CRANberries

Sat, 05 Sep 2026

New package sssp with initial version 0.1.0
Package: sssp
Title: Semi-Symmetric Sparse Projection
Version: 0.1.0
Description: Computes the exact joint sparsity and group sparsity projection using the Semi-symmetric Sparse Projection algorithm of J. Shen and S. Damadi, "Sparse projection onto semi-symmetric sets with applications to sparse optimization", Journal of Global Optimization (2026), <doi:10.1007/s10898-026-01592-y>.
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Suggests: knitr, rmarkdown
NeedsCompilation: yes
Packaged: 2026-08-24 21:35:34 UTC; saeed
Author: Saeed Damadi [aut, cre]
Maintainer: Saeed Damadi <sparsification@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-05 14:10:02 UTC

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New package vbpm with initial version 0.9.1
Package: vbpm
Title: Variational Bayes Psychometric Models
Version: 0.9.1
Description: Variational Bayes estimation for a family of psychometric measurement models. Two models are provided. Variational Bayes factor analysis (vbfa) is a regularized partially confirmatory factor model spanning the confirmatory-exploratory continuum via spike-and-slab priors on the loadings (Chen, Guo, Zhang, and Pan, 2021 <doi:10.1037/met0000293>; Chen, 2023 <doi:10.3758/s13428-022-01884-7>; Jin and Chen, 2025 <doi:10.1080/10705511.2024.2432612>), with an optional dynamic (warm-started) regularization path, an orthogonal bifactor parameterization, and optional sparse residual (local dependence) estimation through a graphical spike-and-slab prior solved by QUIC (Jin, Chen, Yan, and Zhang, 2026 <doi:10.31234/osf.io/dehtv_v2>). Regularized MIMIC (vbmimic) extends this to multiple-indicators multiple-causes models, placing spike-and-slab priors on both the measurement and the structural part (Jin and Chen, 2025 <doi:10.1080/00273171.2025.2483253>). Companion tools [...truncated...]
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: Rcpp, MASS, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: numDeriv, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Jinsong-Chen/vbpm
BugReports: https://github.com/Jinsong-Chen/vbpm/issues
NeedsCompilation: yes
Packaged: 2026-08-24 18:44:24 UTC; HKU
Author: Jinsong Chen [aut, cre] , Yi Jin [aut]
Maintainer: Jinsong Chen <jinsong.chen@live.com>
Repository: CRAN
Date/Publication: 2026-09-05 14:00:02 UTC

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New package suppr with initial version 1.0.0
Package: suppr
Title: Supplementary Idiomatic Utilities and Extensions
Version: 1.0.0
Description: Miscellaneous supplementary functions designed to follow idiomatic 'R' conventions. Some functions are simple wrappers that reduce repetitive code, while others address common tasks or extend existing 'R' functions.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: rlang, testthat (>= 3.0.0)
Imports: methods, stats
Depends: R (>= 4.0.0)
URL: https://lj-jenkins.github.io/suppr/, https://github.com/LJ-Jenkins/suppr
BugReports: https://github.com/LJ-Jenkins/suppr/issues
NeedsCompilation: yes
Packaged: 2026-08-24 14:59:56 UTC; lukej
Author: Luke Jenkins [aut, cre, cph]
Maintainer: Luke Jenkins <luke-jenkins-dev@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-05 13:30:02 UTC

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New package spatpersist with initial version 0.1.0
Package: spatpersist
Title: Create Persistent Identifiers for Longitudinal Spatial Data
Version: 0.1.0
Description: Creates dataset-local persistent identifiers for polygon units observed across time. Configurable overlap metrics, thresholds, and one-to-one matching rules identify continuity while separate identifiers track boundary versions and broader lineages through splits, mergers, and replacements. Candidate-link diagnostics, validation checks, registry reconciliation, and lineage summaries keep the resulting decisions inspectable and reproducible.
License: MIT + file LICENSE
URL: https://github.com/emre-cebeci/spatpersist
BugReports: https://github.com/emre-cebeci/spatpersist/issues
Encoding: UTF-8
Imports: sf
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-24 15:38:56 UTC; emrecebeci
Author: Emre Cebeci [aut, cre]
Maintainer: Emre Cebeci <cebeciemre1@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-05 13:50:02 UTC

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New package qdaR with initial version 0.1.0
Package: qdaR
Title: Read and Analyse Qualitative Coding Exported from Zotero
Version: 0.1.0
Description: Reads the versioned exchange files written by the Zotero plugins 'zotQDA' and 'qdaZ' -- coded fragments, code systems, coding histories and team-consensus results -- validates them against the shipped contract, and reproduces the plugin's graphics with 'ggplot2'. Adds what those plugins deliberately leave out: six agreement coefficients with bootstrap confidence intervals, the reliability of the segmentation itself, chi-squared tests of code by group tables with effect sizes, correspondence analysis, multidimensional scaling and hierarchical clustering of codes. Projects from other programs can be read through the 'REFI-QDA' interchange standard <https://www.qdasoftware.org/>, which makes those analyses available to users of established software that does not offer them; the subset a '.qdpx' supports is reported on import. Reference files are included, so every function can be tried without a Zotero installation.
License: AGPL-3
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: ggplot2, jsonlite, stats, utils, MASS
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, vegawidget, withr, xml2
VignetteBuilder: knitr
URL: https://zotqda.org, https://qdar.zotqda.org/, https://github.com/fre-ms/qdaR
BugReports: https://github.com/fre-ms/qdaR/issues
NeedsCompilation: no
Packaged: 2026-08-24 17:49:08 UTC; felmuell
Author: fre.ms [aut, cre]
Maintainer: fre.ms <fre.ms@fre.ms>
Repository: CRAN
Date/Publication: 2026-09-05 13:50:08 UTC

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New package mvdpd with initial version 0.1-1
Package: mvdpd
Title: Robust DPD Methods for Casewise and Cellwise Contamination
LazyLoad: yes
Version: 0.1-1
Date: 2026-08-23
Description: Robust multivariate estimation based on multivariate, composite and componentwise Density Power Divergence (DPD) minimization in multivariate normal distribution for casewise and cellwise contamination. Robust estimation for multivariate ordered gamma model using multivariate and composite DPD minimization. See A. Ghosh, C. Agostinelli, and A. Basu (2026) A Composite Divergence Approach to Robust Multivariate Estimation under Cellwise and Casewise Contamination. <doi:10.48550/arXiv.2608.18914> for full details.
License: GPL (>= 2)
Depends: R (>= 3.5.0)
Imports: MASS
Suggests: knitr, robustbase, cellWise, dplyr, ggplot2, reshape2, tidyr
SuggestsNote: mostly only because of vignette graphics
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-24 06:50:59 UTC; claudio
Author: Claudio Agostinelli [aut, cre], Abhik Ghosh [aut], Ayanendranath Basu [aut]
Maintainer: Claudio Agostinelli <claudio.agostinelli@unitn.it>
Repository: CRAN
Date/Publication: 2026-09-05 14:00:10 UTC

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New package ctOpenData with initial version 0.1.1
Package: ctOpenData
Title: A Lightweight Interface to Connecticut Open Data APIs
Version: 0.1.1
Description: Provides a unified set of helper functions to access datasets from the Connecticut Open Data platform <https://data.ct.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package provides a consistent interface for discovering and downloading datasets from the Connecticut Open Data Portal using human-readable dataset keys or official Socrata dataset identifiers.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: curl, dplyr, httr, janitor, jsonlite, rlang, tibble
Suggests: ggplot2, knitr, rmarkdown, scales, testthat (>= 3.0.0), tidyr, vcr (>= 0.6.0), webmockr
URL: https://github.com/gomes-sh/ctOpenData
BugReports: https://github.com/gomes-sh/ctOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-08-24 16:53:10 UTC; magic
Author: Shelby Lyn Gomes [aut] , Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-05 13:50:14 UTC

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New package CodeCarbonR with initial version 0.1.0
Package: CodeCarbonR
Title: Track Energy Consumption and Carbon Emissions of R Code
Version: 0.1.0
Description: Wraps the Python 'codecarbon' package via 'reticulate' to measure the energy consumption and estimated carbon emissions of R code. Provides a self-contained setup routine that installs 'codecarbon' into a dedicated conda environment, and an R-facing tracker API for measuring a block of code or a longer-running session.
License: MIT + file LICENSE
URL: https://beabock.github.io/CodeCarbonR/, https://github.com/beabock/CodeCarbonR
BugReports: https://github.com/beabock/CodeCarbonR/issues
Encoding: UTF-8
Imports: R6, reticulate
Suggests: knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
SystemRequirements: Python (>= 3.9); codecarbon Python package (>= 2.2.2), installed via setup_carbon_tracker()
NeedsCompilation: no
Packaged: 2026-08-24 15:33:04 UTC; beabo
Author: Beatrice Bock [aut, cre, cph] , Rachel Paterson [aut], Dylan van Bramer [aut]
Maintainer: Beatrice Bock <beabockm@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-05 13:50:20 UTC

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New package STATassist with initial version 1.0.0
Package: STATassist
Title: Standardised Statistical Comparison Workflows
Version: 1.0.0
Description: Runs the applicable tests for a comparison in one call and returns standardised result tables. One-sample, two-group, multi-group, factorial and categorical workflows report parametric, rank-based and robust results side by side with effect sizes, confidence intervals and multiplicity-adjusted p-values. Supervised fits, embeddings, clustering and simulators follow the same result contracts. Methods include those of Welch (1947) <doi:10.1093/biomet/34.1-2.28>, Wilcoxon (1945) <doi:10.2307/3001968>, Mann and Whitney (1947) <doi:10.1214/aoms/1177730491>, Kruskal and Wallis (1952) <doi:10.1080/01621459.1952.10483441>, Friedman (1937) <doi:10.1080/01621459.1937.10503522>, Tukey (1949) <doi:10.2307/3001913>, Dunn (1964) <doi:10.1080/00401706.1964.10490181>, Yuen (1974) <doi:10.1093/biomet/61.1.165>, Brunner and Munzel (2000) <doi:10.1002/(SICI)1521-4036(200001)42:1%3C17::AID-BIMJ17%3E3.0.CO;2-U>, Algina, Keselman and Penfield (2005) <d [...truncated...]
License: MIT + file LICENSE
URL: https://github.com/hiows/STATassist
BugReports: https://github.com/hiows/STATassist/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: caret, dbscan, glmnet, grDevices, graphics, kernlab, randomForest, Rtsne, stats, umap, utils
Suggests: jsonlite, pROC, testthat (>= 3.0.0), withr
NeedsCompilation: no
Packaged: 2026-08-24 11:03:13 UTC; hiows
Author: Wonseok Oh [aut, cre]
Maintainer: Wonseok Oh <hiows97@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-05 12:50:02 UTC

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Fri, 04 Sep 2026

New package plotomics with initial version 0.1.0
Package: plotomics
Title: High-Performance Bioinformatics Visualizations
Version: 0.1.0
Description: Lightweight, GPU-accelerated bioinformatics visualization widgets (volcano plots, expression and clustered heatmaps, dot plots, stacked violins, embeddings, spatial tissue maps, oncoprints, protein domain lollipops, Kaplan-Meier curves, mutational signature profiles, UpSet plots, treemaps, networks and Hi-C contact matrices) backed by a shared JavaScript core and exposed to R through 'htmlwidgets'. Designed for large datasets that render smoothly in the browser, the 'RStudio' Viewer, R Markdown, Quarto and Shiny.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: htmlwidgets
Suggests: knitr, rmarkdown, shiny, testthat (>= 3.0.0), survival
VignetteBuilder: knitr
URL: https://github.com/samuelbharti/plotomics, https://doi.org/10.5281/zenodo.21926306
BugReports: https://github.com/samuelbharti/plotomics/issues
NeedsCompilation: no
Packaged: 2026-08-24 10:10:36 UTC; Samuel
Author: Samuel Bharti [aut, cre]
Maintainer: Samuel Bharti <samuelbharti.io@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-04 21:50:02 UTC

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New package syrona with initial version 0.2.1
Package: syrona
Title: Stratified Prevalence Comparison Across OMOP CDM Datasets
Version: 0.2.1
Description: Derives stratified prevalence tables from the condition, procedure, and drug records in OMOP CDM (Observational Medical Outcomes Partnership Common Data Model) databases, computes log2 prevalence ratios between paired datasets, and synthesizes them via random-effects meta-analysis at multiple aggregation levels (year, age group, and sex). Between-study variance is estimated with the Paule-Mandel method, as described in Paule and Mandel (1982) <doi:10.6028/jres.087.022>.
License: MIT + file LICENSE
URL: https://github.com/HealthInformaticsUT/Syrona
BugReports: https://github.com/HealthInformaticsUT/Syrona/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: dplyr (>= 1.1.0), dbplyr (>= 2.3.0), DBI (>= 1.2.0), CDMConnector (>= 2.0.0), omopgenerics (>= 1.3.0), tibble, tidyr, cli, rlang, shiny, ggplot2, ggiraph, ggtext, scales, grDevices, stats, readr (>= 2.0.0), meta (>= 6.0.0)
Suggests: testthat (>= 3.0.0), duckdb (>= 0.9.0), RPostgres, CohortConstructor (>= 0.6.0), DT, shinycssloaders, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-06 12:34:32 UTC; maarjapajusalu
Author: Maarja Pajusalu [aut, cre]
Maintainer: Maarja Pajusalu <maarja.pajusalu@ut.ee>
Repository: CRAN
Date/Publication: 2026-09-04 20:10:02 UTC

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New package bGMYC4 with initial version 4.1.6
Package: bGMYC4
Title: Bayesian General Mixed Yule-Coalescent Model for Species Delimitation
Version: 4.1.6
Description: Implements a Bayesian version of the general mixed Yule-coalescent model for species delimitation. It uses Markov Chain Monte Carlo simulation to evaluate the posterior distribution of the model and supports flexible prior specification on model parameters.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: ape (>= 5.0), future, future.apply
Suggests: mcmcse, plotly, base64enc, testthat (>= 3.0.0), knitr, rmarkdown, htmltools, htmlwidgets, treeio, ggtree, dplyr
VignetteBuilder: knitr, rmarkdown
URL: https://github.com/DmitryKarabanov/bGMYC4
BugReports: https://github.com/DmitryKarabanov/bGMYC4/issues
NeedsCompilation: no
Packaged: 2026-08-24 07:20:13 UTC; Professional
Author: Noah Reid [aut, cph] , Dmitry Karabanov [aut, cre]
Maintainer: Dmitry Karabanov <dk@ibiw.ru>
Repository: CRAN
Date/Publication: 2026-09-04 20:30:02 UTC

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New package AugmentedPooledRCBD with initial version 0.1.0
Package: AugmentedPooledRCBD
Title: Augmented Pooled Randomized Complete Block Design Analysis
Version: 0.1.0
Maintainer: Santosha Rathod <santoshagriculture@gmail.com>
Description: Augmented randomized complete block designs (augmented RCBDs) are useful for researchers to evaluate large numbers of unreplicated test entries with limited replicated checks. This R and 'Shiny'-based statistical package provides methods for the analysis of augmented randomized complete block designs (augmented RCBDs) across multiple environments. The package performs environment-wise augmented RCBD analysis and pooled analysis across environments, including analysis of variance (ANOVA), testing for homogeneity of error variances across environments, adjusted treatment means, treatment sum-of-squares partitioning, standard error of the mean (SEM), critical difference (CD), and treatment ranking. For pooled analysis, environment-specific error variances are assessed for homogeneity and used for appropriate transformation where required, followed by a general linear model incorporating environment, block nested within environment, treatment, and environment x treatment interaction. This [...truncated...]
License: GPL-3
Encoding: UTF-8
Imports: car, dplyr, emmeans, shiny, DT, shinybusy, rlang
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-24 05:58:45 UTC; Dr. Santosh Rathod
Author: Santosha Rathod [aut, cre, ctb], Susheel Kumar Sarkar [aut, ctb], Bijoy Chanda [aut, ctb], Bellamkonda Jyostna [aut], Sayantani Karmakar [aut], Vishnu Shankar [aut], Santosh Ganapati Patil [aut], Prabhat Kumar [aut], Prashant Vikram [aut], Mrinmoy Ra [...truncated...]
Repository: CRAN
Date/Publication: 2026-09-04 19:50:09 UTC

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New package ambre with initial version 2.1.2
Package: ambre
Title: Multi-Barrier Approach for Water Reuse Risk Assessment
Version: 2.1.2
Description: Provides a Quantitative Microbial Risk Assessment (QMRA) framework for the reuse of treated wastewater in agricultural irrigation. Following a multi-barrier approach, the package simulates pathogen inflow and removal along a treatment train, estimates human exposure, and computes health risk indicators such as infection probability, illness probability, and Disability-Adjusted Life Years (DALYs). It also supports an economic analysis of the treatment scenarios considered. For more details see <doi:10.36904/20240595>.
License: MIT + file LICENSE
URL: https://forge.inrae.fr/reversaal/reut/ambre-package
BugReports: https://forge.inrae.fr/reversaal/reut/ambre-package/-/issues
Depends: R (>= 4.1.0)
Imports: colorspace, cowplot, dplyr, EnvStats, formattable, ggplot2, plyr, purrr, readxl, rlang, scales, sfsmisc, stats, stringr, tibble, tidyr, utils
Suggests: knitr, rmarkdown, spelling, testthat, writexl
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-24 06:34:38 UTC; flgirard
Author: Flora Girard [aut, cre] , Nicolas Forquet [ctb] , Arthur Breant [ctb], Colin Fay [ctb]
Maintainer: Flora Girard <flora.girard@inrae.fr>
Repository: CRAN
Date/Publication: 2026-09-04 19:50:02 UTC

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Thu, 03 Sep 2026

New package spfcICOMP with initial version 0.1.0
Package: spfcICOMP
Title: Shrinkage Principal Fitted Components with Information Complexity-Based Model Selection
Version: 0.1.0
Description: Implements shrinkage principal fitted components for sufficient dimension reduction in high-dimensional regression and classification. Provides regularised covariance estimation using Oracle Approximating Shrinkage and Maximum Entropy Covariance, structural-dimension selection using conventional and information-complexity criteria, response-guided feature screening, reduced-space prediction, and simulation utilities. Methodological foundations include Cook and Forzani (2008) <doi:10.1214/08-STS275>, Chen et al. (2010) <doi:10.1109/TSP.2010.2053029>, Bozdogan (2000) <doi:10.1006/jmps.1999.1277>, and Olorede and Yahya (2019) <doi:10.48550/arXiv.1909.13017>.
License: MIT + file LICENSE
URL: https://github.com/ilovemaths/spfcICOMP
BugReports: https://github.com/ilovemaths/spfcICOMP/issues
Encoding: UTF-8
Language: en-GB
Imports: MASS
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2026-08-21 20:26:55 UTC; DR OLOREDE
Author: Kabir Opeyemi Olorede [aut, cre, cph]
Maintainer: Kabir Opeyemi Olorede <kabir.olorede@kwasu.edu.ng>
Repository: CRAN
Date/Publication: 2026-09-03 13:50:02 UTC

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New package K4Guru with initial version 0.1.0
Package: K4Guru
Title: Teacher Context Data Files for TIMSS 2023 Grade 4
Version: 0.1.0
Description: The official Trends in International Mathematics and Science Study (TIMSS) 2023 website provides Teacher Context Data Files for Grade 4 in RData format. However, the available data are presented solely as numerical values. This package transforms the numerical data into categorical variables, enabling clearer interpretation and reducing ambiguity in statistical analysis. The category labels are provided in Bahasa Indonesia. This initiative contributes to promoting the use of Bahasa Indonesia in programming, in line with its designation as one of the official languages of the United Nations. For more details see <https://timss2023.org/>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-06 14:40:44 UTC; HP
Author: Fadhlul Mubarak [aut, cre] , Vinny Yuliani Sundara [aut]
Maintainer: Fadhlul Mubarak <mubarakfadhlul@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 13:10:03 UTC

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New package BUSfinancial with initial version 0.1.0
Package: BUSfinancial
Title: Economic Analysis of Islamic Commercial Bank Financial Time Series in Indonesia
Version: 0.1.0
Description: Provides simple economic indicators for analyzing financial position time series of Islamic Commercial Banks in Indonesia.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-24 00:43:03 UTC; HP
Author: Fadhlul Mubarak [aut, cre] , Vinny Yuliani Sundara [aut]
Maintainer: Fadhlul Mubarak <mubarakfadhlul@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 13:20:02 UTC

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New package wishartinference with initial version 0.1.0
Package: wishartinference
Title: Bayesian Inference for the Wishart Distribution Parameters
Version: 0.1.0
Description: Posterior inference for the shape parameter alpha and mean matrix mu in the model X_i ~ Wishart_p(2*alpha, Sigma), under both an improper prior and a proper Gamma/inverse-Wishart prior. The posterior mode is found via a Newton-within-EM algorithm and joint samples are drawn via rejection sampling.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp
LinkingTo: Rcpp, RcppArmadillo, BH
Suggests: testthat (>= 3.1.5)
NeedsCompilation: yes
Packaged: 2026-08-20 16:37:30 UTC; sunnyshi
Author: Philip Everson [aut], Hanqi Shi [aut, cre]
Maintainer: Hanqi Shi <hshi1@swarthmore.edu>
Repository: CRAN
Date/Publication: 2026-09-03 12:10:02 UTC

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New package SujathaDist with initial version 1.0.0
Package: SujathaDist
Title: Statistical Methods for the Sujatha Distribution
Version: 1.0.0
Maintainer: Hosenur Rahman Prodhani <hosenur72@gmail.com>
Description: Provides computational tools for the Sujatha distribution, including probability density, cumulative distribution, quantile function, random number generation, parameter estimation by maximum likelihood, goodness-of-fit procedures, and associated statistical methods for lifetime data analysis. The implemented methods are based on the Sujatha distribution proposed by Shanker (2016) <doi:10.59170/stattrans-2016-023>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr
VignetteBuilder: knitr
URL: https://github.com/hosenur72/SujathaDist
BugReports: https://github.com/hosenur72/SujathaDist/issues
NeedsCompilation: no
Packaged: 2026-08-23 16:53:13 UTC; hosen
Author: Hosenur Rahman Prodhani [aut, cre]
Repository: CRAN
Date/Publication: 2026-09-03 12:20:16 UTC

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New package statfidelity with initial version 0.1.0
Package: statfidelity
Title: Audit Statistical Fidelity of AI-Mediated Official Statistics
Version: 0.1.0
Description: Provides deterministic tools for auditing whether artificial intelligence systems preserve the numerical, semantic, contextual, temporal, geographic, unit, provenance, revision, transformation, and uncertainty properties of official statistics. Structured reference statistics and machine-generated claims can be compared with non-compensatory critical-error rules, weakest-link and geometric fidelity summaries, provenance graphs, and portable SHA-256 proof bundles. The package also provides bounded connectors for official Eurostat, World Bank, OECD, United Nations SDG, United Kingdom Office for National Statistics, and United States Bureau of Labor Statistics application programming interfaces, plus an extensible HTTPS JSON API registry with session-only API-key support. Prompt perturbation, statistical red-team generation, minimal-pair tests, and starter benchmark data support reproducible evaluation of generative, retrieval-augmented, and agentic statistical systems. An embedded alignm [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: digest, jsonlite, stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-20 16:38:12 UTC; marvian
Author: Hossein Hassani [aut], Steve MacFeely [aut], Leila Marvian Mashhad [aut, cre]
Maintainer: Leila Marvian Mashhad <leila.marveian@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:10:08 UTC

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New package SCCDdesign with initial version 0.1.0
Package: SCCDdesign
Title: Construction of Screening Designs for Mixed Level Continuous and Categorical Factors
Version: 0.1.0
Description: Provides functions for constructing screening designs for experiments involving three-level continuous and two-level categorical factors. The package implements three methods proposed by Jones, B., Lekivetz, R., Majumdar, D. and Nachtsheim, C. (2025) <doi:10.1080/00401706.2024.2362149> for generating efficient screening designs for even run sizes. It also includes functions for constructing conference matrices using Paley Type I and Type II constructions, as well as construction of pseudo conference matrices by coordinate exchange algorithm given by Jones, B. and Nachtsheim, C. J. (2011) <doi:10.1080/00224065.2011.11917841> which are used in the development of these screening designs.
License: GPL-3
Encoding: UTF-8
Imports: pracma, AlgDesign
NeedsCompilation: no
Packaged: 2026-08-13 16:47:20 UTC; VYSHNA
Author: Vyshna I C [aut, cre], Cini Varghese [aut, ctb], Safeela Nasrin [aut], Boyina Devi Priyanka [aut, ctb], Mohd Harun [aut, ctb], Anindita Datta [aut, ctb]
Maintainer: Vyshna I C <vyshnaic@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:20:22 UTC

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New package mlr3automl with initial version 0.1.0
Package: mlr3automl
Title: Automated Machine Learning for 'mlr3'
Version: 0.1.0
Description: Flexible automated machine learning (AutoML) system for the 'mlr3' ecosystem. Automatically selects a suitable machine learning algorithm and tunes its hyperparameters for a given task. Constructs preprocessing pipelines with multiple parallel branches using 'mlr3pipelines' and jointly optimizes them together with the learners using 'mlr3tuning'. The optimization is driven by asynchronous decentralized Bayesian optimization by Egele et al. (2023) <doi:10.1109/e-Science58273.2023.10254839>.
License: LGPL-3
URL: https://mlr3automl.mlr-org.com, https://github.com/mlr-org/mlr3automl
BugReports: https://github.com/mlr-org/mlr3automl/issues
Depends: mlr3 (>= 1.6.0), mlr3tuning (>= 1.6.0), R (>= 3.3.0), rush (>= 1.2.1)
Imports: bbotk (>= 1.7.1), checkmate, data.table, lhs, mlr3learners (>= 0.14.0), mlr3mbo (>= 1.2.0), mlr3misc (>= 0.15.1), mlr3pipelines, paradox (>= 1.0.1), R6, utils
Suggests: callr, e1071, fastai, glmnet, kknn, lgr, lightgbm, MASS, mirai, mlr3extralearners, mlr3torch (>= 0.3.3), mlr3viz, ranger, redux, reticulate, rpart, testthat (>= 3.0.0), torch, xgboost (>= 3.2.1.1)
Additional_repositories: https://mlr-org.r-universe.dev
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-20 09:05:18 UTC; marc
Author: Marc Becker [cre, aut, cph] , Damir Pulatov [aut], Baisu Zhou [aut], Lona Koers [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>
Repository: CRAN
Date/Publication: 2026-09-03 12:20:03 UTC

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New package later2 with initial version 0.1
Package: later2
Title: Utilities for Scheduling Functions to Execute Later with Event Loops
Version: 0.1
Description: Executes arbitrary R or C functions some time after the current time, after the R execution stack has emptied. The functions are scheduled in an event loop. This is a derived work from the 'later' package aiming to reduce the number of dependencies.
License: Apache License 2.0
URL: https://github.com/pachadotdev/later2
BugReports: https://github.com/pachadotdev/later2/issues
Depends: R (>= 3.5)
Suggests: tinytest, parallel, litedown
LinkingTo: cpp4r
Encoding: UTF-8
VignetteBuilder: litedown
NeedsCompilation: yes
Packaged: 2026-08-23 18:00:28 UTC; pacha
Author: Winston Chang [aut] , Joe Cheng [aut], Charlie Gao [aut] , Posit Software, PBC [aut, cph] , Marcus Geelnard [ctb, cph] , Evan Nemerson [ctb, cph] , Mauricio Vargas Sepulveda [aut, cre]
Maintainer: Mauricio Vargas Sepulveda <m.vargas.sepulveda@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:50:02 UTC

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New package icons with initial version 1.0.0
Package: icons
Title: Easily Insert SVG Icons into R Outputs
Version: 1.0.0
Description: Provides tools to download, style, and insert scalable vector graphics (SVG) icons into R output, such as 'R Markdown' and 'Quarto' documents, 'Shiny' apps, 'gt' tables, and 'ggplot2' visualisations via the 'ggicons' package. Bundles popular icon libraries, such as 'Font Awesome' (<https://fontawesome.com>), 'Academicons' (<https://jpswalsh.github.io/academicons/>), and 'Material Design Icons' (<https://fonts.google.com/icons>), which are downloaded on demand to keep the package small, or build a custom icon set from any folder of local SVG files. Icon appearance, such as size, colour, and position, can be customised.
Depends: R (>= 3.1.3)
Imports: base64enc, knitr, rlang, htmltools, glue, rappdirs, xml2, stringr, jsonlite, cli, utils, vctrs
Suggests: rsvg, gh, rmarkdown, pillar, shiny, testthat (>= 3.0.0)
URL: https://pkg.mitchelloharawild.com/icons/, https://github.com/mitchelloharawild/icons
BugReports: https://github.com/mitchelloharawild/icons/issues
VignetteBuilder: knitr
License: MIT + file LICENSE
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-23 11:38:49 UTC; mitchell
Author: Mitchell O'Hara-Wild [aut, cre] , Earo Wang [ctb] , Timothy Hyndman [ctb] , Matthew Warkentin [ctb] , Tom Jemmett [ctb]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:10:14 UTC

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New package graphvec with initial version 0.1.0
Package: graphvec
Version: 0.1.0
Title: Vectorised Graph Data Structures
Description: Extends vectors to include graph relationships between their elements, and offers tools to compute useful summaries of the graph structure for use in summarising, filtering, and otherwise manipulating the graph. Node identity is positional rather than value-based, so isolated nodes and repeated values are represented without special handling. Three complementary data structures are provided, each an ordinary vector that stays a column in a data frame and slices consistently with it: 'node_vec' is vectorised along the nodes of a graph, 'edge_vec' is vectorised along its edges, and 'agg_vec' (with the tabular 'agg_df') represents the aggregation structure common in data analysis, such as a total row over a set of categories. This makes graph relationships a native part of tidy rectangular data analysis workflows, alongside tools such as those in 'dplyr'. Each of these can also be converted to 'igraph' objects for further analysis.
License: MIT + file LICENSE
Imports: tibble
Suggests: crayon, dplyr, igraph, pillar, testthat (>= 3.0.0)
Encoding: UTF-8
URL: https://pkg.mitchelloharawild.com/graphvec/, https://github.com/mitchelloharawild/graphvec
BugReports: https://github.com/mitchelloharawild/graphvec/issues
NeedsCompilation: no
Packaged: 2026-08-20 13:54:47 UTC; mitchell
Author: Mitchell O'Hara-Wild [aut, cre]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:40:02 UTC

