.30.0/DeclareDesign/man/ourPkg-deprecated.Rd                              |only
 DeclareDesign-1.0.0/DeclareDesign/DESCRIPTION                                            |   14 
 DeclareDesign-1.0.0/DeclareDesign/MD5                                                    |  114 ++---
 DeclareDesign-1.0.0/DeclareDesign/NAMESPACE                                              |    1 
 DeclareDesign-1.0.0/DeclareDesign/NEWS.md                                                |    6 
 DeclareDesign-1.0.0/DeclareDesign/R/DeclareDesign-deprecated.R                           |only
 DeclareDesign-1.0.0/DeclareDesign/R/compare_designs.R                                    |    2 
 DeclareDesign-1.0.0/DeclareDesign/R/declare_assignment.R                                 |  116 +++--
 DeclareDesign-1.0.0/DeclareDesign/R/declare_estimator.R                                  |  226 ++++++----
 DeclareDesign-1.0.0/DeclareDesign/R/declare_inquiry.R                                    |   81 ++-
 DeclareDesign-1.0.0/DeclareDesign/R/declare_measurement.R                                |   53 +-
 DeclareDesign-1.0.0/DeclareDesign/R/declare_model.R                                      |  137 ++++--
 DeclareDesign-1.0.0/DeclareDesign/R/declare_population.R                                 |   45 -
 DeclareDesign-1.0.0/DeclareDesign/R/declare_potential_outcomes.R                         |   46 --
 DeclareDesign-1.0.0/DeclareDesign/R/declare_reveal.R                                     |    6 
 DeclareDesign-1.0.0/DeclareDesign/R/declare_sampling.R                                   |   74 ++-
 DeclareDesign-1.0.0/DeclareDesign/R/declare_test.R                                       |    8 
 DeclareDesign-1.0.0/DeclareDesign/R/design_helper_functions.R                            |    2 
 DeclareDesign-1.0.0/DeclareDesign/R/design_print_summary.R                               |   22 
 DeclareDesign-1.0.0/DeclareDesign/R/diagnose_design.R                                    |    6 
 DeclareDesign-1.0.0/DeclareDesign/R/set_diagnosands.R                                    |    2 
 DeclareDesign-1.0.0/DeclareDesign/R/tidy_try.R                                           |    4 
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 DeclareDesign-1.0.0/DeclareDesign/man/compare_functions.Rd                               |    2 
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 DeclareDesign-1.0.0/DeclareDesign/man/declare_estimator.Rd                               |  159 ++++---
 DeclareDesign-1.0.0/DeclareDesign/man/declare_inquiry.Rd                                 |   79 ++-
 DeclareDesign-1.0.0/DeclareDesign/man/declare_measurement.Rd                             |   53 +-
 DeclareDesign-1.0.0/DeclareDesign/man/declare_model.Rd                                   |  137 ++++--
 DeclareDesign-1.0.0/DeclareDesign/man/declare_population.Rd                              |   47 --
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 DeclareDesign-1.0.0/DeclareDesign/man/declare_reveal.Rd                                  |    7 
 DeclareDesign-1.0.0/DeclareDesign/man/declare_sampling.Rd                                |   72 ++-
 DeclareDesign-1.0.0/DeclareDesign/man/declare_test.Rd                                    |    8 
 DeclareDesign-1.0.0/DeclareDesign/man/diagnose_design.Rd                                 |    2 
 DeclareDesign-1.0.0/DeclareDesign/man/post_design.Rd                                     |    2 
 DeclareDesign-1.0.0/DeclareDesign/man/set_diagnosands.Rd                                 |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-bootstrap-diagnosands.R            |    4 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-compare-diagnoses.R                |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-continuous-pos.R                   |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-demo.R                             |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-deprecated.R                       |   34 +
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-describe_variable.R                |    4 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-design-summary.R                   |   10 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-diagnosands.R                      |   19 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-diagnose-design.R                  |   64 +-
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-estimators.R                       |   36 -
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-factorial.R                        |    4 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-fanout.R                           |    4 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-get-estimates.R                    |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-labels.R                           |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-model-summary.R                    |   78 +--
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-model.R                            |   54 +-
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-modify-design.R                    |    4 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-multiple-coefficients.R            |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-multiple-estimands-one-estimator.R |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-multiple-estimators.R              |    8 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-quick-design.R                     |    2 
 DeclareDesign-1.0.0/DeclareDesign/tests/testthat/test-reshape-diagnosis.R                |    2 
 60 files changed, 1243 insertions(+), 784 deletions(-)

