Sat, 17 Oct 2026

Package sundialr updated to version 0.2.1 with previous version 0.2.0 dated 2026-08-07

Title: An Interface to 'SUNDIALS' Ordinary Differential Equation (ODE) Solvers
Description: Provides a way to call the functions in 'SUNDIALS' C ODE solving library (<https://computing.llnl.gov/projects/sundials>). Currently the serial version of ODE solver, 'CVODE', sensitivity calculator 'CVODES' and differential algebraic solver 'IDA' from the 'SUNDIALS' library are implemented. The package requires ODE to be written as an 'R' or 'Rcpp' function and does not require the 'SUNDIALS' library to be installed on the local machine.
Author: Satyaprakash Nayak [aut, cre, cph] , Lawrence Livermore National Security [cph], Southern Methodist University [cph], University of Maryland Baltimore County [cph]
Maintainer: Satyaprakash Nayak <satyaprakash.nayak@gmail.com>

Diff between sundialr versions 0.2.0 dated 2026-08-07 and 0.2.1 dated 2026-10-17

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More information about sundialr at CRAN
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Package stratifyR updated to version 2.0-3 with previous version 2.0-2 dated 2026-10-14

Title: Optimal Stratification of Univariate Populations
Description: Determines Optimum Strata Boundaries (OSB) and Optimum Sample Sizes (OSS) for univariate stratified sampling designs under Neyman allocation. The stratification variable is described by a best-fitting parametric distribution, selected automatically by AIC from a set of continuous families (normal, log-normal, gamma, Weibull, exponential, Cauchy, uniform, Pareto, triangular and right-triangular), and the optimum boundaries are obtained by minimising the Neyman objective. Version 2.0 keeps the Dynamic Programming (DP) solver of Reddy and Khan (2020), which is globally optimal for the fitted distribution, as the default. It adds two fast derivative-free solvers, a multi-start 'COBYLA' solver and a two-phase global solver that couples 'DIRECT-L' with 'BOBYQA' refinement, and an exact solver that runs dynamic programming on the sorted data and returns the partition with the smallest empirical Neyman cost. It also provides cost-constrained allocation with unequal per-stratum costs, a desi [...truncated...]
Author: Karuna G. Reddy [aut, cre] , M. G. M. Khan [aut]
Maintainer: Karuna G. Reddy <karuna.reddy@auckland.ac.nz>

Diff between stratifyR versions 2.0-2 dated 2026-10-14 and 2.0-3 dated 2026-10-17

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More information about stratifyR at CRAN
Permanent link

Package RcppAlgos updated to version 2.10.2 with previous version 2.10.1 dated 2026-06-08

Title: High Performance Tools for Combinatorics and Computational Mathematics
Description: Provides optimized functions and flexible iterators implemented in C++ for solving problems in combinatorics and computational mathematics. Handles various combinatorial objects including combinations, permutations, integer partitions and compositions, Cartesian products, unordered Cartesian products, and partition of groups. Utilizes the RMatrix class from 'RcppParallel' for thread safety. The combination and permutation functions contain constraint parameters that allow for generation of all results of a vector meeting specific criteria (e.g. finding all combinations such that the sum is between two bounds). Capable of ranking/unranking combinatorial objects efficiently (e.g. retrieve only the nth lexicographical result) which sets up nicely for parallelization as well as random sampling. Gmp support permits exploration where the total number of results is large (e.g. comboSample(10000, 500, n = 4)). Additionally, there are several high performance number theoretic functions that are [...truncated...]
Author: Joseph Wood [aut, cre], Joseph J. Allaire [ctb]
Maintainer: Joseph Wood <jwood000@gmail.com>

Diff between RcppAlgos versions 2.10.1 dated 2026-06-08 and 2.10.2 dated 2026-10-17

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More information about RcppAlgos at CRAN
Permanent link

Package tikatuwq updated to version 0.11.0 with previous version 0.10.0 dated 2026-08-31

