CRANberries

Sat, 26 Sep 2026

New package memtoc with initial version 0.1.1
Package: memtoc
Title: 'Tictoc'-Style Memory Usage Tracking
Version: 0.1.1
Description: Provides simple start/stop memory tracking functions tic_mem() and toc_mem() that can be nested, inspired by the 'tictoc' package. Track RAM usage during code execution with support for logging, custom messages, nested tracking blocks, and parallel worker monitoring. Features continuous background polling to estimate peak memory usage across main process and workers. Integrates with the 'future' package ecosystem for automatic worker detection. Designed for monitoring memory consumption in parallel workflows.
License: MIT + file LICENSE
URL: https://github.com/jcoa05/memtoc
BugReports: https://github.com/jcoa05/memtoc/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ps (>= 1.7.0), cli (>= 3.0.0), callr (>= 3.7.0)
Suggests: testthat (>= 3.2.0), withr, future, parallelly, knitr, rmarkdown
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-15 19:55:54 UTC; jocampo
Author: Juan Ocampo [aut, cre]
Maintainer: Juan Ocampo <jocampo1997@hotmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 17:10:02 UTC

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New package xplus with initial version 1.0.2
Package: xplus
Title: Positive and Unlabeled Learning from Unbalanced Cases and Sparse Structures
Version: 1.0.2
Description: Provides PLUS-derived extensions for positive and unlabeled (PU) learning from unbalanced cases and sparse structures, based on Zhou et al. (2022) <doi:10.1371/journal.pcbi.1009956>. Iteratively relabels unlabeled observations via penalised logistic regression and pseudo-label updates, then refits a final sparse model. Includes weighted bootstrap sampling, convergence diagnostics, prediction, coefficient extraction, and assessment utilities.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
LazyData: true
Imports: glmnet (>= 4.1-8), Matrix, methods, stats, tibble, utils
Suggests: covr, knitr, rmarkdown, survival, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/alrobles/xplus, https://alrobles.github.io/xplus/
BugReports: https://github.com/alrobles/xplus/issues
NeedsCompilation: no
Packaged: 2026-09-15 13:35:09 UTC; alrobles
Author: Angel Robles [aut, cre]
Maintainer: Angel Robles <a.l.robles.fernandez@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:30:02 UTC

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New package Spec2Annot with initial version 1.3.4
Package: Spec2Annot
Title: Annotation of Mass Spectra
Version: 1.3.4
Description: Provides a comprehensive suite of functions to efficiently annotate mass spectra data. Motivated by the need for rapid and accurate chemical identification in high-resolution mass spectrometry, it integrates built-in chemical databases and high-performance C++ algorithms. Users can perform mass-to-charge (m/Z) and retention time searches, determine elemental compositions of molecules using heuristic rules, including specific isotopes, and annotate MS2 spectra with structural metrics using configurable chemistry rules.
License: CeCILL
URL: https://github.com/odisce/Spec2Annot
BugReports: https://github.com/odisce/Spec2Annot/issues
Depends: R (>= 4.0.0)
Encoding: UTF-8
Imports: data.table, magrittr, Rcpp, stringr
Suggests: testthat (>= 3.0.0)
LazyData: true
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-09-15 15:03:47 UTC; SD265344
Author: Sylvain Dechaumet [aut, cre], Etienne Thevenot [ctb], Eric Venot [rev], Annelaure Damont [ctb], Anais Legrand [ctb]
Maintainer: Sylvain Dechaumet <sylvain.dechaumet@cea.fr>
Repository: CRAN
Date/Publication: 2026-09-26 16:40:25 UTC

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New package sencensus with initial version 0.1.0
Package: sencensus
Title: Access to Senegal Demographic and Census Datasets
Version: 0.1.0
Date: 2026-09-15
Description: Download, cache, and analyze census datasets and demographic statistics from Senegal. Datasets are sourced from public census releases provided by the Agence Nationale de la Statistique et de la Demographie (ANSD) <https://www.ansd.sn> and hosted on GitHub releases <https://github.com/Amady01/sencus>. Also provides tools to search through variable dictionaries and load tabular demographic indicators.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: jsonlite, httr, readr, readxl
URL: https://github.com/Amady01/sencusR
BugReports: https://github.com/Amady01/sencusR/issues
NeedsCompilation: no
Packaged: 2026-09-15 11:20:02 UTC; amsal
Author: Amadou SALL [aut, cre]
Maintainer: Amadou SALL <amadymail01@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:20:02 UTC

