CRAN Updates

Removed from CRAN: timesift (0.3.1), usportsR (1.0.0)

cran.r-project.orgtruedist: Estimating the Distribution of True Effects from Noisy EstimatesEstimates the distribution of true effects (or any latent parameter) from estimates that each have a known, possibly different, standard error. The main function, em_smooth(), implements the smoothed EM (EMS) algorithm of Silverman, Jones, Wilson and Nychka (1990) <<a href="https://doi.org/10.1111%2Fj.2517-6161.1990.tb01788.x" target="_top">doi:10.1111/j.2517-6161.1990.tb01788.x</a>> for a nonparametric mixing distribution on a grid. The smoothing uses one constant standard deviation, set from the typical standard error and the sample size.

New on CRAN: truedist (0.1.0). View at https://CRAN.R-project.org/package=truedist

cran.r-project.orgtransformerpalettes: Color Palettes Inspired by Transformers Toys, Cartoons and ComicsColor palettes drawn from the Transformers franchise, centered on the 1984-1989 Generation 1 toys and extending to their Generation 2 re-releases, the cartoon animation models and the Marvel comics. Covers the leaders, every member and combined form of the combiner teams (Aerialbots, Protectobots, Technobots, Constructicons, Stunticons, Combaticons, Terrorcons, Predacons, Seacons, Pretender Monsters and Breastforce), the Dinobots, the Seeker jets, Soundwave and the cassettes, the Insecticons, the 1984 Autobot cars and Mini Vehicles and the 1986 movie cast, with separate palettes for the toy, the cartoon animation model, the Marvel comic coloring and the Generation 2 re-release where each exists. Includes 'ggplot2' color and fill scales for discrete and continuous data, team palettes that take one color from each member of a combiner team, metadata linking each palette to its character, faction, team and reference page, and helpers to shortlist palettes that suit categorical, color-blind-safe, sequential or diverging use. Hex values are approximations of the toys' plastic and paint colors; the package is a fan project and is not affiliated with or endorsed by Hasbro or Takara Tomy.

New on CRAN: transformerpalettes (0.4.0). View at https://CRAN.R-project.org/package=transformerpalettes

cran.r-project.orgReguGLH: General Linear Hypothesis Tests via Spectral ShrinkageImplements high-dimensional general linear hypothesis tests using ridge, reciprocal cubic polynomial, and user-defined analytic spectral regularizers. Provides prior-based shrinkage selection and Gaussian maximum calibration for composite tests. Implements the methods of Li, Aue and Paul (2020), "High-dimensional general linear hypothesis tests via non-linear spectral shrinkage", Bernoulli, 26(4), 2541-2571 <<a href="https://doi.org/10.3150%2F19-BEJ1186" target="_top">doi:10.3150/19-BEJ1186</a>>.

New on CRAN: ReguGLH (0.1.0). View at https://CRAN.R-project.org/package=ReguGLH

cran.r-project.orgnesstarR: Read and Export 'Nesstar' Binary FilesReads '.Nesstar' binary files into data frames. '.Nesstar' is the file format of 'Nesstar Publisher', survey documentation software from the International Household Survey Network <<a href="https://www.ihsn.org/node/557" target="_top">https://www.ihsn.org/node/557</a>>. Statistical agencies, for example the Ministry of Statistics and Programme Implementation ('MoSPI', India), publish survey microdata in this format.

New on CRAN: nesstarR (0.1.0). View at https://CRAN.R-project.org/package=nesstarR

cran.r-project.orgglyospalettes: Color Palettes Inspired by Glyos ColorwaysColor palettes based on the named colorways of the Glyos toy system: Onell Design's Glyos System Series and the Glyos-compatible lines from partner companies such as TheGodBeast, Spy Monkey Creations, Toyfinity and the Four Horsemen. Includes 'ggplot2' color and fill scales for discrete and continuous data, metadata linking each palette to its company and product line, helpers to shortlist palettes that suit categorical, color-blind-safe, sequential or diverging use, and tools to combine palettes (one color per colorway) or pick the most distinguishable colors from a pool for a light, dark or grayscale plot. Hex values are approximations curated from product photography. This is a fan project and is not affiliated with or endorsed by any of the companies.