Title: Water Quality Assessment and Environmental Compliance in Brazil
Description: Tools to import, clean, validate, and analyze freshwater quality data in Brazil. Implements water quality indices including the Water Quality Index ('WQI'/'IQA') using the weighted geometric mean following 'CETESB' methodology, an independent engine reproducing the 'IQA' of the Minas Gerais water agency 'IGAM' (a documented reproduction, not endorsed by the agency), paired comparison of 'IQA' engines with compare_iqa(), the Trophic State Index ('TSI'/'IET') after Carlson (1977) <doi:10.4319/lo.1977.22.2.0361> and Lamparelli (2004) <https://teses.usp.br/teses/disponiveis/41/41134/tde-20032006-075813/publico/TeseLamparelli2004.pdf>, and the National Sanitation Foundation Water Quality Index ('NSF WQI', Brown (1970)). The package also checks compliance with Brazilian standard 'CONAMA' Resolution 357/2005 <https://conama.mma.gov.br/?id=450&option=com_sisconama&task=arquivo.download> including the legal frequency rule (Art. 15, 80% conformity over six or more sampl [...truncated...]
Author: Vinicius Saraiva Santos [aut, cre] , Fabricio Berton Zanchi [ctb]
Maintainer: Vinicius Saraiva Santos <vinisaraiva@gmail.com>

Diff between tikatuwq versions 0.10.0 dated 2026-08-31 and 0.11.0 dated 2026-10-17

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Package stepwedgepower updated to version 0.4.1 with previous version 0.1.3 dated 2026-07-13

Title: Simulation-Based Power Evaluation for Stepped-Wedge Cluster Randomized Trials
Description: Provides simulation-based power, type I error, and operating- characteristic evaluation for stepped-wedge cluster randomized trials. General binary-outcome designs support arbitrary crossover schedules, unequal clusters per sequence, secular trends, flexible cluster-period sizes, reproducible parallel execution, sensitivity grids, and mixed-model diagnostics. A component-based engine supports the four treatment states Control, A, B, and A+B under arbitrary asynchronous schedules, including structurally unobserved cluster-periods, withdrawal, reintroduction, wash-in delays, user-defined carryover decay, component main effects, an A-by-B interaction, estimability audits, multiplicity adjustment, conditional and failure-aware power, and explicit classification of hard model errors, nonconvergence, non-finite contrasts, singular fits, and successful fits. A batch-aware interface represents classic and batched stepped-wedge designs with delayed cluster initiation, structurally unobserved cl [...truncated...]
Author: Lin Li [aut, cre], Florin Vaida [aut]
Maintainer: Lin (Amanda) Li <amandali14124277@gmail.com>

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Package rsynthbio updated to version 4.2.3 with previous version 4.2.2 dated 2026-10-14

Title: Synthesize Bio API Wrapper
Description: Access Synthesize Bio models from their API <https://app.synthesize.bio/> using this wrapper that provides a convenient interface to the Synthesize Bio API, allowing users to generate realistic gene expression data based on specified biological conditions. This package enables researchers to easily access AI-generated transcriptomic data for various modalities including bulk RNA-seq, single-cell RNA-seq, microarray data, and more.
Author: Synthesize Bio [aut], Alex David [aut, cre]
Maintainer: Alex David <alex@synthesize.bio>

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Package reporter updated to version 1.5.0 with previous version 1.4.9 dated 2026-09-12

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], Bill Huang [aut], Kevin Kramer [ctb], Duong Tran [ctb], Raphael Huang [ctb], Archytas Clinical Solutions [cph]
Maintainer: David Bosak <dbosak01@gmail.com>

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Package progressify updated to version 0.4.0 with previous version 0.2.0 dated 2026-05-31

Title: Progress Reporting of Common Functions via One Magic Function
Description: The progressify() function rewrites (transpiles) calls to sequential and parallel map-reduce functions such as base::lapply(), purrr::map(), foreach::foreach(), and plyr::llply() to signal progress updates. By combining this function with R's native pipe operator, you have a straightforward way to report progress on iterative computations with minimal refactoring, e.g. 'lapply(x, fcn) |> progressify()' and 'purrr::map(x, fcn) |> progressify()'. It is compatible with the parallel-processing map-reduce packages 'future.apply', 'furrr', 'crossmap', 'foreach', 'doFuture', and 'futurize'. It also supports domain-specific packages including 'boot', 'fwb', 'lme4', 'partykit', 'sandwich', and 'SimDesign', e.g. 'boot::boot(data, stat, R) |> progressify()'.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between progressify versions 0.2.0 dated 2026-05-31 and 0.4.0 dated 2026-10-17

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Package IsoplotRgui updated to version 7.1 with previous version 7.0 dated 2026-08-21

Title: Web Interface to 'IsoplotR'
Description: Provides a graphical user interface to the 'IsoplotR' package for radiometric geochronology. The GUI runs in an internet browser and can either be used offline, or hosted on a server to provide online access to the 'IsoplotR' toolbox.
Author: Pieter Vermeesch [aut, cre], Tim Band [ctb]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Permanent link

Package gcplyr updated to version 1.13.1 with previous version 1.12.0 dated 2025-07-29

