Fri, 11 Jul 2025

Package spStack updated to version 1.1.0 with previous version 1.0.1 dated 2024-10-08

Title: Bayesian Geostatistics Using Predictive Stacking
Description: Fits Bayesian hierarchical spatial and spatial-temporal process models for point-referenced Gaussian, Poisson, binomial, and binary data using stacking of predictive densities. It involves sampling from analytically available posterior distributions conditional upon candidate values of the spatial process parameters and, subsequently assimilate inference from these individual posterior distributions using Bayesian predictive stacking. Our algorithm is highly parallelizable and hence, much faster than traditional Markov chain Monte Carlo algorithms while delivering competitive predictive performance. See Zhang, Tang, and Banerjee (2025) <doi:10.48550/arXiv.2304.12414>, and, Pan, Zhang, Bradley, and Banerjee (2025) <doi:10.48550/arXiv.2406.04655> for details.
Author: Soumyakanti Pan [aut, cre] , Sudipto Banerjee [aut]
Maintainer: Soumyakanti Pan <span18@ucla.edu>

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Package tinyplot updated to version 0.4.2 with previous version 0.4.1 dated 2025-06-02

Title: Lightweight Extension of the Base R Graphics System
Description: Lightweight extension of the base R graphics system, with support for automatic legends, facets, themes, and various other enhancements.
Author: Grant McDermott [aut, cre] , Vincent Arel-Bundock [aut] , Achim Zeileis [aut] , Etienne Bacher [ctb]
Maintainer: Grant McDermott <gmcd@amazon.com>

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Package MultiLevelOptimalBayes updated to version 0.0.2.0 with previous version 0.0.1.6 dated 2025-05-29

Title: Regularized Bayesian Estimator for Two-Level Latent Variable Models
Description: Implements a regularized Bayesian estimator that optimizes the estimation of between-group coefficients for multilevel latent variable models by minimizing mean squared error (MSE) and balancing variance and bias. The package provides more reliable estimates in scenarios with limited data, offering a robust solution for accurate parameter estimation in two-level latent variable models. It is designed for researchers in psychology, education, and related fields who face challenges in estimating between-group effects under small sample sizes and low intraclass correlation coefficients. Dashuk et al. (2024) <doi:10.13140/RG.2.2.18148.39048> derived the optimal regularized Bayesian estimator; Dashuk et al. (2024) <doi:10.13140/RG.2.2.34350.01604> extended it to the multivariate case; and Luedtke et al. (2008) <doi:10.1037/a0012869> formalized the two-level latent variable framework.
Author: Valerii Dashuk [aut, cre], Binayak Timilsina [aut], Martin Hecht [aut], Steffen Zitzmann [aut]
Maintainer: Valerii Dashuk <vadashuk@gmail.com>

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Package ActivePathways updated to version 2.0.6 with previous version 2.0.5 dated 2024-07-28

Title: Integrative Pathway Enrichment Analysis of Multivariate Omics Data
Description: Framework for analysing multiple omics datasets in the context of molecular pathways, biological processes and other types of gene sets. The package uses p-value merging to combine gene- or protein-level signals, followed by ranked hypergeometric tests to determine enriched pathways and processes. Genes can be integrated using directional constraints that reflect how the input datasets are expected interact with one another. This approach allows researchers to interpret a series of omics datasets in the context of known biology and gene function, and discover associations that are only apparent when several datasets are combined. The recent version of the package is part of the following publication: Directional integration and pathway enrichment analysis for multi-omics data. Slobodyanyuk M^, Bahcheli AT^, Klein ZP, Bayati M, Strug LJ, Reimand J. Nature Communications (2024) <doi:10.1038/s41467-024-49986-4>.
Author: Juri Reimand [aut, cre], Jonathan Barenboim [ctb], Mykhaylo Slobodyanyuk [aut]
Maintainer: Juri Reimand <juri.reimand@utoronto.ca>

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Package parTimeROC updated to version 0.2.0 with previous version 0.1.1 dated 2025-04-11

Title: Parametric Time-Dependent Receiver Operating Characteristic
Description: Producing the time-dependent receiver operating characteristic (ROC) curve through parametric approaches. Tools for generating random data, fitting, predicting and check goodness of fit are prepared. The methods are developed from the theoretical framework of proportional hazard model and copula functions. Using this package, users can now simulate parametric time-dependent ROC and run experiment to understand the behavior of the curve under different scenario.
Author: Faiz Azhar [aut, cre, cph] , Adina Najwa Kamarudin [cph, ths] , Universiti Teknologi Malaysia, UTM [cph], Universiti Malaya, UM [cph]
Maintainer: Faiz Azhar <faiz.azhar241@gmail.com>

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Package isocountry updated to version 0.5.0 with previous version 0.4.0 dated 2025-06-06

Title: ISO 3166-1 Country Codes
Description: ISO 3166-1 country codes and ISO 4217 currency codes provided by the International Organization for Standardization.
Author: Maximilian Muecke [aut, cre]
Maintainer: Maximilian Muecke <muecke.maximilian@gmail.com>

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Package wikiTools updated to version 1.2.14 with previous version 1.2.8 dated 2025-03-31