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New package semrulesid with initial version 0.4.1
Package: semrulesid
Title: Evaluate Structural Equation Model Identification Rules
Version: 0.4.1
Description: Evaluates selected necessary and sufficient identification conditions in structural equation models (SEMs), including latent-variable scaling constraints. Output reports rule status and applicability and provides diagnostic messages to support model specification and respecification. The package is intended as a diagnostic aid and does not implement a universal identification algorithm. For more details, see Bollen (2026, ISBN:978-1009312820).
License: GPL (>= 3)
Encoding: UTF-8
Imports: lavaan
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
URL: https://github.com/zacharyvig/semrulesid
BugReports: https://github.com/zacharyvig/semrulesid/issues
NeedsCompilation: no
Packaged: 2026-09-15 13:13:05 UTC; ZACHMAC
Author: Zach Vig [aut, cre, cph]
Maintainer: Zach Vig <zachvig@rocketmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:20:07 UTC

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New package Rclade with initial version 1.1.5
Package: Rclade
Title: Automated Deep-Time Phylogenetic Tree Collapsing and Visualization
Version: 1.1.5
Author: Zeng Zichao [aut, cre]
Maintainer: Zeng Zichao <zengzichao@sjtu.edu.cn>
Description: Provides a single-function pipeline for automated collapsing and visualization of large phylogenetic trees with geological timescales. Automatically parses taxonomic labels from multiple formats (GTDB, Silva, NCBI, embedded, custom), identifies Most Recent Common Ancestors (MRCAs), assigns color-blind-safe palettes, executes batch collapsing with automatic nesting-aware ordering, integrates 'deeptime' geologic time scales with adaptive time breaks and unit switching, and manages smart legend layout. Supports special ancestral node identifiers (LUCA, LACA, LBCA) for highlighting key nodes in the tree of life. Provides external taxonomy file support for trees with incomplete or missing taxonomic labels. Features real-time logging with timestamps, step tracking, and multiple log levels. Includes comprehensive input validation for tree and sequence file formats. Reduces a 60-line manual workflow to a single function call while preserving full compatibility with the 'ggtree'/'deeptime' ecos [...truncated...]
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: ape (>= 5.0), ggtree (>= 4.0.0), deeptime (>= 1.0), ggplot2 (>= 3.5.0), rlang, stringr (>= 1.5), tidytree (>= 0.4), viridisLite
Suggests: treeio (>= 1.0), phangorn (>= 2.0), RColorBrewer, cowplot (>= 1.1), patchwork (>= 1.1), shiny (>= 1.7), optparse (>= 1.7), yaml, vdiffr (>= 1.0), testthat (>= 3.0), knitr, rmarkdown, covr, filelock, withr
Encoding: UTF-8
VignetteBuilder: knitr
URL: https://github.com/zengzichao/Rclade, https://zengzichao.github.io/Rclade/
BugReports: https://github.com/zengzichao/Rclade/issues
NeedsCompilation: no
Packaged: 2026-09-15 16:09:30 UTC; zengzichao
Repository: CRAN
Date/Publication: 2026-09-26 16:40:32 UTC

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New package moire with initial version 3.7.0
Package: moire
Title: Multiplicity of Infection and Allele Frequency Recovery from Noisy Polyallelic Genetics Data
Version: 3.7.0
Description: A Markov Chain Monte Carlo (MCMC) based approach to Bayesian estimation of individual level multiplicity of infection, within host relatedness, and population allele frequencies from polyallelic genetic data. Implements the model described in Murphy and Greenhouse (2024) <doi:10.1093/bioinformatics/btae619>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
LazyDataCompression: bzip2
SystemRequirements: C++17, GNU make
LinkingTo: Rcpp, RcppProgress, RcppParallel, BH
Imports: Rcpp, RcppProgress, RcppParallel, dplyr, tidyr, stats, parallel, purrr, rlang, ggplot2
URL: https://github.com/EPPIcenter/moire, https://eppicenter.github.io/moire/, https://eppicenter.ucsf.edu/resources
BugReports: https://github.com/EPPIcenter/moire/issues
Suggests: knitr, rmarkdown, forcats, testthat (>= 3.0.0), parallelly
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: yes
Packaged: 2026-09-15 17:53:11 UTC; mmurphy
Author: Maxwell Murphy [aut, cre] , Bryan Greenhouse [aut, ths]
Maintainer: Maxwell Murphy <mm@maxmurphy.dev>
Repository: CRAN
Date/Publication: 2026-09-26 16:50:02 UTC