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Package declared updated to version 0.17 with previous version 0.16 dated 2022-05-12

Title: Functions to Declare Missing Values
Description: A set of functions to declare labels and missing values, coupled with associated functions to create (weighted) tables of frequencies and various other summary measures. Some of the base functions have been rewritten to make use of the specific information about the missing values, most importantly to distinguish between empty and declared missing values. Many functions have a similar functionality with the corresponding ones from packages "haven" and "labelled". The aim is to ensure as much compatibility as possible with these packages, while offering an alternative in the objects of class "declared".
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

Diff between declared versions 0.16 dated 2022-05-12 and 0.17 dated 2022-06-20

 DESCRIPTION                           |   28 +-
 MD5                                   |   58 ++---
 NAMESPACE                             |    6 
 R/declared.R                          |  360 ++++++----------------------------
 R/haven.R                             |   77 ++-----
 R/internals.R                         |  286 ++++++++++++++-------------
 R/is_empty.R                          |   29 ++
 R/labelled.R                          |   81 ++-----
 R/labels.R                            |   46 ++--
 R/measurement.R                       |only
 R/missing.R                           |   69 ++++--
 R/onLoad.R                            |  114 +++-------
 R/pillar.R                            |   66 ++----
 R/print.R                             |  118 +++--------
 R/vroom.R                             |   25 ++
 R/w_mean.R                            |   44 ++--
 R/w_median.R                          |   33 ++-
 R/w_mode.R                            |   35 ++-
 R/w_quantile.R                        |   46 ++--
 R/w_sd.R                              |   25 ++
 R/w_standardize.R                     |   33 ++-
 R/w_summary.R                         |   31 ++
 R/w_table.R                           |   72 ++----
 R/w_var.R                             |   43 ++--
 inst/ChangeLog                        |  158 +++++++-------
 inst/doc/declared.pdf                 |binary
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Package RSC updated to version 2.0.2 with previous version 2.0.1 dated 2021-10-21

Title: Robust and Sparse Correlation Matrix
Description: Performs robust and sparse correlation matrix estimation. Robustness is achieved based on a simple robust pairwise correlation estimator, while sparsity is obtained based on thresholding. The optimal thresholding is tuned via cross-validation. See Serra, Coretto, Fratello and Tagliaferri (2018) <doi:10.1093/bioinformatics/btx642>.
Author: Luca Coraggio [cre, aut], Pietro Coretto [aut], Angela Serra [aut], Roberto Tagliaferri [ctb]
Maintainer: Luca Coraggio <luca.coraggio@unina.it>

Diff between RSC versions 2.0.1 dated 2021-10-21 and 2.0.2 dated 2022-06-20

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Package PCS updated to version 1.3 with previous version 1.2 dated 2013-08-16

Title: Calculate the Probability of Correct Selection (PCS)
Description: Given k populations (can be in thousands), what is the probability that a given subset of size t contains the true top t populations? This package finds this probability and offers three tuning parameters (G, d, L) to relax the definition.
Author: Jason Wilson
Maintainer: Jason Wilson <jason.wilson@biola.edu>

Diff between PCS versions 1.2 dated 2013-08-16 and 1.3 dated 2022-06-20

 DESCRIPTION                 |   10 +++++-----
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 man/PdofCSt.T1or2.Rd        |    6 +++---
 man/PofCSLt.bootstrap5.Rd   |    7 ++++---
 man/PofCSt.Rd               |    6 +++---
 man/tindep.Rd               |    2 +-
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New package RCTS with initial version 0.2.2
Package: RCTS
Title: Clustering Time Series While Resisting Outliers
Version: 0.2.2
Description: Robust Clustering of Time Series (RCTS) has the functionality to cluster time series using both the classical and the robust interactive fixed effects framework. The classical framework is developed in Ando & Bai (2017) <doi:10.1080/01621459.2016.1195743>. The implementation within this package excludes the SCAD-penalty on the estimations of beta. This robust framework is developed in Boudt & Heyndels (2022) <doi:10.1016/j.ecosta.2022.01.002> and is made robust against different kinds of outliers. The algorithm iteratively updates beta (the coefficients of the observable variables), group membership, and the latent factors (which can be common and/or group-specific) along with their loadings. The number of groups and factors can be estimated if they are unknown.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Imports: stats, magrittr, dplyr, purrr, stringr, tidyr, tibble, ggplot2, ncvreg, robustbase, cellWise, rlang, Rdpack
Suggests: tsqn, doParallel, doSNOW, foreach, mclust, Matrix
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2022-06-17 11:35:21 UTC; hewoud
Author: Ewoud Heyndels [aut, cre]
Maintainer: Ewoud Heyndels <ewoud.heyndels@vub.be>
Repository: CRAN
Date/Publication: 2022-06-20 16:20:02 UTC