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New package Compositionalasmr with initial version 1.0
Package: Compositionalasmr
Title: The alpha-Spatial Median Regression for Compositional Data
Version: 1.0
Date: 2026-08-20
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, minpack.lm, parallel, rangen, Rfast, stats
Suggests: Rfast2
Description: The alpha-spatial median regression is performed via the iteretively reweighted least squares algorithm. At first the alpha-transformation of Tsagris, Preston and Wood (2011) <doi:10.48550/arXiv.1106.1451> is applied and then the non-linear regression model is fitted.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-08-20 09:12:36 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-09-03 12:20:27 UTC

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New package awkreader with initial version 0.1.0
Package: awkreader
Title: File Reading with Pre-Filtering, Pattern Searching, and Distributed Files
Version: 0.1.0
Description: Provides high-performance tools for out-of-core text processing and data ingestion by leveraging system 'AWK' utilities. Allows users to count records, filter rows, and compute streaming aggregations—such as group-by means, streaming medians, standard deviations, and correlations—directly on disk prior to reading data into R. By delegating line-by-line filtering and summarization to system-level 'AWK' commands and streaming results back through data.table::fread(), the package significantly reduces memory footprint and execution times when working with large individual files or multi-file directory structures.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Imports: data.table
NeedsCompilation: no
Packaged: 2026-08-23 16:23:18 UTC; akshat
Author: David Shilane [aut], Akshat Maurya [aut, cre], Jason Livingston [aut], Chung-Woo Lee [aut], Mayur Bansal [aut], Srivastav Budugutta [aut]
Maintainer: Akshat Maurya <codingmaster902@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:20:11 UTC

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New package PTLENKies with initial version 0.1.0
Package: PTLENKies
Title: Computation of PTLENKies Distribution Properties
Version: 0.1.0
Author: Mintode Nicodeme Atchade [aut], Theophile Otodji [aut, cre]
Maintainer: Theophile Otodji <otodjitheodule@gmail.com>
Description: Implements statistical tools for analyzing, simulating, and computing properties of the Power Topp Leone Exponential Negative Kies Burr (PTLENKBurr). See Atchadé M, Otodji T, and Djibril A (2024) <doi:10.1063/5.0179458> and Atchadé M, Otodji T, Djibril A, and N'bouké M (2023) <doi:10.1515/phys-2023-0151> for details.
Depends: R (>= 4.1.0)
License: GPL-2
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Language: en
Imports: graphics, stats
NeedsCompilation: no
Packaged: 2026-08-04 08:54:43 UTC; Théophile OTODJI
Repository: CRAN
Date/Publication: 2026-09-03 11:50:47 UTC

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New package pcatR with initial version 1.0.1
Package: pcatR
Title: Analyze and Visualize Pragmatic Context Assessment Tool Data
Version: 1.0.1
Description: Provides a reproducible workflow for importing, validating, classifying, summarizing, visualizing, and reporting responses to the 14-item Pragmatic Context Assessment Tool (pCAT). The package preserves the instrument's two-part response structure, supports original and updated Consolidated Framework for Implementation Research (CFIR) mappings, describes team agreement and disagreement, compares repeated assessments, and creates implementation action-planning outputs. It does not calculate or claim a validated total pCAT scale score. The instrument is described by Robinson and Damschroder (2023) <doi:10.1186/s43058-022-00380-5>; updated CFIR mappings are from Domlyn et al. (2026) <doi:10.1186/s43058-026-00956-5>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.4.0), grDevices, grid, stats, utils
Suggests: covr, knitr, pkgdown, rmarkdown, shiny, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
URL: https://github.com/JaeManP/pcatR, https://jaemanp.github.io/pcatR/
BugReports: https://github.com/JaeManP/pcatR/issues
Packaged: 2026-08-21 23:25:50 UTC; runner
Author: Lilac Li [aut, cph] , Jae Man Park [cre, cph]
Maintainer: Jae Man Park <jaemanblp2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:40:02 UTC

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New package normalblockr with initial version 0.2.1
Package: normalblockr
Title: Gaussian Graphical Models with Latent Clustering Structure
Version: 0.2.1
Description: Implements the Normal-Block model, a Gaussian graphical model with a latent clustering structure for the multivariate analysis of continuous data. The model clusters variables and, building on the graphical lasso, infers a network of statistical dependencies between clusters rather than between individual variables, for known or unknown clusterings, with an optional zero-inflation extension for data with an excess of exact zeros. See Tous & Chiquet (2026) <doi:10.1016/j.csda.2026.108347> for the model itself and its variational expectation-maximization estimation procedure.
License: GPL (>= 3)
URL: https://github.com/jchiquet/normalblockr
BugReports: https://github.com/jchiquet/normalblockr/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: glassoFast, Matrix, dplyr, tidyr, tibble, purrr, R6, ggplot2, igraph, sbm, corrplot, scales, MASS, stats, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), aricode, covr, Metrics, rmarkdown, pheatmap, paletteer, ggthemes, knitr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-20 11:30:04 UTC; jchiquet
Author: Jeanne Tous [aut], Julien Chiquet [aut, cre]
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>
Repository: CRAN
Date/Publication: 2026-09-03 12:00:02 UTC

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New package modMStates with initial version 0.0.1
Package: modMStates
Title: Simulation and Estimation of Continuous-Time Multi-State Markov Models for Panel Data
Version: 0.0.1
Description: A higher-level interface to continuous-time Markov multi-state models for panel (interval-censored) data. Seven canonical clinical process structures are supplied with structurally valid generator matrices, so that transition matrices and starting values need not be constructed by hand. Panel data can be simulated from exact trajectories under regular or irregular observation schedules, with optional exactly observed absorption times and optional Weibull holding times for assessing the Markov assumption. A single fitting call validates the input against the assumed structure and returns the estimated generator with confidence intervals, mean sojourn times, transition probability matrices and observed transition counts, together with the optimiser's convergence code. A Monte Carlo driver reports Monte Carlo standard errors alongside bias, root mean squared error and interval coverage. Likelihood evaluation is delegated to 'msm' (Jackson, 2011, <doi:10.18637/jss.v038.i08>); the pan [...truncated...]
License: GPL-3
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.5.0)
Imports: msm (>= 1.6), stats, utils
Suggests: testthat (>= 3.0.0), survival
URL: https://github.com/infinitebstats/modMStates
BugReports: https://github.com/infinitebstats/modMStates/issues
NeedsCompilation: no
Packaged: 2026-08-23 10:14:21 UTC; root
Author: Atanu Bhattacharjee [aut, cre, ctb], Akash Pawar [aut, ctb]
Maintainer: Atanu Bhattacharjee <atanustat@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:50:13 UTC

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New package magp with initial version 0.8.0
Package: magp
Title: Mapping-Based Additive Gaussian Process Models
Version: 0.8.0
Description: Fits mapping-based additive Gaussian process models for experiments in which each component has both a quantitative level and a position in an ordered sequence. Two model structures are available: a compact two-dimensional mapping and a full mapping with one fewer dimension than the number of components. Both models support parameter estimation, point prediction, and plug-in predictive uncertainty. Input checks validate the sequence data and apply consistent scaling to the quantitative inputs. Computationally intensive covariance and gradient calculations are implemented in C++ with 'Rcpp'. The model was introduced by Xiao et al. (2024) <doi:10.1080/01621459.2022.2123335>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: Rcpp, nloptr, stats
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-08-22 03:51:29 UTC; skr
Author: Tony Wang [aut, cre, cph], Qian Xiao [aut, cph], Yaping Wang [cph], Abhyuday Mandal [cph], Xinwei Deng [cph]
Maintainer: Tony Wang <wangtony883@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:40:09 UTC

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New package iop with initial version 0.1.0
Package: iop
Title: Inflated Ordered Probit and Logit Models
Version: 0.1.0
Description: Estimation, inference, and quantities of interest for ordered probit and ordered logit models whose outcome contains an inflated category: a single ordered category (bottom, middle, top, or any other) that mixes observations generated by the ordered process with observations generated by a distinct split-population process. Fits the zero-inflated ordered probit of Harris and Zhao (2007) <doi:10.1016/j.jeconom.2007.01.002> and its middle- and top-inflated extensions (Bagozzi and Mukherjee 2012 <doi:10.1093/pan/mps020>; Bagozzi, Hill, Moore and Mukherjee 2015 <doi:10.1177/0022002713520530>; Bagozzi, Joo and Mukherjee 2024 <doi:10.1093/fpa/orae006>), generalized to an arbitrary inflated category and to the logit link, with optional correlated errors for the probit form, plus the standard ordered probit and logit and their partial proportional-odds (non-parallel) variants on the same footing. Provides analytic, robust, and cluster-robust standard errors, survey weig [...truncated...]
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0)
Imports: Rcpp, stats, graphics, methods, numDeriv, MASS
LinkingTo: Rcpp
Suggests: ordinal, VGAM, mvtnorm, pbivnorm, sandwich, DHARMa, testthat (>= 3.0.0), knitr, rmarkdown, broom, modelsummary, texreg, parallel, AER
VignetteBuilder: knitr
URL: https://github.com/bagozzib/iop, https://bagozzib.github.io/iop/
BugReports: https://github.com/bagozzib/iop/issues
NeedsCompilation: yes
Packaged: 2026-08-23 10:03:41 UTC; bagoz
Author: Benjamin E. Bagozzi [aut, cre]
Maintainer: Benjamin E. Bagozzi <bagozzib@udel.edu>
Repository: CRAN
Date/Publication: 2026-09-03 11:50:24 UTC

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New package golosovRST with initial version 0.0.1
Package: golosovRST
Title: Golosov Relative Size Triangle Classification and Plotting
Version: 0.0.1
Description: Computes coordinates for the Golosov Relative Size Triangle (RST), classifies party-system observations into Golosov subtypes using polygon mapping and produces publication-ready Relative Size Triangle plots. Method reference: Golosov, G. V. (2011) "Party system classification: A methodological inquiry" <doi:10.1177/1354068810377189>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, rlang
Suggests: sf, testthat (>= 3.0.0), dplyr
NeedsCompilation: no
Packaged: 2026-08-17 09:22:10 UTC; 39333
Author: Federico Taddei [aut, cre]
Maintainer: Federico Taddei <federico.taddei@unimi.it>
Repository: CRAN
Date/Publication: 2026-09-03 11:50:37 UTC

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New package geolibre with initial version 0.2.0
Package: geolibre
Title: Interactive GIS with 'GeoLibre'
Version: 0.2.0
Description: Embeds the full 'GeoLibre' geographic information system in 'R Markdown', 'Quarto', 'Shiny', and the 'RStudio' Viewer. Create maps from 'GeoJSON' and 'sf' objects, markers, heatmaps, and tabular coordinates; add 'Cloud Optimized GeoTIFF', 'XYZ', 'WMS', 'WMTS', 'WFS', 'PMTiles', vector tile, '3D Tiles', and video sources; classify choropleths, arrange layers, and add legends, colorbars, and split-map comparisons. Control the camera, export standalone 'HTML', and read and write '.geolibre.json' project files. The underlying application is described in Wu (2026) <doi:10.5281/zenodo.20785400>.
License: MIT + file LICENSE
URL: https://r.geolibre.app, https://github.com/opengeos/geolibre-r, https://geolibre.app
BugReports: https://github.com/opengeos/geolibre-r/issues
Depends: R (>= 4.1.0)
Imports: htmlwidgets, jsonlite, utils
Suggests: sf, shiny, testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-23 01:48:43 UTC; qiusheng
Author: Qiusheng Wu [aut, cre], Open Geospatial Solutions [cph]
Maintainer: Qiusheng Wu <giswqs@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:30:02 UTC

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New package essential8 with initial version 0.1.0
Package: essential8
Title: Reproducible Cardiovascular Health Metric Scoring
Version: 0.1.0
Description: Provides a reproducible R implementation of the American Heart Association Life's Essential 8 cardiovascular health scoring framework for complete adult records from people aged 20 years or older. Calculates the eight component scores and their unweighted composite score using the 2022 adult definition described by Lloyd-Jones et al. (2022) <doi:10.1161/CIR.0000000000001078>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: cli (>= 3.6.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://thatoneguy006.github.io/essential8/, https://github.com/thatoneguy006/essential8
BugReports: https://github.com/thatoneguy006/essential8/issues
NeedsCompilation: no
Packaged: 2026-08-23 01:51:46 UTC; Carso
Author: Carson Richardson [aut, cre, cph]
Maintainer: Carson Richardson <carson.richardson@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:20:09 UTC

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New package EpiLossR with initial version 0.1.0
Package: EpiLossR
Title: Economic Loss Estimation for Animal Disease Mortality and Morbidity
Version: 0.1.0
Date: 2026-08-01
Description: Provides standardized tools for estimating direct economic losses associated with mortality and morbidity in animal diseases. The package implements reproducible methods for calculating mortality- and morbidity-related losses using a common S3 object framework with methods for summarization, visualization, and data export. It is intended for veterinary epidemiologists, animal health economists, veterinarians, researchers, and students. The methods are informed by Rushton (2009, ISBN:9781845936934) and Bennett (2003, ISBN:9780851996224).
License: GPL (>= 3)
Encoding: UTF-8
Language: en-US
ByteCompile: true
Depends: R (>= 4.2.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/vinodhpmd/EpiLossR
BugReports: https://github.com/vinodhpmd/EpiLossR/issues
NeedsCompilation: no
Packaged: 2026-08-23 11:17:20 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:00:22 UTC

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New package ccwr with initial version 0.0.2
Package: ccwr
Title: Clone-Censor-Weight Methods for Target Trial Emulation
Version: 0.0.2
Description: Provides methods for clone-censor-weight analyses that emulate target trials with grace-period treatment strategies using observational time-to-event data. Tools clone participants across strategies, apply strategy-specific artificial censoring, and estimate inverse probability of censoring weights using pooled logistic or Cox models, fit weighted outcome models, and obtain subject-level bootstrap confidence intervals by repeating the complete analysis. The methods are described by Maringe et al. (2020) <doi:10.1093/ije/dyaa057> and Gaber et al. (2024) <doi:10.1002/cam4.70461>.
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS
URL: https://github.com/CausalInferenceLab/ccwr
BugReports: https://github.com/CausalInferenceLab/ccwr/issues
Encoding: UTF-8
Depends: R (>= 4.4.0)
Imports: dplyr, readr, survival, tibble, rlang, glue
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 23:02:09 UTC; sanghopark
Author: Sang Ho Park [aut, cre], Youngrok Lee [aut], Jihyeon Baek [aut], Hye Won Yang [aut], Donghoon Jeong [aut]
Maintainer: Sang Ho Park <shstat1729@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 12:00:16 UTC

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New package biohttp with initial version 0.1.2
Package: biohttp
Title: Normalized HTTP Transport with Circuit Breaking and Caching
Version: 0.1.2
Description: Web service calls return a normalized result value instead of raising a condition, so a caller branches on data rather than on an error handler. Transport failure, a non-success status code, and an unreadable response body are reported as three distinct outcomes. Per-host circuit breaking, retry with a transient-failure predicate, optional throttling, redacted request headers, and a success-only cache come as defaults. Many questions to one source can be asked as a single batch, where only the entries the cache is missing reach the network. Service-specific knowledge is left to the client packages built on top. The circuit breaker is the pattern described in Nygard (2018, ISBN:9781680502398).
License: MIT + file LICENSE
URL: https://github.com/samuelbharti/biohttp, https://www.samuelbharti.com/biohttp/
BugReports: https://github.com/samuelbharti/biohttp/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.0)
Imports: cachem, curl, httr2, jsonlite, rlang, tools
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), webfakes, withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-23 03:19:46 UTC; Samuel
Author: Samuel Bharti [aut, cre, cph]
Maintainer: Samuel Bharti <samuelbharti.io@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:50:41 UTC

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New package biobouncer with initial version 0.1.4
Package: biobouncer
Title: Validate Biological Identifiers and Inputs
Version: 0.1.4
Description: Gene symbols, ontology terms, variant formats, and database accessions are validated through one small application programming interface (API), either offline against identifier patterns and bundled snapshots or live against a source web service. Results are designed to match those of the companion 'Python' package for the same inputs. Input order and length are preserved, and errors are reported explicitly rather than as a silent failure. Identifier patterns follow the registry and nomenclature described in Hoyt et al. (2022) <doi:10.1038/s41597-022-01807-3> and den Dunnen et al. (2016) <doi:10.1002/humu.22981>.
License: MIT + file LICENSE
URL: https://github.com/samuelbharti/biobouncer, https://www.samuelbharti.com/biobouncer/r/
BugReports: https://github.com/samuelbharti/biobouncer/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: checkmate, cli, curl, jsonlite, tibble, tools, utils, yaml
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-22 22:09:12 UTC; Samuel
Author: Samuel Bharti [aut, cre, cph]
Maintainer: Samuel Bharti <samuelbharti.io@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-03 11:20:15 UTC

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Wed, 02 Sep 2026

New package scalednap with initial version 1.0.0
Package: scalednap
Title: Community Detection by Scaled Null-Adjusted Persistence
Version: 1.0.0
Description: Finds the vertex partition of an undirected graph that maximises a persistence-based objective, using the Milano local-search algorithm. Three related quality measures are supported: the persistence probability of a community, its null-adjusted persistence (NAP), and the scaled null-adjusted persistence (Scaled-NAP), which interpolates between NAP and modularity. The methods are described in Avellone et al. (2023) <doi:10.1007/s10288-023-00559-z> and Avellone et al. (2025) <doi:10.1016/j.ins.2025.123032>.
License: GPL (>= 2)
Encoding: UTF-8
SystemRequirements: C++20
URL: https://github.com/aavellone/scalednap-r
BugReports: https://github.com/aavellone/scalednap-r/issues
Suggests: igraph, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-08-22 22:18:09 UTC; ale
Author: Alessandro Avellone [aut, cre], Paolo Bartesaghi [aut], Stefano Benati [aut], Rosanna Grassi [aut]
Maintainer: Alessandro Avellone <alessandro.avellone@unimib.it>
Repository: CRAN
Date/Publication: 2026-09-02 22:10:02 UTC

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New package BivKLD with initial version 0.1.0
Package: BivKLD
Title: Bivariate Kullback-Leibler Divergence
Version: 0.1.0
Date: 2026-08-22
Description: Estimates the directed Kullback-Leibler divergence between two bivariate continuous distributions by numerical integration of kernel density estimates. Also computes pairwise divergences among groups and exact divergences for discrete, bivariate normal, bivariate Pareto type II, and independent bivariate Weibull models. The kernel estimator follows Chackochan, Sankaran and Nair (2026) <doi:10.1080/03610926.2025.2496687>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ks
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-22 19:56:54 UTC; Saurav Singla
Author: Saurav Singla [aut, cre], Rafflesia Chackochan [aut]
Maintainer: Saurav Singla <s00singla@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-02 21:30:09 UTC

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New package dScoreTest with initial version 1.0.0
Package: dScoreTest
Title: Debiased Score Tests for Goodness of Fit and Model Comparison
Version: 1.0.0
Description: Debiased (Neyman-orthogonalized) score tests for assessing whether a semiparametric or parametric regression model is well-specified and for comparing nested models. The test employs a hunt-and-test strategy: on a held-out hunt sample, it fits the null model and uses machine learning to find a direction in which the null model's score seems positive; on an independent test sample, it assesses the significance of the score in the hunted direction. The test employs orthogonalization to eliminate the bias from estimating the null model, yielding a test statistic that is asymptotically standard normal under the null without requiring a parametric form for the alternative. Methods are provided for 'glm', 'lm' and 'mgcv::gam' fits as well as for detecting heterogeneous treatment effects. The methodology is described in Dhawan, Guo and Shah (2026) <doi:10.48550/arXiv.2607.28861>.
URL: https://unbiased.co.in/dScoreTest/, https://github.com/richardkwo/dScoreTest
BugReports: https://github.com/richardkwo/dScoreTest/issues
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Imports: grf, mgcv
Suggests: knitr, rmarkdown, speff2trial, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 12:12:54 UTC; ricguo
Author: F. Richard Guo [aut, cre, cph] , Aditya Dhawan [aut]
Maintainer: F. Richard Guo <ricguo@umich.edu>
Repository: CRAN
Date/Publication: 2026-09-02 20:20:02 UTC

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New package rollcast with initial version 0.1.0
Package: rollcast
Title: Probabilistic Forecasting with Adaptive Mixtures of Rolling Statistics
Version: 0.1.0
Description: Implements a probabilistic time-series forecasting framework based on adaptive mixtures of rolling statistical anchors. Rolling means, medians, minimum and maximum values, regression endpoints, and user-specified quantiles define candidate forecast locations. A proper-score gating model assigns state-dependent mixture weights, optional state-conditional residual sampling adds local dispersion, and recursive simulation produces marginal and joint predictive distributions. Numeric hyperparameters can be supplied as scalars or candidate vectors for causal validation-based selection.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.12), stats, graphics, grDevices, utils
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-21 07:09:06 UTC; gianc
Author: Giancarlo Vercellino [aut, cre]
Maintainer: Giancarlo Vercellino <giancarlo.vercellino@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-02 12:30:02 UTC

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New package mwana with initial version 0.2.5
Package: mwana
Title: An Efficient Workflow for Plausibility Checks and Prevalence Analysis of Wasting in R
Version: 0.2.5
Description: A simple and streamlined workflow for plausibility checks and prevalence analysis of wasting based on the Standardized Monitoring and Assessment of Relief and Transition (SMART) Methodology <https://smartmethodology.org/>, with application in R.
License: GPL (>= 3)
Depends: R (>= 4.1)
Imports: dplyr, lubridate, nipnTK, rlang, scales, srvyr (>= 1.3.0), stats, zscorer, tibble, methods, purrr
Suggests: knitr, rmarkdown, quarto, spelling, testthat (>= 3.0.0),
Encoding: UTF-8
Language: en-GB
LazyData: true
URL: https://github.com/mphimo/mwana, https://mphimo.github.io/mwana/
BugReports: https://github.com/mphimo/mwana/issues
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-08-22 16:39:54 UTC; tomaszaba
Author: Tomas Zaba [aut, cre, cph] , Ernest Guevarra [aut, cph] , Mark Myatt [aut]
Maintainer: Tomas Zaba <tomas.zaba@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-02 12:20:02 UTC

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New package ExperimentalDesignGeneratorandRandomiser with initial version 0.1.0
Package: ExperimentalDesignGeneratorandRandomiser
Version: 0.1.0
Date: 2026-08-22
Title: 'EDGAR': Experimental Design Generator and Randomiser
Description: Native R implementation of 'EDGAR', the Experimental Design Generator and Randomiser. 'EDGAR' was originally developed as a suite of 'Excel' <https://www.microsoft.com/microsoft-365/excel> workbooks by the Biometrics team at Rothamsted Research <http://www.edgarweb.org.uk/>. The algorithms were subsequently re-implemented in the open-source 'Python' <https://www.python.org/> project 'rotsl/edgar' <https://rotsl.github.io/edgar/>, distributed as the 'edgar-design' package on 'PyPI' <https://pypi.org/project/edgar-design/>. This R package is a native R port of that 'Python' implementation: it does not require 'Python', 'reticulate' <https://CRAN.R-project.org/package=reticulate>, or any external service at runtime, and provides deterministic, reproducible randomisation for nine experimental designs including alpha designs (Patterson and Williams, 1976) <doi:10.1093/biomet/63.1.83>. Cross-language reproducibility with the 'Python' implementation i [...truncated...]
Maintainer: BiologyAutomation <phonics-tiffs1i@icloud.com>
URL: https://github.com/biologyautomation/edgar-r, https://rotsl.github.io/edgar/, http://www.edgarweb.org.uk/
BugReports: https://github.com/biologyautomation/edgar-r/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.6)
Suggests: jsonlite, openxlsx, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-22 16:42:43 UTC; tslwork
Author: Rohan R [aut, cph] , BiologyAutomation [cre]
Repository: CRAN
Date/Publication: 2026-09-02 12:30:13 UTC

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New package biopalette with initial version 0.2.2
Package: biopalette
Title: Image-Inspired Color Palettes for Biomedical Visualization
Version: 0.2.2
Description: Provides a curated collection of image-inspired color palettes for biomedical visualization. The palettes are organized as qualitative, sequential, or diverging scales and include documented source context and intended use. The package provides functions to retrieve, inspect, preview, and apply these palettes in base R and 'ggplot2' graphics, together with utilities for working with palette definitions.
License: MIT + file LICENSE
URL: https://github.com/evanbio/biopalette, https://evanbio.github.io/biopalette/
BugReports: https://github.com/evanbio/biopalette/issues
Depends: R (>= 4.1)
Imports: cli, ggplot2, jsonlite, scales
Encoding: UTF-8
Language: en-US
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-08-22 15:45:05 UTC; 84241
Author: Yibin Zhou [aut, cre]
Maintainer: Yibin Zhou <evanzhou.bio@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-02 12:10:02 UTC

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New package rhythm.metrics with initial version 1.1.0
Package: rhythm.metrics
Title: Analyse and Visualise Speech Rhythm and Timing Metrics
Version: 1.1.0
Description: Calculates and visualises speech rhythm and timing metrics. The 'rhythm.metrics' package provides a standardised workflow to compute common metrics including Delta C, Delta V, VarcoC, VarcoV, the percentage of vocalic intervals (%V), and both raw and normalised Pairwise Variability Indices (rPVI, nPVI). It includes functions for calculating and visualising these measures to facilitate cross-linguistic and developmental rhythm research. Delta C, Delta V, and %V measures are based on Ramus et al. (1999) <doi:10.1016/S0010-0277(99)00058-X>; VarcoC and VarcoV measures are based on Dellwo (2006, ISBN: 9783631554777); and rPVI-C and nPVI-V are based on Grabe & Low (2002) <doi:10.1515/9783110197105.2.515>.
License: GPL (>= 3)
Depends: R (>= 4.5.0)
Imports: dplyr, ggplot2, ggsci, magrittr, rlang
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-22 12:00:38 UTC; Cong
Author: Cong Zhang [aut, cre]
Maintainer: Cong Zhang <cong.zhang@newcastle.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-02 11:50:02 UTC

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New package nethist with initial version 1.0.0
Package: nethist
Title: Network Histograms
Version: 1.0.0
Date: 2026-08-17
Maintainer: Youngseok Song <youngseok.song@mail.wvu.edu>
Description: Estimates network histograms, a blockmodel approximation to the graphon underlying a network's connectivity pattern, for both single-layer and multilayer networks. Implements graphon estimation methods including the profile-likelihood method of Olhede and Wolfe (2014) <doi:10.1073/pnas.1400374111> and the least-squares method of Gao, Lu, and Zhou (2015) <doi:10.1214/15-AOS1354> for single-layer networks, and the multilayer extension of Song and Olhede (2026) <doi:10.48550/arXiv.2608.14536>.
SystemRequirements: Fortran compiler (for linking LAPACK/BLAS via 'RcppArmadillo')
Suggests: testthat (>= 3.0.0), tinytest, igraphdata, xml2, knitr, rmarkdown, Matrix, network, ergm.multi, lifecycle, withr, mclust, plot3D
Encoding: UTF-8
Imports: lattice, methods, Rcpp(>= 1.0.9), stats, RSpectra, ggplot2, ggtext, graphics, reshape2, igraph, rlang
LinkingTo: Rcpp, RcppArmadillo, testthat
Depends: R (>= 3.5.0)
LazyData: true
URL: https://enigmasong.github.io/nethist/
BugReports: https://github.com/EnigmaSong/nethist/issues
License: MIT + file LICENSE
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-22 05:04:09 UTC; ys00030
Author: Youngseok Song [aut, cre], Sofia C. Olhede [aut]
Repository: CRAN
Date/Publication: 2026-09-02 11:30:02 UTC

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New package ltgsmd with initial version 0.2.2
Package: ltgsmd
Title: Latent True-Score and Target-Population Anchored Geometric SMD
Version: 0.2.2
Description: Implements the latent true-score and target-population anchored geometric standardized mean difference (LTG-SMD) framework for two-group effect-size analysis. Provides plug-in estimation, analytic delta-method confidence intervals using a sample fourth-moment plug-in, bias-corrected and bias-corrected-accelerated nonparametric bootstrap confidence intervals with study x group stratification, denominator-sensitivity profiles, and multi-site meta-analytic wrappers. Includes denominator-diagnostic reporting, a pluggable reliability estimator interface, and an explicit interface for specifying the target reference distribution. Companion software to the methodological paper "The Denominator Chooses the Estimand: A Target-Population True-Score Framework for Standardized Mean Differences" (Nakamura, in press, Psychological Methods).
License: MIT + file LICENSE
URL: https://doi.org/10.17605/OSF.IO/KW9R6
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: boot, metafor, psych, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-22 06:39:42 UTC; root
Author: Daiki Nakamura [aut, cre]
Maintainer: Daiki Nakamura <nakamura@miyazaki-u.ac.jp>
Repository: CRAN
Date/Publication: 2026-09-02 11:30:09 UTC

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New package ggstratify with initial version 0.0.1
Package: ggstratify
Title: Fast Stratified Descriptive Figures with a Point-and-Click GUI
Version: 0.0.1
Description: A point-and-click 'shiny' interface for the descriptive analysis that comes before any model is chosen. Pass a data frame, pick the variable to describe, and add the layers you want to see it within: a second variable becomes the panels of a 'ggplot2' facet_wrap(), and further variables become separate figures, one file each, taken either one variable at a time or crossed. Every stratum is reported with the number of observations behind it, on the figure and on each of its panels; strata that contain none are listed rather than dropped, and rows with a missing value in a layer variable are excluded and counted. A continuous variable can be categorized into quantile groups, equal-width bins or user-supplied cut points and then used as a layer; the figure types follow those offered by the 'ggplotgui' package and add the line plot for change over time, an optional LOWESS smoother, and the Kaplan-Meier curve estimated by 'survival', with an optional number-at-risk table. Columns are descri [...truncated...]
License: GPL-3
URL: https://github.com/AkiShiroshita/ggstratify, https://akishiroshita.github.io/ggstratify/
BugReports: https://github.com/AkiShiroshita/ggstratify/issues
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: bslib (>= 0.5.0), checkmate (>= 2.1.0), data.table (>= 1.14.0), ggplot2 (>= 3.4.0), grDevices, patchwork (>= 1.1.0), ragg, shiny (>= 1.7.0), stats, survival (>= 3.2.0), utils
Suggests: knitr, rmarkdown, svglite (>= 2.1.0), testthat (>= 3.0.0), tibble
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-22 09:00:30 UTC; shiroa1
Author: Akihiro Shiroshita [aut, cre, cph], Yuki Kataoka [aut]
Maintainer: Akihiro Shiroshita <akihirokun8@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-02 11:40:02 UTC