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New package mappingAS with initial version 1.13.2
Package: mappingAS
Title: Spatial Metrics and Habitat Conversion for Extinction Risk Assessment
Version: 1.13.2
Author: Antonio Lucas Barreira [aut, cre, cph]
Maintainer: Antonio Lucas Barreira <barreira_rodrigues@hotmail.com>
Description: A spatial analytical framework for preliminary species extinction-risk screening following the IUCN Red List Criterion B guidelines. From occurrence points it computes the Extent of Occurrence (EOO) and Area of Occupancy (AOO) on a data-centred equal-area projection, assigns provisional Criterion B categories, and integrates 'MapBiomas' land-use/land-cover data to quantify the proportion of anthropogenic conversion versus remaining natural habitat within each range metric, with per-class breakdowns and land-cover time series. Several 'MapBiomas' initiatives are supported through one standardised legend - 'MapBiomas' Brazil, the Pan-Amazon / Amazonia collection (RAISG), Colombia, Argentina, Bolivia, Chile, Ecuador, Peru, Venezuela, Paraguay and Uruguay - so a species anywhere these products cover can be screened as readily as a Brazilian one. For ranges outside 'MapBiomas' coverage it can fall back to the global 'Esri' / 'Impact Observatory' 10 m annual land cover derived from 'Sentinel [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: sf (>= 1.0.0), terra (>= 1.7.0), shiny, bslib, leaflet, units, lwgeom, readxl, rlang, grid, tools, utils, stats, graphics, grDevices, DT, htmltools, htmlwidgets, ggplot2, plotly, officer
Suggests: rgee, reticulate, writexl, zip, curl, ggnewscale, ggtrendline, ragg, shinyWidgets, testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
URL: https://github.com/lucasbarreirageo/mappingAS
BugReports: https://github.com/lucasbarreirageo/mappingAS/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-15 17:14:56 UTC; codespace
Repository: CRAN
Date/Publication: 2026-09-26 16:50:08 UTC

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New package heteroTests with initial version 0.11.2
Package: heteroTests
Title: Heteroscedasticity Diagnostics for Linear Models
Version: 0.11.2
Description: Provides a unified set of heteroscedasticity diagnostics for linear-model workflows. It implements classical auxiliary-regression tests, including those of White (1980) <doi:10.2307/1912934>, Breusch and Pagan (1979) <doi:10.2307/1911963>, Koenker (1981) <doi:10.1016/0304-4076(81)90062-2>, Goldfeld and Quandt (1965) <doi:10.1080/01621459.1965.10480811> and Harvey (1976) <doi:10.2307/1913974>; the score test of Cook and Weisberg (1983) <doi:10.1093/biomet/70.1.1>; the ARCH test of Engle (1982) <doi:10.2307/1912773>; and group-wise tests of equal variance, including those of Bartlett (1937) <doi:10.1098/rspa.1937.0109>, Brown and Forsythe (1974) <doi:10.1080/01621459.1974.10482955> and Hartley (1950) <doi:10.2307/2332383>. Resampling and scalable variants, simulation utilities, diagnostic visualisation and remediation helpers share a consistent interface designed for reproducible statistical workflows and integration with common [...truncated...]
License: Apache License (>= 2.0)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1)
Imports: MASS, stats, ggplot2, curl, generics, scales, R6, parallel, SuppDists
Suggests: quickcheck, testthat (>= 3.0.0), styler, lintr, digest, covr, knitr, rmarkdown, gridExtra, shiny, DT, plotly, htmlwidgets, readxl, Matrix, bench, lmtest, plm, withr, car, vartest, mgcv, quantreg, sandwich, spdep, broom, workflows, parsnip, recipes, survey, data.table, dtplyr, dplyr
VignetteBuilder: knitr
URL: https://github.com/DiogoRibeiro7/heteroTests, https://diogoribeiro7.github.io/heteroTests/
BugReports: https://github.com/DiogoRibeiro7/heteroTests/issues
NeedsCompilation: no
Packaged: 2026-09-15 16:55:05 UTC; runner
Author: Diogo Ribeiro [aut, cre]
Maintainer: Diogo Ribeiro <dfr@esmad.ipp.pt>
Repository: CRAN
Date/Publication: 2026-09-26 16:50:16 UTC

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New package gpuinfo with initial version 0.1.0
Package: gpuinfo
Title: Lightweight Hardware and GPU Compute Detection
Version: 0.1.0
Description: Detects central processing unit and graphics processing unit hardware and reports the apparent availability of 'CUDA', 'Metal', 'ROCm', and 'OpenCL' compute backends. Detection uses operating-system information, documented platform interfaces, and optional command-line utilities, without requiring a GPU framework, 'Python', or a vendor software development kit. Backend interpretation follows the official 'CUDA' <https://docs.nvidia.com/cuda/cuda-driver-api/>, 'Metal' <https://developer.apple.com/documentation/metal>, 'ROCm' <https://rocm.docs.amd.com/>, and 'OpenCL' <https://registry.khronos.org/OpenCL/> documentation. Missing hardware, drivers, libraries, and utilities are handled safely.
License: MIT + file LICENSE
URL: https://github.com/tkcaccia/gpuinfo
BugReports: https://github.com/tkcaccia/gpuinfo/issues
Encoding: UTF-8
NeedsCompilation: yes
Depends: R (>= 3.6.0)
Suggests: jsonlite, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Packaged: 2026-09-15 14:45:12 UTC; stefano
Author: Stefano Cacciatore [aut, cre]
Maintainer: Stefano Cacciatore <tkcaccia@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:40:08 UTC