New on CRAN: glyospalettes (0.3.0). View at https://CRAN.R-project.org/package=glyospalettes

Updates on CRAN: glmulti (1.0.9), iq (2.1.0), kindisperse (0.10.3), markdown (2.1), OmopIndices (0.2.0), rYWAASB (0.4.2), SpaDES.tools (2.2.0), tempted (0.1.2)

Updates on CRAN: adbcdrivermanager (0.25.0), asymmetry (2.0.7), bifactory (0.6.1), caugi (1.4.0), discoCVI (0.2.0), doclingr (0.1.1), dyadMLM (0.3.0), figsr (0.2.0)

cran.r-project.orgzuxml: Small XML Parser and Document TreeReads, navigates, and writes XML documents using a bundled copy of the 'Expat' parser (<<a href="https://libexpat.github.io/" target="_top">https://libexpat.github.io/</a>>), so that no system XML library is required. Documents are parsed into a faithful immutable tree exposed through a small vectorized navigation interface. Parsing is strict by default: document type declarations are rejected, external entity resolution is not compiled in, and configurable limits bound nesting depth and memory use. A registered C interface allows other packages to parse XML without linking against the parser themselves, and to feed it incrementally so that a large document need not be held in memory all at once.

New on CRAN: zuxml (0.1.0). View at https://CRAN.R-project.org/package=zuxml

cran.r-project.orgzigimports: Call 'Zig' Code from RLoads shared libraries compiled from 'Zig' ('.so' files on Linux, '.dll' files on Windows) and binds their exported functions to R functions. Arguments are passed by value using the native calling convention, so functions with mixed integer, double, logical, string and vector arguments and with return values can be called. Also compiles and runs 'Zig' code directly from R. Compiling code requires the 'Zig' compiler.

New on CRAN: zigimports (0.1.0). View at https://CRAN.R-project.org/package=zigimports

cran.r-project.orgwindscape: Model Landscape Connectivity by WindModel landscape connectivity by wind for ecological and evolutionary analyses. Summarize long time series of gridded wind data, downloaded from reanalyses or supplied by the user, into wind roses describing directional conductance between neighboring grid cells. Model dispersal through them with least-cost path and random walk algorithms, to map windsheds around sites and estimate pairwise connectivity among them, test hypotheses relating wind to ecological data, and visualize wind and connectivity with 'ggplot2'. The approach builds on Kling and Ackerly (2020) <<a href="https://doi.org/10.1038%2Fs41558-020-0848-3" target="_top">doi:10.1038/s41558-020-0848-3</a>> and Kling and Ackerly (2021) <<a href="https://doi.org/10.1073%2Fpnas.2017317118" target="_top">doi:10.1073/pnas.2017317118</a>>.

New on CRAN: windscape (2.0.0). View at https://CRAN.R-project.org/package=windscape

cran.r-project.orgTTM: Terminal Trend Models on the Retrospective Time ScaleFits retrospective-time longitudinal models for terminal trend analysis using weighted generalized estimating equations and related joint modeling tools. The package provides functions to estimate spline-based baseline and treatment effect trajectories on the retrospective time scale, obtain pointwise confidence intervals, and visualize fitted trajectories.

New on CRAN: TTM (0.1.0). View at https://CRAN.R-project.org/package=TTM

cran.r-project.orgsurveynnet: Neural Network for Complex Survey DataThe goal of 'surveynnet' is to extend the functionality of 'nnet', which already supports survey weights, by enabling it to handle clustered and stratified data. It achieves this by incorporating design effects through the use of effective sample sizes as outlined by Chen and Rust (2017), <<a href="https://doi.org/10.1093%2Fjssam%2Fsmw036" target="_top">doi:10.1093/jssam/smw036</a>>, and performed by 'deffCR' in the package 'PracTools' (Valliant, Dever, and Kreuter (2018), <<a href="https://doi.org/10.1007%2F978-3-319-93632-1" target="_top">doi:10.1007/978-3-319-93632-1</a>>).