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New package flexsynth with initial version 0.2.1
Package: flexsynth
Title: Flexible Synthetic Data for Nested, Longitudinal and Linked Multi-Table Data
Version: 0.2.1
Description: Generates utility-oriented synthetic data for supported flat, nested, longitudinal and tree-linked multi-table designs, including patients, admissions, procedures and laboratory results linked by identifiers. The default engine uses sequential conditional synthesis; an opt-in differentially private engine implements person-level (epsilon, delta) mechanisms and records their budget accounting. Synthetic output is not anonymisation. Empirical utility and disclosure-risk diagnostics are descriptive and do not by themselves establish that a release is safe.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: graphics, grDevices, parallel, stats, utils
Suggests: testthat (>= 3.0.0), rpart, ranger, partykit, data.table, knitr, litedown
VignetteBuilder: litedown
URL: https://github.com/lauyeehow1986-hub/Flexsynth
BugReports: https://github.com/lauyeehow1986-hub/Flexsynth/issues
NeedsCompilation: no
Packaged: 2026-08-19 00:32:29 UTC; lauye
Author: Yee How Lau [aut, cre]
Maintainer: Yee How Lau <lauyeehow1986@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-02 12:00:02 UTC

More information about flexsynth at CRAN
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New package BKVerify with initial version 0.1.1
Package: BKVerify
Title: Consistency Auditing of Reported Plant Breeding Statistics
Version: 0.1.1
Description: Audits published or draft plant breeding tables for internal arithmetic consistency. Analysis of variance tables, precision statistics and genetic variability parameters are jointly over-determined by exact algebraic identities; 'BKVerify' recomputes every derivable quantity using rounding-interval arithmetic and reports a value as inconsistent only when no combination of values inside the reported rounding intervals can satisfy the identity. The package deliberately restricts itself to relationships that hold irrespective of which variance-component definition an author adopted, so that flagged results reflect arithmetic inconsistency rather than methodological disagreement. Implemented checks cover analysis of variance internal structure, coefficient of variation, standard error of mean and critical difference, the genetic advance identity of Johnson, Robinson and Comstock (1955) <doi:10.2134/agronj1955.00021962004700070009x>, the relation between genotypic and phenotypic coeff [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-22 09:41:37 UTC; ASUS
Author: Praveen Kumar [aut, cre]
Maintainer: Praveen Kumar <bkpraveenars@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-02 11:40:08 UTC

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Tue, 01 Sep 2026

New package FitVerse with initial version 1.0-1
Package: FitVerse
Title: Parametric Distribution Fitting and Analysis
Version: 1.0-1
Date: 2026-08-09
Description: Provides a unified, user-friendly interface for fitting parametric probability distributions to continuous univariate data. 'FitVerse' supports 52 distribution families spanning symmetric, right-skewed, heavy-tailed, bounded, and extreme-value shapes, and three estimation methods: Maximum Likelihood Estimation (MLE), Method of Moments (MOM), and L-Moments (L-MOM). Automatic best-fit selection is performed using AIC, BIC, and goodness-of-fit tests (Kolmogorov-Smirnov, Anderson-Darling, Cramer-von Mises (CvM)). Every fitted model produces a publication-quality diagnostic plot: a histogram overlaid with the fitted density curve and the estimated PDF formula annotated directly on the figure. An optional interactive version is produced via 'plotly'. Additional tools include bootstrap confidence intervals for parameter estimates and return levels, batch fitting across multiple columns for automated workflows and web-upload use cases, JSON serialisation for integration with 'Shiny' web applic [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics, grDevices, utils, tools, actuar (>= 3.1.0), mc2d (>= 0.1.18), evd (>= 2.3.3), sn (>= 2.1.0), fitdistrplus (>= 1.1.0), lmomco (>= 2.3.7), ggplot2 (>= 3.4.0), goftest (>= 1.2.3), gridExtra (>= 2.3)
Suggests: shiny (>= 1.7.0), bslib (>= 0.5.0), DT, plotly (>= 4.10.0), testthat (>= 3.0.0), knitr (>= 1.40), rmarkdown (>= 2.20), kableExtra, jsonlite (>= 1.8.0), base64enc, MASS, GeneralizedHyperbolic, truncnorm
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-22 01:24:26 UTC; karunareddy
Author: Karuna G. Reddy [aut, cre] , M. G. M. Khan [aut]
Maintainer: Karuna G. Reddy <karuna.reddy@auckland.ac.nz>
Repository: CRAN
Date/Publication: 2026-09-01 14:20:02 UTC

More information about FitVerse at CRAN
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New package getaca with initial version 0.1.6
Package: getaca
Title: Reproducible External Data Dependencies
Version: 0.1.6
Language: en-GB
Description: Declares, retrieves, verifies, tracks and actively manages external data dependencies too large or too fast-moving to ship inside a package. Resources are identified by package, name and version, pinned to a Secure Hash Algorithm (SHA-256) checksum, and resolved through an explicit policy so that the same installed package always resolves the same bytes. A registry served from a remote host may be signed with Ed25519 and verified against a key the declaring package ships, so the declaration and the key that vouches for it arrive by different routes. Hashing follows National Institute of Standards and Technology (2015) "Secure Hash Standard" <doi:10.6028/NIST.FIPS.180-4>; signing follows Bernstein, Duif, Lange, Schwabe and Yang (2012) "High-Speed High-Security Signatures" <doi:10.1007/s13389-012-0027-1> and Josefsson and Liusvaara (2017) "Edwards-Curve Digital Signature Algorithm (EdDSA)" <doi:10.17487/RFC8032>. Designed for reproducible offline use and graceful behavi [...truncated...]
License: MIT + file LICENSE
URL: https://gillescolling.com/getaca/, https://github.com/gcol33/getaca
BugReports: https://github.com/gcol33/getaca/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: curl (>= 5.0.0), stats, tools, utils
Suggests: jsonlite, knitr, rmarkdown, testthat (>= 3.0.0), withr, yaml
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-22 00:53:37 UTC; Gilles Colling
Author: Gilles Colling [aut, cre, cph] , Daniel J. Bernstein [ctb] , Bernard van Gastel [ctb] , Wesley Janssen [ctb] , Tanja Lange [ctb] , Peter Schwabe [ctb] , Sjaak Smetsers [ctb]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 14:00:02 UTC

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New package AvatarTLA with initial version 0.1.0
Package: AvatarTLA
Title: Color Palettes from 'Avatar: The Last Airbender'
Version: 0.1.0
Description: Color palettes inspired by characters and nations from the animated series 'Avatar: The Last Airbender' for use in R graphics.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, grDevices
URL: https://github.com/Gerardo-Manzanarez-Villasana/AvatarTLA
BugReports: https://github.com/Gerardo-Manzanarez-Villasana/AvatarTLA/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-22 01:04:22 UTC; Gerardo Manzanarez
Author: Gerardo Manzanarez-Villasana [aut, cre]
Maintainer: Gerardo Manzanarez-Villasana <jupiter.gmv@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 14:00:29 UTC

More information about AvatarTLA at CRAN
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New package phynotype with initial version 0.6.2
Package: phynotype
Title: Clustering and Consensus Meta-Clustering
Version: 0.6.2
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>
Description: Tools for clustering, consensus meta-clustering, validation, exploratory interpretation, cluster prediction, and plotting. The package provides a clustering workflow with consensus clustering following Strehl and Ghosh (2002) <https://www.jmlr.org/papers/v3/strehl02a.html>.
URL: https://CRAN.R-project.org/package=phynotype
BugReports: https://github.com/ielbadisy/phynotype/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cluster, clustMixType, dbscan, functionals, ggplot2, ggrepel, mclust, parallel, rlang, stats, utils
Suggests: FactoMineR, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 14:46:53 UTC; imad-el-badisy
Repository: CRAN
Date/Publication: 2026-09-01 11:30:02 UTC

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New package fastgbm with initial version 0.6.1
Package: fastgbm
Title: Fast Histogram Gradient Boosting for Regression, Classification, and Survival Analysis
Version: 0.6.1
Description: A fast gradient boosting machine covering four task types with one interface: regression (squared error), binary and multiclass classification (logistic and one-vs-rest), and right-censored survival analysis via Cox (Breslow ties), accelerated failure time (normal location-scale), or piecewise-exponential objectives. Provides native missing-value routing, baseline-hazard estimation and survival-probability prediction for the survival objectives, and deterministic multi-threaded training via 'RcppParallel'. Methods are described in Friedman (2001) <doi:10.1214/aos/1013203451>.
License: MIT + file LICENSE
URL: https://github.com/ielbadisy/fastgbm
BugReports: https://github.com/ielbadisy/fastgbm/issues
Encoding: UTF-8
Depends: R (>= 4.5.0)
Imports: stats, utils, Rcpp, RcppParallel
LinkingTo: Rcpp, RcppParallel
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, survival, ggplot2, pdp, gbm, xgboost, ranger
VignetteBuilder: knitr
SystemRequirements: C++17, GNU make
NeedsCompilation: yes
Packaged: 2026-08-21 22:11:27 UTC; imad-el-badisy
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 11:50:12 UTC

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New package datom with initial version 0.1.1
Package: datom
Title: A Unified Framework for Versioned, Traceable Tabular Data
Version: 0.1.1
Description: Provides versioned storage for tabular data without a database or a server. Each table is written as an immutable, content-addressed version -- identical content is detected and stored only once -- while its version history and metadata are kept as code in a 'git' repository and the data itself in a local filesystem or cloud object storage ('S3'). Any past version can be read back exactly by its identifier, and each table records the sources it was derived from, so a project carries full data lineage. A lightweight reader role retrieves current or historical data from storage alone, without 'git' or write access, giving downstream analyses and pipelines a single versioned source of truth. It targets analytical and scientific data management, such as preparing clinical study datasets, and is designed as a foundation for higher-level governance tooling.
License: MIT + file LICENSE
URL: https://github.com/amashadihossein/datom, https://amashadihossein.github.io/datom/
BugReports: https://github.com/amashadihossein/datom/issues
Depends: R (>= 4.1.0)
Imports: arrow, cli, digest, fs, glue, httr2, jsonlite, paws.storage, purrr, rlang, utils, yaml
Suggests: covr, git2r, knitr, mockery, rio, rmarkdown, testthat (>= 3.0.0), withr
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 23:39:05 UTC; afshinmashadi-hossein
Author: Afshin Mashadi-Hossein [aut, cre, cph]
Maintainer: Afshin Mashadi-Hossein <amashadihossein@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 11:40:15 UTC

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New package urbstatdata with initial version 0.1.0
Package: urbstatdata
Title: Seven Data Sets for Urban and Built-Environment Statistics
Version: 0.1.0
Description: Seven documented data sets from transport, traffic safety, urban planning, construction and architectural engineering. The package provides fixed, redistributable snapshots with consistent variable names. Each help page records the source, licence, unit of observation, transformations and limitations of its data set. Sources include Yeh (2018) <doi:10.24432/C5J30W>, Tsanas and Xifara (2012) <doi:10.24432/C51307>, Yeh (1998) <doi:10.24432/C5PK67>, Seoul Bike Sharing Demand (2020) <doi:10.24432/C5F62R>, and Singh and Chaudhari (2018) <doi:10.24432/C5P605>.
URL: https://github.com/mariocools/urbstatdata
BugReports: https://github.com/mariocools/urbstatdata/issues
License: MIT + file LICENSE
Copyright: See inst/COPYRIGHTS.
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-08-10 14:05:03 UTC; djdim
Author: Mario Cools [aut, cre, cph]
Maintainer: Mario Cools <mario.cools@uliege.be>
Repository: CRAN
Date/Publication: 2026-09-01 08:50:02 UTC

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New package tmdbR with initial version 0.2.2
Package: tmdbR
Title: Modern 'R' Client for 'The Movie Database' API
Version: 0.2.2
Copyright: Original 'TMDb' 1.1 components copyright Andrea Capozio. 'tmdbR' modifications copyright Gordon Kuzet.
Description: A modern, tested client for version 3 of 'The Movie Database' ('TMDB') API. It modernises the interface originally provided by the legacy 'TMDb' package by Capozio (2020) <https://CRAN.R-project.org/package=TMDb> while adding secure web requests, bearer-token authentication, structured errors, retries, safe query encoding, and automatic pagination.
License: Artistic-2.0
URL: https://developer.themoviedb.org/docs/getting-started, https://CRAN.R-project.org/package=TMDb, https://github.com/vader75/tmdbR
BugReports: https://github.com/vader75/tmdbR/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.0.0), jsonlite (>= 1.8.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 21:39:19 UTC; gkuzet
Author: Gordon Kuzet [aut, cre, cph], Andrea Capozio [ctb, cph]
Maintainer: Gordon Kuzet <gordon@kuzet.com>
Repository: CRAN
Date/Publication: 2026-09-01 09:00:02 UTC

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New package tidygedcom with initial version 0.2.0
Package: tidygedcom
Title: Read and Tidy 'GEDCOM' Genealogy Files
Version: 0.2.0
Description: Reads and parses 'GEDCOM' (Genealogical Data Communication) files, the standard interchange format exported by genealogical software, and converts them into tidy data frames. Individuals, families, life events, and parent-child links are extracted into rectangular structures suitable for pedigree and kinship analysis. Additional helpers summarize file contents, convert place coordinates, and repair malformed records. Wikipedia family tree templates can be parsed into the same tidy structure. For a discussion of these and related data structures see [Hunter et al. (2026) <doi:10.1007/s10519-026-10259-z>].
License: GPL-3
URL: https://github.com/R-Computing-Lab/tidygedcom/, https://r-computing-lab.github.io/tidygedcom/
BugReports: https://github.com/R-Computing-Lab/tidygedcom/issues
Depends: R (>= 3.5.0)
Imports: BGmisc, dplyr, igraph, purrr, rlang, stringr, tidyr
Suggests: discord, EasyMx, ggpedigree, ggplot2, kinship2, knitr, OpenMx, rmarkdown, testthat (>= 3.0.0), tidyverse, withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-21 20:28:00 UTC; smaso
Author: S. Mason Garrison [aut, cre, cph] , Christian Waugh [aut, dtc]
Maintainer: S. Mason Garrison <garrissm@wfu.edu>
Repository: CRAN
Date/Publication: 2026-09-01 08:50:08 UTC

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New package theoryforge with initial version 0.6.0
Package: theoryforge
Title: Systematic Theory Development
Version: 0.6.0
Description: Provides a rigorous, reproducible workflow for building, developing and testing scientific theories represented as versioned, machine-checkable objects. Functions read and validate theory objects, score them against a versioned rigour checklist, screen constructs for lexical redundancy, and emit byte-identical diagram intermediate representations. The package is the feature-parity twin of a 'Python' package of the same name, with behaviour pinned by a shared specification so the two implementations produce identical verdicts.
License: MIT + file LICENSE
URL: https://github.com/pablobernabeu/theoryforge, https://pablobernabeu.github.io/theoryforge/r/
BugReports: https://github.com/pablobernabeu/theoryforge/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: jsonlite, stats, tools, utils, yaml
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, httr, curl, dagitty, ggm, DiagrammeR, DiagrammeRsvg, htmltools, spelling
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 13:53:12 UTC; PabloB
Author: Pablo Bernabeu [aut, cre]
Maintainer: Pablo Bernabeu <pcbernabeu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 08:30:02 UTC

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New package depictr with initial version 0.3.0
Package: depictr
Title: A Unified Toolkit for Visualising Statistical Models and Data
Version: 0.3.0
Description: A cohesive, publication-ready toolkit of plots that span the whole analysis workflow with one consistent look. It covers exploratory data analysis (distributions, categorical summaries, bivariate plots, scatter-plot matrices, correlation heatmaps, missing-data maps, outliers, estimation statistics and descriptive tables); multivariate analysis, clustering with diagnostics and Kaplan-Meier survival curves; time series (trends, autocorrelation, decomposition, seasonality and forecasting); model estimates and inference (forest plots, model comparison, frequentist and Bayesian estimates, predicted values, interactions, random effects and optimiser checks); diagnostics and classification (residual panels, binned residuals, influence, quantile-quantile, receiver operating characteristic (ROC) curves, calibration, threshold tuning and confusion matrices); uncertainty and power; and reporting helpers (a shared theme, colourblind-aware palettes, plot composition and saving). Every plotting func [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.5.0), stringr, scales, patchwork (>= 1.3.0), rlang, stats, grDevices, utils, Rdpack
Suggests: lme4, lmerTest, broom, simr, knitr, rmarkdown, survival, ggdist, posterior, boot, cluster, colorspace, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
URL: https://pablobernabeu.github.io/depictr/, https://github.com/pablobernabeu/depictr
BugReports: https://github.com/pablobernabeu/depictr/issues
NeedsCompilation: no
Packaged: 2026-08-21 13:55:09 UTC; PabloB
Author: Pablo Bernabeu [aut, cre]
Maintainer: Pablo Bernabeu <pcbernabeu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 08:30:09 UTC

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New package deOpenData with initial version 0.1.0
Package: deOpenData
Title: A Lightweight Interface to Delaware Open Data APIs
Version: 0.1.0
Description: Provides a unified set of helper functions to access datasets from the Delaware Open Data platform <https://data.delaware.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package provides a consistent interface for discovering and downloading datasets from the Delaware Open Data Portal using human-readable dataset keys or official Socrata dataset identifiers.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: curl, dplyr, httr, janitor, jsonlite, rlang, tibble
Suggests: ggplot2, knitr, rmarkdown, scales, testthat (>= 3.0.0), tidyr, vcr (>= 0.6.0), webmockr
URL: https://github.com/gomes-sh/nolaOpenData
BugReports: https://github.com/gomes-sh/nolaOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-08-21 17:44:21 UTC; magic
Author: Shelby Lyn Gomes [aut] , Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-01 08:40:02 UTC

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New package dawnn with initial version 2.1.1
Package: dawnn
Title: Differential Abundance with Neural Networks
Version: 2.1.1
Description: Detects regions of differential abundance in single-cell transcriptomic data by applying a pre-trained neural network model to the labels of each cell's nearest neighbours. Tests for both local and global differential abundance, controlling the false discovery rate with the Benjamini-Yekutieli procedure. The method is described in Hall and Castellano (2023) <doi:10.1101/2023.05.05.539427>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: stats, Seurat, reticulate, keras, utils, withr, tools
Depends: R (>= 4.0.0)
Suggests: rmarkdown, knitr, testthat (>= 3.1.7), callr, dplyr, pkgload, viridis
VignetteBuilder: knitr
URL: https://george-hall-ucl.github.io/dawnn/, https://github.com/george-hall-ucl/dawnn
BugReports: https://github.com/george-hall-ucl/dawnn/issues
SystemRequirements: Python (>= 3.9) with TensorFlow (>= 2.0), typically installed in a conda environment and selected via the 'tf_conda_env' argument of run_dawnn(). See the package documentation for setup instructions.
NeedsCompilation: no
Packaged: 2026-08-21 19:03:16 UTC; georgehall2
Author: George Hall [aut, cre] , Sergi Castellano [aut] , University College London [cph]
Maintainer: George Hall <george.hall@ucl.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-01 08:40:09 UTC

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New package BsplineQuantRegGui with initial version 0.2.2
Package: BsplineQuantRegGui
Title: Interactive 'Shiny' Interface for 'BsplineQuantReg'
Version: 0.2.2
Language: en-GB
Date: 2026-07-28
Description: A user-friendly interactive Shiny interface for the 'BsplineQuantReg' package, enabling quantile regression using B-splines with shape constraints, based on the method described in Abbes (2025). Almost all parameters of the main function 'quantile_spline()' can be tuned. Features include interactive knot placement, per-region constraint specification, 'CSV' data import, direct demo access, reproducible R code generation, and solver selection. The version 0.2.2 handles knots multiplicity, Bspline basis visualisation, mean-square regression, pp form visualisation under human readable form, in local or canonical bases, The GUI provides two modes, basic (compatible with 'BsplineQuantReg' >= 0.2.2) and advanced (requires 'BsplineQuantReg' >= 0.2.5 for stable multiplicity features). This GUI an improved version of the 'Python Tk' version of 'BsplineQuantRegPy'.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.6.0)
Imports: BsplineQuantReg (>= 0.2.5), shiny, shinyjs, DT, plotly, png, shinythemes, colourpicker, png, ECOSolveR
Suggests: cobs, testthat
NeedsCompilation: no
Packaged: 2026-08-21 20:18:23 UTC; abbes
Author: Alexandre Abbes [aut, cre]
Maintainer: Alexandre Abbes <alexandre.abbes@proton.me>
Repository: CRAN
Date/Publication: 2026-09-01 08:50:15 UTC

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New package actiquantiles with initial version 0.1.0
Package: actiquantiles
Title: Map Activity Data to Normalized Quantiles
Version: 0.1.0
Description: Provides functions mapping physical activity measures to normalized quantiles. Currently, only maps the 'NHANES' quantiles, but other quantiles will be integrated.
License: GPL-3
Depends: R (>= 3.5)
Suggests: testthat, covr, knitr, rmarkdown, dplyr
Encoding: UTF-8
Imports: mapnhanespa
URL: https://github.com/jhuwit/actiquantiles, https://jhuwit.github.io/actiquantiles/
BugReports: https://github.com/jhuwit/actiquantiles/issues
NeedsCompilation: no
Packaged: 2026-08-21 18:25:40 UTC; johnmuschelli
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-01 08:40:15 UTC

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Mon, 31 Aug 2026

New package metaselection with initial version 0.3.0
Package: metaselection
Title: Meta-Analytic Selection Models for Dependent Effect Sizes
Version: 0.3.0
Description: Fits a flexible class of p-value selection models for meta-analysis and meta-regression models, providing standard errors and confidence intervals based on either cluster-robust variance estimators (i.e., sandwich estimators) or cluster-level bootstrapping to handle dependent effect size estimates, as described in Pustejovsky, Citkowicz, and Joshi (2025) <DOI:10.31222/osf.io/qg5x6_v1> and Citkowicz, Pustejovsky, and Joshi (2026) <DOI:10.31222/osf.io/wjpxk_v1>. Supported models include generalizations of the step-function selection model as proposed by Vevea and Hedges (1995) <DOI:10.1007/BF02294384> and the beta-function selection model as proposed by Citkowicz and Vevea (2017) <DOI:10.1037/met0000119>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Formula, stats, utils, MASS, mvtnorm, optimx, nleqslv, purrr, future.apply, progressr, rlang, ggplot2 (>= 3.5.0), scales, Rdpack, simhelpers (>= 0.3.1)
Suggests: testthat (>= 3.0.0), future, metafor (>= 4.8-0), metadat, clubSandwich, DescTools, knitr, rmarkdown, bookdown, dplyr
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/jepusto/metaselection
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-21 16:15:17 UTC; jamespustejovsky
Author: James E. Pustejovsky [aut, cre] , Megha Joshi [aut] , Martyna Citkowicz [aut]
Maintainer: James E. Pustejovsky <jepusto@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-31 14:10:02 UTC

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New package figsr with initial version 0.1.0
Package: figsr
Title: Fast Interpretable Greedy-Tree Sums for Tree Ensembles
Version: 0.1.0
Description: Flexible, interpretable machine learning algorithm for additive tree sums ('FIGS'). Fits a sum of shallow 'Classification and Regression Trees' ('CART') by greedily minimizing residual impurity, growing a new tree or deepening an existing one at each step, whichever reduces the residuals most. Supports regression and two-class classification, variable importance, bootstrap ensembling and seamless integration with 'parsnip' and 'tidymodels' workflows. The method is described in Tan et al. (2023) <doi:10.1073/pnas.2310151122>.
License: MIT + file LICENSE
URL: https://github.com/bonijoao/figsr
BugReports: https://github.com/bonijoao/figsr/issues
Depends: R (>= 4.1)
Imports: dials, graphics, parsnip, rlang, stats, tibble
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-21 16:33:30 UTC; jpab2
Author: Joao Paulo Assis Bonifacio [aut, cre, cph] , Geraldo Magela da Cruz Pereira [aut, cph] , Pedro Mambelli Fernandes [aut, cph] , Joao Vitor Andrade Alves de Souza [aut, cph]
Maintainer: Joao Paulo Assis Bonifacio <jpab.27@hotmail.com>
Repository: CRAN
Date/Publication: 2026-08-31 14:10:07 UTC

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New package transittraj with initial version 1.0.0
Package: transittraj
Title: Reconstruct and Visualize Transit Vehicle Trajectories
Version: 1.0.0
Date: 2026-08-11
Description: Today's public transit vehicles produce a large amount of automatic vehicle location (AVL) data. This data is very useful for planning and performance studies, but can be noisy, error-prone, and sparse. This package provides tools for cleaning AVL point data and turning it into continuous, differentiable, monotonic, and invertible vehicle trajectory functions, based on the work of Robbennolt et al. (2025) <doi:10.48550/arXiv.2509.00119> and Huang et al. (2023) <doi:10.1109/ITSC57777.2023.10422524>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://utel-uiuc.github.io/transittraj/
BugReports: https://github.com/UTEL-UIUC/transittraj/issues
Imports: data.table, dplyr, gganimate, ggnewscale, ggplot2, ggspatial, hms, ivs, leaflet, magrittr, purrr, rlang, sf, slider, tidyr, tidytransit, viridis
Depends: R (>= 3.5)
LazyData: true
Suggests: knitr, prettymapr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-21 16:20:22 UTC; obrie
Author: Benjamin O'Brien [aut, cre, cph], Lewis Lehe [aut]
Maintainer: Benjamin O'Brien <obrienbenjaminj@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-31 14:00:02 UTC

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New package rdborrow with initial version 0.0.4.0
Package: rdborrow
Title: External Control Borrowing for Rare Disease Trials
Description: Implements causal inference methods for incorporating external control data into randomized controlled trials (RCTs) with longitudinal outcomes. Provides an analysis module supporting weighting-based methods such as inverse probability weighting (IPW) and augmented inverse probability weighting (AIPW), difference-in-differences (DID), and synthetic control approaches for borrowing external control information, as well as a simulation module for generating trial and external control data, evaluating estimator performance via Monte Carlo studies, and conducting power analyses for sample size determination. Methods are based on Zhou et al. (2024) <doi:10.1093/biostatistics/kxae012> and Zhou et al. (2024) <doi:10.1080/01621459.2024.2395586>.
Version: 0.0.4.0
License: Apache License (>= 2)
Depends: R (>= 4.1.0)
Imports: checkmate, futile.logger, mvtnorm, dplyr, tidyr, boot, Matrix, CVXR, copula, future.apply, progress, stats, utils, methods
Suggests: covr, ECOSolveR, knitr, pkgdown, rmarkdown, lintr, spelling, styler, testthat (>= 3.0.0)
URL: https://genentech.github.io/rdborrow/, https://github.com/Genentech/rdborrow
BugReports: https://github.com/Genentech/rdborrow/issues
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-20 18:15:27 UTC; matts
Author: Lei Shi [aut], Matt Secrest [cre, aut] , Herbert Pang [aut], Chen Chen [aut], Jiawen Zhu [aut], Genentech, Inc. [cph]
Maintainer: Matt Secrest <secrmatt@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-31 14:00:10 UTC

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New package biomes with initial version 0.9.4
Package: biomes
Title: Reproducible Occurrence-to-Biome Classification Using 31 Global Biome Schemes
Version: 0.9.4
Description: Reproducibly classifies occurrence records into biome classes using 31 published global terrestrial biome schemes compiled by Fischer and colleagues (2022) <doi:10.1111/geb.13574>, provided as harmonised raster layers at 10x10 km resolution globally. Includes functions to choose the most suitable biome scheme for a dataset by a data-driven ranking, to classify occurrence records, and to tabulate and visualise the result. Works with user-provided occurrences or a taxon name, in which case occurrences are downloaded from GBIF (<https://www.gbif.org>) and cleaned automatically.
URL: https://azizka.github.io/biomes/, https://github.com/azizka/biomes
BugReports: https://github.com/azizka/biomes/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0), terra
Imports: readr, checkmate, rlang, ggplot2, sf, viridis, tidyterra, utils
VignetteBuilder: knitr
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), dplyr, tidyr, rgbif, CoordinateCleaner, cowplot, ggforce, rstudioapi
License: CC BY 4.0
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-21 15:07:14 UTC; hcgro
Author: Hans Christian Gross [cre, aut], Alexander Zizka [aut, fnd], Anna Walentowitz [aut], Jan-Christopher Fischer [aut]
Maintainer: Hans Christian Gross <hc.gross@gmx.de>
Repository: CRAN
Date/Publication: 2026-08-31 13:40:02 UTC

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New package AsyPeer with initial version 0.0.1
Package: AsyPeer
Title: Estimating Asymmetric Peer Effects
Version: 0.0.1
Date: 2026-08-21
Description: Simulating and estimating asymmetric peer-effect models (Houndetoungan and Lambotte, 2026 <doi:10.48550/arXiv.2608.09219>). The model nests the widely used linear-in-means model (Manski, 1993 <doi:10.2307/2298123>; Bramoulle et al., 2009 <doi:10.1016/j.jeconom.2008.12.021>) and allows agents to be influenced differently by friends who exert more or less effort than themselves.
SystemRequirements: Requires the OpenMP library for parallel computing. If the OpenMP library is not available, the code is executed sequentially, and a warning is printed.
License: GPL-3
Language: en-US
Encoding: UTF-8
BugReports: https://github.com/MathieuLambotte/AsyPeer/issues
URL: https://github.com/MathieuLambotte/AsyPeer
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.0), ranger, glmnet, xgboost, formula.tools, doParallel, parallel, foreach, doRNG
LinkingTo: Rcpp, RcppEigen, RcppProgress
Suggests: PartialNetwork
NeedsCompilation: yes
Packaged: 2026-08-21 15:10:33 UTC; haache
Author: Aristide Houndetoungan [aut] , Mathieu Lambotte [cre, aut]
Maintainer: Mathieu Lambotte <mathieu.lambotte@univ-rennes.fr>
Repository: CRAN
Date/Publication: 2026-08-31 13:50:02 UTC