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Package mixtox updated to version 1.4.0 with previous version 1.3.2 dated 2017-02-18

Title: Dose Response Curve Fitting and Mixture Toxicity Assessment
Description: Curve Fitting of monotonic(sigmoidal) & non-monotonic(J-shaped) dose-response data. Predicting mixture toxicity based on reference models such as 'concentration addition', 'independent action', and 'generalized concentration addition'.
Author: Xiangwei Zhu
Maintainer: Xiangwei Zhu <xwzhunc@gmail.com>

Diff between mixtox versions 1.3.2 dated 2017-02-18 and 1.4.0 dated 2022-06-20

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New package MainExistingDatasets with initial version 1.0.0
Package: MainExistingDatasets
Title: Main Existing Human Datasets
Version: 1.0.0
Description: Shiny for Open Science to visualize, share, and inventory the main existing human datasets for researchers.
License: GPL-3
Depends: R (>= 2.10)
Imports: config, dplyr, DT, glue, golem, grDevices, htmltools, htmlwidgets, magrittr, openxlsx, pkgload, processx, rlang, sf, shiny, spData, tidyr, tmap, tmaptools, utils
Suggests: covr, knitr, rmarkdown, testthat
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: false
NeedsCompilation: no
Packaged: 2022-06-17 11:29:14 UTC; rstudio
Author: Etienne Camenen [aut, cre], Baptiste Couvy-Duchesne [aut]
Maintainer: Etienne Camenen <etienne.camenen@gmail.com>
Repository: CRAN
Date/Publication: 2022-06-20 16:20:06 UTC

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Package DLMtool updated to version 6.0.6 with previous version 6.0.5 dated 2022-06-08

Title: Data-Limited Methods Toolkit
Description: A collection of data-limited management procedures that can be evaluated with management strategy evaluation with the 'MSEtool' package, or applied to fishery data to provide management recommendations.
Author: Tom Carruthers [aut], Quang Huynh [aut], Adrian Hordyk [aut, cre], M. Bryan [ctb], HF. Geremont [ctb], C. Grandin [ctb], W. Harford [ctb], Q. Huynh [ctb], C. Walters [ctb]
Maintainer: Adrian Hordyk <adrian@bluematterscience.com>

Diff between DLMtool versions 6.0.5 dated 2022-06-08 and 6.0.6 dated 2022-06-20

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New package CRABS with initial version 1.1.0
Package: CRABS
Title: Congruent Rate Analyses in Birth-Death Scenarios
Version: 1.1.0
Encoding: UTF-8
Description: Features tools for exploring congruent phylogenetic birth-death models. It can construct the pulled speciation- and net-diversification rates from a reference model. Given alternative speciation- or extinction rates, it can construct new models that are congruent with the reference model. Functionality is included to sample new rate functions, and to visualize the distribution of one congruence class. See also Louca & Pennell (2020) <doi:10.1038/s41586-020-2176-1>.
LazyData: true
Depends: R (>= 3.5.0), ggplot2
Imports: magrittr, deSolve, dplyr, tibble, colorspace, patchwork, latex2exp, tidyr, pracma, ape
License: GPL-3
Suggests: knitr, rmarkdown
URL: https://github.com/afmagee/CRABS
NeedsCompilation: no
Packaged: 2022-06-17 13:28:42 UTC; bjorn
Author: Bjoern Tore Kopperud [aut, cre], Sebastian Hoehna [aut], Andrew F. Magee [aut]
Maintainer: Bjoern Tore Kopperud <kopperud@protonmail.com>
Repository: CRAN
Date/Publication: 2022-06-20 16:30:02 UTC

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Package hzar (with last version 0.2-5) was removed from CRAN

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Package waveslim updated to version 1.8.3 with previous version 1.8.2 dated 2020-03-13

