suwo: Access Nature Media Repositories Streamline searching, downloading and formatting of nature media files (e.g. audios, photos) from online repositories. The package offers functions for obtaining media metadata from online repositories, downloading associated media files and updating data sets with new records.

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

inequality: Inequality Measurement, Decomposition, and Poverty Analysis Tools for measuring income and wealth inequality. Computes the Gini coefficient with bootstrap or asymptotic confidence intervals following Davidson (2009) &lt;<a href="https://doi.org/10.1016%2Fj.jeconom.2008.09.011" target="_top">doi:10.1016/j.jeconom.2008.09.011</a>&gt;, the extended S-Gini family, Theil T and L indices (generalised entropy family), the Atkinson index, the Kolm absolute inequality index, Palma ratio, Hoover index, percentile ratios, and Lorenz curves. Supports between-within group decomposition following Bourguignon (1979) &lt;<a href="https://doi.org/10.2307%2F1914138" target="_top">doi:10.2307/1914138</a>&gt;, income share tabulation, concentration indices for health inequality with Erreygers (2009) correction, Kakwani tax progressivity and Reynolds-Smolensky redistribution indices, Foster-Greer-Thorbecke poverty measures including the Sen index, growth incidence curves following Ravallion and Chen (2003) &lt;<a href="https://doi.org/10.1016%2FS0165-1765%2802%2900205-7" target="_top">doi:10.1016/S0165-1765(02)00205-7</a>&gt;, and Wolfson polarisation. All functions accept optional survey weights and work with data from any source.

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

Updates on CRAN: AIscreenR (0.3.2), arakno (1.3.2), dsp (1.3.0), episomer (3.0.34), genieBPC (2.2.0), hmetad (0.1.1), pysparklyr (0.2.1), resemble (3.0.0), robustlmm (3.4-3), widr (0.1.1)

Updates on CRAN: cts (1.0-25), CUSUMdesign (1.1.6), maestro (1.1.0), Nestimate (0.4.3), pizzarr (0.2.0), upset.hp (0.0.6)

srcpkgs: R Source Packages Manager Manage a collection/library of R source packages. Discover, document, load, test source packages. Enable to use those packages as if they were actually installed. Quickly reload only what is needed on source code change. Run tests and checks in parallel.

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

SQIpro: Comprehensive Soil Quality Index Computation and Visualization Provides a comprehensive, modular framework for computing the Soil Quality Index (SQI) using six established methods: Linear Scoring (Doran and Parkin, 1994, &lt;<a href="https://doi.org/10.2136%2Fsssaspecpub35.c1" target="_top">doi:10.2136/sssaspecpub35.c1</a>&gt;), Regression-based (Masto et al., 2008, &lt;<a href="https://doi.org/10.1007%2Fs10661-007-9697-z" target="_top">doi:10.1007/s10661-007-9697-z</a>&gt;), Principal Component Analysis-based (Andrews et al., 2004, &lt;<a href="https://doi.org/10.2136%2Fsssaj2004.1945" target="_top">doi:10.2136/sssaj2004.1945</a>&gt;), Fuzzy Logic, Entropy Weighting (Shannon, 1948, &lt;<a href="https://doi.org/10.1002%2Fj.1538-7305.1948.tb01338.x" target="_top">doi:10.1002/j.1538-7305.1948.tb01338.x</a>&gt;), and TOPSIS (Hwang and Yoon, 1981, &lt;<a href="https://doi.org/10.1007%2F978-3-642-48318-9" target="_top">doi:10.1007/978-3-642-48318-9</a>&gt;). Implements four variable scoring functions: more-is-better, less-is-better, optimum-value, and trapezoidal, following Karlen and Stott (1994, &lt;<a href="https://doi.org/10.2136%2Fsssaspecpub35.c4" target="_top">doi:10.2136/sssaspecpub35.c4</a>&gt;). Includes automated Minimum Data Set selection via Principal Component Analysis with Variance Inflation Factor filtering (Kaiser, 1960, &lt;<a href="https://doi.org/10.1177%2F001316446002000116" target="_top">doi:10.1177/001316446002000116</a>&gt;), one-way ANOVA with Tukey HSD post-hoc tests, leave-one-out sensitivity analysis, and publication-quality visualization using 'ggplot2'.

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

drrglm: Doubly Regularized Matrix-Variate Regression The doubly regularized matrix-variate regression solves a low-rank-plus-sparse structure for matrix-variate generalized linear models through a weighted combination of nuclear-norm and L1-norm. The methodology implemented by this package is described in the paper "Doubly Regularized Matrix-Variate Regression", which has been tentatively accepted for publication but does not yet have a DOI or URL. A formal citation will be added in a future update once the final publication details are available.

New on CRAN: drrglm (0.3.2). View at https://CRAN.R-project.org/package=drrglm

confMeta: Confidence Curves and P-Value Functions for Meta-Analysis Provides tools for the combination of individual study results in meta-analyses using 'p-value' functions. Implements various combination methods including those by Fisher, Stouffer, Tippett, Edgington along with weighted generalizations. Contains functionality for the visualization and calculation of confidence curves and drapery plots to summarize evidence across studies.

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

cdlsim: Simulation of Cropland Data Layer Products from the USDA Provides tools to simulate categorical raster data, including objects from the 'terra' package. Functions focus on generating edge pixel values from reclassified raster data derived from the United States Department of Agriculture (USDA) Cropland Data Layer products.