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New package PropTestR with initial version 1.0.0
Package: PropTestR
Title: Comprehensive Two-Proportion Inference
Version: 1.0.0
Description: Unified methods for comparing two independent or paired proportions. Provides classical, exact, score-based, non-inferiority, equivalence, effect-size, confidence-interval, and stratified procedures with standardized publication-ready output. Farrington-Manning inference is supported through established score-based methods described by Farrington and Manning (1990) <doi:10.2307/2532443> and implemented through 'ratesci', while additional established methods are provided through 'DescTools' and base R.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: DescTools (>= 0.99.60), ratesci (>= 1.1.0), stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/vinodhpmd/PropTestR
BugReports: https://github.com/vinodhpmd/PropTestR/issues
NeedsCompilation: no
Packaged: 2026-08-21 04:44:50 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-31 12:30:08 UTC

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New package gpci with initial version 0.1.0
Package: gpci
Title: Generalized Process Capability Indices and Bootstrap Confidence Intervals
Version: 0.1.0
Description: A comprehensive, generalized framework for computing, estimating, and validating Generalized Process Capability Indices (GPCIs). Supports user-supplied probability density functions (PDF/PMF), cumulative distribution functions (CDF), survival functions (SF), and quantile functions with uncensored data parameter estimation via Maximum Likelihood Estimation (MLE). Provides classical and non-normal capability indices, including Cpy (Maiti, Saha and Nanda, 2010) <doi:10.1080/16843703.2010.11673233>, Spmk (Dey and Saha, 2019) <doi:10.1007/s41872-019-00081-4>, CpTk (Saha, Dey and Maiti, 2019) <doi:10.1007/s13198-019-00789-7>, Cpc (Saha, Dey and Nadarajah, 2022) <doi:10.1080/02664763.2021.1971632>, CNpmc (Alotaibi, Dey and Saha, 2022) <doi:10.1155/2022/3135264>, CNpmkc (Saha, Tripathi and Dey, 2024) <doi:10.1142/S021853932450013X>, CNpk (Saha, Dey and Maiti, 2018) <doi:10.1080/21681015.2018.1437793>, and Vannman capability indices. Computes parametric [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, ggplot2, numDeriv, boot
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 22:11:13 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-31 12:30:02 UTC

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Sun, 30 Aug 2026

New package stow with initial version 0.3.0
Package: stow
Title: Durable Managed Local Copies of Remote Files
Version: 0.3.0
Description: Turns remote file URLs into paths to durable managed local copies stored in a fixed subdirectory of platform-appropriate, package-specific user data directories. Matching copies are reused across R sessions and remain available for offline use. Supports optional ETag-based versions, content validation, and staged replacement that prevents failed downloads and files that fail a supplied validator from becoming managed local copies. Includes tools to inspect, conservatively prune, and explicitly remove retained copies.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: curl, digest
Suggests: testthat (>= 3.2.0), withr
URL: https://github.com/cole-brokamp/stow
BugReports: https://github.com/cole-brokamp/stow/issues
NeedsCompilation: no
Packaged: 2026-08-21 14:06:26 UTC; cole
Author: Cole Brokamp [aut, cre, cph]
Maintainer: Cole Brokamp <cole@colebrokamp.com>
Repository: CRAN
Date/Publication: 2026-08-30 10:00:02 UTC

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New package rifexpectile with initial version 0.1.0
Package: rifexpectile
Title: Density-Free RIF Decompositions for Unconditional Expectiles
Version: 0.1.0
Description: Implements a density-free recentered influence function (RIF) regression framework for unconditional expectiles, and embeds it in a two-sample Oaxaca-Blinder decomposition indexed continuously by the expectile level. Unlike quantile-based RIF decompositions, which require estimating an inverse density term at each quantile, the expectile RIF depends only on primitive moments of the outcome distribution and requires no density estimation, no bandwidth selection, and no kernel smoothing. The package provides expectile estimation by iteratively reweighted least squares, closed-form RIF construction, two-sample composition/structure decomposition across a grid of expectile levels, bootstrap-based inference, and plotting methods. The underlying methodology is described in Ndoye (2025), "Semi-Nonparametric Expectile RIF Regression for Distributional Decomposition," presented at the 2025 World Congress of the Econometric Society, Seoul, Korea, <https://www.econometricsociety.org/regional-a [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, wooldridge
VignetteBuilder: knitr
URL: https://github.com/aandoye/rifexpectile
BugReports: https://github.com/aandoye/rifexpectile/issues
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-21 13:06:16 UTC; aziz
Author: Abdoul Aziz Ndoye [aut, cre]
Maintainer: Abdoul Aziz Ndoye <abdoulaziz1.ndoye@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-30 09:10:02 UTC

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New package PaddleOCR with initial version 0.2.1
Package: PaddleOCR
Title: R Client for the 'PaddleOCR' Cloud API
Version: 0.2.1
Description: An R client for the 'PaddleOCR' cloud service API <https://www.paddleocr.ai/latest/en/version3.x/inference_deployment/serving/paddleocr_official_api/overview.html>. Submit images, PDFs, or URLs for OCR processing using models like 'PaddleOCR-VL-1.6'. Supports job submission, polling, result retrieval, automatic image download, and streaming PDF-to-markdown conversion with batch processing.
License: MIT + file LICENSE
URL: https://github.com/xiaoluolorn/PaddleOCR
BugReports: https://github.com/xiaoluolorn/PaddleOCR/issues
Depends: R (>= 4.0.0)
Imports: httr (>= 1.4.0), jsonlite (>= 1.7.0), tools, utils
Suggests: pdftools (>= 3.0.0), testthat (>= 3.0.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-19 09:01:58 UTC; Lenovo
Author: Chaoyang Luo [aut, cre]
Maintainer: Chaoyang Luo <xiaoluolorn@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-30 09:50:02 UTC

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New package nolaOpenData with initial version 0.1.1
Package: nolaOpenData
Title: A Lightweight Interface to New Orleans Open Data APIs
Version: 0.1.1
Description: Provides a unified set of helper functions to access datasets from the New Orleans Open Data platform <https://data.nola.gov/>. Functions return results as tidy tibbles and support optional filtering, sorting, and row limits via the Socrata API. The package provides a consistent interface for discovering and downloading datasets from the San Francisco Open Data Portal using human-readable dataset keys or official Socrata dataset identifiers.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: curl, dplyr, httr, janitor, jsonlite, rlang, tibble
Suggests: ggplot2, knitr, rmarkdown, scales, testthat (>= 3.0.0), tidyr, vcr (>= 0.6.0), webmockr
URL: https://github.com/gomes-sh/nolaOpenData
BugReports: https://github.com/gomes-sh/nolaOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-08-21 14:10:27 UTC; magic
Author: Shelby Lyn Gomes [aut] , Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-08-30 10:00:09 UTC

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New package NBvarsel with initial version 0.1.1
Package: NBvarsel
Title: Variable Selection via Cross-Validated Net Benefit
Version: 0.1.1
Description: Performs exhaustive or groupwise (backward elimination) variable selection for binary outcome prediction models using cross-validated Net Benefit as the optimization criterion. It supports predictor costs, restricted cubic splines, interaction terms, permutation importance, and parallel computation. It includes visualizations for model comparison and variable importance. References include Vickers AJ & Elkin EB (2006) <doi:10.1177/0272989X06295361>, Van Calster B et al. (2018) <doi:10.1016/j.eururo.2018.08.038>, Vickers AJ et al. (2019) <doi:10.1186/s41512-019-0064-7>, and Baker SG et al. (2012) <doi:10.1515/1557-4679.1395>.
License: GPL (>= 3)
URL: https://lasaibarrenada.github.io/NB_varsel/, https://github.com/LasaiBarrenada/NB_varsel
BugReports: https://github.com/LasaiBarrenada/NB_varsel/issues
Depends: R (>= 4.1.0)
Encoding: UTF-8
LazyData: true
Imports: caret, DescTools, doParallel, dplyr, foreach, ggplot2, ggtext, parallel, patchwork, pROC, rlang, rms, scales, stats, stringr, tidyr
Suggests: glmnet, ggsci, gt, knitr, quarto, testthat (>= 3.0.0)
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-08-21 12:17:31 UTC; u0158158
Author: Lasai Barrenada [aut, cre] , KU Leuven, Belgium), Laure Wynants [aut] , KU Leuven, Belgium; Department of Epidemiology, CAPHRI Care and Public Health Research Institute, Maastricht University, Maastricht, Netherlands), Ewout W. Steyerberg [aut] , And [...truncated...]
Maintainer: Lasai Barrenada <lasai.barrenadataleb@kuleuven.be>
Repository: CRAN
Date/Publication: 2026-08-30 09:10:33 UTC

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New package mziln with initial version 1.0
Package: mziln
Title: Regression for Compositional Data with Zero Values
Version: 1.0
Date: 2026-08-21
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: rangen, Rfast, stats
Suggests: Compositional, Rfast2
Description: A multivariate zero inflated logistic normal regression model is implemented for compositional data with zero values present. The relevant paper is Li Z., Lee K., Karagas M. R., Madan J. C., Hoen A. G., O'Malley A. J. and Li H. (2018). "Conditional regression based on a multivariate zero-inflated logistic-normal model for microbiome relative abundance data", <doi:10.1007/s12561-018-9219-2>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-08-21 11:41:30 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-08-30 09:10:08 UTC

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New package morphErr with initial version 1.0.0
Package: morphErr
Title: Measurement Error Models for Morphometric Data
Version: 1.0.0
Date: 2026-08-18
Description: Morphometric data collected on animal populations can be subject to measurement error, which leads to biased estimators using line-fitting techniques such as linear regression and reduced major axis. The models implemented in this package were described by Stevenson, Smit, and Setyawan (2026) <DOI:10.1214/26-AOAS2164>. They explicitly accommodate measurement error, allow for multivariate data, estimate relationships between dimensions, allow missing data, and provide tests for isometric relationships between dimensions. Morphometric data of the reef manta ray, collected in Raja Ampat, Indonesia, are included.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: graphics, grDevices, lmeInfo, Matrix, msm, mvtnorm, nlme, parallel, pbapply, stats, utils
Depends: R (>= 3.5.0),
Suggests: testthat (>= 3.0.0)
LazyData: true
URL: https://github.com/elismit01/morphErr
BugReports: https://github.com/elismit01/morphErr/issues
NeedsCompilation: no
Packaged: 2026-08-21 13:33:24 UTC; ben
Author: Ben C. Stevenson [aut, cre, cph], Elizabeth Smit [aut]
Maintainer: Ben C. Stevenson <ben.stevenson@st-andrews.ac.uk>
Repository: CRAN
Date/Publication: 2026-08-30 09:10:13 UTC

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New package gganime with initial version 0.1.0
Package: gganime
Title: Animate 'ggplot2' Plots with 'Anime.js'
Version: 0.1.0
Description: Renders 'ggplot2' plots written with 'gganimate' syntax as animated Scalable Vector Graphics (SVG) drawn in the browser by the 'Anime.js' JavaScript library (<https://animejs.com>), through the 'animejs' package. The result is a single self-contained, resolution-independent 'htmlwidget' with one timeline over the plot's elements.
License: MIT + file LICENSE
URL: https://github.com/long39ng/gganime, https://long39ng.github.io/gganime/
BugReports: https://github.com/long39ng/gganime/issues
Depends: R (>= 4.1.0)
Imports: animejs (>= 1.1.0), cli, gganimate (>= 1.0.11), ggplot2 (>= 4.0.0), grDevices, grid, gridSVG (>= 1.7-5), rlang, utils, xml2
Suggests: jsonlite, knitr, rmarkdown, shiny, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-21 13:39:51 UTC; long
Author: Long Nguyen [aut, cre]
Maintainer: Long Nguyen <nguyen@dezim-institut.de>
Repository: CRAN
Date/Publication: 2026-08-30 09:20:02 UTC

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New package EasyPCA with initial version 0.1.1
Package: EasyPCA
Title: Principal Component Analysis with Automated Interpretation and Visualization
Version: 0.1.1
Description: Provides an automated workflow for Principal Component Analysis (PCA) that simplifies multivariate data analysis by performing essential preprocessing, statistical tests, component extraction, and visualization in a single function call. The package automatically standardizes variables, computes correlation matrices, performs Kaiser-Meyer-Olkin (KMO) and Bartlett's tests, determines the optimal number of principal components using multiple selection criteria, generates component loadings and scores, and produces publication-ready tables and graphical outputs for researchers and students. Methodological background is described in Shankar et al. (2024) <doi:10.1007/s12665-024-11985-5>.
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, ggcorrplot, corrplot, psych, factoextra, stats, graphics, utils
NeedsCompilation: no
Packaged: 2026-08-21 14:17:55 UTC; JARVIS
Author: S. Vishnu Shankar [aut, cre], V. Lavanya [aut], Santosha Rathod [aut], Mrinmoy Ray [aut], Anil Kumar [aut], Balaji Kannan [aut]
Maintainer: S. Vishnu Shankar <S.vishnushankar55@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-30 10:00:22 UTC

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New package diffwrap with initial version 0.6-3
Package: diffwrap
Title: Differential Expression Analysis of RNA-Seq Data
Version: 0.6-3
Date: 2026-08-10
Description: Functions for differential expression analysis of read counts from messenger RNA (mRNA) sequencing (RNA-Seq) data or micro RNA (miRNA) expression values generated by the Comprehensive Analysis Pipeline for microRNA Sequencing (CAP-miRSeq) 'expression_reports.sh' script. The workflow follows the 'edgeR'-'limma' expression data analysis pipeline providing options for different approaches, such as "pure" 'edgeR', voom or paired samples. The functions in the package generate text files with differential expression lists, optionally annotated with information from 'biomart', expression summary plots as well as several quality control (QC) plots. The main function, diffExpr(), is a convenience wrapper performing all steps automatically based on sensible defaults. Methods are described in Robinson, McCarthy and Smyth (2010) <doi:10.1093/bioinformatics/btp616>, Ritchie et al. (2015) <doi:10.1093/nar/gkv007>, Law et al. (2014) <doi:10.1186/gb-2014-15-2-r29> and Sun et al. (201 [...truncated...]
Maintainer: Vidal Fey <vidal.fey@gmail.com>
Depends: R (>= 4.0.0)
Imports: plyr, ggplot2, edgeR, limma, RColorBrewer, convertid (>= 0.3.4), pheatmap, ggrepel, data.table, magrittr, methods, Hmisc, ltm, openxlsx, purrr, dplyr, venn, VennDiagram, grid, scales
Suggests: testthat (>= 3.0.0), withr, futile.logger, rappdirs, knitr, quarto, dendextend, rmarkdown, AnnotationDbi, org.Hs.eg.db, org.Mm.eg.db, clusterProfiler, gprofiler2, topGO, igraph, scatterplot3d, readxl, WriteXLS, biomaRt
License: GPL-3
Encoding: UTF-8
LazyData: true
VignetteBuilder: quarto
NeedsCompilation: no
Author: Vidal Fey [aut, cre], Meeri Pekkarinen [aut], Reija Hieta [aut], Bogdan Iancu [aut], Adrien Janssens [aut]
Packaged: 2026-08-10 12:45:35 UTC; fsvife
Repository: CRAN
Date/Publication: 2026-08-30 09:10:19 UTC

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New package causalsim with initial version 0.1.0
Package: causalsim
Title: Simulation-Ready Causal Data Generating Processes
Version: 0.1.0
Description: Construct, simulate, and evaluate causal data generating processes (DGPs) with known ground truth. Designed for benchmarking causal estimators, studying confounding and treatment-effect heterogeneity, and building reproducible teaching examples. Covariate roles (confounder, effect modifier, noise) and heterogeneous treatment effects are first-class concepts in the API, and estimator performance is summarised with bias, root mean squared error, confidence-interval coverage, and power.
License: MIT + file LICENSE
URL: https://chaycereed.github.io/causalsim/, https://github.com/chaycereed/causalsim
BugReports: https://github.com/chaycereed/causalsim/issues
Encoding: UTF-8
Depends: R (>= 4.0.0)
Suggests: knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 12:34:36 UTC; chayce
Author: Chayce Reed [aut, cre]
Maintainer: Chayce Reed <Chayce.Reed.HSE@dartmouth.edu>
Repository: CRAN
Date/Publication: 2026-08-30 10:00:15 UTC

More information about causalsim at CRAN
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New package aiEvalR with initial version 0.1.0
Package: aiEvalR
Title: Statistical and Psychometric Evaluation of AI Systems
Version: 0.1.0
Description: Evaluates artificial intelligence (AI) systems as measurement instruments using psychometric methods. Provides multi-facet generalizability theory (G-study and D-study) via 'lme4', reliability via the intraclass correlation coefficient (ICC), calibration via the expected calibration error (ECE) and Brier score, robustness stress testing, and group disparity diagnostics. Item-level differential item functioning (DIF) based on item response theory (IRT) is delegated to the 'aiDIF' package. Methods follow Cronbach, Gleser, Nanda and Rajaratnam (1972, <ISBN:9780471188506>) and Brennan (2001) <doi:10.1007/978-1-4757-3456-0>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr, boot, lme4, dplyr, ggplot2, aiDIF, spelling
URL: https://github.com/causalfragility-lab/aiEvalR
BugReports: https://github.com/causalfragility-lab/aiEvalR/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 12:55:28 UTC; subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-08-30 09:10:27 UTC

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New package CohortUtilisation with initial version 0.6.1
Package: CohortUtilisation
Title: Healthcare Resource Utilization on OMOP CDM Cohorts
Version: 0.6.1
Description: In-database healthcare resource utilization (HCRU) extraction across inpatient, emergency, outpatient, pharmacy, and procedure domains for Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) cohorts following DARWIN EU standards.
License: MIT + file LICENSE
Copyright: IOMED, S.L.
URL: https://www.iomed.health/, https://github.com/iomedhealth/omopHeor
BugReports: https://github.com/iomedhealth/omopHeor/issues
Depends: R (>= 4.1.0)
Imports: CDMConnector (>= 1.4.0), omopgenerics (>= 0.3.0), dbplyr (>= 2.4.0), dplyr (>= 1.1.0), ggplot2, rlang, cli, glue
Suggests: DBI, tibble, gt, PatientProfiles (>= 1.2.0), CohortConstructor (>= 0.2.0), CohortCharacteristics (>= 0.3.0), visOmopResults, duckdb, testthat (>= 3.0.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-21 11:20:14 UTC; gabriel.maeztu
Author: Gabriel Maeztu [aut, cre]
Maintainer: Gabriel Maeztu <gabriel@iomed.health>
Repository: CRAN
Date/Publication: 2026-08-30 09:00:02 UTC

More information about CohortUtilisation at CRAN
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New package CohortCosts with initial version 0.6.1
Package: CohortCosts
Title: Direct Medical Cost Extraction and Health Economics Costing on OMOP CDM
Version: 0.6.1
Description: Links polymorphic Observational Medical Outcomes Partnership (OMOP) COST records to clinical events and tracks medical expenditures, unit cost tariffs, and healthcare price indices for OMOP Common Data Model (CDM) cohorts following DARWIN EU standards.
License: MIT + file LICENSE
Copyright: IOMED, S.L.
URL: https://www.iomed.health/, https://github.com/iomedhealth/omopHeor
BugReports: https://github.com/iomedhealth/omopHeor/issues
Depends: R (>= 4.1.0)
Imports: CDMConnector (>= 1.4.0), omopgenerics (>= 0.3.0), dbplyr (>= 2.4.0), dplyr (>= 1.1.0), ggplot2, rlang, cli, glue
Suggests: DBI, tibble, gt, PatientProfiles (>= 1.2.0), visOmopResults, duckdb, testthat (>= 3.0.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-21 11:20:23 UTC; gabriel.maeztu
Author: Gabriel Maeztu [aut, cre]
Maintainer: Gabriel Maeztu <gabriel@iomed.health>
Repository: CRAN
Date/Publication: 2026-08-30 09:00:07 UTC

More information about CohortCosts at CRAN
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Fri, 28 Aug 2026

New package VanillaCalendar with initial version 1.0.0
Package: VanillaCalendar
Title: Interactive Calendar and Date Picker Widget
Version: 1.0.0
Description: An R interface to the 'Vanilla Calendar Pro' 'JavaScript' library (version 3.2.0, bundled) for creating interactive and customizable calendar widgets and date pickers. The package enables integration of modern calendar components in R and 'Shiny' applications, with support for date, month, year and time selection, popup input mode, theming, and in-place updates from the 'Shiny' server.
URL: https://github.com/ESCRI11/vanilla-calendar-r
BugReports: https://github.com/ESCRI11/vanilla-calendar-r/issues
License: GPL (>= 3)
Copyright: The bundled Vanilla Calendar Pro library is copyright Yury Uvarov and released under the MIT licence; see inst/htmlwidgets/lib/VanillaCalendar-3.2.0/LICENSE.
Encoding: UTF-8
Imports: htmlwidgets
Suggests: shiny, testthat (>= 3.0.0), shinytest2, chromote, htmltools, withr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 09:11:28 UTC; massagno
Author: Xavier Escriba Montagut [aut, cre], Yury Uvarov [ctb, cph]
Maintainer: Xavier Escriba Montagut <xavier.escriba.montagut@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-28 10:00:15 UTC

More information about VanillaCalendar at CRAN
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New package layeranalyzer with initial version 0.4.1
Package: layeranalyzer
Title: Time Series Analysis Tool using Linear Layered SDEs
Version: 0.4.1
Date: 2026-08-16
Encoding: UTF-8
Maintainer: Trond Reitan <trond.reitan@geo.uio.no>
Description: Time series analysis tool using linear layered stochastic differential equations. The package allows for multiple time series with correlative and/or causal links between them. Unmeasured causal processes are allowed to affect the measured processes in a layered structure, hence the name of the package. In case of causal feedback loops, the matrix operations (including eigenvalue decompositions) allows for complex numbers. In this case, cyclic behavior can be expected. Details can be found in Reitan and Liow (2019)<doi:10.1111/2041-210X.13299>.
License: LGPL-3
Suggests: knitr, rmarkdown, markdown
Depends: R (>= 2.10)
Imports: methods, stats, Rcpp, coda (>= 0.19.1)
LinkingTo: Rcpp
URL: https://folk.universitetetioslo.no/trondr/R/
LazyData: true
ByteCompile: yes
Biarch: no
NeedsCompilation: yes
Packaged: 2026-08-21 07:53:48 UTC; trondr
Author: Trond Reitan [aut, cre] , Lee Hsiang Liow [ctb] , Adam T. Kocsis [ctb]
Repository: CRAN
Date/Publication: 2026-08-28 09:50:08 UTC

More information about layeranalyzer at CRAN
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New package deli with initial version 0.1.0
Package: deli
Title: M-Estimation and Empirical Sandwich Variance Estimation
Version: 0.1.0
Description: Solves estimating equations to obtain M-estimators together with empirical sandwich variance estimates, providing a general interface for both custom and built-in estimating equations. Built-in equations cover basic statistics, regression, causal inference, survival analysis, measurement error, and more. An 'R' port of the 'Python' library 'delicatessen' described in 'Zivich et al. (2022)' <doi:10.48550/arXiv.2203.11300>.
License: MIT + file LICENSE
URL: https://github.com/r-causal/deli, https://r-causal.github.io/deli/
BugReports: https://github.com/r-causal/deli/issues
Depends: R (>= 4.3)
Imports: cli, generics, rlang (>= 1.0.0), rootSolve, S7 (>= 0.2.0), stats
Suggests: causaldata, jsonlite, knitr, MASS, minpack.lm, nleqslv, nlme, quarto, readxl, rmarkdown, testthat (>= 3.0.0), yaml
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-08-21 08:13:57 UTC; malcolmbarrett
Author: Malcolm Barrett [aut, cre, cph] , Paul Zivich [ctb]
Maintainer: Malcolm Barrett <malcolmbarrett@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-28 09:40:02 UTC

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Thu, 27 Aug 2026

New package MultiSEp with initial version 4.1.3
Package: MultiSEp
Title: Predict Synthetic Lethality and Other Gene Dependency Relationships from Multiomics Data
Version: 4.1.3
BuildVignettes: TRUE
Description: Predicts gene dependency relationships (GDRs) from functional genomics data. Regularised Gaussian mixture modelling may be applied for unsupervised clustering in addition to other data partitioning strategies. GDR analysis tools include discovery of synthetic lethal relationships and predicting population coverage for candidate drug targets from cancer patient mutational profiles. Functionality for visualisation is also available. 'MultiSEp' is applicable to data from a variety of sources including clinical cohorts, organoids and cell lines.
License: LGPL-2.1
Depends: R (>= 3.5.0)
Imports: pracma, pbapply, pbmcapply, reshape2, ggplot2, gtools, testthat, igraph, grid, patchwork, scales
Encoding: UTF-8
LazyData: true
LazyDataCompression: bzip2
NeedsCompilation: no
VignetteBuilder: knitr, rmarkdown
Suggests: rmarkdown, kableExtra, magrittr, knitr, dplyr
Language: en-GB
Packaged: 2026-08-20 23:43:29 UTC; ianover
Author: Adeline McKie [aut], Mark Wappett [aut], Ian Overton [aut, cre]
Maintainer: Ian Overton <i.overton@qub.ac.uk>
Repository: CRAN
Date/Publication: 2026-08-27 10:30:02 UTC

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New package lasars with initial version 0.1.1
Package: lasars
Title: Explore Response Style in Survey Responding
Version: 0.1.1
Description: Provides tools to fit the latent state and response style ('lasars') model to survey data using either Particle Metropolis within Gibbs ('pmwg') or maximum likelihood estimation. The package facilitates estimation of less-biased latent state and psychologically interpretable response style parameters.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: purrr, pmwg, stats
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-21 05:20:20 UTC; jkg582
Author: Jess Grimmond [aut, cre], Guy Hawkins [aut], Scott Brown [aut], Quentin Gronau [aut]
Maintainer: Jess Grimmond <jess.grimmond@newcastle.edu.au>
Repository: CRAN
Date/Publication: 2026-08-27 10:10:02 UTC

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New package ExpDesignR with initial version 0.1.0
Package: ExpDesignR
Title: Experimental Design and Randomization Methods for Biomedical and Veterinary Research
Version: 0.1.0
Description: Generates randomized experimental designs for biomedical, veterinary, agricultural, and clinical research, including simple, block, stratified, and cluster randomization, Latin square and crossover designs, allocation summaries, schedule export, and visualization of treatment allocations. The methods are based on established principles of randomization and experimental design; see Rosenberger and Lachin (2015, ISBN:9781118742242) and Jones and Kenward (2014, ISBN:9781439861424).
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: stats, utils, tibble, dplyr, ggplot2, rlang
Suggests: testthat (>= 3.0.0), covr, spelling, knitr, rmarkdown
URL: https://github.com/vinodhpmd/ExpDesignR
BugReports: https://github.com/vinodhpmd/ExpDesignR/issues
Language: en-US
NeedsCompilation: no
VignetteBuilder: knitr
Packaged: 2026-08-21 07:53:39 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-27 10:30:08 UTC

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New package ORCI.Welch with initial version 0.1.1
Package: ORCI.Welch
Title: Approximate Odds Ratio Confidence Intervals with Welch's Adjustments
Version: 0.1.1
Author: Cosette Clinton [aut], McKenna Morgan [ctb], Kimihiro Noguchi [aut, cre]
Maintainer: Kimihiro Noguchi <kimihiro.noguchi@wwu.edu>
Description: Calculates approximate odds ratio confidence intervals with Welch's adjustments for a given dataset and ranks different odds ratio confidence intervals in terms of multiple metrics based on the dataset given. References for Welch's adjustments can be found at Pan (2002) <doi:10.1016/S0167-9473(01)00107-4> and Clinton, Morgan, and Noguchi (2026) <https://meetings.ams.org/math/jmm2026/meetingapp.cgi/Paper/58471>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: graphics
NeedsCompilation: no
Packaged: 2026-08-21 05:10:42 UTC; main
Repository: CRAN
Date/Publication: 2026-08-27 10:00:12 UTC

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Wed, 26 Aug 2026

New package sportsR with initial version 0.1.0
Package: sportsR
Title: A Comprehensive Collection of Sports and Athletics Datasets
Version: 0.1.0
Maintainer: Renzo Caceres Rossi <arenzocaceresrossi@gmail.com>
Description: Offers a rich and diverse collection of datasets focused on sports, athletics, physical performance, and related disciplines. The package includes professional and amateur sports data covering team sports such as soccer, basketball, baseball, American football, volleyball, rugby, cricket, hockey, and handball, as well as individual sports including tennis, badminton, table tennis, golf, swimming, cycling, athletics, gymnastics, wrestling, boxing, martial arts, weightlifting, triathlon, rowing, canoeing, climbing, surfing, skiing, snowboarding, and motorsports. Datasets cover player and team performance, match statistics, tournament results, championship standings, Olympic and international competitions, rankings, player demographics, coaching and training, biomechanics, sports medicine, injuries, exercise physiology, fitness assessment, sports nutrition, wearable sensor measurements, talent identification, and sports analytics. Additional datasets include historical competitions, refer [...truncated...]
License: GPL-3
Language: en
URL: https://github.com/lightbluetitan/sportsr, https://lightbluetitan.github.io/sportsr/
BugReports: https://github.com/lightbluetitan/sportsr/issues
Encoding: UTF-8
LazyData: true
Suggests: ggplot2, testthat (>= 3.0.0), dplyr, knitr, rmarkdown
Depends: R (>= 4.1.0)
Imports: utils
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-21 00:22:16 UTC; Renzo
Author: Renzo Caceres Rossi [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-26 20:20:02 UTC

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New package mvboxcox with initial version 0.1.4
Package: mvboxcox
Title: Bivariate Logistic Box-Cox Regression
Version: 0.1.4
Description: Fits bivariate logistic Box-Cox regression models for binary outcomes and positive continuous predictors. Transformation parameters are selected by cross-validated grid search with adaptive refinement and thin-plate spline smoothing. The package also provides prediction, empirical and sampling-weighted median effects, simulation tools, and sampling-weighted model fitting. The methodology extends the logistic Box-Cox approach of Xing et al. (2021) <doi:10.1002/cjs.11587>.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: methods, stats, parallel, fields
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 20:50:38 UTC; xushiyu
Author: Shiyu Xu [aut], Xuekui Zhang [aut, cre]
Maintainer: Xuekui Zhang <ubcxzhang@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 20:10:02 UTC