New on CRAN: surveynnet (1.0.1). View at https://CRAN.R-project.org/package=surveynnet

cran.r-project.orgsppt: Spatial Point Pattern Test for Areal DataImplements the area-based nonparametric spatial point pattern test of Andresen (2009) <<a href="https://doi.org/10.1016%2Fj.apgeog.2008.12.004" target="_top">doi:10.1016/j.apgeog.2008.12.004</a>> for comparing two spatial distributions of events aggregated to areal units, with the applications and extensions reviewed in Andresen (2016) <<a href="https://doi.org/10.1177%2F2059799116630659" target="_top">doi:10.1177/2059799116630659</a>>. Unit-level inference uses bounded Monte Carlo bootstrap p-values, with marginal confidence interval overlap retained as an option. Global similarity is summarised by the robust S index, accompanied by a test of whether two patterns are more different than two realisations of a single process, and a test of the spatial arrangement of the differences. A longitudinal extension compares each period of a time series against a base period and classifies unit-level trajectories. Publication-ready maps can be redrawn with user-chosen layouts.

New on CRAN: sppt (1.0.0). View at https://CRAN.R-project.org/package=sppt

cran.r-project.orgrpspanel: US State Energy-Economy Panels with Renewable Portfolio StandardsBuilds a documented, reproducible state-by-year panel for the 50 US states and the District of Columbia that combines energy consumption, prices and production from the US Energy Information Administration (EIA) State Energy Data System, electricity generation and retail sales, state energy-related carbon dioxide emissions, and state GDP, income and population from the Bureau of Economic Analysis (BEA). Data are downloaded on demand through the official APIs and cached locally, with the source, vintage and transformation of every variable recorded in a codebook. Renewable Portfolio Standard (RPS) rules are turned into standardised annual stringency indices (adoption, nominal, coverage-adjusted and incremental requirements, following Yin and Powers (2010) <<a href="https://doi.org/10.1016%2Fj.enpol.2009.10.067" target="_top">doi:10.1016/j.enpol.2009.10.067</a>>, plus design-flexibility indicators). Output works directly with the 'plm', 'fixest' and 'csdm' packages.

New on CRAN: rpspanel (0.1.0). View at https://CRAN.R-project.org/package=rpspanel

cran.r-project.orgrapidxlsx: Fast Parallel Excel Spreadsheet WriterSerializes tabular data frames to Microsoft Excel 'OpenXML' ('xlsx') workbooks using a multi-threaded Rust core with parallel Deflate compression and zero-copy columnar memory mapping.

New on CRAN: rapidxlsx (0.1.0). View at https://CRAN.R-project.org/package=rapidxlsx

cran.r-project.orgradiatR: Analyse and Visualise Headings and Trajectories on the Unit DiskA complete pipeline for analysing directional data – headings and trajectories on the unit disk. Supply a table of angles directly, or reconstruct headings from movement trajectories imported from tracking tools ('EthoVision', 'DeepLabCut', 'SLEAP', 'TRex', 'ANY-maze', 'TrackMate', 'idtracker.ai', and others) via a unified dialect-based loader system, including multi-bodypart pose estimation with likelihood-weighted centroid. Derives per-trial heading directions using multiple rules (ring-crossing, distal point, pose body-axis, velocity-based, and more). Computes circular statistics including mean direction, resultant length, von Mises and wrapped Cauchy parametric fits, circular correlation (circular-linear and circular-circular), circular-linear regression (Fisher and Lee (1992) <<a href="https://doi.org/10.2307%2F2532334" target="_top">doi:10.2307/2532334</a>>), model selection among orientation models (Fitak and Johnsen (2017) <<a href="https://doi.org/10.1242%2Fjeb.167056" target="_top">doi:10.1242/jeb.167056</a>>), and uniformity and multi-sample hypothesis tests (Rayleigh, Watson-Williams, Hermans-Rasson (Landler, Ruxton and Malkemper (2019) <<a href="https://doi.org/10.1186%2Fs12898-019-0246-8" target="_top">doi:10.1186/s12898-019-0246-8</a>>), and others) with multiple-comparison correction. Path tortuosity follows Benhamou (2004) <<a href="https://doi.org/10.1016%2Fj.jtbi.2004.03.016" target="_top">doi:10.1016/j.jtbi.2004.03.016</a>>. Renders publication-quality 'ggplot2' radial plots with overlaid rose diagrams, parametric density curves, non-parametric kernel density estimates, and circular boxplots (Buttarazzi, Pandolfo and Porzio (2018) <<a href="https://doi.org/10.1111%2Fbiom.12889" target="_top">doi:10.1111/biom.12889</a>>). Includes a browser-based 'shiny' graphical interface requiring no R coding via launch_app().

