Wed, 07 Oct 2026

Package tabulergm updated to version 0.2.0 with previous version 0.1.0 dated 2026-08-21

Title: Publication-Ready Tables and Summaries for Exponential-Family Random Graph Models
Description: Creates publication-ready tables documenting exponential-family random graph models (ERGMs), a class of statistical models for social networks (Robins et al., 2007, <doi:10.1016/j.socnet.2006.08.002>). Tables describe model terms through their definitions, mathematical representations, and graphical representations, and can be generated from ERGM formulas or from models fitted with the 'ergm' package (Hunter et al., 2008, <doi:10.18637/jss.v024.i03>). Resulting tables can be integrated into 'quarto' and 'rmarkdown' documents.
Author: George Vega Yon [aut, cre]
Maintainer: George Vega Yon <g.vegayon@gmail.com>

Diff between tabulergm versions 0.1.0 dated 2026-08-21 and 0.2.0 dated 2026-10-07

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Package gtheoryr updated to version 0.2.0 with previous version 0.1.0 dated 2026-03-19

Title: Simple Generalizability Theory for Crossed and Nested Designs
Description: Provides a small, beginner-friendly interface for estimating variance components in simple generalizability theory designs. The package currently supports a fully crossed persons-by-items design, generic balanced crossed designs with one or more additional facets such as raters, occasions, or forms, and a simple items-within-person nested design, along with design-study summaries for relative and absolute decisions. Includes data diagnostics, measurement error intervals, design comparison and cost planning, sensitivity analysis, Gaussian simulation and parametric bootstrap uncertainty estimates for balanced crossed designs.
Author: Ujjwal Tyagi [aut, cre]
Maintainer: Ujjwal Tyagi <ujjwaltyagiii@gmail.com>

Diff between gtheoryr versions 0.1.0 dated 2026-03-19 and 0.2.0 dated 2026-10-07

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More information about gtheoryr at CRAN
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Package BMIselect updated to version 1.0.10 with previous version 1.0.9 dated 2026-08-21

Title: Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Datasets
Description: Provides a suite of Bayesian MI-LASSO for variable selection methods for multiply-imputed datasets. The package includes four Bayesian MI-LASSO models using shrinkage (Multi-Laplace, Horseshoe, ARD) and Spike-and-Slab (Spike-and-Laplace) priors, along with tools for model fitting via MCMC, four-step projection predictive variable selection, and hyperparameter calibration. Methods are suitable for both continuous and binary covariates under missing-at-random or missing-completely-at-random assumptions. See Zou, J., Wang, S. and Chen, Q. (2025), Bayesian MI-LASSO for Variable Selection on Multiply-Imputed Data. ArXiv, 2211.00114. <doi:10.48550/arXiv.2211.00114> for more details. We also provide the frequentist MI-LASSO function.
Author: Jungang Zou [aut, cre], Sijian Wang [aut], Qixuan Chen [aut]
Maintainer: Jungang Zou <jungang.zou@gmail.com>

Diff between BMIselect versions 1.0.9 dated 2026-08-21 and 1.0.10 dated 2026-10-07

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More information about BMIselect at CRAN
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Package letsRept updated to version 1.1.3 with previous version 1.1.2 dated 2026-06-22

Title: An Interface to the Reptile Database
Description: Provides tools to retrieve and summarize taxonomic information and synonymy data for reptile species using data scraped from The Reptile Database website (<https://reptile-database.reptarium.cz/>). Outputs include clean and structured data frames useful for ecological, evolutionary, and conservation research.
Author: Joao Paulo dos Santos Vieira-Alencar [aut, cre] , Christoph Liedtke [aut]
Maintainer: Joao Paulo dos Santos Vieira-Alencar <joaopaulo.valencar@gmail.com>

Diff between letsRept versions 1.1.2 dated 2026-06-22 and 1.1.3 dated 2026-10-07

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