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New package AgriFusionR with initial version 0.1.0
Package: AgriFusionR
Title: An Integration Framework for Agricultural Analytics
Version: 0.1.0
Description: Assembles agricultural analyses around a single unit of observation, the management unit within a season, and keeps climate, soil and remote-sensing covariates aligned to it. Covariates are aggregated over phenological windows derived from accumulated growing degree days rather than calendar months, following McMaster and Wilhelm (1997) <doi:10.1016/S0168-1923(97)00027-0>. Models are validated with spatial resampling by default, since random cross-validation inflates apparent skill when observations are spatially autocorrelated, as shown by Roberts and others (2017) <doi:10.1111/ecog.02881>. Prediction intervals use split conformal inference after Lei and others (2018) <doi:10.1080/01621459.2017.1307116>. Data sources and learning algorithms are supplied through registries so that new providers and methods can be added without modifying the package.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats, utils
Suggests: testthat (>= 3.0.0), ranger, xgboost, Cubist, glmnet, kernlab, mgcv, treeshap, nasapower, chirps, daymetr, geodata, terra, agridat, knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/mqfarooqi1/AgriFusionR
BugReports: https://github.com/mqfarooqi1/AgriFusionR/issues
NeedsCompilation: no
Packaged: 2026-08-20 23:18:42 UTC; faroo
Author: Muhammad Farooqi [aut, cre]
Maintainer: Muhammad Farooqi <mqfarooqi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 20:20:08 UTC

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New package textclassificationtutorial with initial version 0.1.2
Package: textclassificationtutorial
Title: Reproducible Text Classification Workflows
Version: 0.1.2
Description: Dependency-light tools and tutorials for teaching reproducible text classification. The package covers HTML text extraction, sentence segmentation, text preprocessing, document-term matrices, TF-IDF, keyword extraction, cosine similarity, stratified cross-validation, classification metrics, and a multinomial Naive Bayes classifier. It modernizes the code accompanying Kobayashi, V. B., Berkers, H. A., Mol, S. T. Kismihok, G., and Den Hartog, D. N. (2017) <doi:10.1177/1094428117719322> The package replaces the original scripts in the paper.
License: Apache License (>= 2)
URL: https://github.com/vkobayashi/textclassificationtutorial
BugReports: https://github.com/vkobayashi/textclassificationtutorial/issues
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), xml2
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-20 21:22:17 UTC; vladimerkobayashi
Author: Vladimer Kobayashi [aut, cre], Stefan Mol [aut], Gabor Kismihok [aut]
Maintainer: Vladimer Kobayashi <vladimer.kobayashi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 19:30:02 UTC

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New package gpciLindApproxProgII with initial version 0.1.0
Package: gpciLindApproxProgII
Title: Lindley Approximation for Capability Indices under Progressive Censoring
Version: 0.1.0
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Description: Implements Bayesian parameter and Generalized Process Capability Indices (GPCIs) estimation using the Lindley approximation method (Lindley, 1980 <doi:10.2307/2345271>) under progressive Type-II censored data (Balakrishnan & Aggarwala, 2000 <doi:10.1007/978-1-4612-1334-5>). Evaluates point estimates and posterior expectations for classical and non-normal capability indices, including Cpy (Maiti et al., 2010 <doi:10.1080/16843703.2010.11673233>), Spmk (Dey & Saha, 2019 <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022 <doi:10.1080/02664763.2021.1971632>), CNpmc (Alotaibi et al., 2022 <doi:10.1155/2022/3135264>), CNpmkc (Saha et al., 2024 <doi:10.1142/S021853932450013X>), CNpk (Saha et al., 2018 <doi:10.1080/21681015.2018.1437793>), and Vannman's Cp(u,v) family (Vannman, 1995 <doi:10.1111/j.1467-9574.1995.tb01472.x>). Calculates point estimates, bias, mean squared error (MSE), Bayes risk under [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, ggplot2, numDeriv, boot, coda
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 22:06:37 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Repository: CRAN
Date/Publication: 2026-08-26 19:50:02 UTC

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New package enrollcast with initial version 0.1.0
Package: enrollcast
Title: Project School Enrollment with Grade Progression Ratios
Version: 0.1.0
Description: Projects school enrollment using the cohort survival / grade progression ratio method described in Webster (1970) <doi:10.1080/00220973.1970.11011238>, implemented as a matrix projection. Works at any level of aggregation and any number of grades. Provides functions to compute progression ratios from historical grade-level enrollment and to project future enrollment forward an arbitrary horizon.
License: MIT + file LICENSE
URL: https://rorylawless.r-universe.dev/enrollcast, https://github.com/localopen/enrollcast, https://localopen.github.io/enrollcast/
BugReports: https://github.com/localopen/enrollcast/issues
Depends: R (>= 4.0)
Imports: cli (>= 3.4.0), rlang (>= 1.0.0), stats
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-20 23:13:15 UTC; rory
Author: Rory Lawless [aut, cre, cph]
Maintainer: Rory Lawless <rory@rorylawless.com>
Repository: CRAN
Date/Publication: 2026-08-26 20:00:02 UTC

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New package cantrends with initial version 0.1.0
Package: cantrends
Title: Fit Segmented Regression Models
Version: 0.1.0
Description: Estimates piecewise linear spline models for assessing temporal trends in cancer incidence and mortality rates. Provides tools for identifying and reporting knot locations, annual percent changes (APCs), and average annual percent changes (AAPCs), facilitating the analysis and communication of changes in cancer rates over time.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: broom, carrier (>= 0.3.0), cli, dplyr, glue, lspline, mirai (>= 2.5.1), purrr (>= 1.1.0), rlang, tibble
URL: https://github.com/mattwarkentin/cantrends
BugReports: https://github.com/mattwarkentin/cantrends/issues
NeedsCompilation: no
Packaged: 2026-08-20 23:00:05 UTC; matt
Author: Matthew T. Warkentin [aut, cre, cph] , John Hutchinson [ctb], Yibing Ruan [ctb]
Maintainer: Matthew T. Warkentin <matthew.warkentin@ucalgary.ca>
Repository: CRAN
Date/Publication: 2026-08-26 20:00:08 UTC

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New package AISanalyze with initial version 3.1.2
Package: AISanalyze
Title: Processing and Analyzing AIS Vessel Tracking Data
Version: 3.1.2
Description: Processes Automatic Identification System (AIS) vessel tracking data, including travel estimation, trajectory correction, interpolation, extraction, and summarising vessel information. The package is designed to facilitate reproducible analyses of maritime traffic in ecological, environmental, and marine spatial planning applications. For more details see <https://remip48.github.io/AISanalyze/>.
License: MIT + file LICENSE
Depends: R(>= 4.2.0)
Imports: dplyr, sf, purrr, stats, stringr, doParallel, parallel, foreach, assertthat, data.table, magrittr
Suggests: knitr, units, lubridate, rmarkdown, testthat
URL: https://github.com/remip48/AISanalyze, https://remip48.github.io/AISanalyze/
BugReports: https://github.com/remip48/AISanalyze/issues
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 21:25:59 UTC; 234028
Author: Remi Pigeault [aut, cre]
Maintainer: Remi Pigeault <remi.pigeault@tiho-hannover.de>
Repository: CRAN
Date/Publication: 2026-08-26 19:40:01 UTC

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New package ggnext with initial version 0.1.0
Package: ggnext
Title: A Next-Generation Grammar of Graphics
Version: 0.1.0
Description: An implementation of the Grammar of Graphics described by Wilkinson (2005, ISBN:978-0-387-24544-7), built on 'S7' classes. The familiar grammar vocabulary of aesthetics, geometries, statistics, scales, coordinates, facets and themes composed with '+' is preserved; every constructor that takes an argument also accepts a plot as the first argument of a native pipe ('|>') stage, so the two styles are interchangeable. The package is extended with built-in interactivity, animation, an exact-data export, a plot linter that flags common statistical-graphics mistakes before a figure ships, and a catalogue covering layout diagrams (Sankey, treemap, network, radar), machine-learning diagnostics (SHAP, receiver operating characteristic, calibration, partial dependence) and clinical reporting (Kaplan-Meier, forest, swimmer, CONSORT). Static output is written to Scalable Vector Graphics; interactive output is a self-contained 'HTML' document using a canvas element and vanilla 'JavaScript'. Both [...truncated...]
URL: https://itsmdivakaran.github.io/ggnext/, https://github.com/itsmdivakaran/ggnext
BugReports: https://github.com/itsmdivakaran/ggnext/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: S7, grDevices, stats, utils
Suggests: knitr, markdown, rmarkdown, testthat (>= 3.0.0), xml2
NeedsCompilation: no
Packaged: 2026-08-20 19:17:15 UTC; maheshdivakaran
Author: Mahesh Divakaran [aut, cre, cph]
Maintainer: Mahesh Divakaran <itsmdivakaran@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-26 18:40:02 UTC

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Tue, 25 Aug 2026

New package MDaRes with initial version 0.0.2
Package: MDaRes
Title: MD Analysis of Residue Properties Using Structural Alphabets
Version: 0.0.2
Description: Analyze molecular dynamics (MD) simulation data using structural alphabets. Protein local conformations from molecular simulations are encoded in a compressed string representation. Residue-level UniProt annotations can be directly retrieved. Comparative analysis tools are available to investigate conformational variability, coordinated motions, and differences between systems (e.g. wild-type vs mutant; bound vs unbound). Methodological details for the structural alphabet analysis can be found in Pandini et al. (2013) <doi:10.1093/bioinformatics/btt326>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: bio3d, DescTools, SOMMD, tools, dplyr, tidyr, stringr, UniprotR, Rcpp
LinkingTo: Rcpp, RcppArmadillo
Suggests: httr, future, future.apply, curl, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-08-20 18:15:17 UTC; apandini
Author: Nancy D'Arminio [aut] , Anna Marabotti [aut] , Alessandro Pandini [aut, cph, cre]
Maintainer: Alessandro Pandini <alessandro.pandini@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-25 15:10:09 UTC

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New package DRLAP2 with initial version 0.1.1
Package: DRLAP2
Title: Dynamic Reinforcement Learning and Adaptive Progressive Censoring
Version: 0.1.1
Description: Implements Maximum Likelihood Estimation (MLE) and Bayesian Markov Chain Monte Carlo (MCMC) sampling algorithms for progressive censoring models, with support for dynamic reinforcement learning environment simulation and accelerated computational routines written in C++.
License: GPL (>= 3)
Encoding: UTF-8
Imports: Rcpp, stats
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-08-20 18:23:38 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-25 15:10:16 UTC

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New package deltabreedquery with initial version 1.0.3
Package: deltabreedquery
Title: Fast, Simple API Tools for Retrieving Data from 'DeltaBreed'
Version: 1.0.3
Maintainer: Tyr Wiesner-Hanks <twiesnerhanks@ufl.edu>
Description: Simplified data retrieval from the 'DeltaBreed' breeding data management platform (<https://sandbox.breedinginsight.net/>) via the 'BrAPI' open-source breeding data API (<https://brapi.org/specification>). Each of the four main data types stored in 'DeltaBreed' (germplasm, trait variables, experiments/environments, and observations) are handled by a get_datatype() function that constructs and executes the request, handles paginated responses, and parses the retrieved data. Responses are reformatted into a consistent, R-friendly data frame format that resembles how the data appears on the 'DeltaBreed' web interface as closely as possible.
License: Apache License 2.0
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), vcr
Depends: R (>= 4.1)
Imports: httr2, dplyr, tidyr, rlang, jsonlite
NeedsCompilation: no
Packaged: 2026-08-20 18:02:56 UTC; twiesnerhanks
Author: Tyr Wiesner-Hanks [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-25 14:50:09 UTC

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New package CohortIncidence with initial version 4.2.0
Package: CohortIncidence
Title: Cohort Incidence Analysis for the OMOP Common Data Model
Version: 4.2.0
Date: 2026-07-27
Description: Provides functionality for performing cohort incidence analyses against data stored in the OMOP Common Data Model (CDM). The package generates database-specific SQL, executes analyses across supported database platforms, and returns standardized incidence estimates using configurable time-at-risk, stratification, and cohort definitions. It is intended to support reproducible observational research within the OHDSI analytics framework.
License: Apache License 2.0
VignetteBuilder: knitr
URL: https://ohdsi.github.io/CohortIncidence/
BugReports: https://github.com/OHDSI/CohortIncidence/issues
Depends: R (>= 3.2.2), DatabaseConnector (>= 3.0.0)
Imports: rlang, rJava(>= 0.9-10), checkmate, jsonlite, SqlRender (>= 1.6.0)
SystemRequirements: Java (>= 8)
NeedsCompilation: yes
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, withr, readr, Eunomia, duckdb, R6
Packaged: 2026-08-20 17:23:17 UTC; cknoll1
Author: Christopher Knoll [aut, cre]
Maintainer: Christopher Knoll <cknoll@ohdsi.org>
Repository: CRAN
Date/Publication: 2026-08-25 14:10:02 UTC

More information about CohortIncidence at CRAN
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New package interSAE with initial version 0.1.0
Package: interSAE
Title: Intersectional Small Area Estimation from Survey and Census Data
Version: 0.1.0
Description: Implements design-aware, margin-constrained estimation of population indicators for geographic areas crossed with demographic subgroups. Complex-survey microdata supply outcomes and association information, while one or more aggregate census tables supply overlapping population margins. A generalized iterative proportional fitting engine reconstructs a coherent latent population table, and an augmented model-assisted estimator produces domain means, proportions, and totals for sampled and unsampled intersections. Tools diagnose non-identification, compute linear-programming sensitivity bounds, propagate sampling and model uncertainty with replicate-weight or multiplier bootstrap procedures, enforce structural zeros, and benchmark estimates to official totals. The framework extends calibration ideas from Deville and Sarndal (1992) <doi:10.1080/01621459.1992.10475217> and small area estimation ideas from Fay and Herriot (1979) <doi:10.1080/01621459.1979.10482505>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: graphics, stats, utils
Suggests: knitr, lpSolve, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-24 16:38:42 UTC; marvian
Author: Leila Marvian Mashhad [aut, cre]
Maintainer: Leila Marvian Mashhad <leila.marveian@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-25 05:20:31 UTC

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New package IGPFrailty with initial version 0.1.0
Package: IGPFrailty
Title: Inverse Gaussian Process Degradation Models with Frailty
Version: 0.1.0
Description: Maximum likelihood estimation and reliability inference for Inverse Gaussian Process (IGP) degradation models with gamma and inverse Gaussian frailty terms, as formulated by Morita et al. (2021) <doi:10.1002/qre.2762>. Classical IGP degradation models are described in Wasan (1968) and Meeker and Escobar (1998, ISBN:978-0471143284). The package provides tools for calculating lifetime cumulative distribution functions, probability density functions, lifetime quantiles with confidence intervals, posterior individual unit frailties, and goodness-of-fit diagnostics.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: stats, graphics, grDevices, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-24 16:43:23 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-25 05:21:06 UTC

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Mon, 24 Aug 2026

New package ctgimme with initial version 0.0.12
Package: ctgimme
Title: Continuous-Time Subgrouping with GIMME
Version: 0.0.12
Description: Estimates group-, subgroup-, and individual-level dynamic structures from multivariate intensive longitudinal data using continuous-time state-space models. The subgrouping procedure combines iterative shared-path searches with recurrent-evidence feature screening and partitioning around medoids. The continuous-time group iterative multiple model estimation method is described in Park et al. (2025) <doi:10.1080/10705511.2024.2429544>.
URL: https://github.com/JPark93/ctgimme
BugReports: https://github.com/JPark93/ctgimme/issues
License: Apache License (== 2.0)
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: cluster, gtools, matrixStats, methods, OpenMx, parallel, ps, qgraph, stats, utils
Suggests: expm, igraph, nloptr, testthat (>= 3.2.0)
NeedsCompilation: no
Packaged: 2026-08-20 16:10:11 UTC; imjpark
Author: Jonathan J. Park [aut, cre, cph] , Nathan Xin Mills [aut, ctb]
Maintainer: Jonathan J. Park <imJPark@UCDavis.edu>
Repository: CRAN
Date/Publication: 2026-08-24 15:20:02 UTC

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New package SmartPK with initial version 0.1.0
Package: SmartPK
Title: Automated Noncompartmental Pharmacokinetic Analysis
Version: 0.1.0
Maintainer: N. Shreenithi <Shreenithi092@gmail.com>
Description: Provides functions for automated noncompartmental pharmacokinetic (NCA) analysis using concentration-time data. The package estimates pharmacokinetic parameters including area under the concentration-time curve (AUC), area under the first moment curve (AUMC), maximum concentration (Cmax), time to maximum concentration (Tmax), terminal elimination rate constant (Kel), elimination half-life, clearance, volume of distribution, and mean residence time (MRT). It supports automatic terminal phase selection, bootstrap confidence intervals, and publication-ready concentration-time profiles. Methods are based on Gibaldi and Perrier (1982, ISBN:9780824710422).
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, rlang
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-17 15:15:28 UTC; JARVIS
Author: N. Shreenithi [aut, cre], S. Vishnu Shankar [aut], Balaji Kannan [aut]
Repository: CRAN
Date/Publication: 2026-08-24 14:40:02 UTC

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New package PenalReg with initial version 0.1.0
Package: PenalReg
Title: Automated Penalized Regression Analysis Using Ridge, Lasso and Elastic Net
Version: 0.1.0
Description: Provides an automated framework for penalized regression analysis using Ridge Regression, Lasso Regression and Elastic Net Regression. The package performs data standardization, training-testing data partitioning, cross-validation for hyperparameter tuning, model fitting, coefficient estimation, variable importance assessment, prediction, and performance evaluation. It simplifies regularized regression analysis by integrating the complete modeling workflow into a single function suitable for researchers for better understanding of the data.The methods are based on Hoerl and Kennard (1970) <doi:10.1080/00401706.1970.10488634>, Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, and Friedman et al. (2010) <doi:10.18637/jss.v033.i01>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: caret, stats, utils
Suggests: glmnet
NeedsCompilation: no
Packaged: 2026-08-17 14:58:54 UTC; JARVIS
Author: S. Vishnu Shankar [aut, cre], V. Lavanya [aut], Santosha Rathod [aut], Mrinmoy Ray [aut], Anil Kumar [aut]
Maintainer: S. Vishnu Shankar <S.vishnushankar55@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-24 14:40:07 UTC

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New package hellometry with initial version 1.0.1
Package: hellometry
Title: Biomass Estimation from Allometric Relationships
Version: 1.0.1
Description: Estimates body size and biomass of organisms from allometric relationships. It works with any data that follow a few column-naming conventions, using the measurements you supply to impute the ones that are missing.
License: GPL (>= 3)
URL: https://github.com/pierrerogy/hellometry
BugReports: https://github.com/pierrerogy/hellometry/issues
Encoding: UTF-8
Imports: dplyr, magrittr, performance, progress, purrr, rlang, stats, tibble, tidyr, tidyselect, utils
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 16:21:00 UTC; pagro
Author: Pierre Rogy [aut, cre] , Olivier Dezerald [ctb] , Gustavo Q. Romero [ctb] , Fabiola Ospina-Bautista [ctb] , Sarah Abdelazim [ctb] , Nicholas A. C. Marino [ctb] , Diane S. Srivastava [ctb]
Maintainer: Pierre Rogy <pierre.rogy@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-24 14:50:02 UTC

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New package gwrf with initial version 0.1.1
Package: gwrf
Title: Geographically Weighted Random Forests
Version: 0.1.1
Description: Fits geographically weighted random forest models using spatially localized training neighborhoods and 'ranger' as the random forest engine. Supports fixed-distance and adaptive neighborhoods defined by observation rows or unique spatial locations, including repeated observations at the same location. Provides local predictions and permutation-based variable importance for examining spatial variation in predictive relationships. The geographical random forest approach is described by Georganos et al. (2021) <doi:10.1080/10106049.2019.1595177>, and the 'ranger' engine by Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01>.
License: MIT + file LICENSE
URL: https://github.com/hac-lab/gwrf
BugReports: https://github.com/hac-lab/gwrf/issues
Encoding: UTF-8
Imports: ranger, tibble, dplyr, pbapply, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-10 17:36:46 UTC; seamone
Author: Erich Seamon [aut, cre, cph]
Maintainer: Erich Seamon <erich_seamon@baylor.edu>
Repository: CRAN
Date/Publication: 2026-08-24 14:50:08 UTC

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New package cropwatMUL with initial version 0.1.0
Package: cropwatMUL
Title: Crop Water Requirement and Irrigation Scheduling Across Multiple Locations
Version: 0.1.0
Description: Estimates reference evapotranspiration, crop evapotranspiration, effective rainfall, crop water requirements, root-zone water balance, and irrigation schedules across multiple locations. The calculations use temperature-based procedures described in Food and Agriculture Organization Irrigation and Drainage Paper No. 56 and a workflow inspired by the 'CROPWAT' software for monthly-to-daily interpolation, aggregation into 10-day periods, and irrigation scheduling. Further details of the evapotranspiration calculations are provided by Allen, R.G., Pereira, L.S., Raes, D. and Smith, M. (1998, ISBN:92-5-104219-5) "Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements" <https://www.fao.org/4/X0490E/X0490E00.htm>. The package is an independent implementation and is not affiliated with or endorsed by the Food and Agriculture Organization of the United Nations.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.2.0)
Imports: dplyr, lubridate, openxlsx, purrr, readxl, stats, tibble, tidyr, utils
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-20 13:35:11 UTC; win11
Author: Manish Naskar [aut, cre, cph] , Debasish Chakraborty [aut] , Koushik Bag [aut] , Shariti Syiem [aut] , Akmaul Hoque [aut]
Maintainer: Manish Naskar <manishkumarnaskar@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-24 14:30:02 UTC

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New package ConsensusCPA with initial version 0.1.0
Package: ConsensusCPA
Title: Consensus-Based Change-Point Analysis Using Multiple Statistical Tests
Version: 0.1.0
Maintainer: S. Vishnu Shankar <S.vishnushankar55@gmail.com>
Description: Provides a unified framework for detecting change points in univariate time series using multiple statistical methods, including Pettitt's test, Buishand Range test, Buishand U test, and the Standard Normal Homogeneity Test (SNHT). The package summarizes individual test results, determines a consensus change point using majority, median, or weighted agreement approaches, exports results with graphical comparisons of observations for before and after the detected change point. The methodology is further described in Laasya et al. (2026) <doi:10.1007/s11069-025-07783-2>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, ggplot2, rlang, trend, openxlsx, zoo
NeedsCompilation: no
Packaged: 2026-08-17 15:25:51 UTC; JARVIS
Author: S. Vishnu Shankar [aut, cre], Santosha Rathod [aut], Mrinmoy Ray [aut], Anil Kumar [aut], V. Lavanya [aut], Prabhat Kumar [aut]
Repository: CRAN
Date/Publication: 2026-08-24 14:50:13 UTC

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New package ebdt with initial version 1.0.1
Package: ebdt
Title: Evaluation of Binary Diagnostic Test
Version: 1.0.1
Description: Calculate the point estimator and its confidence interval for the quality parameters of a binary diagnostic test, such as sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, weighted Kappa coefficient, a global diagnostic accuracy index, prevalence in a cross-sectional study, and sensitivity, specificity, positive and negative likelihood ratio, and a global diagnostic accuracy index in a retrospective study.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/migmontal/ebdt, https://migmontal.github.io/ebdt/
Imports: stats
Suggests: knitr, readxl, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-20 12:38:04 UTC; Montero
Author: Miguel Angel Montero-Alonso [aut, cre] , Juan de Dios Luna del Castillo [aut]
Maintainer: Miguel Angel Montero-Alonso <mmontero@ugr.es>
Repository: CRAN
Date/Publication: 2026-08-24 13:40:14 UTC

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New package pressfreedom.data with initial version 0.3.0
Package: pressfreedom.data
Title: Download and Process Reporters Without Borders Press Freedom Index Data
Version: 0.3.0
Maintainer: Peter Baumgartner <petzi53@gmail.com>
Description: Download press freedom index data from Reporters Without Borders (RSF) with period-aware encoding handling. Data are downloaded from the RSF website (<https://rsf.org/en/index>). Provides infrastructure for data cleaning and ISO 3166 standardization in downstream phases.
License: MIT + file LICENSE
URL: https://github.com/petzi53/pressfreedom.data, https://www.peter-baumgartner.net/pressfreedom.data/
BugReports: https://github.com/petzi53/pressfreedom.data/issues
Encoding: UTF-8
LazyData: true
Imports: readr, here, rlang, countrycode, dplyr, stringr, cli, fs, glue, purrr, tibble, stringi
Suggests: usethis, knitr, rmarkdown, ggplot2, tidyr, forcats, patchwork, scales, sf, rnaturalearth, testthat (>= 3.0.0), covr
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-08-20 09:57:27 UTC; petzi
Author: Peter Baumgartner [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-24 12:40:02 UTC

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New package decimal with initial version 0.1.0
Package: decimal
Title: Exact Arbitrary-Precision Decimal Vectors
Version: 0.1.0
Description: Arbitrary-precision vectors with an exact decimal representation, avoiding the rounding surprises of binary floating point. Built on the 'mpdecimal' C library, arithmetic is governed by an explicit decimal context controlling precision, rounding, and signalling, and vectors integrate with 'vctrs' for use in data frames, 'tibble' objects, summaries, and common numeric workflows. Missing values, signed zeros, infinities, and not-a-number values are supported throughout. The arithmetic model follows Cowlishaw (2009) "General Decimal Arithmetic" <https://speleotrove.com/decimal/decarith.html>.
License: MIT + file LICENSE
Language: en-US
Depends: R (>= 4.2.0)
Imports: methods, rlang, vctrs, withr
Suggests: covr, knitr, pillar, rmarkdown, tibble, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-08-20 11:31:30 UTC; pbtz
Author: Pedro Baltazar [aut, cre, cph], Stefan Krah [ctb, cph]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-24 12:40:09 UTC

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New package reapeR with initial version 0.2.0
Package: reapeR
Title: Interface to the 'REAPER' Library
Version: 0.2.0
Description: Wrapper for David Talkin's 'Robust Epoch and Pitch EstimatoR' (REAPER) software for estimating pitch and glottal closure instants from recordings of speech. For more information about the procedure, see <https://github.com/google/REAPER/tree/master>.
Encoding: UTF-8
Depends: R (>= 3.1.0)
Imports: dplyr (>= 1.1.4), emuR (>= 2.5.2), readr (>= 2.1.5), stats (>= 4.5.1), tuneR (>= 1.4.7), wrassp (>= 1.0.5), Rcpp (>= 1.0.0)
LinkingTo: Rcpp
License: Apache License (>= 2)
URL: https://github.com/rpuggaardrode/reapeR
BugReports: https://github.com/rpuggaardrode/reapeR/issues
NeedsCompilation: yes
Packaged: 2026-08-20 08:50:11 UTC; cpgl0183
Author: Rasmus Puggaard-Rode [aut, cre], David Talkin [ctb], Google Inc. [cph]
Maintainer: Rasmus Puggaard-Rode <rasmus.puggaard-rode@ling-phil.ox.ac.uk>
Repository: CRAN
Date/Publication: 2026-08-24 10:10:02 UTC

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New package CompositionalMPT with initial version 1.0
Package: CompositionalMPT
Title: Compositional Data Two-Sample Test of Equal Distributions
Version: 1.0
Date: 2026-08-20
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, Rfast, Rfast2
Description: Two-sample tests of equal distributions for compositional data, with zero values present. The p-value is computed via permutations. The relevant papers are Stewart C., Iverson S. and Field C. (2014). "Testing for a diet change using fatty acid signatures". Environmental and Ecological Statistics, <doi:10.1007/s10651-014-0280-9> and Sevinc V. and Tsagris. M. (2026). "Energy Based Equality of Distributions Testing for Compositional Data". Communications in Statistics--Simulation and Computation, <doi:10.1080/03610918.2026.2636167>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-08-20 08:18:07 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-08-24 10:10:27 UTC

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New package CausalState with initial version 0.10.2
Package: CausalState
Title: Causal Inference in a Longitudinal Transitioning State Environment
Version: 0.10.2
Description: Implements Sequential Doubly Robust (SDR) and infinite-dimensional Targeted Maximum Likelihood (iTMLE) estimators for longitudinal modified treatment policies in settings with transitioning states, such as ICU, ward, or emergency department care episodes. Treatment is permitted in active states and becomes structurally inapplicable after a state transition (e.g. discharge or death). Supports asymmetric g- and Q-model regularisation, k-fold cross-fitting, and pluggable SuperLearner ensembles. Includes specialised SuperLearner wrappers (SL.tgt.* and SL.tmle_* families) for the iTMLE targeting step, which pass the logit offset as a covariate column to preserve correct subsetting during SuperLearner cross-validation. Methods based on Diaz et al. (2021) <doi:10.1080/01621459.2021.1955691> and Luedtke et al. (2017) <doi:10.48550/arXiv.1705.02459>.
URL: https://github.com/sebastiaan-blank/CausalState
BugReports: https://github.com/sebastiaan-blank/CausalState/issues
License: AGPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: data.table (>= 1.14.0), SuperLearner, origami, glmnet, xgboost, dplyr, tidyr, rlang, magrittr, parallel, stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, ggplot2, scales, stringr, hal9001, dbarts, mgcv, earth, nnls
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 08:04:00 UTC; bas
Author: Sebastiaan Blank [aut, cre, cph]
Maintainer: Sebastiaan Blank <sebastiaan.blank@mail.com>
Repository: CRAN
Date/Publication: 2026-08-24 09:10:08 UTC

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Sun, 23 Aug 2026

New package orthoMTL with initial version 0.1.0
Package: orthoMTL
Title: Multi-Task Learning with Orthogonal Constraints
Version: 0.1.0
Description: Fits regularised multi-task learning models where relationships between tasks are controlled via orthogonality or disjoint-support constraints. Supports regression, binary classification, and censored survival data. In survival mode, time-to-event outcomes are converted into binary labels at user-defined thresholds, enabling the discovery of features with time-varying effects that standard proportional-hazards models cannot detect. Implements the penalty described in Vervier et al. (2014) <https://hal.science/hal-00985654>.
License: GPL-3
Encoding: UTF-8
Imports: parallel, doParallel, foreach, ggplot2, rlang, stats
VignetteBuilder: knitr
Suggests: knitr, glmnet, testthat (>= 3.0.0), survival, rmarkdown
Depends: R (>= 4.0.0)
NeedsCompilation: no
Packaged: 2026-08-07 13:45:33 UTC; Shadow
Author: Kevin Vervier [aut, cre], Novartis Pharma AG [cph, fnd]
Maintainer: Kevin Vervier <kevin.vervier@novartis.com>
Repository: CRAN
Date/Publication: 2026-08-23 10:10:02 UTC