Title: Tools for Wikidata and Wikipedia
Description: A set of wrappers intended to check, read and download information from the Wikimedia sources. It is specifically created to work with names of celebrities, in which case their information and statistics can be downloaded. Additionally, it also builds links and snippets to use in combination with the function gallery() in netCoin package.
Author: Modesto Escobar [aut, cph, cre] , Angel Zazo [aut], Carlos Prieto [aut] , David Barrios [aut], Cristina Calvo [aut]
Maintainer: Modesto Escobar <modesto@usal.es>

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Package waldo updated to version 0.6.2 with previous version 0.6.1 dated 2024-11-07

Title: Find Differences Between R Objects
Description: Compare complex R objects and reveal the key differences. Designed particularly for use in testing packages where being able to quickly isolate key differences makes understanding test failures much easier.
Author: Hadley Wickham [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Hadley Wickham <hadley@posit.co>

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Package emmeans updated to version 1.11.2 with previous version 1.11.1 dated 2025-05-04

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

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Package mHMMbayes updated to version 1.1.1 with previous version 1.1.0 dated 2024-04-01

Title: Multilevel Hidden Markov Models Using Bayesian Estimation
Description: An implementation of the multilevel (also known as mixed or random effects) hidden Markov model using Bayesian estimation in R. The multilevel hidden Markov model (HMM) is a generalization of the well-known hidden Markov model, for the latter see Rabiner (1989) <doi:10.1109/5.18626>. The multilevel HMM is tailored to accommodate (intense) longitudinal data of multiple individuals simultaneously, see e.g., de Haan-Rietdijk et al. <doi:10.1080/00273171.2017.1370364>. Using a multilevel framework, we allow for heterogeneity in the model parameters (transition probability matrix and conditional distribution), while estimating one overall HMM. The model can be fitted on multivariate data with either a categorical, normal, or Poisson distribution, and include individual level covariates (allowing for e.g., group comparisons on model parameters). Parameters are estimated using Bayesian estimation utilizing the forward-backward recursion within a hybrid Metropolis within Gibbs samp [...truncated...]
Author: Emmeke Aarts [aut, cre], Sebastian Mildiner Moraga [aut]
Maintainer: Emmeke Aarts <e.aarts@uu.nl>

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Package hce updated to version 0.8.0 with previous version 0.7.2 dated 2025-05-14

Title: Design and Analysis of Hierarchical Composite Endpoints
Description: Simulate and analyze hierarchical composite endpoints. Includes implementation for the kidney hierarchical composite endpoint as defined in Heerspink HL et al (2023) “Development and validation of a new hierarchical composite end point for clinical trials of kidney disease progression” (Journal of the American Society of Nephrology 34 (2): 2025–2038, <doi:10.1681/ASN.0000000000000243>). Win odds, also called Wilcoxon-Mann-Whitney or success odds, is the main analysis method. Other win statistics (win probability, win ratio, net benefit) are also implemented in the univariate case, provided there is no censoring. The win probability analysis is based on the Brunner-Munzel test and uses the DeLong-DeLong-Clarke-Pearson variance estimator, as described by Brunner and Konietschke (2025) in “An unbiased rank-based estimator of the Mann–Whitney variance including the case of ties” (Statistical Papers 66 (1): 20, <doi:10.1007/s00362-024-01635-0>). Stratification and covariate adju [...truncated...]
Author: Samvel B. Gasparyan [aut, cre]
Maintainer: Samvel B. Gasparyan <gasparyan.co@gmail.com>

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Package downloadthis updated to version 0.5.0 with previous version 0.4.1 dated 2024-10-14

Title: Implement Download Buttons in 'rmarkdown'
Description: Implement download buttons in HTML output from 'rmarkdown' without the need for 'runtime:shiny'.
Author: Felipe Mattioni Maturana [aut, cre] , John Coene [ctb]
Maintainer: Felipe Mattioni Maturana <felipe.mattioni@med.uni-tuebingen.de>

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Package profileCI updated to version 1.1.0 with previous version 1.0.0 dated 2025-06-04

Title: Profiling a Log-Likelihood to Calculate Confidence Intervals
Description: Provides tools for profiling a user-supplied log-likelihood function to calculate confidence intervals for model parameters. Speed of computation can be improved by adjusting the step sizes in the profiling and/or starting the profiling from limits based on the approximate large sample normal distribution for the maximum likelihood estimator of a parameter. The accuracy of the limits can be set by the user. A plot method visualises the log-likelihood and confidence interval. Cases where the profile log-likelihood flattens above the value at which a confidence limit is defined can be handled, leading to a limit at plus or minus infinity. Disjoint confidence intervals will not be found.
Author: Paul J. Northrop [aut, cre, cph]
Maintainer: Paul J. Northrop <p.northrop@ucl.ac.uk>

Diff between profileCI versions 1.0.0 dated 2025-06-04 and 1.1.0 dated 2025-07-11

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 NAMESPACE                                |    1 
 NEWS.md                                  |only
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Package praatpicture updated to version 1.5.0 with previous version 1.4.3 dated 2025-05-13

Title: 'Praat Picture' Style Plots of Acoustic Data
Description: Quickly and easily generate plots of acoustic data aligned with transcriptions similar to those made in 'Praat' using either derived signals generated directly in R with 'wrassp' or imported derived signals from 'Praat'. Provides easy and fast out-of-the-box solutions but also a high extent of flexibility. Also provides options for embedding audio in figures and animating figures.
Author: Rasmus Puggaard-Rode [aut, cre, cph]
Maintainer: Rasmus Puggaard-Rode <r.puggaard@phonetik.uni-muenchen.de>