Title: Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing
Description: Basic wavelet routines for time series (1D), image (2D) and array (3D) analysis. The code provided here is based on wavelet methodology developed in Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001); the dual-tree complex wavelet transform (DTCWT) from Kingsbury (1999, 2001) as implemented by Selesnick; and Hilbert wavelet pairs (Selesnick 2001, 2002). All figures in chapters 4-7 of GSW (2001) are reproducible using this package and R code available at the book website(s) below.
Author: Brandon Whitcher
Maintainer: Brandon Whitcher <bwhitcher@gmail.com>

Diff between waveslim versions 1.8.2 dated 2020-03-13 and 1.8.3 dated 2022-06-20

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Package rMIDAS updated to version 0.4.1 with previous version 0.4.0 dated 2022-02-10

Title: Multiple Imputation with Denoising Autoencoders
Description: A tool for multiply imputing missing data using 'MIDAS', a deep learning method based on denoising autoencoder neural networks. This algorithm offers significant accuracy and efficiency advantages over other multiple imputation strategies, particularly when applied to large datasets with complex features. Alongside interfacing with 'Python' to run the core algorithm, this package contains functions for processing data before and after model training, running imputation model diagnostics, generating multiple completed datasets, and estimating regression models on these datasets.
Author: Thomas Robinson [aut, cre, cph] , Ranjit Lall [aut, cph] , Alex Stenlake [ctb, cph]
Maintainer: Thomas Robinson <ts.robinson1994@gmail.com>

Diff between rMIDAS versions 0.4.0 dated 2022-02-10 and 0.4.1 dated 2022-06-20

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Package packMBPLSDA updated to version 0.9.0 with previous version 0.8.0 dated 2020-03-15

Title: Multi-Block Partial Least Squares Discriminant Analysis
Description: Several functions are provided to implement a MBPLSDA : components search, optimal model components number search, optimal model validity test by permutation tests, observed values evaluation of optimal model parameters and predicted categories, bootstrap values evaluation of optimal model parameters and predicted cross-validated categories. The use of this package is described in Brandolini-Bunlon et al (2019. Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10):134).
Author: Marion Brandolini-Bunlon, Stephanie Bougeard, Melanie Petera, Estelle Pujos-Guillot
Maintainer: Marion Brandolini-Bunlon <marion.brandolini-bunlon@inra.fr>

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Package MESS updated to version 0.5.9 with previous version 0.5.7 dated 2020-07-21

Title: Miscellaneous Esoteric Statistical Scripts
Description: A mixed collection of useful and semi-useful diverse statistical functions, some of which may even be referenced in The R Primer book.
Author: Claus Thorn Ekstroem [aut, cre]
Maintainer: Claus Thorn Ekstroem <claus@rprimer.dk>

Diff between MESS versions 0.5.7 dated 2020-07-21 and 0.5.9 dated 2022-06-20

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Package coxinterval (with last version 1.2) was removed from CRAN

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2010-06-06 1.0

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Package see updated to version 0.7.1 with previous version 0.7.0 dated 2022-03-31

Title: Model Visualisation Toolbox for 'easystats' and 'ggplot2'
Description: Provides plotting utilities supporting easystats-packages (<https://github.com/easystats/easystats>) and some extra themes, geoms, and scales for 'ggplot2'. Color scales are based on <https://materialui.co/colors>.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, inv] , Indrajeet Patil [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Philip Waggoner [aut, ctb] , Jeffrey R. Stevens [ctb] , Matthew Smith [rev] , Jakob Bossek [re [...truncated...]
Maintainer: Daniel Luedecke <d.luedecke@uke.de>

Diff between see versions 0.7.0 dated 2022-03-31 and 0.7.1 dated 2022-06-20

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Package cpfa updated to version 1.0-4 with previous version 1.0-3 dated 2022-06-15

Title: Classification with Parallel Factor Analysis
Description: Classification using Richard A. Harshman's Parallel Factor Analysis (Parafac) model-1 fit to a three-way or four-way data tensor/array. See Harshman and Lundy (1994): <doi:10.1016/0167-9473(94)90132-5>. Uses Parafac factor weights from one mode of this model as predictors to tune parameters for one or more classification methods via a k-fold cross-validation procedure. Supports penalized logistic regression, support vector machine, random forest, and feed-forward neural network. Supports binary and multiclass classification. Predicts class labels or class probabilities and calculates multiple classification performance measures. Parallel computing is implemented via the 'parallel' and 'doParallel' packages.
Author: Matthew A. Snodgress <snodg031@umn.edu>
Maintainer: Matthew A. Snodgress <snodg031@umn.edu>