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New package inedemogR with initial version 0.1.0
Package: inedemogR
Title: Tidy Access to Spanish INE Demographic Data
Version: 0.1.0
Description: Provides tidy, harmonized access to demographic data from the Spanish National Statistics Institute (INE) fenomenos demograficos domain, including population, births, and deaths, retrieved live via the official 'ineapir' API wrapper, with optional spatial integration at municipality and province level via 'mapSpain'. Mortality indicators follow the Human Mortality Database Methods Protocol, including the average age at death in infancy method of Andreev and Kingkade (2015) <doi:10.4054/DemRes.2015.33.13>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, ggplot2, httr2, ineapir, mapSpain, purrr, readr, rlang, scales, sf, stringi, stringr, tibble, tidyr
Suggests: mockery, R.rsp, testthat (>= 3.0.0), withr
Depends: R (>= 4.1.0)
LazyData: true
VignetteBuilder: R.rsp
NeedsCompilation: no
Packaged: 2026-08-20 06:34:41 UTC; josecaro
Author: J. R. Caro-Barrera [aut, cre, cph]
Maintainer: J. R. Caro-Barrera <jrcaro@uco.es>
Repository: CRAN
Date/Publication: 2026-08-23 10:30:08 UTC

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Fri, 21 Aug 2026

New package MuTATE with initial version 0.1.0
Package: MuTATE
Title: Multi-Target Automated Tree Engine (MuTATE)
Version: 0.1.0
Description: Recursively partitions datasets on binary splits across multiple targets having different dependent variable types, including categorical, continuous, count, and survival outcomes. This overcomes single-target limitations of traditional decision trees while retaining model interpretability. See Ayton and Trevino (2023) <doi:10.1093/bioinformatics/btad507> and Ayton et al. (2025) <doi:10.1038/s44401-025-00025-4> for details.
License: GPL (>= 3)
URL: https://github.com/SarahAyton/MuTATE
BugReports: https://github.com/SarahAyton/MuTATE/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5)
Imports: reshape2, matrixStats, survival, stringr, irr, Metrics, plotrix, scales, stats, caret, dplyr, igraph, ggraph, grDevices
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 03:06:13 UTC; sarahayton
Author: Sarah Ayton [aut, cre, cph]
Maintainer: Sarah Ayton <sarahgabrielleayton@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 15:40:09 UTC

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New package grayleafspotdata with initial version 0.1.0
Package: grayleafspotdata
Title: File Manifest for the S-BSST3199 Magnaporthe Colony Image Dataset
Version: 0.1.0
Date: 2026-08-19
Description: Provides a machine-readable file and image manifest for the research data deposited in EMBL-EBI BioStudies under accession S-BSST3199 (a time-series petri-dish image dataset of Magnaporthe colonies from twelve plates, with associated morphometric analysis outputs produced by metrics-petri 3.0.0). The original research files are not bundled in this R package; they remain hosted by BioStudies. The manifest can be used in image-analysis and plant-pathology workflows, including workflows based on the 'grayleafspotr' software. Related research outputs are documented using their persistent identifiers.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Maintainer: Rohan R <phonics-tiffs1i@icloud.com>
URL: https://github.com/rotsl/grayleafspotdata, https://www.ebi.ac.uk/biostudies/studies/S-BSST3199, https://rotsl.r-universe.dev/
BugReports: https://github.com/rotsl/grayleafspotdata/issues
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-20 03:10:26 UTC; tslwork
Author: Rohan R [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-21 15:30:09 UTC

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New package CoxAalenCR with initial version 0.1.0
Package: CoxAalenCR
Title: Additive-Multiplicative Cox-Aalen Subdistribution Hazard Model for Competing Risks
Version: 0.1.0
Description: Implements the flexible additive-multiplicative Cox-Aalen subdistribution hazard regression model for competing risks data as proposed by Li and Long (2019) <doi:10.1007/s11424-019-7281-6>. The framework accommodates both time-varying non-parametric additive covariate effects through an Aalen (1980) additive model and constant multiplicative effects via a Cox proportional hazards structure, generalizing Scheike and Zhang (2002) <doi:10.1111/1467-9469.00065> and Martinussen and Scheike (2002) <doi:10.1093/biomet/89.2.283>. Includes inverse probability of censoring weighting (IPCW) with both Kaplan-Meier weights (Fine and Gray, 1999 <doi:10.1080/01621459.1999.10474144>) and covariate-dependent Cox censoring weights (He et al., 2016 <doi:10.1111/sjos.12172>; Li and Long, 2019 <doi:10.1007/s11424-019-7281-6>). Provides simultaneous estimating equations based on Huffer and McKeague (1991) <doi:10.1080/01621459.1991.10475010>, asymptotic sandwich var [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils, survival
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 03:20:11 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 15:20:02 UTC

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New package TieFreeCensor with initial version 0.1.0
Package: TieFreeCensor
Title: Algorithm for Generating Tie-Free Progressive Type-II Censored Samples
Version: 0.1.0
Description: Generates tie-free progressive Type-II censored samples from discrete distributions and user-specified discrete probability mass functions (PMF) or cumulative distribution functions (CDF). Provides maximum likelihood estimation (MLE), Bayesian estimation via Markov chain Monte Carlo (MCMC) Metropolis-within-Gibbs sampling, likelihood-based parametric bootstrap goodness-of-fit (GOF) tests, profile log-likelihood diagnostics, and discrete survival and probability calculations. Methods are based on Ahmad and Mansour (2026) <doi:10.1155/jom/3657078>, Balakrishnan and Dembinska (2008) <doi:10.1016/j.jspi.2007.02.006>, Joe and Zhu (2005) <doi:10.1002/bimj.200410102>, and Balakrishnan and Aggarwala (2000, ISBN:978-1-4612-1334-5).
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-05 19:52:59 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 12:41:06 UTC

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New package tabulergm with initial version 0.1.0
Package: tabulergm
Title: Publication-Ready Tables and Summaries for Exponential-Family Random Graph Models
Version: 0.1.0
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.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: base64enc, ergm (>= 4.0), netplot (>= 0.4-0), network, yaml
Suggests: knitr, rmarkdown, rstudioapi, tinytest
URL: https://gvegayon.github.io/tabulergm/, https://github.com/gvegayon/tabulergm
BugReports: https://github.com/gvegayon/tabulergm/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 02:21:33 UTC; runner
Author: George Vega Yon [aut, cre]
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:50:02 UTC

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New package rewind with initial version 0.2.0
Package: rewind
Title: Undo and Redo for 'Shiny' Applications
Version: 0.2.0
Description: Adds a user-facing undo and redo history to 'Shiny' applications. Application state, comprising registered inputs and optionally server-side reactive values, is captured as the user interacts with the application. Users may then step backwards and forwards through that history with the keyboard, with buttons, or by scrubbing a visual history rail. Rapid successive changes, such as dragging a slider, are coalesced into a single history entry, and related changes may be grouped explicitly into semantic steps.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: htmltools, R6, shiny (>= 1.7.0), utils
Suggests: shinytest2, testthat (>= 3.0.0), withr
URL: https://github.com/tenmeh/rewind, https://tenmeh.github.io/rewind/
BugReports: https://github.com/tenmeh/rewind/issues
NeedsCompilation: no
Packaged: 2026-08-20 03:02:42 UTC; tchan
Author: Tanmay Chanda [aut, cre, cph]
Maintainer: Tanmay Chanda <tanmaychanda96@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:50:08 UTC

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New package rankingQ with initial version 0.2.0
Package: rankingQ
Title: Design-Based Methods for Ranking Questions
Version: 0.2.0
Description: Provides a design-based toolkit for survey ranking questions. Estimates average ranks, marginal rank probabilities, pairwise comparisons, and ranking distributions, with optional bias correction for random responding via anchor-ranking items or user-supplied random-response rates. Includes Plackett-Luce simulation, visualization, format conversion, and diagnostic checks. Methods are described in Atsusaka and Kim (2025) <doi:10.1017/pan.2024.33>.
URL: https://github.com/sysilviakim/rankingQ, https://sysilviakim.com/rankingQ/
BugReports: https://github.com/sysilviakim/rankingQ/issues
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: dplyr, tidyr (>= 1.3.0), tidyselect, purrr, tibble, generics, ggplot2, rlang, combinat, estimatr, stats, Rcpp
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, cli, testthat (>= 3.0.0)
Depends: R (>= 4.1.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-07-23 13:43:31 UTC; owner
Author: Seo-young Silvia Kim [aut, cre, cph] , Yuki Atsusaka [aut, cph]
Maintainer: Seo-young Silvia Kim <sy.silvia.kim@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:50:14 UTC

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New package PowerXgammaRF with initial version 1.0.0
Package: PowerXgammaRF
Title: Random Forest Regression with Power Xgamma Distribution Error Model
Version: 1.0.0
Description: Implements Random Forest regression under the Power Xgamma distribution error model. Provides core distribution functions (density, cumulative distribution, quantile, random generation, hazard, survival), parameter estimation via Expectation-Maximization (EM) and Markov Chain Monte Carlo (MCMC), non-parametric bootstrap confidence intervals (at 90%, 95%, and 99% levels), Highest Posterior Density (HPD) intervals, Heidelberger and Welch's MCMC convergence diagnostic, convergence probability, model evaluation metrics (estimated values, bias, mean squared error, risk value), homoscedastic prediction intervals, and goodness-of-fit diagnostic tests (Kolmogorov-Smirnov and Anderson-Darling tests, Akaike Information Criterion, and Bayesian Information Criterion). References: Tyagi et al. (2022, Int. J. Stat. Reliab. Eng., 9(1), 51-60); Breiman (2001) <doi:10.1023/A:1010933404324>; Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01>; Heidelberger and Welch (1983) <doi:10.1287/ [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: ranger, coda, goftest, stats, graphics
Suggests: testthat (>= 3.0.0)
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-18 15:13:50 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Aruna Rajballie [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:20:24 UTC

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New package phylowise with initial version 0.0.1
Package: phylowise
Title: Phylogenetic Pairwise Contrasts
Version: 0.0.1
Maintainer: Jordan Douglas <jordan.douglas@auckland.ac.nz>
Author: Jordan Douglas [aut, cre], Lindell Bromham [aut]
Description: A phylogenetic comparative method for finding associations between biological traits and molecular evolutionary rates. The method samples pairs from a phylogeny such that each pair has non-overlapping edge paths, and can therefore be treated as statistically independent observations. Linear regression is performed on the pair contrasts. This approach is similar to phylogenetically independent contrasts (PIC) but without reconstructing the traits at internal nodes, and is better suited for finding trait-rate associations than phylogenetic generalised least squares (PGLS). Refer to Douglas and Bromham (2026) <doi:10.64898/2026.08.13.744736> for further details.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/jordandouglas/phylowise
Depends: ape, BMA, phylotate
Imports: Rcpp
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-08-16 11:28:21 UTC; jdou557
Repository: CRAN
Date/Publication: 2026-08-21 13:40:02 UTC

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New package pHMC with initial version 0.1.0
Package: pHMC
Title: Proximal Hamiltonian Monte Carlo for Non-Smooth Bayesian Inference
Version: 0.1.0
Description: Implements the Proximal Hamiltonian Monte Carlo (p-HMC) algorithm for Bayesian sampling and estimation from non-differentiable target densities. The method decomposes a target potential into a smooth component f(x) and a non-smooth convex component g(x), approximating only g(x) via its Moreau-Yosida envelope while retaining exact gradient information for f(x). This approach, based on the methodology described in Shukla, Vats, and Chi (2025) <doi:10.48550/arXiv.2510.22252>, yields improved Hamiltonian conservation over full-potential smoothing approaches. The package provides generalized routines accepting user-defined probability density functions, log-likelihoods, priors, and proximal operators, together with automated hyperparameter tuning for the Moreau-Yosida regularization parameter, Markov chain Monte Carlo convergence diagnostics, effective sample size computation, and model evaluation metrics including the Akaike information criterion and Bayesian information criterion.
License: GPL (>= 2)
Encoding: UTF-8
Imports: stats, graphics, grDevices, utils, Matrix
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-05 11:36:31 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 12:40:09 UTC

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New package pb210dating with initial version 1.0.1
Package: pb210dating
Title: Pb-210 Dating of Sediment Cores
Version: 1.0.1
Date: 2026-08-01
Encoding: UTF-8
Description: Dates sediment cores from lead-210 (Pb-210) activity profiles measured by alpha or gamma spectrometry, following the unified formulation and nomenclature of Sanchez-Cabeza and Ruiz-Fernandez (2012) <doi:10.1016/j.gca.2010.12.024>. Implements the Constant Flux (CF) and Constant Flux Constant Sedimentation (CFCS) dating models, together with supporting tools for data input, decay correction, missing inventory estimation, calculation of sediment and mass accumulation rates, and Monte Carlo propagation of dating uncertainties as described in Sanchez-Cabeza et al. (2014) <doi:10.1016/j.quageo.2014.06.002>. Also provides functions to visualize activity profiles and resulting age models.
Depends: R (>= 4.3)
Imports: lubridate
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-08-19 20:46:14 UTC; jasc2
Author: Joan-Albert Sanchez-Cabeza [aut, cre, cph] , Ana Carolina Ruiz-Fernandez [aut] , David Morina Soler [aut]
Maintainer: Joan-Albert Sanchez-Cabeza <jasanchez@cmarl.unam.mx>
Repository: CRAN
Date/Publication: 2026-08-21 13:30:02 UTC

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New package openfhe.R with initial version 1.5.1
Package: openfhe.R
Title: R Interface to the 'OpenFHE' Fully Homomorphic Encryption Library
Version: 1.5.1
Description: Provides an R interface to 'OpenFHE', the open-source C++ library for fully homomorphic encryption (Al Badawi and others, 2022) <https://eprint.iacr.org/2022/915>, which allows computation directly on encrypted data without access to the secret key. Supports the Brakerski-Fan-Vercauteren (BFV, 2012) <https://eprint.iacr.org/2012/144>, Brakerski-Gentry-Vaikuntanathan (BGV, 2014) <doi:10.1145/2633600>, and Cheon-Kim-Kim-Song (CKKS, 2017) <https://eprint.iacr.org/2016/421> schemes for arithmetic on encrypted numbers, together with the Ducas-Micciancio (FHEW, 2015) <https://eprint.iacr.org/2014/816> and Chillotti-Gama-Georgieva-Izabachene (TFHE, 2020) <https://eprint.iacr.org/2018/421> schemes for evaluating arbitrary functions on encrypted bits.
License: BSD_2_clause + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://openfheorg.github.io/openfhe.R/, https://github.com/openfheorg/openfhe.R
BugReports: https://github.com/openfheorg/openfhe.R/issues
Depends: R (>= 4.3.0)
Imports: S7, cli, methods
Suggests: tinytest, knitr, rmarkdown
VignetteBuilder: knitr
LinkingTo: cpp11 (>= 0.4.2)
SystemRequirements: cmake (>= 3.16), GNU make, C++17
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-08-19 17:55:39 UTC; naras
Author: Balasubramanian Narasimhan [aut, cre, cph] , New Jersey Institute of Technology [cph] , Duality Technologies, Inc. [ctb, cph] , Samuel Neves [ctb, cph] , Jean-Philippe Aumasson [ctb, cph] , Randolph Voorhies [ctb, cph] , Shane Grant [ctb, cph] , Juan [...truncated...]
Maintainer: Balasubramanian Narasimhan <naras@stanford.edu>
Repository: CRAN
Date/Publication: 2026-08-21 13:30:08 UTC

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New package MTLRF with initial version 1.0.0
Package: MTLRF
Title: Random Forest Regression with Modified Topp-Leone Error Model
Version: 1.0.0
Date: 2026-08-18
Description: Implements Random Forest regression under the Modified Topp-Leone (MTL) distribution error model. Provides core distribution functions (density, cumulative distribution, exact closed-form quantile, random generation, hazard, and survival), parameter estimation via closed-form Expectation-Maximization/Maximum Likelihood (EM/MLE) and Bayesian Markov Chain Monte Carlo (MCMC), non-parametric bootstrap confidence intervals (at 90%, 95%, and 99% levels), Highest Posterior Density (HPD) intervals, Heidelberger and Welch MCMC convergence diagnostics, model evaluation metrics (estimated values, bias, mean squared error, risk value), homoscedastic prediction intervals, and goodness-of-fit diagnostic tests (Kolmogorov-Smirnov and Anderson-Darling tests, Akaike Information Criterion, and Bayesian Information Criterion). References: Breiman (2001) <doi:10.1023/A:1010933404324>; Singh, Tyagi, Singh, and Tyagi (2025) <https://statassoc.or.th>; Topp and Leone (1955) <doi:10.1080/0162145 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: ranger, coda, goftest, stats, graphics
Suggests: testthat (>= 3.0.0)
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-17 23:01:40 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Aruna Rajballie [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:10:42 UTC

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New package investdatar with initial version 0.1.5
Package: investdatar
Title: Investment Data Access and Preparation Toolkit
Version: 0.1.5
Description: A toolkit for loading, transforming, and managing structured investment-related data. Includes functions for retrieving macroeconomic and public financial series, regulatory filings, futures positioning, energy and fiscal data, market open-high-low-close-volume data, fund holdings, narrative feeds, and crypto derivatives from multiple providers. It detects time-series gaps and synchronizes local '.rds' data stores with sidecar metadata for analysis and trading workflows. It also generates structured dataset descriptions for LLM-based analyst agents that produce R code for analysis and visualization.
License: MIT + file LICENSE
URL: https://github.com/OliverLDS/investdatar
BugReports: https://github.com/OliverLDS/investdatar/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: data.table, jsonlite, curl, httr, xml2, yaml
Suggests: binxr, okxr, quantmod, testthat (>= 3.0.0), xts, waldo, wbstats, withr, zoo
NeedsCompilation: no
Packaged: 2026-08-20 00:51:53 UTC; oliver
Author: Oliver Zhou [aut, cre]
Maintainer: Oliver Zhou <oliver.yxzhou@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:40:07 UTC

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New package GFT with initial version 1.0.0
Package: GFT
Title: Generalized Fisher Transformation of Correlation Matrices
Version: 1.0.0
Description: Forward and inverse generalized Fisher transformation ('GFT') of correlation matrices, gamma = vecl(log C), which maps the positive definite correlation matrices one-to-one onto the Euclidean space of dimension n(n-1)/2, see Archakov and Hansen (2021) <doi:10.3982/ECTA16910>. The inverse is computed from a variational characterization by the 'GFT-FP+N' algorithm: a fixed-point phase in the log domain followed by a matrix-free inexact Newton phase with preconditioned conjugate gradients. Reference implementations of the plain fixed point, Broyden's method, and full Newton are included. Uses base R only.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/reinhardhansen/GFT
BugReports: https://github.com/reinhardhansen/GFT/issues
NeedsCompilation: no
Packaged: 2026-08-08 15:16:24 UTC; prhansen
Author: Ilya Archakov [aut], Peter Reinhard Hansen [aut, cre]
Maintainer: Peter Reinhard Hansen <hansen@unc.edu>
Repository: CRAN
Date/Publication: 2026-08-21 13:40:42 UTC

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New package fuzzyurn with initial version 0.1.0
Package: fuzzyurn
Title: Generalized Non-Central Fuzzy Dynamic Hypergeometric Processes
Version: 0.1.0
Description: Implements Generalized Non-Central Fuzzy Dynamic Hypergeometric Processes. Includes discrete Markov chain sampling under dynamic weight decay and continuous fuzzy membership maps, infinitesimal generator evaluation, weak convergence to Itô diffusion SDEs, numerical solutions for Fokker-Planck PDEs, stationary Gibbs-Boltzmann densities, and Azuma-Hoeffding concentration bounds.
License: GPL (>= 3)
Encoding: UTF-8
Imports: stats
Suggests: deSolve, graphics, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-19 22:20:47 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-21 13:30:20 UTC

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New package FITclust with initial version 1.0.0
Package: FITclust
Title: Fair Interpolated Transport for Group-Fair Clustering
Version: 1.0.0
Date: 2026-08-19
Author: Jesse S. Ghashti [aut, cre], Warren Hare [aut], John R.J. Thompson [aut]
Maintainer: Jesse S. Ghashti <jesse.ghashti@ubc.ca>
Description: Implementation of Fair Interpolated Transport (FIT), an algorithm-agnostic preprocessing framework for group-fair clustering. Group-conditional empirical distributions are moved along Wasserstein-2 geodesics toward a shared barycenter at a tunable transport intensity, and the smallest intensity meeting a soft-fairness tolerance is selected. Three soft clustering families are provided, centroid based, graph based, and model based.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, transport, Matrix, mvtnorm
Suggests: ggplot2, knitr, rmarkdown, devtools, spelling,
VignetteBuilder: knitr
NeedsCompilation: no
Language: en-US
Packaged: 2026-08-20 01:36:55 UTC; jesseghashti
Repository: CRAN
Date/Publication: 2026-08-21 13:40:48 UTC

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New package citcdf with initial version 1.1.0
Package: citcdf
Title: Conditional Independence Testing with Cumulative Distribution Functions
Version: 1.1.0
Depends: R (>= 4.1)
Imports: ggplot2, pbapply, parallel, patchwork, RcppNumerical, survey, viridisLite
Suggests: BiocSet, bnlearn, GSA, knitr, quarto, reactable, rmarkdown, sessioninfo, SeuratObject, testthat (>= 3.0.0)
Description: Complex hypothesis testing through conditional cumulative distribution function estimation. Method is detailed in: Gauthier M, Agniel D, Thiébaut R & Hejblum BP (2021). "Distribution-free complex hypothesis testing for single-cell RNA-seq differential expression analysis", bioRxiv <doi:10.1101/2021.05.21.445165>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/sistm/citcdf, https://sistm.github.io/citcdf/
BugReports: https://github.com/sistm/citcdf/issues
Language: en-US
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-08-19 21:24:56 UTC; boris
Author: Denis Agniel [aut], Kalidou Ba [ctb], Sara Fallet [aut], Marine Gauthier [aut], Boris P. Hejblum [aut, cre, cph], Pierre Neuvial [ctb]
Maintainer: Boris P. Hejblum <boris.hejblum@u-bordeaux.fr>
Repository: CRAN
Date/Publication: 2026-08-21 13:30:32 UTC

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New package bruno with initial version 0.1.0
Package: bruno
Title: Predicting User-Defined Event Recurrence under Exchangeability
Version: 0.1.0
Description: Implements analytical prediction of recurrence for user-defined binary events; 'bruno' abbreviates Beta-Bernoulli Recurrence for Unobserved Next Outcomes. The procedure applies when the observed and future event indicators are judged exchangeable for the intended prediction. For an indefinitely extendible exchangeable binary sequence, de Finetti's representation theorem expresses the assigned joint probabilities as a mixture of Bernoulli laws over a mixing distribution on the unit interval (de Finetti, 1931) <doi:10.4064/fm-17-1-298-329>. The package adopts a beta distribution as an additional parametric specification of this mixing distribution. Users specify an initial probability mu0 assigned to the event and a positive concentration parameter tau, giving beta parameters a = mu0 * tau and b = (1 - mu0) * tau. If the declared event occurs s times among n observed cases, conditioning gives Beta(a + s, b + n - s). From this conditional assessment, the package computes analyticall [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: testthat (>= 3.0.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-19 21:13:49 UTC; irene
Author: Irene Gianeselli [aut, cre]
Maintainer: Irene Gianeselli <irene.gianeselli@unibz.it>
Repository: CRAN
Date/Publication: 2026-08-21 13:30:38 UTC

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New package brfssdata with initial version 0.1.0
Package: brfssdata
Title: Access CDC Behavioral Risk Factor Surveillance System Data
Version: 0.1.0
Description: Download, cache, and analyze annual microdata from the United States Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS) <https://www.cdc.gov/brfss/>. Each requested survey year is downloaded once as a compact file hosted on public releases, verified against a published checksum, and cached locally; queries then run through 'DuckDB' (via the 'duckdb' package), so column selection and repeat analyses never re-transfer data. Survey-design helpers construct 'srvyr' design objects with year-appropriate weights, strata, and primary sampling units, including explicit handling of the 2011 weighting methodology change and of the codes CDC uses for missing-type answers.
License: MIT + file LICENSE
Depends: R (>= 4.2)
Encoding: UTF-8
Suggests: curl, dplyr, knitr, rmarkdown, spelling, survey, testthat, withr
LazyData: true
Imports: cli, DBI, duckdb (>= 1.5.5), jsonlite, rlang, srvyr (>= 1.0.0), tibble, tools, utils
URL: https://muntasirmasum.github.io/brfssdata/, https://github.com/muntasirmasum/brfssdata
VignetteBuilder: knitr
BugReports: https://github.com/muntasirmasum/brfssdata/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-17 15:42:24 UTC; mm992584
Author: Muntasir Masum [aut, cre, cph]
Maintainer: Muntasir Masum <muntasir.1124@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:10:31 UTC

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New package autotune with initial version 0.1.0
Package: autotune
Title: Faster and more Efficient Lasso (than 'glmnet' and 'scalreg') with Data-Driven Tuning
Version: 0.1.0
Maintainer: Tathagata Sadhukhan <ts767@cornell.edu>
Description: Fits Lasso paths for high-dimensional regression using coordinate descent with automatic, data-driven tuning of the regularization parameter. The implementation is 10 to 50 times faster than the standard 'glmnet' implementation of Lasso and over 100 times faster than scaled Lasso. It also provides a reliable estimate of the regression noise level. For details of the method, see Sadhukhan, Wilms, Smeekes and Basu (2025) "Autotune: fast, accurate, and automatic tuning parameter selection for Lasso" <doi:10.48550/arXiv.2512.11139>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 2.10)
Imports: Rcpp (>= 1.0.13)
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, glmnet, AUC, ggplot2, ggExtra, dplyr, tidyr, Matrix
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-20 00:18:39 UTC; ts767
Author: Tathagata Sadhukhan [aut, cre], Ines Wilms [aut], Stephan Smeekes [aut], Sumanta Basu [aut]
Repository: CRAN
Date/Publication: 2026-08-21 13:40:26 UTC

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New package AstraeaDB with initial version 0.2.1
Package: AstraeaDB
Title: Client for the 'AstraeaDB' Graph Database
Version: 0.2.1
Description: Provides a client for 'AstraeaDB', a graph database with vector search capabilities. Supports node and edge create, read, update, and delete operations, label and edge-type lookups, graph traversals (breadth-first search, depth-first search, shortest path), temporal (time-travel) queries, graph algorithms (PageRank, Louvain community detection, connected components, and degree and betweenness centrality), vector similarity search, hybrid graph-vector search, Graph Query Language (GQL) execution, and graph-based retrieval-augmented generation (subgraph extraction with large language model integration). Communicates with the 'AstraeaDB' server over a JSON-over-TCP protocol. An optional 'Apache Arrow Flight' transport is available for high-performance bulk operations when the 'arrow' package is installed.
License: MIT + file LICENSE
URL: https://github.com/AstraeaDB/R-AstraeaDB
BugReports: https://github.com/AstraeaDB/R-AstraeaDB/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: jsonlite, R6
Suggests: arrow, knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-20 02:12:25 UTC; jimharris
Author: James Harris [aut, cre]
Maintainer: James Harris <jimeharrisjr@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:50:28 UTC

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New package ArvindRF with initial version 1.0.0
Package: ArvindRF
Title: Random Forest Regression with Arvind Distribution Error Model
Version: 1.0.0
Description: Implements Random Forest regression under the Arvind distribution error model. Provides core distribution functions (density, cumulative distribution, quantile, random generation, hazard, survival), parameter estimation via Expectation-Maximization (EM) and Markov Chain Monte Carlo (MCMC), non-parametric bootstrap confidence intervals (at 90%, 95%, and 99% levels), Highest Posterior Density (HPD) intervals, model evaluation metrics (estimated values, bias, mean squared error, risk value), homoscedastic prediction intervals, and goodness-of-fit diagnostic tests (Kolmogorov-Smirnov and Anderson-Darling tests, Akaike Information Criterion, and Bayesian Information Criterion). References: Breiman (2001) <doi:10.1023/A:1010933404324>; Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: ranger, coda, goftest, stats, graphics
Suggests: testthat (>= 3.0.0)
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-11 04:51:50 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Aruna Rajballie [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:10:53 UTC

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New package OneShotEM with initial version 0.1.0
Package: OneShotEM
Title: Efficient eM-Algorithm for One-Shot Device Data Analysis
Version: 0.1.0
Description: Implements the simple and efficient Expectation-Maximization (eM) algorithm proposed by Zhu, Li, Li, and Balakrishnan (2026) <doi:10.1080/03610918.2025.2515193> for parameter estimation in one-shot device accelerated life testing (ALT) data. Unlike traditional EM algorithms that impute exact failure times, this method treats failure counts between inspection intervals as missing data, resulting in faster convergence and enhanced numerical stability. Supports Exponential, Weibull, Lognormal, Gamma, and custom user-defined lifetime distributions under log-linear stress models. Standard errors, confidence intervals, model selection statistics (AIC, BIC, AICc, HQIC), residual diagnostics, and visualization tools are provided. References: Balakrishnan and Ling (2012) <doi:10.1016/j.csda.2011.09.010>, Fan, Balakrishnan, and Chang (2009) <doi:10.1080/00949650802142592>.
License: GPL (>= 3)
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils, methods, numDeriv
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Encoding: UTF-8
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-07 23:14:09 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 12:41:11 UTC