Diff between praatpicture versions 1.4.3 dated 2025-05-13 and 1.5.0 dated 2025-07-11

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New package CompositionalHDDA with initial version 1.0
Package: CompositionalHDDA
Title: High Dimensional Discriminant Analysis with Compositional Data
Version: 1.0
Date: 2025-07-08
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, HDclassif, Rfast, stats
Suggests: Rfast2
Description: High dimensional discriminant analysis with compositional data is performed. The compositional data are first transformed using the alpha-transformation of Tsagris M., Preston S. and Wood A.T.A. (2011) <doi:10.48550/arXiv.1106.1451>, and then the High Dimensional Discriminant Analysis (HDDA) algorithm of Bouveyron C. Girard S. and Schmid C. (2007) <doi:10.1080/03610920701271095> is applied.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2025-07-08 20:13:08 UTC; mtsag
Author: Michail Tsagris [aut, cre]
Repository: CRAN
Date/Publication: 2025-07-11 13:10:02 UTC

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Package validatetools updated to version 0.6.1 with previous version 0.5.2 dated 2023-09-30

Title: Checking and Simplifying Validation Rule Sets
Description: Rule sets with validation rules may contain redundancies or contradictions. Functions for finding redundancies and problematic rules are provided, given a set a rules formulated with 'validate'.
Author: Edwin de Jonge [aut, cre] , Mark van der Loo [aut], Jacco Daalmans [ctb]
Maintainer: Edwin de Jonge <edwindjonge@gmail.com>

Diff between validatetools versions 0.5.2 dated 2023-09-30 and 0.6.1 dated 2025-07-11

 DESCRIPTION                                         |   13 +-
 MD5                                                 |   91 +++++++++---------
 NAMESPACE                                           |    2 
 NEWS.md                                             |   17 +++
 R/categorical.R                                     |    4 
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 man/expect_values.Rd                                |    1 
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 49 files changed, 568 insertions(+), 246 deletions(-)

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New package topolow with initial version 1.0.0
Package: topolow
Title: Antigenic Mapping and Antigenic Velocity Algorithm
Version: 1.0.0
Description: An implementation of the TopoLow algorithm, a novel, physics-inspired method for antigenic cartography. TopoLow addresses significant challenges in mapping antigenic relationships, especially from sparse and noisy experimental data. The package transforms cross-reactivity and binding affinity measurements into accurate spatial representations in a phenotype space. Key features include: * Robust Mapping from Sparse Data: Effectively creates complete and consistent maps even with high proportions of missing data (e.g., >95%). * Physics-Inspired Optimization: Models antigens as particles connected by springs (for measured interactions) and subject to repulsive forces (for missing interactions), reducing the need for complex gradient computations. * Automatic Dimensionality Detection: Employs a likelihood-based approach to determine the optimal number of dimensions for the antigenic map, avoiding distortions common in methods with fixed low dimensions. * Noise and Bias Reduction: Natura [...truncated...]
License: BSD_3_clause + file LICENSE
Encoding: UTF-8
Imports: ggplot2 (>= 3.4.0), dplyr (>= 1.1.0), data.table (>= 1.14.0), reshape2 (>= 1.4.4), stats, utils, plotly (>= 4.10.0), Racmacs (>= 1.1.2), parallel (>= 4.1.0), coda (>= 0.19-4), MASS, vegan, filelock, igraph, lhs, umap, gridExtra, scales, Rtsne, ggrepel, rgl (>= 1.0.0), rlang, ape
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/omid-arhami/topolow
BugReports: https://github.com/omid-arhami/topolow/issues
LazyData: true
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2025-07-07 16:30:10 UTC; aomid
Author: Omid Arhami [aut, cre, cph]
Maintainer: Omid Arhami <omid.arhami@uga.edu>
Repository: CRAN
Date/Publication: 2025-07-11 12:30:02 UTC

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New package tidytitanic with initial version 0.0.1
Package: tidytitanic
Title: Dataframes Based on Titanic Passengers and Crew
Version: 0.0.1
Description: A version of the Titanic survival data tailored for people analytics demonstrations and practice. While another package, 'titanic', reproduces the Kaggle competition files with minimal preprocessing, 'tidytitanic' combines the train and test datasets into the single dataset, 'passengers', for exploration and summary across all passengers. It also extracts personal identifiers—such as first names, last names, and titles from the raw 'name' field, enabling demographic analysis. The 'passengers' data does not cover the crew, but this package also provides the more bare-bones, crew-containing datasets 'tidy_titanic' and 'flat_titanic' based on the 'Titanic' data set from 'datasets' for further exploration. This human-centered data package is designed to support exploratory data analysis, feature engineering, and pedagogical use cases.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2025-07-07 16:50:11 UTC; evangelinereynolds
Author: Evangeline Reynolds [aut, cre]
Maintainer: Evangeline Reynolds <evangeline.mae@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-11 12:30:07 UTC

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Package ResIN updated to version 2.2.0 with previous version 2.1.0 dated 2025-06-13