Title: Wrangle and Analyze Growth Curve Data
Description: Easy importing, wrangling, and model-free analysis of microbial growth curve data, as commonly output by plate readers. Tools for flexibly importing all the common data formats output by plate readers and reshaping them into 'tidy' formats for analyses. Tools for importing experimental designs from files or generating them in R and merging design information with density data, making it easy to analyze with 'gcplyr' and 'tidyverse' or 'dplyr' functions, and to plot with 'ggplot2'. Streamlines extracting parameters like growth rate/doubling time, maximum density (carrying capacity), lag time, area under the curve, diauxic shifts, extinction, and more without fitting an equation for growth to your data. Has several methods to deal with noise in growth curve data. See methods at <https://mikeblazanin.github.io/gcplyr/>.
Author: Mike Blazanin [aut, cre]
Maintainer: Mike Blazanin <mikeblazanin@gmail.com>

Diff between gcplyr versions 1.12.0 dated 2025-07-29 and 1.13.1 dated 2026-10-17

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Permanent link

Package datawizard updated to version 1.4.1 with previous version 1.4.0 dated 2026-09-10

Title: Easy Data Wrangling and Statistical Transformations
Description: A lightweight package to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. It is also the data wrangling backend for packages in 'easystats' ecosystem. References: Patil et al. (2022) <doi:10.21105/joss.04684>.
Author: Jeffrey Girard [aut, cre] , Indrajeet Patil [aut] , Etienne Bacher [aut] , Dominique Makowski [aut] , Daniel Luedecke [aut] , Mattan S. Ben-Shachar [aut] , Brenton M. Wiernik [aut] , Remi Theriault [ctb] , Elin Waring [ctb], Thomas J. Faulkenberry [re [...truncated...]
Maintainer: Jeffrey Girard <me@jmgirard.com>

Diff between datawizard versions 1.4.0 dated 2026-09-10 and 1.4.1 dated 2026-10-17

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More information about datawizard at CRAN
Permanent link

Package confoundvis updated to version 0.3.0 with previous version 0.2.0 dated 2026-09-30

Title: A Common Interface for Visualizing and Reporting Sensitivity Analyses for Unmeasured Confounding
Description: A common interface to established sensitivity analyses for unmeasured confounding in observational studies. Results of impact threshold and robustness of inference to replacement analysis (Frank, 2000, <doi:10.1177/0049124100029002001>; Frank et al., 2013, <doi:10.3102/0162373713493129>), partial R-squared omitted-variable bias analysis (Cinelli and Hazlett, 2020, <doi:10.1111/rssb.12348>), E-values (VanderWeele and Ding, 2017, <doi:10.7326/M16-2607>), and Rosenbaum bounds for matched pairs (Rosenbaum, 2002, <doi:10.1007/978-1-4757-3692-2>) are stored in one object that keeps each framework's own parameter. Robustness curves, summary tables, and plain-language reports are available for every framework; two-parameter surfaces, the exact correlation contour, and observed-covariate benchmarks are provided where the corresponding framework defines them. Results can be computed from fitted models or matched-pair differences, or converted from the 'sensemakr', ' [...truncated...]
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>

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Package amorem updated to version 1.1.0 with previous version 1.0.0 dated 2026-06-29

Title: Augmented Modelling of Relational Events
Description: An integrated workflow for relational event models, in which timestamped interactions among actors arrive in continuous time and the event rate depends on the history of the network itself. Event streams are simulated by an exact Gillespie kernel or an approximate tau-leap kernel; non-events are drawn by case-control sampling in the manner of Lerner and Lomi (2020) <doi:10.1017/nws.2019.57>, or from a time-shifted copy of the process so that covariates shared by all dyads at a given time remain estimable (Lembo et al. 2025, <doi:10.1093/jrsssc/qlaf058>); the timing- and closure-based endogenous statistics of Juozaitiene and Wit (2024) <doi:10.1093/jrsssa/qnae132> are computed from that history; and one front-end fits the resulting case-control data by conditional-logistic partial likelihood, by penalised regression on its degenerate one-control binomial form (which admits smooth, time-varying and actor random effects), or by stochastic gradient descent, including the [...truncated...]
Author: Francisco Richter [aut, cre, cph], Martina Boschi [aut], Ernst C. Wit [aut], Melania Lembo [aut]
Maintainer: Francisco Richter <richtf@usi.ch>

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Package teems updated to version 1.0.0 with previous version 0.1.1 dated 2026-06-17