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Package partykit updated to version 1.2-16 with previous version 1.2-15 dated 2021-08-23

Title: A Toolkit for Recursive Partytioning
Description: A toolkit with infrastructure for representing, summarizing, and visualizing tree-structured regression and classification models. This unified infrastructure can be used for reading/coercing tree models from different sources ('rpart', 'RWeka', 'PMML') yielding objects that share functionality for print()/plot()/predict() methods. Furthermore, new and improved reimplementations of conditional inference trees (ctree()) and model-based recursive partitioning (mob()) from the 'party' package are provided based on the new infrastructure. A description of this package was published by Hothorn and Zeileis (2015) <https://jmlr.org/papers/v16/hothorn15a.html>.
Author: Torsten Hothorn [aut, cre] , Heidi Seibold [ctb] , Achim Zeileis [aut]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>

Diff between partykit versions 1.2-15 dated 2021-08-23 and 1.2-16 dated 2022-06-20

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New package ElstonStewart with initial version 1.2
Package: ElstonStewart
Title: Elston-Stewart Algorithm
Depends: kinship2
Imports: methods, parallel, digest
Version: 1.2
Date: 2022-06-06
Author: Herve Perdry
Maintainer: Herve Perdry <herve.perdry@universite-paris-saclay.fr>
Description: Flexible implementation of Elston-Stewart algorithm.
License: GPL (>= 2)
Encoding: UTF-8
LazyLoad: yes
LazyData: yes
NeedsCompilation: no
Packaged: 2022-06-09 09:04:49 UTC; rv
Repository: CRAN
Date/Publication: 2022-06-20 13:40:02 UTC

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Package reporter updated to version 1.3.3 with previous version 1.3.1 dated 2022-03-10

Title: Creates Statistical Reports
Description: Contains functions to create regulatory-style statistical reports. Originally designed to create tables, listings, and figures for the pharmaceutical, biotechnology, and medical device industries, these reports are generalized enough that they could be used in any industry. Generates text, rich-text, PDF, HTML, and Microsoft Word file formats. The package specializes in printing wide and long tables with automatic page wrapping and splitting. Reports can be produced with a minimum of function calls, and without relying on other table packages. The package supports titles, footnotes, page header, page footers, spanning headers, page by variables, and automatic page numbering.
Author: David Bosak [aut, cre], Kevin Kramer [ctb], Archytas Clinical Solutions [cph]
Maintainer: David Bosak <dbosak01@gmail.com>

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Package corporaexplorer updated to version 0.8.6 with previous version 0.8.5 dated 2022-04-08

Title: A 'Shiny' App for Exploration of Text Collections
Description: Facilitates dynamic exploration of text collections through an intuitive graphical user interface and the power of regular expressions. The package contains 1) a helper function to convert a data frame to a 'corporaexplorerobject', 2) a 'Shiny' app for fast and flexible exploration of a 'corporaexplorerobject', and 3) a 'Shiny' app for simple retrieval/extraction of documents from a 'corporaexplorerobject' in a reading-friendly format. The package also includes demo apps with which one can explore Jane Austen's novels and the State of the Union Addresses (data from the 'janeaustenr' and 'sotu' packages respectively).
Author: Kristian Lundby Gjerde [aut, cre]
Maintainer: Kristian Lundby Gjerde <kristian.gjerde@gmail.com>

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Package marginaleffects updated to version 0.6.0 with previous version 0.5.0 dated 2022-05-17

Title: Marginal Effects, Marginal Means, Predictions, and Contrasts
Description: Compute, summarize, and plot marginal effects, adjusted predictions, contrasts, and marginal means for a wide variety of models.
Author: Vincent Arel-Bundock [aut, cre, cph]
Maintainer: Vincent Arel-Bundock <vincent.arel-bundock@umontreal.ca>

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Package cyphr updated to version 1.1.4 with previous version 1.1.2 dated 2021-05-17

Title: High Level Encryption Wrappers
Description: Encryption wrappers, using low-level support from 'sodium' and 'openssl'. 'cyphr' tries to smooth over some pain points when using encryption within applications and data analysis by wrapping around differences in function names and arguments in different encryption providing packages. It also provides high-level wrappers for input/output functions for seamlessly adding encryption to existing analyses.
Author: Rich FitzJohn [aut, cre], Jai Ranganathan [ctb]
Maintainer: Rich FitzJohn <rich.fitzjohn@gmail.com>