New on CRAN: radiatR (0.1.3). View at https://CRAN.R-project.org/package=radiatR

cran.r-project.orgquerychat: Filter and Query Data Frames in 'shiny' Using an LLM Chat InterfaceAdds an LLM-powered chatbot to your 'shiny' app, that can turn your users' natural language questions into 'SQL' queries that run against your data, and return the result as a reactive data frame. Use it to drive reactive calculations, visualizations, downloads, and more.

New on CRAN: querychat (0.4.2). View at https://CRAN.R-project.org/package=querychat

cran.r-project.orgpyrt: Runtime Support for Converted 'Python' PackagesProvides the 'Python' runtime semantics required by 'R' packages generated with 'pyport', including reference-semantics containers, class and method-resolution-order dispatch, exception hierarchies, iteration and slicing helpers, arbitrary-precision integer arithmetic, and bit-exact random number generation.

New on CRAN: pyrt (0.1.0). View at https://CRAN.R-project.org/package=pyrt

cran.r-project.orgptLasso: Pretraining the LassoImplements lasso pretraining for generalized linear models for data with grouped observations; data without grouped observations, but with multinomial responses; data with multiple Gaussian responses; and data with repeated measurements over time. The method fits a lasso model to an initial dataset and then uses its support and coefficient values to guide model fitting for a related task, which can improve performance by leveraging larger datasets and preserve interpretability by identifying features which are generally shared, and which are task specific. See Craig et al. (2026) <<a href="https://doi.org/10.1093%2Fjrsssb%2Fqkaf050" target="_top">doi:10.1093/jrsssb/qkaf050</a>> for details. Model fitting in this package is done with cv.glmnet() from the 'glmnet' package, and syntax closely follows that of 'glmnet' (Friedman, Hastie and Tibshirani (2010) <<a href="https://doi.org/10.18637%2Fjss.v033.i01" target="_top">doi:10.18637/jss.v033.i01</a>>).

New on CRAN: ptLasso (1.0.2). View at https://CRAN.R-project.org/package=ptLasso

cran.r-project.orgmospiR: Client for the 'MoSPI' Microdata PortalDownload unit-level survey microdata from the Ministry of Statistics and Programme Implementation ('MoSPI', Government of India) Microdata Portal <<a href="https://microdata.gov.in" target="_top">https://microdata.gov.in</a>>. Provides functions to list datasets, list files within a dataset, and download individual files or entire datasets through the portal's 'NADA' API.

New on CRAN: mospiR (0.1.0). View at https://CRAN.R-project.org/package=mospiR

cran.r-project.orgmirrorslope: Mirror Slope Plots for Two-Arm Clinical Trial DataCreates mirrored slope plots comparing two treatment arms over a single observation interval. Both arms share a common x-axis and converge at a central endpoint, making the between-arm gap the primary visual quantity. Returns standard 'ggplot2' objects for full extensibility. The display was designed by Kati Maharry and is described in Maharry and Sullivan (2026, manuscript in preparation); it was first used in the supplementary appendix of McDonald and colleagues (2026) <<a href="https://doi.org/10.1016%2FS0140-6736%2826%2901385-1" target="_top">doi:10.1016/S0140-6736(26)01385-1</a>>.