Title: Trade and Environment Equilibrium Modeling System
Description: Equilibrium models are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. The 'teems' package handles all aspects of running equilibrium models while facilitating transparent and reproducible workflows.
Author: Matthew Cantele [aut, cre, cph] , Tom Kompas [ctb, ths] , Ha Van Pham [ctb] , Martin Ingram [ctb]
Maintainer: Matthew Cantele <matthew.cantele@protonmail.com>

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Package DataQualityDashboard updated to version 2.9.1 with previous version 2.9.0 dated 2026-10-06

Title: Execute and View Data Quality Checks on OMOP CDM Database
Description: Assesses data quality in Observational Medical Outcomes Partnership Common Data Model (OMOP CDM) databases. Executes data quality checks and provides an R 'shiny' application to view the results.
Author: Katy Sadowski [aut, cre], Clair Blacketer [aut], Maxim Moinat [aut], Ajit Londhe [aut], Anthony Sena [aut], Anthony Molinaro [aut], Frank DeFalco [aut], Pavel Grafkin [aut]
Maintainer: Katy Sadowski <sadowski@ohdsi.org>

Diff between DataQualityDashboard versions 2.9.0 dated 2026-10-06 and 2.9.1 dated 2026-10-17

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Package mlr3cluster updated to version 0.7.0 with previous version 0.6.0 dated 2026-09-17

Title: Cluster Extension for 'mlr3'
Description: Extends the 'mlr3' package with cluster analysis.
Author: Maximilian Muecke [aut, cre] , Damir Pulatov [aut], Michel Lang [aut] , Marc Becker [ctb]
Maintainer: Maximilian Muecke <muecke.maximilian@gmail.com>

Diff between mlr3cluster versions 0.6.0 dated 2026-09-17 and 0.7.0 dated 2026-10-17

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 mlr3cluster-0.7.0/mlr3cluster/MD5                                                   |  233 ++++------
 mlr3cluster-0.7.0/mlr3cluster/NAMESPACE                                             |    3 
 mlr3cluster-0.7.0/mlr3cluster/NEWS.md                                               |   41 +
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClust.R                                      |   21 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustAffinityPropagation.R                   |   49 +-
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustAgnes.R                                 |    8 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustCLARA.R                                 |   11 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustCMeans.R                                |   10 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustCobweb.R                                |    7 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustDBSCAN.R                                |   14 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustDBSCANfpc.R                             |   23 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustDiana.R                                 |   13 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustEM.R                                    |    6 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustFanny.R                                 |    8 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustFarthestFirst.R                         |    7 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustFeatureless.R                           |    8 
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 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustGenie.R                                 |    4 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustHDBSCAN.R                               |   19 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustHclust.R                                |    4 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustKCCA.R                                  |    4 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustKKMeans.R                               |   12 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustKMeans.R                                |    6 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustKMeansRcpp.R                            |   14 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustKModes.R                                |   15 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustKProto.R                                |   20 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustMclust.R                                |    6 
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 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustMiniBatchKMeans.R                       |   14 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustMovMF.R                                 |    6 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustOPTICS.R                                |   18 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustPAM.R                                   |   11 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustProtoclust.R                            |   22 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustSKMeans.R                               |    8 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustSOM.R                                   |    4 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustSTDBSCAN.R                              |   16 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustSimpleKMeans.R                          |    7 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustSpectral.R                              |    7 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustTclust.R                                |   17 
 mlr3cluster-0.7.0/mlr3cluster/R/LearnerClustXMeans.R                                |    8 
 mlr3cluster-0.7.0/mlr3cluster/R/MeasureClustSimple.R                                |    2 
 mlr3cluster-0.7.0/mlr3cluster/R/PredictionDataClust.R                               |    6 
 mlr3cluster-0.7.0/mlr3cluster/R/TaskGeneratorBlobs.R                                |    9 
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 mlr3cluster-0.7.0/mlr3cluster/R/cluster_stats.R                                     |    5 
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 mlr3cluster-0.7.0/mlr3cluster/R/zzz.R                                               |    9 
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 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_LearnerClust.R                    |    6 
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 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_cmeans.R       |   10 
 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_cobweb.R       |    7 
 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_dbscan.R       |    1 
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 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_em.R           |    7 
 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_ff.R           |    7 
 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_flexmix.R      |   18 
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 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_kmeans.R       |    6 
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 mlr3cluster-0.7.0/mlr3cluster/tests/testthat/test_mlr_learners_clust_kproto.R       |   16 
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More information about mlr3cluster at CRAN
Permanent link

Package mcmcsae updated to version 0.8.2 with previous version 0.8.1 dated 2026-07-20