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New package gpciLindleyApprox with initial version 0.1.0
Package: gpciLindleyApprox
Title: Lindley Approximation Method for Generalized Process Capability Indices
Version: 0.1.0
Description: Provides a comprehensive framework for estimating Generalized Process Capability Indices (GPCIs) using the Lindley approximation method for uncensored data under Bayesian inference. Evaluates point estimates and posterior expectations for classical and non-normal capability indices, including Cpy (Maiti et al., 2010), Spmk (Dey & Saha, 2019), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022), CNpmc (Alotaibi et al., 2022), CNpmkc (Saha et al., 2024), CNpk (Saha et al., 2018), and Vannman's Cp(u,v) family. Computes parametric and non-parametric bootstrap confidence intervals at 90%, 95%, and 99% levels of significance. Supports MCMC chain generation with burn-in and thinning, Highest Posterior Density (HPD) intervals, Bias, MSE, Risk values, and Heidelberger and Welch's MCMC Convergence Diagnostic with convergence probabilities. References: Lindley (1980) <doi:10.2307/2345271>, Maiti, Saha & Nanda (2010) <doi:10.1080/16843703.2010.11673233>, Saha, Dey & Maiti (20 [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, ggplot2, numDeriv, boot
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-07 23:30:25 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 12:50:25 UTC

More information about gpciLindleyApprox at CRAN
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New package gpcihybridIImcmc with initial version 0.1.0
Package: gpcihybridIImcmc
Title: Generalized Process Capability Indices for Hybrid Type-II Censored Data using MCMC
Version: 0.1.0
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Description: Implements Bayesian Markov Chain Monte Carlo (MCMC) estimation using Metropolis-Hastings within Gibbs sampler for Generalized Process Capability Indices (GPCIs) under Hybrid Type-II censored lifetime data. Supports classical and generalized capability indices including Cpy, Cp, Cpk, Cpm, Cpmk, Spmk, CpTk, Cpc, CNp, CNpk, CNpm, CNpmk, CNpmc, and CNpmkc. Calculates posterior point estimates, bias, mean squared error (MSE), Bayes risk, Highest Posterior Density (HPD) credible intervals at 90%, 95%, and 99% levels, Heidelberger and Welch's MCMC convergence diagnostics, and coverage probabilities. Accommodates user-defined probability density/mass functions, cumulative distribution functions, and survival functions. Based on methods described in Childs et al. (2003) <doi:10.1080/0266476032000053637>, Kundu and Pradhan (2009) <doi:10.1016/j.spl.2008.09.006>, Saha and Dey (2019) <doi:10.1007/s41872-019-00081-4>, Alotaibi et al. (2022) <doi:10.1155/2022/3135264>, Dey et [...truncated...]
License: GPL (>= 2)
Encoding: UTF-8
Imports: coda, stats, graphics
Suggests: gofPHCS, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-16 03:25:50 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Vrijesh Tripathi [aut]
Repository: CRAN
Date/Publication: 2026-08-21 13:00:14 UTC

More information about gpcihybridIImcmc at CRAN
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New package gpcihybridIILinApp with initial version 0.1.0
Package: gpcihybridIILinApp
Title: Lindley Approximation for Capability Indices under Hybrid Censoring
Version: 0.1.0
Description: Provides a comprehensive framework for estimating Generalized Process Capability Indices (GPCIs) under Hybrid Type-II censored lifetime data using Lindley's 3rd-order approximation method (Lindley, 1980 <doi:10.2307/2345271>). Supports user-supplied probability density/mass functions (PDF/PMF), cumulative distribution functions (CDF), survival functions (SF), and quantile functions. Computes Maximum Likelihood Estimates (MLE) using the 'MleCensoR' package (Childs et al., 2003 <doi:10.1007/BF02517803>; Balakrishnan & Kundu, 2013 <doi:10.1002/nav.21545>) and Bayesian posterior expectations for classical and non-normal capability indices, including Cpy (Maiti et al., 2010 <doi:10.1080/16843703.2010.11673233>), Spmk (Dey & Saha, 2019 <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022 <doi:10.1080/02664763.2021.1971632>), CNpmc (Alotaibi et al., 2022 <doi:10.1155/2022/3135264>), CNpmkc (Saha et al., 2024 < [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, numDeriv, MleCensoR, gofPHCS
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-16 23:25:40 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:00:20 UTC

More information about gpcihybridIILinApp at CRAN
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New package gpcihybridIIImpSam with initial version 0.1.0
Package: gpcihybridIIImpSam
Title: Process Capability Indices for Hybrid Type-II Data via Importance Sampling
Version: 0.1.0
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Description: Evaluates Generalized Process Capability Indices (GPCIs) under Hybrid Type-II censored lifetime data using Importance Sampling (Sampling Importance Resampling, SIR). Implements Bayesian parameter estimation and evaluates classical and generalized capability indices including Cpy, Cp, Cpk, Cpu, Cpl, Cpm, Cpmk, Spmk, CpTk, Cpc, CNp, CNpk, CNpm, CNpmk, CNpmc, CNpmkc, and Vannman's Cp(u,v) family. Computes initial maximum likelihood estimates under Hybrid Type-II censoring, parameter MCMC chains, GPCI posterior chains, posterior point estimates, bias, mean squared error (MSE), Bayes risk, Highest Posterior Density (HPD) credible intervals at 90%, 95%, and 99% levels, Heidelberger and Welch's MCMC convergence diagnostics, and convergence probabilities. Accommodates user-defined probability density/mass functions, cumulative distribution functions, and survival functions. Goodness-of-fit testing for Hybrid Type-II censored data is supported via 'gofPHCS'. Methods are based on Childs et al. ( [...truncated...]
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: coda, stats, graphics
Suggests: gofPHCS, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-16 17:34:19 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre]
Repository: CRAN
Date/Publication: 2026-08-21 13:00:26 UTC

More information about gpcihybridIIImpSam at CRAN
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New package gpcihybridIIEM with initial version 0.1.0
Package: gpcihybridIIEM
Title: Generalized Process Capability Indices via EM for Hybrid Type-II Data
Version: 0.1.0
Description: Implements the Expectation-Maximization (EM) algorithm of Dempster, Laird, and Rubin (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> for parameter estimation under Hybrid Type-II censored data (Childs et al. (2003) <doi:10.1007/BF02517803>; Balakrishnan and Kundu (2013) <doi:10.1002/nav.21545>) using the 'UniCensorEM' package and computes Generalized Process Capability Indices (GPCIs). Supports classical and generalized capability indices including Cpy (Maiti et al. (2010) <doi:10.1080/16843703.2010.11673233>), Cp, Cpk, Cpu, Cpl, Cpm, Cpmk, Spmk (Dey and Saha (2019) <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al. (2018) <doi:10.1080/21681015.2018.1437793>), Cpc, CNpmc (Alotaibi et al. (2022) <doi:10.1155/2022/3135264>), CNpmkc (Saha et al. (2024) <doi:10.1142/S021853932450013X>), and CNpk (Saha et al. (2022) <doi:10.1080/02664763.2021.1971632>). Computes point estimates, bias, mean squared error, risk, Heidelberger and Welch co [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, UniCensorEM, gofPHCS
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-17 00:13:14 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:00:31 UTC

More information about gpcihybridIIEM at CRAN
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New package gpcihybridII with initial version 0.1.0
Package: gpcihybridII
Title: Generalized Process Capability Indices under Hybrid Type-II Censoring
Version: 0.1.0
Description: A comprehensive, generalized framework for computing, estimating, and validating Generalized Process Capability Indices (GPCIs) under Hybrid Type-II censored lifetime data. Supports user-supplied probability density or mass functions (PDF/PMF), cumulative distribution functions (CDF), survival functions (SF), and quantile functions. Parameter estimation under Hybrid Type-II censoring is performed via Maximum Likelihood Estimation using the 'MleCensoR' package (Childs et al., 2003 <doi:10.1007/BF02517803>; Balakrishnan & Kundu, 2013 <doi:10.1002/nav.21545>). Computes classical and non-normal capability indices, including Cpy (Maiti et al., 2010 <doi:10.1080/16843703.2010.11673233>), Spmk (Dey & Saha, 2019 <doi:10.1007/s41872-019-00081-4>), CpTk (Saha et al., 2019), Cpc (Saha et al., 2022 <doi:10.1080/02664763.2021.1971632>), CNpmc (Alotaibi et al., 2022 <doi:10.1155/2022/3135264>), CNpmkc (Saha et al., 2024 <doi:10.1142/S021853932450013X> [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, numDeriv, MleCensoR, gofPHCS
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-15 03:05:30 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Sumit Kumar [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 13:00:36 UTC

More information about gpcihybridII at CRAN
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New package AugBalWeight with initial version 0.1.0
Package: AugBalWeight
Title: Augmented Balancing Weights as Linear Regression
Version: 0.1.0
Description: Implements augmented balancing weights for causal inference and linear functional estimation based on David Bruns-Smith, Oliver Dukes, Avi Feller, and Elizabeth L. Ogburn (2026) <doi:10.1093/jrsssb/qkaf019>. Establishes numerical equivalence between augmented balancing weight estimators and single linear models with weighted regression coefficients. Provides flexible routines for double ridge (l2 balancing), double lasso (l-infinity balancing), and generalized augmented linear outcome models. Features cross-validation procedures for tuning outcome penalty parameters, covariate balance, and Riesz loss. Supports robust influence-function-based standard errors, bootstrap confidence intervals, balance diagnostic tools, and counterfactual prediction for treatment effects such as average treatment effect (ATE) and average treatment effect on the treated (ATT), expanding upon the doubly robust estimation framework established by Robins, Rotnitzky, and Zhao (1994) <doi:10.1080/0162145 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-07 23:02:57 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-21 12:41:17 UTC

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Thu, 20 Aug 2026

New package ivdtools with initial version 0.1.2
Package: ivdtools
Title: Statistical Tools for Evaluation of in Vitro Diagnostic Reagents
Version: 0.1.2
Description: Provides statistical workflows used in the evaluation of in vitro diagnostic reagents. Facilities include method comparison and Bland-Altman analysis, receiver operating characteristic analysis, qualitative agreement, precision and variance-component analysis, reference intervals, stability studies, quality-control charts, curve fitting, analytical sensitivity, outlier and normality assessment, and sample-size calculations. For methodological details, see Bland and Altman (1986) <doi:10.1016/S0140-6736(86)90837-8>, Passing and Bablok (1983) <doi:10.1515/cclm.1983.21.11.709>, Linnet (1993) <doi:10.1093/clinchem/39.3.424>, Hanley and McNeil (1982) <doi:10.1148/radiology.143.1.7063747>, Horn et al. (1998) <doi:10.1093/clinchem/44.3.622>, Westgard et al. (1981) <doi:10.1093/clinchem/27.3.493>, and Lu et al. (2016) <doi:10.1515/ijb-2015-0039>.
License: MIT + file LICENSE
URL: https://github.com/hiox-tech/ivdtools
BugReports: https://github.com/hiox-tech/ivdtools/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2, ggrepel, minpack.lm, nloptr, nls2, nortest, rlang, stats, utils, VCA, VFP
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-19 14:34:51 UTC; zhangkai
Author: hiox-tech [cph, aut, cre]
Maintainer: hiox-tech <GeorgeBinDragon@outlook.com>
Repository: CRAN
Date/Publication: 2026-08-20 17:00:02 UTC

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New package dgraphs with initial version 0.1.0
Package: dgraphs
Title: Data-Derived Graph Construction Utilities
Version: 0.1.0
Description: Constructs data-derived graphs from numerical observations using mutual, shared-neighbor, intersection, geodesic, radius, adaptive-radius, and minimum-spanning-tree completion methods. Provides graph conversion, pruning, diagnostics, spectral embedding, endpoint detection, and path utilities. The implemented graph constructions include methods described by Jarvis and Patrick (1973) <doi:10.1109/T-C.1973.223640>, Brito et al. (1997) <doi:10.1016/S0167-7152(96)00213-1>, Berry and Sauer (2019) <doi:10.3934/fods.2019001>, and Gower and Ross (1969) <doi:10.2307/2346439>.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://github.com/pgajer/dgraphs
BugReports: https://github.com/pgajer/dgraphs/issues
Encoding: UTF-8
Language: en-US
SystemRequirements: C++17
Depends: R (>= 4.1.0)
Imports: FNN, igraph (>= 2.2.0), parallel
LinkingTo: Rcpp, RcppEigen
Suggests: Matrix, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-08-06 07:57:36 UTC; pgajer
Author: Peter Gajer [aut, cre], Sunil Arya [ctb] , David M. Mount [ctb] , University of Maryland [cph] , Yixuan Qiu [ctb, cph] , Anna Araslanova [ctb, cph] , Gael Guennebaud [ctb, cph] , Jitse Niesen [ctb, cph] , Netherlands eScience Center [ctb, cph]
Maintainer: Peter Gajer <pgajer@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 17:00:11 UTC

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New package underdisp with initial version 0.1.0
Package: underdisp
Title: Diagnostics and Models for Underdispersed Count Data
Version: 0.1.0
Description: Tools for detecting and modeling underdispersion in count data (conditional variance below the conditional mean), a phenomenon overlooked by the Poisson and negative binomial defaults. Provides a screening diagnostic that benchmarks at-risk dispersion against a zero-truncated Poisson; the continuous parameter binomial (CPB) regression and its zero-truncated variant, with an interpretable observation-specific bound and high-dimensional fixed-effects support; validated bootstrap (for coefficients) and profile-likelihood (for the dispersion parameter) inference; and quantities of interest including predicted probabilities and the implied ceiling. The likelihood is implemented in C++ for speed.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0)
Imports: Rcpp, stats, MASS, VGAM, graphics, methods, numDeriv
LinkingTo: Rcpp
Suggests: sandwich, pscl, DHARMa, testthat (>= 3.0.0), knitr, rmarkdown, broom, modelsummary, texreg
VignetteBuilder: knitr
URL: https://github.com/bagozzib/underdisp
BugReports: https://github.com/bagozzib/underdisp/issues
NeedsCompilation: yes
Packaged: 2026-08-19 12:44:18 UTC; bagoz
Author: Benjamin E. Bagozzi [aut, cre]
Maintainer: Benjamin E. Bagozzi <bagozzib@udel.edu>
Repository: CRAN
Date/Publication: 2026-08-20 16:40:02 UTC

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New package scanr with initial version 0.1.0
Package: scanr
Title: Sequential Change-Point Detection via Nonparametric Inference
Version: 0.1.0
Description: Detects change points in long univariate time series using the SCAN framework. The implementation uses a native Rust backend exposed to R via 'extendr'.
License: GPL-3
Language: en-US
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc, Quarto CLI
Imports: ggplot2, jsonlite, rlang
Suggests: knitr, quarto, testthat (>= 3.0.0)
VignetteBuilder: quarto
URL: https://github.com/Prabashoka/scanr, https://prabashoka.github.io/scanr-vignette/
BugReports: https://github.com/Prabashoka/scanr/issues
NeedsCompilation: yes
Packaged: 2026-08-19 14:18:45 UTC; aseelappumud
Author: Ashoka Prabashwara [aut, cre], Patricia Menendez [aut], Liam Hodgkinson [aut], Stuart Lee [aut]
Maintainer: Ashoka Prabashwara <smashoka123@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 16:50:02 UTC

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New package weatherMRJD with initial version 0.1.1
Package: weatherMRJD
Title: Weather Analysis and Markov Regime Switching Jump Diffusion Models
Version: 0.1.1
Description: Provides statistical tools for analyzing weather patterns, temperature anomalies, and climate risk. Implements Markov regime-switching jump diffusion (MRJD) models to capture abrupt shifts, extreme weather events, and structural breaks in environmental time series data. Estimates model parameters using maximum likelihood estimation and offers utility functions for simulating regime-dependent stochastic processes. The regime-switching methodology is based on Hamilton (1989) "Analysis of Time Series Subject to Changes in Regime" <doi:10.2307/1912559>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-19 16:35:46 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-20 15:20:02 UTC

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New package robustrcp with initial version 0.1.0
Package: robustrcp
Title: Outlier-Robust Ratio-cum-Product Estimators of Finite Population Mean
Version: 0.1.0
Description: Implements robust ratio-cum-product estimators using auxiliary medians for estimating the population mean under simple random sampling without replacement (SRSWOR). Provides analytical optimal tuning parameters, bias, Mean Squared Error (MSE), and Percent Relative Efficiency (PRE) evaluations.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats
Depends: R (>= 3.5)
NeedsCompilation: no
Packaged: 2026-08-06 20:15:01 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-20 15:30:02 UTC

More information about robustrcp at CRAN
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New package MLMES with initial version 0.1.2
Package: MLMES
Title: Model-Based Effect Sizes for Multilevel Models
Version: 0.1.2
Description: Computes model-based effect sizes for fixed-effect coefficients in multilevel (hierarchical) models. The coefficient effect sizes are standardized mean differences from zero (d) and unique variance-explained measures (squared semi-partial correlations, sr2). The package also reports variance components and level-specific and total R-squared values. It supports 2-level and 3-level linear and binary logistic models fitted with 'lme4' (Bates et al., 2015) <doi:10.18637/jss.v067.i01>, and 2-level Gaussian and Bernoulli models fitted with 'brms' (Bürkner, 2017) <doi:10.18637/jss.v080.i01>. Sanders, Konold, and Cheng (in press), "Model-based effect sizes for multilevel linear regression coefficients," Methodology: European Journal of Research Methods for the Behavioral and Social Sciences, describe the 2-level linear-model methods.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: lme4 (>= 1.1.34), Matrix (>= 1.6-5), dplyr, stats
Suggests: brms, bayestestR, lmerTest (>= 3.1-0), testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-06 14:14:22 UTC; zigzag
Author: Yijun Cheng [aut, cre], Elizabeth A. Sanders [aut], Timothy R. Konold [aut], Zhigang Zhang [aut], Zixie Zheng [aut]
Maintainer: Yijun Cheng <chengxb@uw.edu>
Repository: CRAN
Date/Publication: 2026-08-20 15:52:04 UTC

More information about MLMES at CRAN
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New package caverify with initial version 0.1.2
Package: caverify
Title: Fast Strength-t Coverage Verification for Covering Arrays
Version: 0.1.2
Description: Verifies that an array covers every t-way interaction, the certificate check for covering arrays, using compiled C code with optional 'OpenMP' threading. Missing values are treated as wildcard ("flexible") entries that count as every symbol. Designed to be easy to embed in other packages: a single C file with a registered .Call entry point and one R wrapper.
License: MIT + file LICENSE
URL: https://github.com/chrispbsmolen/ca-tools
BugReports: https://github.com/chrispbsmolen/ca-tools/issues
Encoding: UTF-8
Language: en-US
Imports: parallel
NeedsCompilation: yes
Packaged: 2026-08-19 16:02:20 UTC; root
Author: Christopher Smolen [aut, cre]
Maintainer: Christopher Smolen <chrispbsmolen@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 15:02:05 UTC

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New package themescopeR with initial version 0.1.1
Package: themescopeR
Title: Social Representation Analysis via Semantic Network Mapping
Version: 0.1.1
Description: Implements the ThemeScope framework for detecting and visualising social representations in large-scale digital text corpora. From raw documents it builds, via 'udpipe' annotation, sentence-level word co-occurrence networks and derives two community-level indicators grounded in Social Representation Theory: the Prototypical Salience Index (PSI) for anchoring and the Concreteness Score (CS) for objectification. Communities are located in a two-dimensional, theoretically grounded representational map. The whole pipeline is usable from the R console; an optional 'shiny' graphical interface calls the same exported functions. The method is described in Misuraca, Spano and D'Aniello (2026) <doi:10.1177/01655515261454276>.
License: MIT + file LICENSE
URL: https://github.com/lucadaniello/themescopeR
BugReports: https://github.com/lucadaniello/themescopeR/issues
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 4.1.0)
Imports: cli (>= 3.6.0), dplyr (>= 1.1.0), ggplot2 (>= 3.4.0), ggrepel (>= 0.9.0), igraph (>= 2.1.0), Matrix (>= 1.6.0), methods, readr, readxl, rlang, stats, tools, udpipe (>= 0.8.11), utils
Suggests: bslib, DT, ggraph (>= 2.1.0), htmltools, knitr, plotly, rmarkdown, shiny, shinycssloaders, testthat (>= 3.0.0), visNetwork, writexl
NeedsCompilation: no
Packaged: 2026-08-19 10:10:22 UTC; lucadaniello
Author: Luca D'Aniello [aut, cre] , Michelangelo Misuraca [aut] , Maria Spano [aut]
Maintainer: Luca D'Aniello <luca.daniello@unina.it>
Repository: CRAN
Date/Publication: 2026-08-20 14:10:02 UTC

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New package scmix with initial version 0.1.1
Package: scmix
Title: Bayesian Model-Based Clustering with Sparse Conditional Mixture Models
Version: 0.1.1
Description: Fits Bayesian sparse conditional (Gaussian) mixture models for model-based clustering. Each mixture component factorizes into a chain of univariate polynomial regressions with per-component, per-equation Bayesian variable selection under a centered Zellner g-prior; the number of clusters is selected within a single run via an overfitted sparse mixture (Dirichlet concentration 1/K). The blocked Gibbs sampler draws the selection sets exactly by enumeration (or by validated single-flip Metropolis-Hastings in higher dimension), is provably well-posed under a documented proper fallback prior, and reports a label-invariant consensus partition (Dahl's least-squares criterion). Companion package to Dong, Liao, and Lee (2026), "Replacing three nested searches with one sweep: a Bayesian treatment of sparse conditional mixture clustering". Multiple-imputation functionality for the same engine is also exposed.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: graphics, stats
Suggests: knitr, mclust, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-15 17:13:34 UTC; july
Author: Aqi Dong [aut, cre], Yang-Li Liao [aut], Danhyang Lee [aut]
Maintainer: Aqi Dong <donga2@erau.edu>
Repository: CRAN
Date/Publication: 2026-08-20 14:30:02 UTC

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New package RtForecastR with initial version 0.1.0
Package: RtForecastR
Title: Real-Time Effective Reproduction Number Estimation and Forecasting
Version: 0.1.0
Description: Filtered (real-time/causal) and smoothed (retrospective) estimation of the time-varying effective reproduction number (Rt) from case-count time series, using the EpiFilter algorithm of Parag (2021) <doi:10.1371/journal.pcbi.1009347>, together with a one-step-ahead in-sample prediction check, a genuine out-of-sample one-step forecast with predictive intervals, elimination probability P(Rt < 1), and forecast calibration metrics (mean absolute error, mean squared error, root mean squared error, empirical coverage, and the weighted interval score of Bracher et al. (2021) <doi:10.1371/journal.pcbi.1008618>). Disease-agnostic: works for any pathogen given a known generation interval.
Language: en-US
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: graphics, grDevices, stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/rajsubediresearch/RtForecastR
BugReports: https://github.com/rajsubediresearch/RtForecastR/issues
NeedsCompilation: no
Packaged: 2026-08-19 12:33:48 UTC; razsu
Author: Raj Subedi [aut, cre, cph] ; author of R/recursPredict.R's configurable-grid maxI extension and R/recursPredictQuantiles.R), Kris V. Parag [ctb, cph] ; files R/epiFilter.R, R/epiSmoother.R and R/recursPredict.R are unmodified or lightly modified port [...truncated...]
Maintainer: Raj Subedi <rajsubediresearch@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 14:12:38 UTC

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New package ofemeantest with initial version 1.0.0
Package: ofemeantest
Title: On Farm Experimentation Mean Test
Version: 1.0.0
Description: Provides tools for comparing treatments in unreplicated on-farm experiments (OFE) using georeferenced data. The package includes functions for constructing spatial grids, estimating the effective sample size from spatial autocorrelation, performing repeated permutation tests, adjusting pairwise comparisons, and visualizing the results. It implements the OFE-mean test described in Córdoba, Paccioretti and Balzarini (2025) <doi:10.1007/s11119-024-10206-0>.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: multcompView, permuco, sf, spatialreg, spdep, withr
Suggests: ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 4.1.0)
VignetteBuilder: knitr
URL: https://ppaccioretti.github.io/ofemeantest/, https://github.com/PPaccioretti/ofemeantest
BugReports: https://github.com/PPaccioretti/ofemeantest/issues
NeedsCompilation: no
Packaged: 2026-08-19 12:43:09 UTC; ariel
Author: Mariano Cordoba [aut, cph], Pablo Paccioretti [aut, cre, cph], Monica Balzarini [aut]
Maintainer: Pablo Paccioretti <pablopaccioretti@agro.unc.edu.ar>
Repository: CRAN
Date/Publication: 2026-08-20 14:20:14 UTC

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New package nwaa with initial version 0.1.4
Package: nwaa
Title: USGS NWAA Data Download
Version: 0.1.4
Description: Download and parse model outputs from the U.S. Geological Survey (USGS) National Water Availability Assessment (NWAA) Data Companion web services. Provides typed, validated wrappers for the published NWAA models across the Water Use, Water Quantity, and Integrated Water Availability families, returning results at HUC12 spatial resolution.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: httr2, jsonlite, readr, rlang, tibble
Suggests: httptest2, knitr, pkgdown, rmarkdown, sf, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://laljeet.github.io/nwaa/, https://github.com/laljeet/nwaa
BugReports: https://github.com/laljeet/nwaa/issues
NeedsCompilation: no
Packaged: 2026-08-19 16:10:13 UTC; laljeetsangha
Author: Laljeet Sangha [aut, cre]
Maintainer: Laljeet Sangha <lsanghah2o@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 14:40:02 UTC

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New package mditools with initial version 0.1.0
Package: mditools
Title: Microdata Infrastructure Tools for Firm-Level Microdata Research
Version: 0.1.0
License: GPL-3
URL: https://github.com/Secretariat-CompNet/mditools
BugReports: https://github.com/Secretariat-CompNet/mditools/issues
Description: Supports the full analysis pipeline for researchers working with firm-level microdata. Provides data tools for panel preparation (import, outlier detection, classification harmonization), analytical methods (production function estimation, capital stock measurement, markups, intensity measures, distributions, regression, clustering), and disclosure tools for tagging outputs with dominance and observation counts before aggregation and publication. Production function estimation implements methods by Ackerberg, Caves and Frazer (2015) <doi:10.3982/ECTA13408>, Levinsohn and Petrin (2003) <doi:10.1111/1467-937X.00246>, Wooldridge (2009) <doi:10.1016/j.econlet.2009.04.026>, Petrin, Poi and Levinsohn (2004) <doi:10.1177/1536867X0400400202>, and Arellano and Bond (1991) <doi:10.2307/2297968> with the "too many instruments" correction by Roodman (2009) <doi:10.1111/j.1468-0084.2008.00542.x>. Markup estimation follows De Loecker and Warzynski (2012) <doi:1 [...truncated...]
Encoding: UTF-8
Imports: data.table, fixest, haven, readxl, Matrix, cluster, dbscan, mclust, stats, utils, graphics, grDevices
Suggests: testthat (>= 3.0.0), arrow
NeedsCompilation: no
Packaged: 2026-08-19 16:23:58 UTC; johanna
Author: Daniele Aglio [aut], Eric Bartelsman [aut], Mirja Haelbig [aut], Marco Miorandi [aut], Johanna Weiss [aut, cre], Alessandro Zona Mattioli [aut], Julian Diaz-Acosta [ctb], Alberto Ferreira [ctb], Javier Miranda [ctb], Marcelo Piemonte Ribeiro [ctb], Re [...truncated...]
Maintainer: Johanna Weiss <johanna.weiss@iwhesl.onmicrosoft.com>
Repository: CRAN
Date/Publication: 2026-08-20 14:50:02 UTC

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New package lineager with initial version 0.1.1
Package: lineager
Title: Row-Level Data Provenance and Exclusion Tracking
Version: 0.1.1
Description: Provides row-level data provenance tracking for analytical pipelines. Tags datasets with unique lineage identifiers that persist through filter, join, and derive operations. Requires documented reasons for every row exclusion, capturing who was removed, why, and at which pipeline stage. Variable derivations are registered as structured specifications linking output variables back to their source. Any row in any downstream dataset can be traced back to its origin via lg_trace(). Generates structured HTML provenance reports suitable for regulatory submissions, internal audit, or analytical documentation. General-purpose: works for clinical data, machine learning pipelines, financial modelling, epidemiology, or any workflow where row-level accountability matters. Optional features support pharmaceutical users including population flag definitions, source-to-analysis variable mapping, and Reviewer's Guide-aligned report output. Complements the 'regulog' package for tamper-evident session-l [...truncated...]
License: MIT + file LICENSE
URL: https://reprostats.org, https://github.com/repro-stats/lineager
BugReports: https://github.com/repro-stats/lineager/issues
Imports: dplyr (>= 1.1.0), magrittr (>= 2.0.3)
Suggests: admiral, DiagrammeR, ggplot2, haven, knitr, mockery, rmarkdown, testthat (>= 3.0.0), tibble
Encoding: UTF-8
Language: en-GB
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-19 12:35:38 UTC; ndohpenn
Author: Ndoh Penn [aut, cre]
Maintainer: Ndoh Penn <ndohpenn9@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 14:20:20 UTC

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New package kpp2019 with initial version 0.0.1
Package: kpp2019
Title: Kenya Population Projections 2019
Version: 0.0.1
Description: Provides population projection data for Kenya and its 47 counties from 2020 to 2045, derived from the 2019 Kenya Population and Housing Census and subsequent projections published by the Kenya National Bureau of Statistics (KNBS). Includes annual and five-year age and sex distributions, along with components of population change such as births, deaths, and migration.
License: CC BY 4.0
URL: https://kpp2019.damurka.com, https://github.com/damurka/kpp2019
BugReports: https://github.com/damurka/kpp2019/issues
Suggests: dplyr, ggplot2, knitr, purrr, readxl, rmarkdown, spelling, stringr, tidyr, testthat (>= 3.0.0)
Depends: R (>= 2.10)
Encoding: UTF-8
Language: en-GB
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-19 12:07:26 UTC; Murage
Author: David Kariuki [aut, cre, cph]
Maintainer: David Kariuki <hello@damurka.com>
Repository: CRAN
Date/Publication: 2026-08-20 14:10:09 UTC