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Package Compind updated to version 2.5 with previous version 2.4 dated 2022-06-09

Title: Composite Indicators Functions
Description: A collection of functions to calculate Composite Indicators methods, focusing, in particular, on the normalisation and weighting-aggregation steps, as described in OECD Handbook on constructing composite indicators: methodology and user guide <https://www.oecd.org/els/soc/handbookonconstructingcompositeindicatorsmethodologyanduserguide.htm>, 'Vidoli' and 'Fusco' and 'Mazziotta' <doi:10.1007/s11205-014-0710-y>, 'Mazziotta' and 'Pareto' (2016) <doi:10.1007/s11205-015-0998-2>, 'Van Puyenbroeck and 'Rogge' <doi:10.1016/j.ejor.2016.07.038> and other authors.
Author: Francesco Vidoli, Elisa Fusco
Maintainer: Francesco Vidoli <fvidoli@gmail.com>

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Package admisc updated to version 0.29 with previous version 0.28 dated 2022-06-06

Title: Adrian Dusa's Miscellaneous
Description: Contains functions used across packages 'DDIwR', 'QCA' and 'venn'. Interprets and translates, factorizes and negates SOP - Sum of Products expressions, for both binary and multi-value crisp sets, and extracts information (set names, set values) from those expressions. Other functions perform various other checks if possibly numeric (even if all numbers reside in a character vector) and coerce to numeric, or check if the numbers are whole. It also offers, among many others, a highly versatile recoding routine and a more flexible alternative to the base function 'with()'. Some of the functions in this package use related functions from package 'QCA'. Users are encouraged to install that package despite not being listed in the Imports field, due to circular dependency issues.
Author: Adrian Dusa [aut, cre, cph]
Maintainer: Adrian Dusa <dusa.adrian@unibuc.ro>

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Package StepBeta updated to version 1.0.1 with previous version 1.0.0 dated 2022-04-28

Title: Stepwise Procedure for Beta Regression Models
Description: Starting from a Beta Regression Model, it provides a stepwise procedure to select the linear predictor.
Author: Sergio Garofalo
Maintainer: Sergio Garofalo <sergio.garofalo96@gmail.com>

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Package randtests updated to version 1.0.1 with previous version 1.0 dated 2014-11-16

Title: Testing Randomness in R
Description: Provides several non parametric randomness tests for numeric sequences.
Author: Frederico Caeiro [aut, cre] , Ayana Mateus [aut]
Maintainer: Frederico Caeiro <fac@fct.unl.pt>

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Package qmd updated to version 1.1.0 with previous version 1.0.0 dated 2021-09-28

Title: Quantification of Multivariate Dependence
Description: A multivariate copula-based dependence measure. For more information, see Griessenberger, Junker, Trutschnig (2022), On a multivariate copula-based dependence measure and its estimation, Electronic Journal of Statistics, 16, 2206-2251.
Author: Florian Griessenberger [aut, cre], Robert R. Junker [aut], Valentin Petztel [aut], Wolfgang Trutschnig [aut]
Maintainer: Florian Griessenberger <florian.griessenberger@sbg.ac.at>

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Package performance updated to version 0.9.1 with previous version 0.9.0 dated 2022-03-30

Title: Assessment of Regression Models Performance
Description: Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Vincent Arel-Bundock [ctb] , Martin Jullum [rev], gjo11 [rev]
Maintainer: Daniel Luedecke <d.luedecke@uke.de>

Diff between performance versions 0.9.0 dated 2022-03-30 and 0.9.1 dated 2022-06-20

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Package BiDAG updated to version 2.0.9 with previous version 2.0.7 dated 2022-05-16