Title: Markov Chain Monte Carlo Small Area Estimation
Description: Fit multi-level models with possibly correlated random effects using Markov Chain Monte Carlo simulation. Such models allow smoothing over space and time and are useful in, for example, small area estimation.
Author: Harm Jan Boonstra [aut, cre], Grzegorz Baltissen [ctb]
Maintainer: Harm Jan Boonstra <hjboonstra@gmail.com>

Diff between mcmcsae versions 0.8.1 dated 2026-07-20 and 0.8.2 dated 2026-10-17

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More information about mcmcsae at CRAN
Permanent link

Package ggstatsplot updated to version 1.1.3 with previous version 1.1.2 dated 2026-10-09

Title: 'ggplot2' Based Plots with Statistical Details
Description: Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) <doi:10.21105/joss.03167>.
Author: Indrajeet Patil [cre, aut, cph]
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

Diff between ggstatsplot versions 1.1.2 dated 2026-10-09 and 1.1.3 dated 2026-10-17

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 ggstatsplot-1.1.3/ggstatsplot/NEWS.md                                                                                |   22 
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 ggstatsplot-1.1.3/ggstatsplot/R/data.R                                                                               |    2 
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Package FastGP updated to version 1.5 with previous version 1.4 dated 2026-09-19

Title: Efficiently Using Gaussian Processes with Rcpp and RcppEigen
Description: Contains Rcpp and RcppEigen implementations of matrix operations useful for Gaussian process models, such as the inverse and determinant of a symmetric and positive-definite Toeplitz matrix, sampling from multivariate normal distributions, evaluation of the log-density of a multivariate normal vector, and Bayesian inference for latent variable Gaussian process models with elliptical slice sampling (Murray, Adams, and MacKay 2010).
Author: Giri Gopalan [aut, cre], Luke Bornn [aut]
Maintainer: Giri Gopalan <gopalan88@gmail.com>

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Package foreign updated to version 0.8-92 with previous version 0.8-91 dated 2026-01-29

Title: Read Data Stored by 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', 'dBase', ...
Description: Reading and writing data stored by some versions of 'Epi Info', 'Minitab', 'S', 'SAS', 'SPSS', 'Stata', 'Systat', 'Weka', and for reading and writing some 'dBase' files.
Author: R Core Team [aut, cph, cre] , Roger Bivand [ctb, cph], Vincent J. Carey [ctb, cph], Saikat DebRoy [ctb, cph], Stephen Eglen [ctb, cph], Rajarshi Guha [ctb, cph], Swetlana Herbrandt [ctb], Nicholas Lewin-Koh [ctb, cph], Mark Myatt [ctb, cph], Michael [...truncated...]
Maintainer: R Core Team <R-core@R-project.org>

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Package Ruido updated to version 1.2.0 with previous version 1.1.1 dated 2026-09-20

Title: Soundscape Spectral Metrics
Description: Accessible and flexible implementation of spectral ecoacoustic indices. The functions were design to accommodate a variety of sampling designs. Users can tailor calculations by specifying spectrogram time bin size, amplitude thresholds and normality tests. By simplifying computation and standardizing reproducible methods, the package aims to support ecoacoustics studies.
Author: Arthur Igor da Fonseca-Freire [aut, cre, cph], Weslley Geremias dos Santos [aut], Lucas Rodriguez Forti [aut]
Maintainer: Arthur Igor da Fonseca-Freire <arthur.igorr@gmail.com>

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Package IsoplotR updated to version 7.1 with previous version 7.0 dated 2026-08-21

Title: Statistical Toolbox for Radiometric Geochronology
Description: Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington', 'Ludwig' and Omnivariant Generalised Least-Squares ('OGLS') approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, Th-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isoch [...truncated...]
Author: Pieter Vermeesch [aut, cre]
Maintainer: Pieter Vermeesch <p.vermeesch@ucl.ac.uk>

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Package Maeswrap (with last version 1.7) was removed from CRAN

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

2015-06-30 1.7
2012-05-25 1.4.11
2012-01-17 1.4.9
2011-09-21 1.4.8

Permanent link
Package preventr updated to version 0.12.1 with previous version 0.12.0 dated 2026-06-24

Title: An Implementation of the PREVENT and Pooled Cohort Equations
Description: Implements the American Heart Association Predicting Risk of cardiovascular disease EVENTs (PREVENT) equations from Khan SS, Matsushita K, Sang Y, and colleagues (2023) <doi:10.1161/CIRCULATIONAHA.123.067626>, with optional comparison with their de facto predecessor, the Pooled Cohort Equations from the American Heart Association and American College of Cardiology (2013) <doi:10.1161/01.cir.0000437741.48606.98> and the revision to the Pooled Cohort Equations from Yadlowsky and colleagues (2018) <doi:10.7326/M17-3011>.
Author: Martin Mayer [aut, cre, cph]
Maintainer: Martin Mayer <mmayer@ebsco.com>