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New package hydrogeofetch with initial version 2.0.0
Package: hydrogeofetch
Title: Hydrologic Geospatial Fabric Extraction Tool Chain
Version: 2.0.0
Description: Traverses and works with National Hydrography Dataset Plus (NHDPlus) data. All methods implemented in 'hydrogeofetch' are available in the NHDPlus documentation available from the US Environmental Protection Agency <https://www.epa.gov/waterdata/basic-information>. Previously published as 'nhdplusTools'.
URL: https://doi-usgs.github.io/nhdplusTools/ https://github.com/doi-usgs/nhdplusTools/
BugReports: https://github.com/doi-usgs/nhdplusTools/issues/
Depends: R (>= 4.1)
Imports: hydroloom, dataRetrieval, dplyr, sf, units, jsonlite, httr2, xml2, utils, data.table, methods, arrow, tools, zip, memoise, digest
Suggests: testthat, knitr, rmarkdown, ggmap, ggplot2, lwgeom, gifski, leaflet, httptest2, StreamCatTools, terra, maptiles, mapsf
License: CC0
Encoding: UTF-8
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-17 13:07:00 UTC; root
Author: David Blodgett [aut, cre] , Mike Johnson [ctb] , Marc Weber [ctb] , Josh Erickson [ctb], Lauren Koenig [ctb]
Maintainer: David Blodgett <dblodgett@usgs.gov>
Repository: CRAN
Date/Publication: 2026-08-20 14:40:08 UTC

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New package grout with initial version 0.1.0
Package: grout
Title: Abstract Raster Tiling Schemes
Version: 0.1.0
Description: Impose a tiling scheme on a raster grid defined by its dimension and extent. Computes tile counts, pixel offsets (suitable for spatial library windowed reads), and geographic extents for each tile. Also supports standard Web Mercator and geodetic tiling profiles with zoom levels, and provides a spatial map of what each chunk covers for interrogating virtual raster stores. Based on the analysis of Lamb (1994, ISBN-13: 978-0748403158) "Tiling very large rasters" in 'Advances in GIS Research: Proceedings of the Sixth International Symposium on Spatial Data Handling', volume 1, pages 449-461.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: graphics, tibble, utils, vaster (>= 0.6.0)
Suggests: testthat (>= 3.0.0), wk
URL: https://github.com/hypertidy/grout
BugReports: https://github.com/hypertidy/grout/issues
NeedsCompilation: no
Packaged: 2026-08-19 12:57:18 UTC; mdsumner
Author: Michael D. Sumner [aut, cre, cph]
Maintainer: Michael D. Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-20 14:30:13 UTC

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New package alepe with initial version 0.1.0
Package: alepe
Title: Access the Open Data API of the Legislative Assembly of Pernambuco
Version: 0.1.0
Description: A tidy interface to the open data API of the Legislative Assembly of the State of Pernambuco, Brazil ('ALEPE', <https://dadosabertos.alepe.pe.gov.br>). Retrieve data on representatives, staff, positions, departments, remuneration, contracts, procurement processes, and legislative propositions as tibbles with clean names and parsed column types. Requests are cached locally and retried with exponential backoff; network failures are handled gracefully.
License: MIT + file LICENSE
URL: https://github.com/StrategicProjects/alepe, https://strategicprojects.github.io/alepe/
BugReports: https://github.com/StrategicProjects/alepe/issues
Depends: R (>= 4.1)
Imports: cli, httr2 (>= 1.0.0), readr, rlang (>= 1.1.0), tibble
Suggests: dplyr, ggplot2, httptest2, jsonlite, knitr, rmarkdown, testthat (>= 3.0.0), tidyr, withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-19 12:53:57 UTC; leite
Author: Andre Leite [aut, cre] , Marcos Wasiliew [aut], Hugo Vasconcelos [aut] , Carlos Amorim [aut] , Diogo Bezerra [aut] , Julia Nascimento Barreto [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-08-20 14:22:29 UTC

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Sun, 09 Aug 2026

New package ratingtables with initial version 0.2.0
Package: ratingtables
Title: Table-Driven Insurance Rating
Version: 0.2.0
Description: Provides a lightweight, table-driven engine for executing insurance rating plans, including coverage-specific rating specifications, entity aggregation, and trace output for auditing. Given policy data, an ordered rating specification, and rating factor tables, it returns rated policies and, optionally, a step-by-step trace of the calculation.
License: MIT + file LICENSE
URL: https://github.com/gs-actuary/ratingtables
BugReports: https://github.com/gs-actuary/ratingtables/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-04 22:03:58 UTC; yagre
Author: Greg Sollenberger [aut, cre, cph]
Maintainer: Greg Sollenberger <yagreg7@yahoo.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:40:02 UTC

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New package rapsimng.decide.core with initial version 0.1.0
Package: rapsimng.decide.core
Title: Decision-Oriented Analysis Core for APSIM Next Generation Outputs
Version: 0.1.0
Description: Provides a low-level interface for analysing APSIM Next Generation simulation outputs to support structured decision-making workflows.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0)
URL: https://core.decide.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.decide.core
BugReports: https://github.com/byzheng/rapsimng.decide.core/issues
NeedsCompilation: no
Packaged: 2026-08-05 01:16:10 UTC; zhe00a
Author: Bangou Zheng [aut, cre]
Maintainer: Bangou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:40:08 UTC

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New package ProgVine with initial version 0.1.0
Package: ProgVine
Title: Progressive Regularized Vine Copula for Masked Competing Risks
Version: 0.1.0
Description: Implements Progressive Regularized Vine Copula (Prog-Vine) frameworks for high-dimensional dependent competing risks with masked failure causes under Progressive Type-II Censoring. Fits Weibull marginals, estimates pair-copula trees using Expectation-Maximization (EM) algorithms, computes Louis observed information confidence intervals, and implements Data Augmentation Gibbs Samplers for Bayesian credible intervals.
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: no
Packaged: 2026-08-05 06:57:36 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:10 UTC

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New package PINNProgCens with initial version 0.1.0
Package: PINNProgCens
Title: Physics-Informed Neural Networks for Progressive Censoring
Version: 0.1.0
Description: Implementation of Physics-Informed Neural Networks ('PINN') for lifetime estimation under progressive Type-II censoring schemes. Combines parametric baseline hazards with physical differential degradation models.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: deSolve, stats
NeedsCompilation: no
Packaged: 2026-08-05 07:02:56 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:15 UTC

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New package phontrast with initial version 2.3.1
Package: phontrast
Title: Contrast and Separation Metrics for Phonological Categories
Version: 2.3.1
Author: Grant M. Berry [aut, cre]
Maintainer: Grant M. Berry <berry.grant@gmail.com>
Description: Computes and compares multiple measures of separation and overlap between phonological categories (for example vowels or consonants) in arbitrary multi-dimensional acoustic spaces such as formant values, mel-frequency cepstral coefficients (MFCCs), duration, or learned embeddings. The main entry point, phontrast(), reports several contrast metrics in one call -- Jensen-Shannon divergence and distance (Lin, 1991) <doi:10.1109/18.61115>, the Pillai-Bartlett trace, Bhattacharyya distance and affinity, Mahalanobis distance, and proportional overlap -- globally or by group on a common separation-oriented scale, with bootstrap confidence intervals. Also provides utilities for preparing estimates for downstream modelling such as generalized additive models and mixed-effects models. Formerly released as 'phonJSD'.
License: MIT + file LICENSE
URL: https://github.com/berrygrant/phontrast
BugReports: https://github.com/berrygrant/phontrast/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ks, dplyr, purrr, tibble, rlang, stats, grDevices, utils
Suggests: ggplot2, mgcv, mvtnorm, tuneR, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 21:26:44 UTC; grantberry
Repository: CRAN
Date/Publication: 2026-08-09 08:30:02 UTC

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New package palettecore with initial version 0.4.1
Package: palettecore
Title: Derive, Optimise and Audit a Scientific Colour Palette from One Seed Colour
Version: 0.4.1
Description: Generates sequential, diverging and categorical colour palettes from a single seed colour in OKLCH (the cylindrical lightness-chroma-hue representation of the Oklab perceptual colour space), with spacing measured by the CIEDE2000 colour-difference formula of the International Commission on Illumination. Audits every palette under simulated colour-vision deficiency, greyscale conversion, the standard Red Green Blue (sRGB) gamut and Web Content Accessibility Guidelines (WCAG) contrast. Colour-vision deficiency is simulated at severity 1.0 with the model of Machado, Oliveira and Fernandes (2009) <doi:10.1109/TVCG.2009.113>; the design rationale follows Crameri, Shephard and Heron (2020) <doi:10.1038/s41467-020-19160-7>. Mirrors the 'Python' reference implementation maintained in the same repository and is validated against shared parity fixtures. Thresholds are configurable design rules, not established accessibility cut-offs.
License: Apache License (>= 2)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: stats, utils
Suggests: ggplot2, jsonlite
URL: https://github.com/heidihelena/palettecore
BugReports: https://github.com/heidihelena/palettecore/issues
NeedsCompilation: no
Packaged: 2026-08-03 20:36:25 UTC; root
Author: Heidi Helena Andersen [aut, cre]
Maintainer: Heidi Helena Andersen <andersenheidihelena@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:02 UTC

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New package NeutroBasicDesignsAnalysis with initial version 0.0.1
Package: NeutroBasicDesignsAnalysis
Title: Neutrosophic Analysis of Completely Randomized Designs and Randomized Complete Block Designs
Version: 0.0.1
Maintainer: Vinaykumar L.N. <vinaymandya123@gmail.com>
Description: Provides neutrosophic statistical methods for interval-valued data from completely randomized and randomized complete block designs. Methods include neutrosophic analysis of variance, analysis of covariance, multivariate analysis of variance, pooled analysis of variance, Levene's test, and Aitken transformation. When the lower and upper bounds are equal (crisp data), the methods reduce to their corresponding classical statistical analyses. The basic concept of neutrosophic statistics is based on Smarandache (2014) <https://fs.unm.edu/NeutrosophicStatistics.pdf>, while the statistical analysis procedures implemented in this package are newly developed.
License: GPL (>= 3)
Encoding: UTF-8
Imports: MASS, stats
NeedsCompilation: no
Packaged: 2026-08-05 04:16:59 UTC; admin
Author: Neethu R.S. [aut, ctb], Boyina Devi Priyanka [aut, ctb], Cini Varghese [aut, ctb], Susheel Kumar Sarkar [aut, ctb], Mohd Harun [aut, ctb], Vinaykumar L.N. [aut, cre], Anindita Datta [aut, ctb]
Repository: CRAN
Date/Publication: 2026-08-09 08:40:13 UTC

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New package ModToppLeone with initial version 0.1.0
Package: ModToppLeone
Title: Modified Topp-Leone Distribution: Properties, Estimation, and Applications
Version: 0.1.0
Description: Provides density, cumulative distribution function, quantile function, random number generation, survival function, hazard rate function, statistical properties, classical point and interval estimation (maximum likelihood, ordinary least squares, weighted least squares, Cramer-von Mises, and maximum product of spacings), Bayesian estimation under symmetric and asymmetric loss functions (squared error, entropy, precautionary, and generalized entropy loss functions) with highest posterior density intervals, censoring schemes (random, Type-I, Type-II, and progressive Type-II censoring), and real data applications for the 'Modified Topp-Leone' distribution. Methods are based on Singh et al. (2025) <https://statassoc.or.th>, Cheng and Amin (1983) <doi:10.1111/j.2517-6161.1983.tb01267.x>, Swain et al. (1988) <doi:10.1080/00949658808811094>, Chen and Shao (1999) <doi:10.1080/10618600.1999.10474802>, and Balakrishnan and Aggarwala (2000) <doi:10.1007/978-1-4612-1178- [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5.0)
Imports: stats, graphics
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-05 02:51:05 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Abhishek Tyagi [aut], Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:40:18 UTC

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New package MiCT with initial version 2.0.0
Package: MiCT
Title: Minimal Important Change and Threshold Estimation
Version: 2.0.0
Description: Provides methods for estimating minimal important change (MIC) and interpretation thresholds for multi-item questionnaires and single-item continuous or ordinal measures. Methods include predictive modelling, adjusted predictive modelling, improved adjusted predictive modelling using anchor reliability, confirmatory factor analysis for anchor reliability, longitudinal confirmatory factor analysis for MIC estimation, longitudinal confirmatory factor analysis-based MIC estimation for single-item measures, and confirmatory factor analysis-based threshold estimation for single-item and multi-item measures. Implemented methods include those developed by Terluin et al. (2015) <doi:10.1016/j.jclinepi.2015.03.015>, Terluin et al. (2017) <doi:10.1016/j.jclinepi.2016.12.015>, Terluin et al. (2022) <doi:10.1016/j.jclinepi.2022.04.018>, Terluin et al. (2023) <doi:10.1007/s11136-023-03355-8>, Terluin et al. (2024) <doi:10.1007/s11136-023-03577-w>, Terluin et al. (2024) [...truncated...]
Depends: R (>= 4.1.0)
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: lavaan, MASS, mirt, pROC
Suggests: testthat (>= 3.0.0)
URL: https://github.com/yhpua/MiCT, https://yhpua.github.io/MiCT/
BugReports: https://github.com/yhpua/MiCT/issues
NeedsCompilation: no
Packaged: 2026-08-04 22:25:38 UTC; PYH
Author: Iris Eekhout [aut] , Berend Terluin [aut], Yong-Hao Pua [aut, cre]
Maintainer: Yong-Hao Pua <gmspuyh@duke-nus.edu.sg>
Repository: CRAN
Date/Publication: 2026-08-09 08:30:08 UTC

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New package IntegMultiReg with initial version 0.1.0
Package: IntegMultiReg
Title: Integrative Bayesian Multiple Regression for Multi-Platform Biomarkers
Version: 0.1.0
Description: A Bayesian framework that integrates several regression models to identify a parsimonious set of biomarkers shared across disparate data platforms (for example genomic, transcriptomic and proteomic assays). Subjects are partitioned into subgroups defined by their pattern of platform availability, so that no subject with partially missing platform data is excluded, and information is borrowed across subgroups through a Markov random field prior on the variable-selection indicators together with non-local (product moment) priors on the regression effects. The methodology was introduced for time-to-event outcomes by Chekouo, Stingo, Doecke and Do (2017) <doi:10.1111/biom.12587>; this package additionally supports continuous (Gaussian) and binary (probit) outcomes. Posterior inference is carried out by a Markov chain Monte Carlo sampler implemented in C for computational efficiency.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: graphics, grDevices, stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
SystemRequirements: GSL (>= 2.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-05 01:44:33 UTC; tchekouo
Author: Sinian Zhang [aut], Jianfeng Wang [aut], Thierry Chekouo [aut, cre]
Maintainer: Thierry Chekouo <tchekouo@umn.edu>
Repository: CRAN
Date/Publication: 2026-08-09 08:20:07 UTC

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New package gofLorenz with initial version 0.1.0
Package: gofLorenz
Title: Goodness-of-Fit Tests for Location-Scale Distributions via Lorenz Curve
Version: 0.1.0
Description: Implements goodness-of-fit test statistics and graphical methods for symmetric and asymmetric location-scale distributions under progressive Type-II censoring using the modified Lorenz curve and ratio modified sample Lorenz curve, as proposed by Lee (2024) <doi:10.3390/sym16020202>. Also provides order statistics distance test statistics based on Pakyari and Balakrishnan (2013) <doi:10.1080/00949655.2011.625424>. Supports calculation of test statistics, Monte Carlo p-values, critical values, and L-plot visual diagnostics for complete and progressively Type-II censored data.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-05 02:30:42 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:20:02 UTC

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New package GLHD with initial version 1.1-1
Package: GLHD
Title: Grouped Latin Hypercube Designs with Controlled Correlations
Version: 1.1-1
Description: We provide a method of constructing grouped Latin hypercube designs by controlling correlations. Details of the algorithm can be found in Wenlong Li, Jian-Feng Yang and Peter Chien (2026). Grouped Latin hypercube designs with controlled correlations. Technometrics, published online. Important function in this package is "GLHD_CC".
License: LGPL (>= 3)
Imports: stats
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-05 06:47:10 UTC; wenlo
Author: Wenlong Li [aut, cre], Jian-Feng Yang [aut], Peter Chien [aut]
Maintainer: Wenlong Li <wlli1@bjtu.edu.cn>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:19 UTC

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New package exactGMH with initial version 0.1.0
Package: exactGMH
Title: Exact and Permutation-Based Mantel Tests for Differential Item Functioning in Dichotomous and Polytomous Items
Version: 0.1.0
Description: Screens dichotomous and polytomous test items for Differential Item Functioning (DIF) using an extension of the Mantel (1963) <doi:10.1080/01621459.1963.10500879> and generalized Mantel-Haenszel statistic, with statistical significance computed via permutation rather than the conventional asymptotic chi-square approximation. Following Hemerik and Goeman (2018) <doi:10.1007/s11749-017-0571-1>, the permutation p-value is exact at the nominal level rather than an approximation, even for a finite number of permutations. This makes the test valid for small samples (fewer than 200 examinees per group), a condition common in classroom-, program-, and institution-level assessment where existing exact-inference options in other software are restricted to dichotomous items only. An optional Benjamini-Hochberg or Bonferroni correction addresses multiple comparisons when screening many items at once.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: stats
Suggests: testthat (>= 3.0.0), shiny
URL: https://github.com/exactGMH-project/exactGMH
BugReports: https://github.com/exactGMH-project/exactGMH/issues
NeedsCompilation: no
Packaged: 2026-08-04 16:17:04 UTC; root
Author: Tri Zahra Ningsih [aut, cre], Aman [aut], Ahmad Nasrulloh [aut], Hera Hastuti [aut], Suci Kurnia Putri [aut]
Maintainer: Tri Zahra Ningsih <trizahra10019@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 08:10:06 UTC

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New package smartcor with initial version 1.0.1
Package: smartcor
Title: Automatic Correlation Method Selection Based on Variable Types
Version: 1.0.1
Description: Detects variable types (continuous, count, binary, ordinal, categorical) and selects the appropriate correlation method for each pair. Supports Pearson, Spearman, Kendall's tau, point-biserial, rank-biserial, phi, tetrachoric, polychoric, polyserial, Cramer's V, Tschuprow's T, Theil's U, Yule's Q, and Goodman-Kruskal's gamma, each with a confidence interval and p-value. Explains the selection rationale in the output, follows tidy data principles, and works in both interactive and scripted workflows. The methodology is described in Harshvardhan and Ranjan (2026) <doi:10.48550/arXiv.2607.22285>.
License: GPL (>= 3)
URL: https://harshvardhaniimi.github.io/smartcor/, https://github.com/harshvardhaniimi/smartcor
BugReports: https://github.com/harshvardhaniimi/smartcor/issues
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: cli (>= 3.0.0), generics, ggplot2 (>= 3.4.0), graphics, grDevices, mvtnorm, polycor, rlang (>= 1.0.0), stats, tibble, utils, withr
Suggests: knitr, MASS, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 17:52:25 UTC; harshvardhan
Author: M. Harshvardhan [aut, cre, cph], Pritam Ranjan [aut, cph]
Maintainer: M. Harshvardhan <harshvardhan@aus.edu>
Repository: CRAN
Date/Publication: 2026-08-09 07:30:02 UTC

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New package PLSsemEngine with initial version 1.3.0
Package: PLSsemEngine
Title: Transparent PLS-SEM Estimation for Composite-Based Reflective Models
Version: 1.3.0
Date: 2026-07-24
Description: A transparent and modular implementation of Partial Least Squares Structural Equation Modeling (PLS-SEM) focused on reflective measurement models (Mode A). The package separates estimation, bootstrap inference, and predictive evaluation into independent components, emphasising algorithmic transparency, reproducibility, and researcher-controlled analysis. Methods are based on Tenenhaus, Esposito Vinzi, Chatelin & Lauro (2005) <doi:10.1016/j.csda.2004.03.005>, Hair, Risher, Sarstedt & Ringle (2019) <doi:10.1108/EBR-11-2018-0203>, and Henseler, Ringle & Sarstedt (2015) <doi:10.1007/s11747-014-0403-8>.
License: MIT + file LICENSE
URL: https://github.com/msoto-perez/PLSsemEngine
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 15:20:07 UTC; msoto
Author: Manuel Soto-Perez [aut, cre]
Maintainer: Manuel Soto-Perez <msoto@up.edu.mx>
Repository: CRAN
Date/Publication: 2026-08-09 07:30:15 UTC

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New package metabodeconplus with initial version 0.22.0
Package: metabodeconplus
Title: Deconvolution, Alignment and Model Fitting of 1d NMR Spectra
Version: 0.22.0
Author: Tobias Schmidt [aut, cre, cph], Martina Haeckl [aut, cph], Yanren Linda Hu [ctb], Wolfram Gronwald [aut, cph]
Maintainer: Tobias Schmidt <tobias.schmidt331@gmail.com>
Description: An integrated framework for deconvolution, alignment and postprocessing of 1-dimensional (1d) nuclear magnetic resonance (NMR) spectra, extended with end-to-end model fitting that turns the resulting matrix of aligned signal integrals into classification models. The deconvolution part uses the algorithm described in Koh et al. (2009) <doi:10.1016/j.jmr.2009.09.003>. The alignment part is based on functions from the 'speaq' package, described in Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018> and Vu et al. (2011) <doi:10.1186/1471-2105-12-405>. A detailed description and evaluation of an early version of the package can be found in Haeckl et al. (2021) <doi:10.3390/metabo11070452>. 'metabodeconplus' is the actively developed successor to the 'metabodecon' package and introduces backwards-incompatible API changes.
License: GPL (>= 3)
URL: https://github.com/spang-lab/metabodeconplus/, https://spang-lab.github.io/metabodeconplus/
BugReports: https://github.com/spang-lab/metabodeconplus/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: mathjaxr, ranger, readJDX, toscutil (>= 2.8.0), withr
Suggests: BiocManager, cachem, covr, devtools, diffobj, digest, doParallel, e1071, glmnet, glue, impute, inline, knitr, lifecycle, MassSpecWavelet, mdrb, microbenchmark, multtest, pkgbuild, pkgload, pROC, R.devices, rcmdcheck, remotes, rlang, rmarkdown, rpart, speaq, styler, testthat (>= 3.0.0), usethis, V8, vdiffr, waldo
LazyData: true
LazyDataCompression: xz
BuildManual: TRUE
Language: en-US
Additional_repositories: https://spang-lab.r-universe.dev
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-04 18:43:02 UTC; tschmidt
Repository: CRAN
Date/Publication: 2026-08-09 07:30:08 UTC

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New package gp3bayes with initial version 0.1.1
Package: gp3bayes
Title: Contract-First Bayesian Workflows for Hierarchical Behavioural Data
Version: 0.1.1
Description: Provides transparent, contract-first infrastructure for Bayesian analysis of repeated-measures and hierarchical behavioural data. It supports approved Bernoulli-logit and positive lognormal duration workflows with readiness audits, deterministic simulation, explicit preparation, inspectable priors, prior and posterior predictive checks, restricted optional fitting through 'brms' and 'rstan', sampling diagnostics, prior sensitivity, parameter recovery, and conservative reporting. Core contracts and prior checks remain backend-independent.
License: MIT + file LICENSE
URL: https://stefanosbalaskas.github.io/gp3bayes/, https://github.com/stefanosbalaskas/gp3bayes
BugReports: https://github.com/stefanosbalaskas/gp3bayes/issues
Encoding: UTF-8
Imports: withr
Suggests: bayesplot, brms, knitr, posterior, rmarkdown, rstan, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 18:24:13 UTC; Stefanos-PC
Author: Stefanos Balaskas [aut, cre, cph]
Maintainer: Stefanos Balaskas <s.balaskas@ac.upatras.gr>
Repository: CRAN
Date/Publication: 2026-08-09 07:10:02 UTC

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New package FPScausal with initial version 0.1.0
Package: FPScausal
Title: Functional Propensity Score for Causal Inference
Version: 0.1.0
Description: Implements functional propensity score (FPS) weighting for causal inference with functional treatments. Weights are estimated by maximising the empirical likelihood subject to covariate-balancing constraints and solving the resulting dual problem via the BFGS quasi-Newton algorithm, following Ciardulli, S. and Fontana, N. (2026). The package supports scalar, binary, and functional outcomes, as well as functional covariates.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: fda (>= 6.0.0), ggplot2 (>= 3.4.0), tidyr (>= 1.2.0), MASS (>= 7.3-0), wCorr, patchwork (>= 1.1.0), progress (>= 1.2.0), stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-05 07:31:09 UTC; nicole.fontana
Author: Nicole Fontana [aut, cre], Simone Ciardulli [aut]
Maintainer: Nicole Fontana <nicole.fontana@polimi.it>
Repository: CRAN
Date/Publication: 2026-08-09 08:00:02 UTC

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New package FINN with initial version 0.1.0
Package: FINN
Title: Forest Informed Neural Networks
Version: 0.1.0
Maintainer: Yannek Kaeber <y.kaeber@posteo.de>
Description: A hybrid dynamic forest (gap) model (FINN) that can be configured as a fully mechanistic, process-based model, like classic forest gap models, or with its demographic processes (growth, mortality, regeneration) replaced by deep neural networks (DNNs), or any combination of the two. Provides functions to define a model and its mechanistic or empirical components, calibrate it to forest inventory data, and interpret the calibrated processes. FINN is implemented with the 'torch' package, which supplies GPU support and the automatic differentiation used to calibrate the model by stochastic gradient descent; no knowledge of 'torch' is required. The hybrid modeling approach is described in Pichler and Käber (2026) <doi:10.1111/2041-210x.70347>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/FINNverse/FINN, https://finnverse.github.io/FINN/
BugReports: https://github.com/FINNverse/FINN/issues
Depends: R (>= 4.1.0)
LinkingTo: Rcpp
Imports: abind, cli, stats, utils, data.table, coro, Rcpp, torch, ggplot2, glue
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-05 08:00:45 UTC; yannekkaber
Author: Yannek Kaeber [aut, cre] , Maximilian Pichler [aut]
Repository: CRAN
Date/Publication: 2026-08-09 08:00:08 UTC

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New package expoquimR with initial version 0.1.0
Package: expoquimR
Title: Qualitative and Quantitative Assessment of Occupational Chemical Exposure Risk
Version: 0.1.0
Description: Provides a unified toolkit for occupational chemical exposure risk assessment, implementing three internationally recognised methods end to end: the qualitative control-banding methods COSHH Essentials (UK Health and Safety Executive) and the method of the French National Research and Safety Institute (INRS), together with the quantitative statistical procedure of the UNE-EN 689 standard for comparing measured exposure levels against occupational exposure limits. Every step of each method, from hazard banding and exposure scoring to lognormal or normal distribution fitting, one-sided tolerance limits, and monitoring-interval recommendations, is implemented as a small, independently callable, and unit-tested function, so assessments are reproducible and auditable without depending on any graphical interface. Optional 'shiny' applications provide a guided, interactive workflow for occupational hygienists and health and safety practitioners who prefer not to write code. References: UK Hea [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
URL: https://github.com/Aguilar-Elena/expoquimR
BugReports: https://github.com/Aguilar-Elena/expoquimR/issues
Depends: R (>= 4.1.0)
Imports: stats
Suggests: DT, ggplot2, kableExtra, knitr, readxl, rmarkdown, shiny, shinyjs, testthat (>= 3.0.0), tibble, usethis
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-04 18:00:50 UTC; okashi
Author: Raul Aguilar Elena [aut, cre] , Ana Delgado-Garcia [aut] , Alejandro Guillem-Riquelme [aut]
Maintainer: Raul Aguilar Elena <raguilar@universidadviu.com>
Repository: CRAN
Date/Publication: 2026-08-09 07:10:07 UTC

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New package DropCens with initial version 0.1.0
Package: DropCens
Title: Distributionally Robust Progressive Type-II Censoring Inference
Version: 0.1.0
Description: Implements distributionally robust optimization algorithms for progressive Type-II censored Weibull lifetime data under Wasserstein ambiguity balls. Provides primal-dual convex optimization solvers and robust inference bounds.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-05 07:37:30 UTC; Dr. O. J. Obulezi
Author: Okechukwu J. Obulezi [aut, cre]
Maintainer: Okechukwu J. Obulezi <oj.obulezi@unizik.edu.ng>
Repository: CRAN
Date/Publication: 2026-08-09 08:00:17 UTC

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New package scimesh with initial version 0.3.0
Package: scimesh
Title: Headless Publication-Quality 3D Mesh Rendering Engine
Version: 0.3.0
Description: A fast, GPU-free 3D software renderer written in modern C++17 with native R bindings. Renders triangle meshes to publication-quality images entirely on the CPU, requiring no display server or graphics hardware. Features multi-light Blinn-Phong shading, screen-space ambient occlusion, anti-aliasing, depth fog, transparency, wireframe rendering, texture mapping, and procedural geometry generation. Supports standard mesh file formats with PNG and PPM output. Works on high-performance computing clusters, headless servers, containers, and continuous integration pipelines, making it suitable for scientific visualization across neuro-imaging, molecular structures, and general 3D graphics.
License: MIT + file LICENSE
URL: https://github.com/dfsp-spirit/scimesh
BugReports: https://github.com/dfsp-spirit/scimesh/issues
Imports: Rcpp (>= 1.0.0)
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), png, freesurferformats, viridisLite, knitr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: C++17
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-08-03 13:33:29 UTC; timschaefer
Author: Tim Schaefer [aut, cre], Martin Horeňovsky [ctb] ), Christophe Riccio [ctb] ), Dimitri Diakopoulos [ctb] ), Syoyo Fujita [ctb] ), Tim Schaefer [ctb] ), Sebastian Reiter [ctb] ), Sean Barrett [ctb] )
Maintainer: Tim Schaefer <ts+code@rcmd.org>
Repository: CRAN
Date/Publication: 2026-08-09 07:00:02 UTC

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New package qvivid with initial version 0.1.2
Package: qvivid
Title: Fast Quantum Simulation and Vivid Visualizations
Version: 0.1.2
Description: Builds, simulates, inspects, and animates gate-based quantum circuits. The package provides a readable reference implementation and compiled state-vector kernels, reproducible shot sampling, circuit diagrams, phase-aware state plots, reduced-state Bloch spheres, journal-sized figure export, and animated trajectories. For background on the implemented methods, see Nielsen and Chuang (2010, ISBN:9781107002173).
License: MIT + file LICENSE
URL: https://github.com/SanmiAndreSofa/qvivid
BugReports: https://github.com/SanmiAndreSofa/qvivid/issues
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: grDevices, graphics
Suggests: gifski, ggplot2 (>= 3.4.0), knitr, ragg (>= 1.2.0), rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-01 00:47:13 UTC; runner
Author: Sanmi Adenaiye [aut, cre, cph]
Maintainer: Sanmi (Oluwasanmi) Adenaiye <dradenaiyesanmi@gmail.com>
Repository: CRAN
Date/Publication: 2026-08-09 06:50:02 UTC

More information about qvivid at CRAN
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