Title: Response Item Networks
Description: Contains various tools to perform and visualize Response Item Networks ('ResIN's'). 'ResIN' binarizes ordered-categorical and qualitative response choices from (survey) data, calculates pairwise associations and maps the location of each item response as a node in a force-directed network. Please refer to <https://www.resinmethod.net/> for more details.
Author: Philip Warncke [cre, aut], Dino Carpentras [aut], Adrian Lueders [aut]
Maintainer: Philip Warncke <pwarncke@live.unc.edu>

Diff between ResIN versions 2.1.0 dated 2025-06-13 and 2.2.0 dated 2025-07-11

 DESCRIPTION                  |    6 -
 MD5                          |   30 ++---
 R/Boostrap_example.R         |    2 
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 R/globals.R                  |    1 
 data/Bootstrap_example.rda   |binary
 inst/doc/ResIN-VIGNETTE.R    |   29 ++---
 inst/doc/ResIN-VIGNETTE.Rmd  |   51 ++++-----
 inst/doc/ResIN-VIGNETTE.html |  235 +++++++++++++++++++++----------------------
 man/Bootstrap_example.Rd     |    2 
 man/ResIN.Rd                 |    3 
 man/ResIN_boots_extract.Rd   |    2 
 man/ResIN_boots_prepare.Rd   |    4 
 vignettes/ResIN-VIGNETTE.Rmd |   51 ++++-----
 16 files changed, 252 insertions(+), 267 deletions(-)

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New package pridit with initial version 1.0-4
Package: pridit
Title: Principal Component Analysis Applied to Ridit Scoring
Version: 1.0-4
Maintainer: Robert D. Lieberthal <rlieberthal@gmail.com>
Description: Implements the 'PRIDIT' (Principal Component Analysis applied to 'RIDITs') scoring system described in Brockett et al. (2002) <doi:10.1111/1539-6975.00027>. Provides functions for ridit scoring originally developed by Bross (1958) <doi:10.2307/2527727>, calculating 'PRIDIT' weights, and computing final 'PRIDIT' scores for multivariate analysis of ordinal data.
License: Apache License (>= 2)
URL: https://github.com/rlieberthal/PRIDIT
BugReports: https://github.com/rlieberthal/PRIDIT/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-07-08 16:10:02 UTC; rlieberthal
Author: Robert D. Lieberthal [aut, cre]
Repository: CRAN
Date/Publication: 2025-07-11 13:00:02 UTC

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New package MRG with initial version 0.3.10
Package: MRG
Title: Create Non-Confidential Multi-Resolution Grids
Version: 0.3.10
Maintainer: Jon Olav Skoien <jon.skoien@gmail.com>
Imports: magrittr, parallel, terra, sf, stars, plyr, dplyr, rlang, sjmisc, vardpoor, purrr, tidyr, tidyselect, methods, ggplot2, viridis, grDevices, utils
Suggests: patchwork, knitr, rmarkdown, giscoR, bookdown, units, ggforce, kableExtra
Description: The need for anonymization of individual survey responses often leads to many suppressed grid cells in a regular grid. Here we provide functionality for creating multi-resolution gridded data, respecting the confidentiality rules, such as a minimum number of units and dominance by one or more units for each grid cell. The functions also include the possibility for contextual suppression of data. For more details see Skoien et al. (2025) <doi:10.48550/arXiv.2410.17601>.
License: GPL (>= 3)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Depends: R (>= 3.5.0)
LazyData: true
Packaged: 2025-07-08 10:02:59 UTC; skoiejo
Author: Jon Olav Skoien [aut, cre], Nicolas Lampach [aut]
Repository: CRAN
Date/Publication: 2025-07-11 13:00:09 UTC

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New package MeasurementDiagnostics with initial version 0.0.1
Package: MeasurementDiagnostics
Title: Diagnostics for Lists of Codes Based on Measurements
Version: 0.0.1
Description: Diagnostics of list of codes based on concepts from the domains measurement and observation. This package works for data mapped to the Observational Medical Outcomes Partnership Common Data Model.
Imports: cli, CohortConstructor (>= 0.4.0), DBI, dplyr, magrittr, omopgenerics (>= 1.2.0), PatientProfiles (>= 1.4.0), purrr, rlang, tidyr
Suggests: CDMConnector (>= 2.0.0), CodelistGenerator (>= 3.5.0), visOmopResults (>= 1.0.2), duckdb, knitr, omock (>= 0.4.0), rmarkdown, testthat, ggplot2, gt, flextable, RPostgres, lubridate, odbc
Depends: R (>= 4.1)
License: Apache License (>= 2)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-08 15:29:30 UTC; nuriamb
Author: Edward Burn [aut] , Nuria Mercade-Besora [aut, cre] , Marta Alcalde-Herraiz [aut]
Maintainer: Nuria Mercade-Besora <nuria.mercadebesora@ndorms.ox.ac.uk>
Repository: CRAN
Date/Publication: 2025-07-11 13:00:05 UTC

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New package mantar with initial version 0.1.0
Package: mantar
Title: Missingness Alleviation for Network Analysis
Version: 0.1.0
Description: Provides functionality for estimating cross-sectional network structures representing partial correlations in R, while accounting for missing values in the data. Networks are estimated via neighborhood selection, i.e., node-wise multiple regression, with model selection guided by information criteria. Missing data can be handled primarily via multiple imputation or a maximum likelihood-based approach; deletion techniques are available but secondary <doi:10.31234/osf.io/qpj35>.
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Imports: stats
Suggests: mice, lavaan, qgraph, testthat (>= 3.0.0)
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-07-07 20:20:27 UTC; nehler
Author: Kai Jannik Nehler [aut, cre]
Maintainer: Kai Jannik Nehler <nehler@psych.uni-frankfurt.de>
Repository: CRAN
Date/Publication: 2025-07-11 12:40:02 UTC