New on CRAN: mirrorslope (0.2.1). View at https://CRAN.R-project.org/package=mirrorslope

cran.r-project.orggcloglog: Methods for Fitting Binomial Models with the Generalized Complementary Log-Log FunctionFunctionality for fitting a flexible link function in binomial regression based on a latent negative-binomial count. The original link function was proposed by Aranda-Ordaz (1981)<<a href="https://doi.org/10.1093%2Fbiomet%2F68.2.357" target="_top">doi:10.1093/biomet/68.2.357</a>>, and motivation via a negative-binomial latent count by van der Veen and Hui (in prep).

New on CRAN: gcloglog (1.0). View at https://CRAN.R-project.org/package=gcloglog

New on CRAN: FrailtyPackPlus (0.1.0). View at https://CRAN.R-project.org/package=FrailtyPackPlus

cran.r-project.orgfastphylosig: Fast Phylogenetic Signal StatisticsProvides one-command and method-specific workflows for phylogenetic signal in continuous, binary, and categorical traits. Compiled tree-pruning algorithms implement Blomberg's K and Pagel's lambda without constructing a dense phylogenetic covariance matrix in production. Fritz and Purvis D retains separate random and Brownian null models, while categorical Delta combines discrete ancestral-state likelihoods with MCMC and permutation diagnostics. The package also provides reusable prepared trees, explicit tree/data matching, trait-wise missing-value handling, conservative tree diagnostics, bounded simulation memory, and structured timing and Monte Carlo uncertainty metadata. Methods follow Blomberg, Garland and Ives (2003) <<a href="https://doi.org/10.1111%2Fj.0014-3820.2003.tb00285.x" target="_top">doi:10.1111/j.0014-3820.2003.tb00285.x</a>> for K, Pagel (1999) <<a href="https://doi.org/10.1038%2F44766" target="_top">doi:10.1038/44766</a>> for lambda, Fritz and Purvis (2010) <<a href="https://doi.org/10.1111%2Fj.1523-1739.2010.01455.x" target="_top">doi:10.1111/j.1523-1739.2010.01455.x</a>> for D, and Borges et al. (2019) <<a href="https://doi.org/10.1093%2Fbioinformatics%2Fbty800" target="_top">doi:10.1093/bioinformatics/bty800</a>> for categorical Delta.

New on CRAN: fastphylosig (0.3.1). View at https://CRAN.R-project.org/package=fastphylosig

cran.r-project.orgenhancedTtest: Enhanced T-Test with Automatic Selection and APA FormattingProvides enhanced t-test functionality with automatic assumption checking, non-parametric fallbacks, effect size calculation, and APA-formatted tables that can be exported to Word documents. Supports one-sample, two-sample, and paired t-tests with intelligent test selection. Effect size interpretations follow Cohen (1988) <<a href="https://doi.org/10.4324%2F9780203771587" target="_top">doi:10.4324/9780203771587</a>> and APA formatting follows the Publication Manual of the American Psychological Association, 7th edition (2020) <<a href="https://doi.org/10.1037%2F0000165-000" target="_top">doi:10.1037/0000165-000</a>>.

New on CRAN: enhancedTtest (0.1.0). View at https://CRAN.R-project.org/package=enhancedTtest

cran.r-project.orgDynMSR: Connect Systems Biology and Pharmacology Formats to Simulation BackendsProvides a convenient R interface for systems-biology and systems-pharmacology models in Heta, SBML (Systems Biology Markup Language), and DynMS (Dynamic Model Specification) formats. DynMS JSON files are loaded directly; Heta projects and SBML files are converted to DynMS by an optional compatible installation of 'heta-compiler'. Models can be validated, selected from a platform, and generated or built for simulation with 'mrgsolve' as a backend.