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Package chms updated to version 7.2 with previous version 7.1 dated 2026-09-08

Title: Accelerometer Processing Methods for Cycle 7 of the CHMS
Description: 'ActiGraph wGT3X-BT' accelerometer processing methods using the standardized workflow developed by Statistics Canada for cycle 7 of the Canadian Health Measures Survey (CHMS). The package promotes transparent and reproducible data processing while supporting the harmonization of analytical approaches among researchers wishing to align with Statistics Canada's methods. For general details about the processing methods, please consult Clarke J, Gribbon A, St-Laurent M, Ferrao T, Barnes J, Kuzik N, Colley R (2026) <doi: 10.25318/82-003-x202600200001-eng>.
Author: Joel Barnes [aut, cre], Janine Clarke [ctb], Rachel Colley [ctb], His Majesty the King in Right of Canada, as represented by Statistics Canada [cph]
Maintainer: Joel Barnes <joel.barnes@statcan.gc.ca>

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Package emhawkes updated to version 1.0.0 with previous version 0.9.8 dated 2025-08-26

Title: Exponential Multivariate Hawkes Model
Description: Simulate and fit multivariate Hawkes models with exponential kernels, introduced by Hawkes (1971) <doi:10.2307/2334319>. Includes marked, state-dependent, and multi-kernel specifications. Parameter estimation uses maximum likelihood, following Ozaki (1979) <doi:10.1007/BF02480272>, through the optional 'maxLik' package or the optimization functions supplied with R.
Author: Kyungsub Lee [aut, cre]
Maintainer: Kyungsub Lee <kyungsub@gmail.com>

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Package comets updated to version 0.2-3 with previous version 0.2-2 dated 2025-11-05

Title: Covariance Measure Tests for Conditional Independence
Description: Covariance measure tests for conditional independence testing against conditional covariance and nonlinear conditional mean alternatives. The package implements versions of the generalised covariance measure test (Shah and Peters, 2020, <doi:10.1214/19-aos1857>) and projected covariance measure test (Lundborg et al., 2023, <doi:10.1214/24-AOS2447>). The tram-GCM test, for censored responses, is implemented including the Cox model and survival forests (Kook et al., 2024, <doi:10.1080/01621459.2024.2395588>). Application examples to variable significance testing and modality selection can be found in Kook and Lundborg (2024, <doi:10.1093/bib/bbae475>).
Author: Lucas Kook [aut, cre] , Anton Rask Lundborg [ctb]
Maintainer: Lucas Kook <lucasheinrich.kook@gmail.com>

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Package asciiSetupReader updated to version 2.6.0 with previous version 2.5.3 dated 2025-09-23

Title: Reads Fixed-Width ASCII Data Files (.txt or .dat) that Have Accompanying Setup Files (.sps or .sas)
Description: Lets you open a fixed-width ASCII file (.txt or .dat) that has an accompanying setup file (.sps or .sas). These file combinations are sometimes referred to as .txt+.sps, .txt+.sas, .dat+.sps, or .dat+.sas. This will only run in a txt-sps or txt-sas pair in which the setup file contains instructions to open that text file. It will NOT open other text files, .sav, .sas, or .por data files. Fixed-width ASCII files with setup files are common in older (pre-2000) government data.
Author: Jacob Kaplan [aut, cre]
Maintainer: Jacob Kaplan <jkkaplan6@gmail.com>

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Package tramicp updated to version 0.1-1 with previous version 0.1-0 dated 2025-01-31

Title: Model-Based Causal Feature Selection for General Response Types
Description: Extends invariant causal prediction (Peters et al., 2016, <doi:10.1111/rssb.12167>) to generalized linear and transformation models (Hothorn et al., 2018, <doi:10.1111/sjos.12291>). The methodology is described in Kook et al. (2023, <doi:10.1080/01621459.2024.2395588>).
Author: Lucas Kook [aut, cre] , Sorawit Saengkyongam [ctb], Anton Rask Lundborg [ctb], Torsten Hothorn [ctb], Jonas Peters [ctb]
Maintainer: Lucas Kook <lucasheinrich.kook@gmail.com>

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Package tramvs updated to version 0.0-10 with previous version 0.0-9 dated 2026-03-10