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New package LoTTA with initial version 0.1.0
Package: LoTTA
Title: Bayesian Inference in Regression Discontinuity Designs
Version: 0.1.0
Description: Implementation of the LoTTA (Local Trimmed Taylor Approximation) model described in "Bayesian Regression Discontinuity Design with Unknown Cutoff" by Kowalska, van de Wiel, van der Pas (2024) <doi:10.48550/arXiv.2406.11585>.
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats, bayestestR, utils
Depends: R (>= 4.4.0), runjags, ggplot2, ggpubr
NeedsCompilation: no
Packaged: 2025-07-07 15:29:27 UTC; juliakowalska
Author: Julia Kowalska [aut, cre, cph]
Maintainer: Julia Kowalska <j.m.kowalska@vu.nl>
Repository: CRAN
Date/Publication: 2025-07-11 12:20:02 UTC

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New package junco with initial version 0.1.1
Package: junco
Title: Create Common Tables and Listings Used in Clinical Trials
Version: 0.1.1
Date: 2025-06-20
Description: Structure and formatting requirements for clinical trial table and listing outputs vary between pharmaceutical companies. 'junco' provides additional tooling for use alongside the 'rtables', 'rlistings' and 'tern' packages when creating table and listing outputs. While motivated by the specifics of Johnson and Johnson Clinical and Statistical Programming's table and listing shells, 'junco' provides functionality that is general and reusable. Major features include a) alternative and extended statistical analyses beyond what 'tern' supports for use in standard safety and efficacy tables, b) a robust production-grade Rich Text Format (RTF) exporter for both tables and listings, c) structural support for spanning column headers and risk difference columns in tables, and d) robust font-aware automatic column width algorithms for both listings and tables.
License: Apache License (>= 2)
URL: https://github.com/johnsonandjohnson/junco, https://johnsonandjohnson.github.io/junco/
BugReports: https://github.com/johnsonandjohnson/junco/issues
Depends: R (>= 4.4), formatters (>= 0.5.6), rtables (>= 0.6.13)
Imports: tidytlg (>= 0.1.5), tern (>= 0.9.9), rlistings (>= 0.2.11), checkmate (>= 2.1.0), broom, methods, dplyr, generics, stats, survival, tibble, utils, emmeans, mmrm, rbmi (>= 1.3.0), assertthat
Encoding: UTF-8
Language: en-US
Suggests: knitr, rmarkdown, forcats (>= 1.0.0), testthat (>= 3.0.0), mockery, parallel, readxl, pharmaverseadam, rlang
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-08 02:42:37 UTC; gbecker
Author: Gabriel Becker [cre, aut] , Ilse Augustyns [aut], Paul Jenkins [aut], Daniel Hofstaedter [aut], Joseph Kovach [aut], David Munoz Tord [aut], Daniel Sabanes Bove [aut], Ezequiel Anokian [ctb], Renfei Mao [ctb], Mrinal Das [ctb], Isaac Gravestock [cph] [...truncated...]
Maintainer: Gabriel Becker <gabembecker@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-11 12:50:06 UTC

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New package fusedTree with initial version 1.0.1
Package: fusedTree
Title: Fused Partitioned Regression for Clinical and Omics Data
Version: 1.0.1
Description: Fit (generalized) linear regression models in each leaf node of a tree. The tree is constructed using clinical variables only. The linear regression models are constructed using (high-dimensional) omics variables only. The leaf-node-specific regression models are estimated using the penalized likelihood including a standard ridge (L2) penalty and a fusion penalty that links the leaf-node-specific regression models to one another. The intercepts of the leaf nodes reflect the effects of the clinical variables and are left unpenalized. The tree, fitted with the clinical variables only, should be constructed outside of the package with the 'rpart' 'R' package. See Goedhart and others (2024) <doi:10.48550/arXiv.2411.02396> for details on the method.
License: GPL (>= 3)
Encoding: UTF-8
Imports: Matrix, splitTools, survival, treeClust
Suggests: rpart
NeedsCompilation: no
Packaged: 2025-07-07 16:52:44 UTC; P072713
Author: Jeroen M. Goedhart [aut, cre, cph] , Wessel N. van Wieringen [aut] , Thomas Klausch [ths], Mark A. van de Wiel [ths], Hanarth Fonds [fnd]
Maintainer: Jeroen M. Goedhart <jeroengoed@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-11 12:30:10 UTC

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New package armaOptions with initial version 1.0.0
Package: armaOptions
Title: ARMA Models to Value Stock Options
Version: 1.0.0
Maintainer: Brian MacCarvill <brianmaccarvills@gmail.com>
Description: Providing ways to estimate the value of European stock options given historical stock price data. It includes functions for calculating option values based on autoregressive–moving-average (ARMA) models and generates information about these models. This package is make to be easy to understand and for financial analysis capabilities.
License: GPL-3
Encoding: UTF-8
Imports: forecast, stats
NeedsCompilation: no
Packaged: 2025-07-07 19:32:26 UTC; brian
Author: Brian MacCarvill [aut, cre]
Repository: CRAN
Date/Publication: 2025-07-11 12:40:06 UTC