New on CRAN: DynMSR (0.1.1). View at https://CRAN.R-project.org/package=DynMSR

cran.r-project.orgcudacellr: GPU-Aware Single-Cell Analysis WorkflowsProvides single-cell analysis primitives for sparse count matrices, including library-size normalization, log-normalization, highly variable feature selection, principal component analysis, and nearest-neighbour construction. Integrates the 'cudaverse' numerical and sparse layers while preserving matrix identifiers and recording the computation backend for each stage. Optional adapters preserve native 'SingleCellExperiment' and 'SeuratObject' version 5 object structures.

New on CRAN: cudacellr (0.4.0). View at https://CRAN.R-project.org/package=cudacellr

cran.r-project.orgalmanac: Tools for Working with Recurrence RulesProvides tools for defining recurrence rules and recurrence sets. Recurrence rules are a programmatic way to define a recurring event, like the first Monday of December. Multiple recurrence rules can be combined into larger recurrence sets. A full holiday and calendar interface is also provided that can generate holidays within a particular year, can detect if a date is a holiday, can respect holiday observance rules, and allows for custom holidays.

New on CRAN: almanac (1.0.1). View at https://CRAN.R-project.org/package=almanac

Updates on CRAN: adbcpostgresql (0.25.0), adbcsqlite (0.25.0), BANAM (0.2.3), Bergm (6.0.0), BIGpopA (2.2.1), cancerradarr (4.1.0), LorMe (2.0.3), RastaRocket (1.1.6), taxify (0.7.0), tree (1.0-48)

20h

Updates on CRAN: rconfig (0.3.1), RcppTrust (0.2.0), rdomains (0.6.0), releaser (1.3.0), RobustMediate (0.3.0), scopr (0.3.6), slca (1.4.2), survexp.fr (1.3), tidytransit (1.8.1), vectra (0.14.1), videogameinsightsR (0.3.0), VSURF (1.2.2)

20h

Updates on CRAN: antedep (0.3.1), artma (0.5.2), campsismod (1.5.0), contingencytables (3.1.1), iAR (1.3.5), impectR (2.7.0), LeaveOutKSS (0.1.1), mccca (2.5), medfate (5.2.0), pintervals (1.3.3), pmlsp (1.0.2), RALSA (1.7.2)

Removed from CRAN: couplr (1.8.1), stxplore (0.1.0)

Updates on CRAN: araponga (2.0.0), BayesFBHborrow (2.0.21), causalfrag (0.2.1), DFA.CANCOR (0.4.5), pcatsAPIclientR (1.3.1), pseudobibeR (1.3), roundwork (0.1.0)

cran.r-project.orgmathml: Translate R Expressions to 'MathML' and 'LaTeX'/'MathJax'Translate R expressions to 'MathML' or 'MathJax'/'LaTeX' so that they can be rendered in R markdown documents and shiny apps.

New on CRAN: mathml (1.10). View at https://CRAN.R-project.org/package=mathml

cran.r-project.orgLARF: Local Average Response Functions for Instrumental Variable Estimation of Treatment EffectsProvides instrumental variable estimation of treatment effects when both the endogenous treatment and its instrument are binary. Applicable to both binary and continuous outcomes.

New on CRAN: LARF (1.5). View at https://CRAN.R-project.org/package=LARF

cran.r-project.orgevbsreg: Local Influence Diagnostics for the Extreme-Value Birnbaum-Saunders Regression ModelLocal influence diagnostics for the Extreme-Value Birnbaum-Saunders (EVBS) regression model of Ferreira, Gomes and Leiva (2012): joint maximum likelihood estimation, conformal normal curvature diagnostics under case-weight, response and explanatory-variable perturbation, randomized quantile residuals with simulation envelope, the density, distribution and quantile functions, the finite upper endpoint, return levels and expected shortfall, moving-block bootstrap standard errors, a prospective index of endpoint identifiability, the same diagnostics for generalized extreme-value regression, and a 'gamlss' family allowing the tail-shape parameter to depend on covariates. The methods are described in Lima, Ospina, Barros and Macedo (2025) <<a href="https://doi.org/10.48550%2FarXiv.2507.22967" target="_top">doi:10.48550/arXiv.2507.22967</a>> and are applied to monthly maximum wind gusts from Itajai, Brazil.