Title: Optimal Subset Selection for Transformation Models
Description: Greedy optimal subset selection for transformation models (Hothorn et al., 2018, <doi:10.1111/sjos.12291> ) based on the abess algorithm (Zhu et al., 2020, <doi:10.1073/pnas.2014241117> ). Applicable to models from packages 'tram' and 'cotram'. Application to shift-scale transformation models are described in Siegfried et al. (2024, <doi:10.1080/00031305.2023.2203177>).
Author: Lucas Kook [aut, cre] , Sandra Siegfried [ctb], Torsten Hothorn [ctb]
Maintainer: Lucas Kook <lucasheinrich.kook@gmail.com>

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Package arsenal updated to version 3.7.4 with previous version 3.7.1 dated 2026-07-02

Title: An Arsenal of 'R' Functions for Large-Scale Statistical Summaries
Description: An Arsenal of 'R' functions for large-scale statistical summaries, which are streamlined to work within the latest reporting tools in 'R' and 'RStudio' and which use formulas and versatile summary statistics for summary tables and models. The primary functions include tableby(), a Table-1-like summary of multiple variable types 'by' the levels of one or more categorical variables; paired(), a Table-1-like summary of multiple variable types paired across two time points; modelsum(), which performs simple model fits on one or more endpoints for many variables (univariate or adjusted for covariates); freqlist(), a powerful frequency table across many categorical variables; comparedf(), a function for comparing data.frames; and write2(), a function to output tables to a document.
Author: Ethan Heinzen [aut, cre], Jason Sinnwell [aut], Elizabeth Atkinson [aut], Tina Gunderson [aut], Gregory Dougherty [aut], Patrick Votruba [ctb], Ryan Lennon [ctb], Andrew Hanson [ctb], Krista Goergen [ctb], Emily Lundt [ctb], Brendan Broderick [ctb], [...truncated...]
Maintainer: Ethan Heinzen <heinzen.ethan@mayo.edu>

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Package statsExpressions updated to version 2.2.0 with previous version 2.1.2 dated 2026-10-09

Title: Tidy Dataframes and Expressions with Statistical Details
Description: Utilities for producing dataframes with rich details for the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian t-test, one-way ANOVA, correlation analyses, contingency table analyses, and meta-analyses. The functions are pipe-friendly and provide a consistent syntax to work with tidy data. These dataframes additionally contain expressions with statistical details, and can be used in graphing packages. This package also forms the statistical processing backend for 'ggstatsplot'. References: Patil (2021) <doi:10.21105/joss.03236>.
Author: Indrajeet Patil [cre, aut, cph]
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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Package rsvd updated to version 1.0.6 with previous version 1.0.5 dated 2021-04-16

Title: Randomized Singular Value Decomposition
Description: Low-rank matrix decompositions are fundamental tools and widely used for data analysis, dimension reduction, and data compression. Classically, highly accurate deterministic matrix algorithms are used for this task. However, the emergence of large-scale data has severely challenged our computational ability to analyze big data. The concept of randomness has been demonstrated as an effective strategy to quickly produce approximate answers to familiar problems such as the singular value decomposition (SVD). The rsvd package provides several randomized matrix algorithms such as the randomized singular value decomposition (rsvd), randomized principal component analysis (rpca), randomized robust principal component analysis (rrpca), randomized interpolative decomposition (rid), and the randomized CUR decomposition (rcur). In addition several plot functions are provided.
Author: N. Benjamin Erichson [aut, cre]
Maintainer: N. Benjamin Erichson <erichson@icsi.berkeley.edu>

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Package readxl updated to version 1.6.0 with previous version 1.5.0.1 dated 2026-09-16

Title: Read Excel Files
Description: Import excel files into R. Supports '.xls' via the embedded 'libxls' C library <https://github.com/libxls/libxls> and '.xlsx' via the embedded 'RapidXML' C++ library <https://rapidxml.sourceforge.net/>. Works on Windows, Mac and Linux without external dependencies. Reading of password-encrypted '.xlsx' files is supported via the embedded 'tiny-AES-c' C library <https://github.com/kokke/tiny-AES-c>.
Author: Hadley Wickham [aut] , Jennifer Bryan [aut, cre] , Posit, PBC [cph, fnd] , Marcin Kalicinski [ctb, cph] , Komarov Valery [ctb, cph] , Christophe Leitienne [ctb, cph] , Bob Colbert [ctb, cph] , David Hoerl [ctb, cph] , Evan Miller [ctb, cph] , kokke [ [...truncated...]
Maintainer: Jennifer Bryan <jenny@posit.co>