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New package ArctosR with initial version 0.1.0
Package: ArctosR
Title: An Interface to the 'Arctos' Database
Version: 0.1.0
Maintainer: Harlan Williams <harlanrhwilliams@gmail.com>
Date: 2025-6-30
Description: Performs requests to the 'Arctos' API to download data. Provides a set of builder classes for performing complex requests, as well as a set of simple functions for automating many common requests and workflows. More information about 'Arctos' can be found in Cicero et al. (2024) <doi:10.1371/journal.pone.0296478> or on their website <https://arctosdb.org/>.
URL: https://github.com/hrhwilliams/arctosr
BugReports: https://github.com/hrhwilliams/arctosr/issues
Depends: R (>= 4.1.0)
License: GPL-3
Encoding: UTF-8
Imports: R6 (>= 2.5.1), curl (>= 5.0.0), jsonlite (>= 1.8.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-07-07 16:57:59 UTC; harla
Author: Harlan Williams [aut, cre], Marlon E. Cobos [aut], Jocelyn P. Colella [aut], Michelle S. Koo [aut], Vijay Barve [aut]
Repository: CRAN
Date/Publication: 2025-07-11 12:40:13 UTC

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Package red updated to version 1.6.3 with previous version 1.6.2 dated 2025-05-10

Title: IUCN Redlisting Tools
Description: Includes algorithms to facilitate the assessment of extinction risk of species according to the IUCN (International Union for Conservation of Nature, see <https://iucn.org/> for more information) red list criteria.
Author: Pedro Cardoso [aut] , Vasco V. Branco [cre, aut]
Maintainer: Vasco V. Branco <vasco.branco@helsinki.fi>

Diff between red versions 1.6.2 dated 2025-05-10 and 1.6.3 dated 2025-07-11

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Package SchoolDataIT updated to version 0.2.7 with previous version 0.2.6 dated 2025-05-14

Title: Retrieve, Harmonise and Map Open Data Regarding the Italian School System
Description: Compiles and displays the available data sets regarding the Italian school system, with a focus on the infrastructural aspects. Input datasets are downloaded from the web, with the aim of updating everything to real time. The functions are divided in four main modules, namely 'Get', to scrape raw data from the web 'Util', various utilities needed to process raw data 'Group', to aggregate data at the municipality or province level 'Map', to visualize the output datasets.
Author: Leonardo Cefalo [aut, cre] , Alessio Pollice [ctb, ths] , Paolo Maranzano [ctb]
Maintainer: Leonardo Cefalo <leonardo.cefalo@uniba.it>

Diff between SchoolDataIT versions 0.2.6 dated 2025-05-14 and 0.2.7 dated 2025-07-11

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New package jrSiCKLSNMF with initial version 1.2.3
Package: jrSiCKLSNMF
Title: Multimodal Single-Cell Omics Dimensionality Reduction
Version: 1.2.3
Description: Methods to perform Joint graph Regularized Single-Cell Kullback-Leibler Sparse Non-negative Matrix Factorization ('jrSiCKLSNMF', pronounced "junior sickles NMF") on quality controlled single-cell multimodal omics count data. 'jrSiCKLSNMF' specifically deals with dual-assay scRNA-seq and scATAC-seq data. This package contains functions to extract meaningful latent factors that are shared across omics modalities. These factors enable accurate cell-type clustering and facilitate visualizations. Methods for pre-processing, clustering, and mini-batch updates and other adaptations for larger datasets are also included. For further details on the methods used in this package please see Ellis, Roy, and Datta (2023) <doi:10.3389/fgene.2023.1179439>.
License: GPL-3
Encoding: UTF-8
Imports: Rcpp (>= 1.0.9), igraph, umap, kknn, ggplot2, methods, stats, rlang, Matrix, data.table,parallel,pbapply,cluster,MASS,clValid,factoextra, foreach,irlba,scran,Rdpack,ggrepel
Suggests: knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo, RcppProgress
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2025-07-11 09:06:41 UTC; dorothyellis
Author: Dorothy Ellis [aut, cre] , Susmita Datta [ths], Kenneth Perkins [ctb] , Renaud Gaujoux [ctb]
Maintainer: Dorothy Ellis <ddemoreellis@gmail.com>
Depends: R (>= 3.5.0)
Repository: CRAN
Date/Publication: 2025-07-11 10:10:02 UTC

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Package easystats updated to version 0.7.5 with previous version 0.7.4 dated 2025-02-06

Title: Framework for Easy Statistical Modeling, Visualization, and Reporting
Description: A meta-package that installs and loads a set of packages from 'easystats' ecosystem in a single step. This collection of packages provide a unifying and consistent framework for statistical modeling, visualization, and reporting. Additionally, it provides articles targeted at instructors for teaching 'easystats', and a dashboard targeted at new R users for easily conducting statistical analysis by accessing summary results, model fit indices, and visualizations with minimal programming.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut] , Mattan S. Ben-Shachar [aut] , Indrajeet Patil [aut] , Brenton M. Wiernik [aut] , Etienne Bacher [aut] , Remi Theriault [aut]
Maintainer: Daniel Luedecke <d.luedecke@uke.de>