New on CRAN: evbsreg (1.2.3). View at https://CRAN.R-project.org/package=evbsreg

cran.r-project.orgcombcoint: A Joint Test-Statistic for the Null of Non-CointegrationImplements a joint cointegration testing approach that combines Engle-Granger, Johansen maximum eigenvalue, Boswijk, and Banerjee tests into a unified test-statistic for the null of non-cointegration. Also see Bayer and Hanck (2013) <<a href="https://doi.org/10.1111%2Fj.1467-9892.2012.00814.x" target="_top">doi:10.1111/j.1467-9892.2012.00814.x</a>>.

New on CRAN: combcoint (0.3.0). View at https://CRAN.R-project.org/package=combcoint

Updates on CRAN: rdss (1.0.16), S7schema (0.2.1), shinymanager (1.2.0), smartcor (1.2.0), spada (0.1.9), suncalc (0.5.4), tidyfinance (1.0.0), tidynorm (0.5.0), transforEmotion (0.1.9), V8 (8.2.1), vectra (0.14.0)

Updates on CRAN: edgarfundamentals (0.1.3), fairGATE (1.0.0), fds (2.0), gap (1.15.3), genpca (0.2.2), INLAvaan (0.3.3), mcp (0.4.0), MOFAT (2.0), np (0.80-1), NSCA (0.5.2), OpenSourceAP.DownloadR (0.2.0), pomp (6.5)

Updates on CRAN: actiread (0.9.0), actisomni (0.4.0), adlaplace (0.7.5), Analitica (2.4.0), arity (0.2.0), ast2ast (1.1.1), autotestR (1.3.0), baseverse (0.1.6), BayesMoFo (0.2.0), clootl (0.1.5), CRAFT (0.2.0)

Updates on CRAN: conquestr (1.9.2), dtametaTMB (0.1.4), easy.glmnet (1.2), enviPathR (1.0.2), mapi (1.1.6), multiflexscan (0.3.0), qardlr (1.1.2), rbcc (0.2.0), resultcheck (0.3.3), samplrData (1.0.1), statcheck (1.6.1), tgml (0.6.0)

Removed from CRAN: streamConnect (0.1.0)

Updates on CRAN: cardargus (0.3.0), powerjoin (0.2.0), ssel (0.5.1)

Updates on CRAN: FusionForests (1.1.1), qol (1.3.6), robustlmm (3.5.1-1), transforEmotion (0.1.8), zot (0.5.0)

cran.r-project.orgdsld: Data Science Looks at DiscriminationStatistical and graphical tools for exploring group differences and possible discrimination related to sensitive attributes such as race, gender, and age. Includes adjusted group comparisons, matching, distribution plots, and prediction methods that constrain sensitive-attribute influence or deweight selected predictors. Cross-validation supports comparison of prediction error and sensitive-attribute associations. Methods and teaching examples are described by Mittal et al. (2025) <<a href="https://doi.org/10.48550%2FarXiv.2411.04228" target="_top">doi:10.48550/arXiv.2411.04228</a>>. Interfaces to the R implementation are also available for 'Python'.

New on CRAN: dsld (2.0.0). View at https://CRAN.R-project.org/package=dsld

Updates on CRAN: astronomR (0.4.0), chromConverter (0.11.2), DeclareDesign (2.0.0), ggRandomForests (3.5.5), ldpdist (0.1.1), mongolmaps (0.2.0), nethist (1.1.1), rib (0.32.0), sanic (0.1.0), sommer (4.5.12)

Updates on CRAN: admetshiny (1.0.1), CompositionalZADR (1.1), exametrika (2.2.0), ggpicrust2 (2.6.0), ragR (0.1.1), samplingVarEst (1.6), tidyactuarial (0.2.0), wql (1.0.4)

Updates on CRAN: arrow (26.0.0), contrast (0.25.0), enrollcast (0.2.0), pslr (1.2.2), stratifyR (2.0-4), sure (0.3.1), yamlet (1.4.0)