Title: Bayesian Inference for Directed Acyclic Graphs
Description: Implementation of a collection of MCMC methods for Bayesian structure learning of directed acyclic graphs (DAGs), both from continuous and discrete data. For efficient inference on larger DAGs, the space of DAGs is pruned according to the data. To filter the search space, the algorithm employs a hybrid approach, combining constraint-based learning with search and score. A reduced search space is initially defined on the basis of a skeleton obtained by means of the PC-algorithm, and then iteratively improved with search and score. Search and score is then performed following two approaches: Order MCMC, or Partition MCMC. The BGe score is implemented for continuous data and the BDe score is implemented for binary data or categorical data. The algorithms may provide the maximum a posteriori (MAP) graph or a sample (a collection of DAGs) from the posterior distribution given the data. All algorithms are also applicable for structure learning and sampling for dynamic Bayesian networks. References: J. Kuipers, P. Suter, G. Moffa (2022) <doi:10.1080/10618600.2021.2020127>, N. Friedman and D. Koller (2003) <doi:10.1023/A:1020249912095>, J. Kuipers and G. Moffa (2017) <doi:10.1080/01621459.2015.1133426>, M. Kalisch et al. (2012) <doi:10.18637/jss.v047.i11>, D. Geiger and D. Heckerman (2002) <doi:10.1214/aos/1035844981>.
Author: Polina Suter [aut, cre], Jack Kuipers [aut]
Maintainer: Polina Suter <polina.suter@bsse.ethz.ch>

Diff between BiDAG versions 2.0.7 dated 2022-05-16 and 2.0.9 dated 2022-06-20

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Package MaXact (with last version 0.2.1) was removed from CRAN

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2013-12-04 0.2.1
2013-11-28 0.2
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2011-10-10 1.4
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2010-10-17 1.2

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2014-09-04 0.3-3
2014-07-25 0.3-2
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2014-03-26 0.3-0
2013-10-24 0.2-0
2013-06-23 0.1-0

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2015-05-21 1.1.2
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2012-01-15 0.3.2

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2014-04-19 1.1
2014-01-04 1.0

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2014-02-11 1.0

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

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2013-10-16 1.1
2011-12-30 0.1.0

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Package Paneldata (with last version 1.0) was removed from CRAN

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2014-03-20 1.0

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2013-05-15 1.1
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2012-12-08 1.0

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2013-08-23 1.1

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2014-07-08 2.0
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Package quarks updated to version 1.1.2 with previous version 1.1.1 dated 2022-06-13

Title: Simple Methods for Calculating and Backtesting Value at Risk and Expected Shortfall
Description: Enables the user to calculate Value at Risk (VaR) and Expected Shortfall (ES) by means of various types of historical simulation. Currently plain-, age-, volatility-weighted- and filtered historical simulation are implemented in this package. Volatility weighting can be carried out via an exponentially weighted moving average model (EWMA) or other GARCH-type models. The performance can be assessed via Traffic Light Test, Coverage Tests and Loss Functions. The methods of the package are described in Gurrola-Perez, P. and Murphy, D. (2015) <https://EconPapers.repec.org/RePEc:boe:boeewp:0525> as well as McNeil, J., Frey, R., and Embrechts, P. (2015) <https://ideas.repec.org/b/pup/pbooks/10496.html>.
Author: Sebastian Letmathe [aut, cre]
Maintainer: Sebastian Letmathe <sebastian.letmathe@uni-paderborn.de>

Diff between quarks versions 1.1.1 dated 2022-06-13 and 1.1.2 dated 2022-06-20

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Package dsrTest updated to version 1.0.0 with previous version 0.2.1 dated 2017-05-02

Title: Tests and Confidence Intervals on Directly Standardized Rates for Several Methods
Description: Perform a test of a simple null hypothesis about a directly standardized rate and obtain the matching confidence interval using a choice of methods.
Author: Michael Nelson
Maintainer: Michael Nelson <michael.nelson.r.pkg@gmail.com>

Diff between dsrTest versions 0.2.1 dated 2017-05-02 and 1.0.0 dated 2022-06-20

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Package UCSCXenaTools updated to version 1.4.8 with previous version 1.4.7 dated 2021-09-15

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] , Xue-Song Liu [aut] , Martin Morgan [ctb], Christine Stawitz [rev] , Carl Ganz [rev]
Maintainer: Shixiang Wang <w_shixiang@163.com>

Diff between UCSCXenaTools versions 1.4.7 dated 2021-09-15 and 1.4.8 dated 2022-06-20

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New package rgl2gltf with initial version 1.0.0
Package: rgl2gltf
Title: Read and Write '.gltf' and '.glb' Files
Version: 1.0.0
Maintainer: Duncan Murdoch <murdoch.duncan@gmail.com>
Description: The 'glTF' file format is used to describe 3D models. This package provides read and write functions to work with it.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: jsonlite, rgl (>= 0.108.43), grDevices, R6, base64enc
URL: https://github.com/dmurdoch/rgl2gltf
BugReports: https://github.com/dmurdoch/rgl2gltf/issues
Suggests: rmarkdown, knitr, misc3d, V8, manipulateWidget, png, jpeg
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: yes
Packaged: 2022-06-17 11:34:20 UTC; murdoch
Author: Duncan Murdoch [aut, cre], Morten S. Mikkelsen [cph]
Repository: CRAN
Date/Publication: 2022-06-20 08:20:02 UTC