Diff between easystats versions 0.7.4 dated 2025-02-06 and 0.7.5 dated 2025-07-11

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New package spinebil with initial version 0.1.6
Package: spinebil
Title: Investigating New Projection Pursuit Index Functions
Version: 0.1.6
Description: Projection pursuit is used to find interesting low-dimensional projections of high-dimensional data by optimizing an index over all possible projections. The 'spinebil' package contains methods to evaluate the performance of projection pursuit index functions using tour methods. A paper describing the methods can be found at <doi:10.1007/s00180-020-00954-8>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: tourr, ggplot2, tibble, stats, dplyr, tidyr, tictoc, cassowaryr
Suggests: minerva, testthat, purrr
NeedsCompilation: no
Packaged: 2025-07-11 05:07:34 UTC; tras0007
Author: Ursula Laa [aut] , Dianne Cook [aut] , Tina Rashid Jafari [aut, cre]
Maintainer: Tina Rashid Jafari <tina.rashidjafari@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-11 08:20:02 UTC

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Package longmemo updated to version 1.1-4 with previous version 1.1-3 dated 2024-07-30

Title: Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality
Description: Datasets and Functionality from 'Jan Beran' (1994). Statistics for Long-Memory Processes; Chapman & Hall. Estimation of Hurst (and more) parameters for fractional Gaussian noise, 'fARIMA' and 'FEXP' models.
Author: Jan Beran [aut] , Martin Maechler [cre, aut] , Brandon Whitcher [ctb]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

Diff between longmemo versions 1.1-3 dated 2024-07-30 and 1.1-4 dated 2025-07-11

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New package ironseed with initial version 0.1.0
Package: ironseed
Title: Improved Random Number Generator Seeding
Version: 0.1.0
Description: A procedure for seeding R's built in random number generators using a variable-length sequence of values. Accumulates input entropy into a 256-bit hash digest or "ironseed" and is able to generate a variable-length sequence of output seeds from an ironseed.
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Biarch: TRUE
NeedsCompilation: yes
URL: https://github.com/reedacartwright/ironseed
BugReports: https://github.com/reedacartwright/ironseed/issues
Suggests: tinytest
Packaged: 2025-07-06 21:50:57 UTC; reed
Author: Reed Cartwright [aut, cre]
Maintainer: Reed Cartwright <racartwright@gmail.com>
Repository: CRAN
Date/Publication: 2025-07-11 08:40:02 UTC

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Package coat updated to version 0.2.2 with previous version 0.2.1 dated 2025-06-27

Title: Conditional Method Agreement Trees (COAT)
Description: Agreement of continuously scaled measurements made by two techniques, devices or methods is usually evaluated by the well-established Bland-Altman analysis or plot. Conditional method agreement trees (COAT), proposed by Karapetyan, Zeileis, Henriksen, and Hapfelmeier (2025) <doi:10.1093/jrsssc/qlae077>, embed the Bland-Altman analysis in the framework of recursive partitioning to explore heterogeneous method agreement in dependence of covariates. COAT can also be used to perform a Bland-Altman test for differences in method agreement.
Author: Alexander Hapfelmeier [aut, cre] , Siranush Karapetyan [aut] , Achim Zeileis [aut]
Maintainer: Alexander Hapfelmeier <Alexander.Hapfelmeier@mri.tum.de>

Diff between coat versions 0.2.1 dated 2025-06-27 and 0.2.2 dated 2025-07-11

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Package SparseBiplots updated to version 4.1.1 with previous version 4.0.2 dated 2025-05-26

Title: 'HJ-Biplot' using Different Ways of Penalization Plotting with 'ggplot2'
Description: The 'HJ-Biplot' is a multivariate method that represents high-dimensional data in a low-dimensional subspace, capturing most of the information’s variability in just a few dimensions. This package implements three new regularized versions of the HJ-Biplot: Ridge, LASSO, and Elastic Net. These versions introduce restrictions that shrink or zero-out variable weights to improve interpretability based on regularization theory. All methods provide graphical representations using 'ggplot2'.
Author: Mitzi Isabel Cubilla-Montilla [aut, cre], Carlos Alfredo Torres-Cubilla [aut], Maria Purificacion Galindo Villardon [aut], Ana Belen Nieto-Librero [aut]
Maintainer: Mitzi Isabel Cubilla-Montilla <mitzi@usal.es>

Diff between SparseBiplots versions 4.0.2 dated 2025-05-26 and 4.1.1 dated 2025-07-11

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Package SoilTaxonomy updated to version 0.2.8 with previous version 0.2.7 dated 2025-04-05

Title: A System of Soil Classification for Making and Interpreting Soil Surveys
Description: Taxonomic dictionaries, formative element lists, and functions related to the maintenance, development and application of U.S. Soil Taxonomy. Data and functionality are based on official U.S. Department of Agriculture sources including the latest edition of the Keys to Soil Taxonomy. Descriptions and metadata are obtained from the National Soil Information System or Soil Survey Geographic databases. Other sources are referenced in the data documentation. Provides tools for understanding and interacting with concepts in the U.S. Soil Taxonomic System. Most of the current utilities are for working with taxonomic concepts at the "higher" taxonomic levels: Order, Suborder, Great Group, and Subgroup.
Author: Andrew Brown [aut, cre], Dylan Beaudette [aut]
Maintainer: Andrew Brown <andrew.g.brown@usda.gov>