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Package RcppArmadillo updated to version 15.6.2-1 with previous version 15.6.0-1 dated 2026-09-08

Title: 'Rcpp' Integration for the 'Armadillo' Templated Linear Algebra Library
Description: 'Armadillo' is a templated C++ linear algebra library aiming towards a good balance between speed and ease of use. It provides high-level syntax and functionality deliberately similar to Matlab. It is useful for algorithm development directly in C++, or quick conversion of research code into production environments. It provides efficient classes for vectors, matrices and cubes where dense and sparse matrices are supported. Integer, floating point and complex numbers are supported. A sophisticated expression evaluator (based on template meta-programming) automatically combines several operations to increase speed and efficiency. Dynamic evaluation automatically chooses optimal code paths based on detected matrix structures. Matrix decompositions are provided through integration with LAPACK, or one of its high performance drop-in replacements (such as 'MKL' or 'OpenBLAS'). It can automatically use 'OpenMP' multi-threading (parallelisation) to speed up computationally expensive operations [...truncated...]
Author: Dirk Eddelbuettel [aut, cre] , Romain Francois [aut] , Doug Bates [aut] , Binxiang Ni [aut], Conrad Sanderson [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

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Package ggpath updated to version 1.1.2 with previous version 1.1.1 dated 2025-10-16

Title: Robust Image Rendering Support for 'ggplot2'
Description: A 'ggplot2' extension that enables robust image grobs in panels and theme elements.
Author: Sebastian Carl [aut, cre, cph]
Maintainer: Sebastian Carl <mrcaseb@gmail.com>

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Package bifrost updated to version 0.2.2 with previous version 0.2.0 dated 2026-09-27

Title: Branch-Level Inference Framework for Recognizing Optimal Shifts in Traits
Description: Methods for detecting, visualizing, and evaluating cladogenic shifts in multivariate trait data on phylogenies. Implements penalized-likelihood multivariate generalized least squares models and a greedy step-wise shift search for high-dimensional trait datasets and large trees via searchOptimalConfiguration(). Provides tools for inspecting search trajectories, summarizing branch and lineage rates, analyzing shift timing and magnitudes, estimating post-hoc regime covariance and integration, and running simulation-based calibration and tuning. The search follows approaches developed in Smith et al. (2023) <doi:10.1111/nph.19099> and Berv et al. (2024) <doi:10.1126/sciadv.adp0114>. Methods build on multivariate generalized least squares approaches described in Clavel et al. (2019) <doi:10.1093/sysbio/syy045> and implemented in the mvgls() function from the 'mvMORPH' package. Documentation and worked examples are available at <https://jakeberv.com/bifrost/>.
Author: Jacob S. Berv [aut, cre, cph, fnd] , Nathan Fox [aut] , Matt J. Thorstensen [aut] , Henry Lloyd-Laney [aut] , Emily M. Troyer [aut] , Rafael A. Rivero-Vega [aut] , Stephen A. Smith [aut, fnd] , Matt Friedman [aut, fnd] , David F. Fouhey [aut, fnd] , [...truncated...]
Maintainer: Jacob S. Berv <jacob.berv@gmail.com>

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Package command updated to version 0.3.0 with previous version 0.2.0 dated 2026-07-22

Title: Process Command Line Arguments
Description: Process command line arguments. Processing includes checking, naming, and coercing to numeric, date, or logical. By capturing assumptions about inputs and outputs, the 'command' package can provide scripts with well defined interfaces, leading to safer, more modular data analysis pipelines.
Author: John Bryant [aut, cre], Bayesian Demography Limited [cph]
Maintainer: John Bryant <john@bayesiandemography.com>

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Package ascent updated to version 0.5.0 with previous version 0.1.1 dated 2026-07-30

Title: Multi-Layer Decomposition of Functional Community Restructuring
Description: Implements the 'ASC-CFD' (Assemblage Shift Characterization - Community Functional Dynamics) framework for decomposing functional community restructuring into positional (centroid displacement), dispersive (functional dispersion), and boundary (convex hull volume) components. Tests each component against two null models: a sampling null model (individuals or replicates reassigned between communities) and a stratified trait-permutation null model, with a single global test when many communities are compared. Functional entities (species with similar traits) help detect replacement among similar species, and species-level leverage identifies the taxa driving functional shifts. Supports both temporal (paired) and spatial (pairwise) comparisons.
Author: Rogelio R. Munoz-Li [aut, cre], Flavia Alvarez-Denis [aut]
Maintainer: Rogelio R. Munoz-Li <munozrogelio16@gmail.com>

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