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New package ipsecr with initial version 1.1.1
Package: ipsecr
Title: Spatially Explicit Capture-Recapture by Inverse Prediction
Version: 1.1.1
Date: 2022-06-17
Depends: R (>= 3.5.0), secr (>= 4.5.4)
Imports: graphics, grDevices, MASS, utils, parallel, stats, tools, stringr, nlme, Rcpp (>= 0.12.14)
Suggests: FrF2, rmarkdown, knitr, testthat
LinkingTo: Rcpp, BH
VignetteBuilder: knitr
Description: Estimates the density of a spatially distributed animal population sampled with an array of passive detectors, such as traps. Models incorporating distance-dependent detection are fitted by simulation and inverse prediction as proposed by Efford (2004) <doi:10.1111/j.0030-1299.2004.13043.x>.
License: GPL (>= 2)
LazyData: yes
LazyDataCompression: xz
URL: https://github.com/MurrayEfford/ipsecr/, https://www.otago.ac.nz/density/
NeedsCompilation: yes
Packaged: 2022-06-17 10:11:31 UTC; Murray
Author: Murray Efford [aut, cre]
Maintainer: Murray Efford <murray.efford@otago.ac.nz>
Repository: CRAN
Date/Publication: 2022-06-20 08:20:06 UTC

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New package detourr with initial version 0.1.0
Package: detourr
Title: Portable and Performant Tour Animations
Version: 0.1.0
Description: Provides 2D and 3D tour animations as HTML widgets. The user can interact with the widgets using orbit controls, tooltips, brushing, and timeline controls. Linked brushing is supported using 'crosstalk', and widgets can be embedded in Shiny apps or HTML documents.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: tourr, tibble, htmlwidgets, tidyselect, rlang, purrr, viridisLite, grDevices
Suggests: testthat (>= 3.0.0), crosstalk, shiny, htmltools, knitr, dplyr, liminal, rmarkdown, geozoo
URL: https://casperhart.github.io/detourr/
BugReports: https://github.com/casperhart/detourr/issues
Depends: R (>= 4.1)
NeedsCompilation: no
Packaged: 2022-06-17 07:29:19 UTC; chart
Author: Casper Hart [aut, cre], Earo Wang [aut, ths]
Maintainer: Casper Hart <casperhart93@gmail.com>
Repository: CRAN
Date/Publication: 2022-06-20 08:00:02 UTC

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Package WoodSimulatR updated to version 0.6.0 with previous version 0.5.0 dated 2020-11-10

Title: Generate Simulated Sawn Timber Strength Grading Data
Description: Tools for generating simulated sawn timber strength grading data with a main focus on statistical simulation based on covariance matrices. Simulation data for Norway spruce sawn timber from Austria and reference values of means and standard deviations of grade determining properties from literature for a number of European countries are provided, as well.
Author: Andreas Weidenhiller [cre, aut] , Anton Wegscheider [aut]
Maintainer: Andreas Weidenhiller <a.weidenhiller@holzforschung.at>

Diff between WoodSimulatR versions 0.5.0 dated 2020-11-10 and 0.6.0 dated 2022-06-20

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Package wiqid updated to version 0.3.1 with previous version 0.3.0 dated 2020-06-10

Title: Quick and Dirty Estimates for Wildlife Populations
Description: Provides simple, fast functions for maximum likelihood and Bayesian estimates of wildlife population parameters, suitable for use with simulated data or bootstraps. Early versions were indeed quick and dirty, but optional error-checking routines and meaningful error messages have been added. Includes single and multi-season occupancy, closed capture population estimation, survival, species richness and distance measures.
Author: Mike Meredith [aut, cre], Jason Bryer [ctb] , John Kruschke [ctb], Brian Neelon [ctb] , Michael Schaub [ctb] , R Core Team [ctb]
Maintainer: Mike Meredith <mike@mmeredith.net>

Diff between wiqid versions 0.3.0 dated 2020-06-10 and 0.3.1 dated 2022-06-20

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More information about wiqid at CRAN
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