Diff between SoilTaxonomy versions 0.2.7 dated 2025-04-05 and 0.2.8 dated 2025-07-11

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Package rgrass updated to version 0.5-3 with previous version 0.5-2 dated 2025-02-14

Title: Interface Between 'GRASS' Geographical Information System and 'R'
Description: An interface between the 'GRASS' geographical information system ('GIS') and 'R', based on starting 'R' from within the 'GRASS' 'GIS' environment, or running a free-standing 'R' session in a temporary 'GRASS' location; the package provides facilities for using all 'GRASS' commands from the 'R' command line. The original interface package for 'GRASS 5' (2000-2010) is described in Bivand (2000) <doi:10.1016/S0098-3004(00)00057-1> and Bivand (2001) <https://www.r-project.org/conferences/DSC-2001/Proceedings/Bivand.pdf>. This was succeeded by 'spgrass6' for 'GRASS 6' (2006-2016) and 'rgrass7' for 'GRASS 7' (2015-present). The 'rgrass' package modernizes the interface for 'GRASS 8' while still permitting the use of 'GRASS 7'.
Author: Roger Bivand [aut] , Sebastian Jeworutzki [ctb] , Rainer Krug [ctb] , Robin Lovelace [ctb] , Markus Neteler [ctb] , Steven Pawley [cre, aut] , Floris Vanderhaeghe [ctb]
Maintainer: Steven Pawley <dr.stevenpawley@gmail.com>

Diff between rgrass versions 0.5-2 dated 2025-02-14 and 0.5-3 dated 2025-07-11

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Package earthdatalogin updated to version 0.0.3 with previous version 0.0.2 dated 2023-12-15

Title: NASA 'EarthData' Access Utilities
Description: Providing easy, portable access to NASA 'EarthData' products through the use of bearer tokens. Much of NASA's public data catalogs hosted and maintained by its 12 Distributed Active Archive Centers ('DAACs') are now made available on the Amazon Web Services 'S3' storage. However, accessing this data through the standard 'S3' API is restricted to only to compute resources running inside 'us-west-2' Data Center in Portland, Oregon, which allows NASA to avoid being charged data egress rates. This package provides public access to the data from any networked device by using the 'EarthData' login application programming interface (API), <https://www.earthdata.nasa.gov/data/earthdata-login>, providing convenient authentication and access to cloud-hosted NASA 'EarthData' products. This makes access to a wide range of earth observation data from any location straight forward and compatible with R packages that are widely used with cloud native earth observation data (such as 'terra', 's [...truncated...]
Author: Carl Boettiger [aut, cre, cph] , Luis Lopez [aut] , Yuvi Panda [aut], Bri Lind [aut] , Andy Teucher [ctb] , Openscapes [fnd]
Maintainer: Carl Boettiger <cboettig@gmail.com>

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Package AccSamplingDesign updated to version 0.0.5 with previous version 0.0.4 dated 2025-06-26

Title: Acceptance Sampling Plans Design
Description: Provides tools for designing and analyzing Acceptance Sampling plans. Supports both Attributes Sampling (Binomial and Poisson distributions) and Variables Sampling (Normal and Beta distributions), enabling quality control for fractional and compositional data. Uses nonlinear programming for sampling plan optimization, minimizing sample size while controlling producer's and consumer's risks. Operating Characteristic curves are available for plan visualization.
Author: Ha Truong [aut, cre, cph], Victor Miranda [ths, rev], Roger Kissling [ths, rev]
Maintainer: Ha Truong <truongvietha87@gmail.com>

Diff between AccSamplingDesign versions 0.0.4 dated 2025-06-26 and 0.0.5 dated 2025-07-11

 AccSamplingDesign-0.0.4/AccSamplingDesign/man/OCdata-accessors.Rd    |only
 AccSamplingDesign-0.0.5/AccSamplingDesign/DESCRIPTION                |    6 
 AccSamplingDesign-0.0.5/AccSamplingDesign/MD5                        |   25 
 AccSamplingDesign-0.0.5/AccSamplingDesign/NAMESPACE                  |   24 
 AccSamplingDesign-0.0.5/AccSamplingDesign/R/OCdata.R                 |  311 ++--------
 AccSamplingDesign-0.0.5/AccSamplingDesign/R/manualPlan.R             |only
 AccSamplingDesign-0.0.5/AccSamplingDesign/R/optVarPlan.R             |    8 
 AccSamplingDesign-0.0.5/AccSamplingDesign/R/summary.R                |   75 +-
 AccSamplingDesign-0.0.5/AccSamplingDesign/README.md                  |   23 
 AccSamplingDesign-0.0.5/AccSamplingDesign/inst/doc/introduction.R    |   36 -
 AccSamplingDesign-0.0.5/AccSamplingDesign/inst/doc/introduction.Rmd  |   36 -
 AccSamplingDesign-0.0.5/AccSamplingDesign/inst/doc/introduction.html |  252 +++-----
 AccSamplingDesign-0.0.5/AccSamplingDesign/man/OCdata.Rd              |  125 ----
 AccSamplingDesign-0.0.5/AccSamplingDesign/man/manualPlan.Rd          |only
 AccSamplingDesign-0.0.5/AccSamplingDesign/vignettes/introduction.Rmd |   36 -
 15 files changed, 374 insertions(+), 583 deletions(-)

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