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

BoundIRT: Fit Bounded Continuous Item Response Theory Models to Data Bounded continuous data are encountered in many areas of test application. Examples include visual analogue scales used in the measurement of personality, mood, depression, and quality of life; item response times from tests with item deadlines; confidence ratings; and pain intensity ratings. Using this package, item response theory (IRT) models suitable for bounded continuous item scores can be fitted to data within a Bayesian framework. The package draws on posterior sampling facilities provided by R-package 'rstan' (Stan Development Team, 2025)&lt;<a href="https://mc-stan.org/" target="_top">https://mc-stan.org/</a>&gt;. Available models include the Beta IRT model by Noel and Dauvier (2007)&lt;<a href="https://doi.org/10.1177%2F0146621605287691" target="_top">doi:10.1177/0146621605287691</a>&gt;, the continuous response model by Samejima (1973)&lt;<a href="https://doi.org/10.1007%2FBF03372160" target="_top">doi:10.1007/BF03372160</a>&gt;, the unbounded normal model by Mellenbergh (1994)&lt;<a href="https://doi.org/10.1207%2Fs15327906mbr2903_2" target="_top">doi:10.1207/s15327906mbr2903_2</a>&gt;, and the Simplex IRT model by Flores et al. (2020)&lt;<a href="https://doi.org/10.1007%2F978-3-030-43469-4_8" target="_top">doi:10.1007/978-3-030-43469-4_8</a>&gt;. All models can be fitted with or without zero-one inflation (Molenaar et al., 2022)&lt;<a href="https://doi.org/10.3102%2F10769986221108455" target="_top">doi:10.3102/10769986221108455</a>&gt;. Model fit comparisons can be conducted using the Watanabe–Akaike information criterion (WAIC), the deviance information criterion (DIC), and the fully marginalized likelihood (i.e., Bayes factors).

New on CRAN: BoundIRT (0.0.1). View at https://CRAN.R-project.org/package=BoundIRT

Updates on CRAN: ggmlR (0.7.5), nanoparquet (0.5.1), poissonreg (1.0.2), popbayes (1.3), ps (1.9.3), retrosheet (1.1.7), RSiena (1.6.6), spicy (0.9.0), testcorr (0.4.0)

Removed from CRAN: ggtaxplot (0.0.1), srcpkgs (0.2), S4Vectors (0.49.1-1)

hrbrthemes: Additional Themes, Theme Components and Utilities for 'ggplot2' A compilation of extra 'ggplot2' themes, scales and utilities, including a spell check function for plot label fields and an overall emphasis on typography. A copy of the 'Google' font 'Roboto Condensed' is also included.

New on CRAN: hrbrthemes (0.9.3). View at https://CRAN.R-project.org/package=hrbrthemes

Updates on CRAN: DQA (0.1.1), gerda (0.6.0), tmap (4.3)

Removed from CRAN: tynding (0.1.2)

Updates on CRAN: cellGeometry (0.6.3), MazamaLocationUtils (0.4.5)

Updates on CRAN: osrm.backend (0.3.0)

Updates on CRAN: ciecl (0.9.6), coda.pack (0.1.3), domir (1.3.0), GeNetIt (0.1-7), ncmR (0.2.0), varPro (3.1.0), yaImpute (1.0-36)

Removed from CRAN: clootl (0.1.3), ShortRead (1.69.3-2)

Updates on CRAN: akin (0.3.0), BioThermR (0.1.1), CovEsts (1.1.0)

Updates on CRAN: sasif (0.1.3)

Updates on CRAN: BEND (2.0.1), detectseparation (0.4.0), energyr (0.4), faunabr (1.0.1), randomForestSRC (3.6.2)

Updates on CRAN: metamedian (1.2.2), xpose.xtras (0.1.3)

hierNest: Penalized Regression with Hierarchical Nested Parameterization Structure Efficient implementation of penalized regression with hierarchical nested parametrization for grouped data. The package provides penalized regression methods that decompose subgroup specific effects into shared global effects, Major subgroup specific effects, and Minor subgroup specific effects, enabling structured borrowing of information across related clinical subgroups. Both lasso and hierarchical overlapping group lasso penalties are supported to encourage sparsity while respecting the nested subgroup structure. Efficient computation is achieved through a modified design matrix representation and a custom algorithm for overlapping group penalties.

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

Updates on CRAN: finetune (1.3.0), h5lite (2.1.1.0), kardl (1.3.0), matrixCorr (0.11.1), multiScaleR (0.6.13), pxmake (0.20.1), rextendr (0.5.0)

Updates on CRAN: ffiec (0.2.0), fs (2.1.0), mnirs (0.6.2), PriceIndices (0.3.1), qol (1.3.0), Ruido (1.0.3), scaledescr (0.2.5), zCompositions (1.6.1)

Updates on CRAN: neuroSCC (1.0.2), zarr (0.3.0)

Updates on CRAN: GCCfactor (1.1.6), ReliaPlotR (0.5), sparklyr (1.9.4)

Updates on CRAN: tidyILD (0.4.0)

Updates on CRAN: fasterRaster (8.4.1.2), PACVr (1.1.5), quickr (0.3.0), RHclust (3.0.0)