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New package ggCheysson with initial version 1.0.1
Package: ggCheysson
Title: Graphic Styles of Emile Cheysson for 'ggplot2'
Version: 1.0.1
Date: 2026-09-14
Description: Implements for 'ggplot2' the stylistic elements (fonts, hatched patterns, color palettes) used by 'Emile Cheysson' in the 'Albums de Statistique Graphique', sometimes called the pinnacle of the Golden Age of Statistical Graphics.
Imports: ggplot2
Suggests: ggpattern, ggthemes, gridpattern, systemfonts, showtext, sysfonts, ragg, knitr, rmarkdown, Guerry, sf, tidyr, dplyr
License: GPL (>= 3)
Language: en-US
Encoding: UTF-8
URL: https://github.com/friendly/ggCheysson, https://friendly.github.io/ggCheysson/
BugReports: https://github.com/friendly/ggCheysson/issues
Depends: R (>= 3.5)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-15 15:39:21 UTC; friendly
Author: Michael Friendly [aut, cre] , RJ Andrews [ctb], Tom Shanley [ctb], Kenneth Fields [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>
Repository: CRAN
Date/Publication: 2026-09-26 16:40:13 UTC

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New package gcf with initial version 0.1.0
Package: gcf
Title: Generalized Covariate Field
Version: 0.1.0
Description: Generates generalized covariate field (GCF) variables from spatial covariates observed at projected coordinates, and selects a stable subset of them for geospatial prediction. For each input covariate the method builds spatial-pattern features (local indicator of spatial association, local Geary's c, log local variance, rank quantile entropy, geocomplexity, log scale variance, local variogram exponent, and signed z-score and median absolute deviation outlier strengths over a series of buffer radii) and neighbourhood-distribution features (buffer-wise quantiles of the covariate values surrounding each location), reduces the buffer and quantile sweeps to a compact set of interpretable functional summaries, and selects variables by random forest importance combined with spatial-block stability resampling and group voting. The GCF method is positioned as prediction-oriented feature construction: its output feeds any downstream regression learner. Methods are described in Song (2026) <do [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: geocomplexity, ranger, sf, spdep, stats, utils
Suggests: knitr, randomForest, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-09-15 07:02:05 UTC; 268222h
Author: Yongze Song [aut, cre, cph]
Maintainer: Yongze Song <yongze.song@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:10:02 UTC

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New package fastconley with initial version 0.11.1
Package: fastconley
Title: Fast Conley Standard Errors for 'lfe' and 'fixest' Models
Version: 0.11.1
Maintainer: Richard Bluhm <richard.bluhm@gmail.com>
Description: Conley (1999) <doi:10.1016/S0304-4076(98)00084-0> spatial heteroscedasticity and autocorrelation consistent (HAC) standard errors for fixed effects panel and cross-sectional models estimated with felm() from the 'lfe' package (ordinary least squares and instrumental variables) or with feols(), feglm(), and fepois() from the 'fixest' package. Instrumental-variable support is limited to ordinary two-stage least squares. Generalized linear model fits use the M-estimation sandwich built from the stored scores and inverse Hessian. The spatial path uses score accumulation, a three-dimensional cell-grid neighbour search, and compressed sparse row neighbour lists instead of dense distance matrices, yielding large speedups over the original 'conley' package <https://github.com/rbluhm/conley> on big cross-sections and high-dimensional regressions.
License: MIT + file LICENSE
URL: https://github.com/rbluhm/fastconley, https://rbluhm.github.io/fastconley/
BugReports: https://github.com/rbluhm/fastconley/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: data.table, Rcpp, stats
Suggests: fixest, knitr, lfe, rmarkdown, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppArmadillo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-09-15 17:35:20 UTC; richard
Author: Richard Bluhm [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-09-26 17:00:02 UTC

More information about fastconley at CRAN
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New package eiballots with initial version 0.1.0-1
Package: eiballots
Title: Ballot-Level Microdata and Summaries for Ecological Inference (Florida 2000)
Version: 0.1.0-1
Description: Provides access to ballot-level electoral microdata from the Florida 2000 general election and tools for computing summaries suitable for ecological inference. Includes functions to load data by county or race (election), compute marginal distributions at the precinct level, and build joint contingency arrays across multiple races for use with ecological inference packages. Data files are stored in a remote repository and downloaded on demand; local copies are supported via the 'data_dir' option. Acknowledgements: We thank Jaime Ventura (ANES, University of Michigan) and Dan Keating (The Washington Post) for providing the raw data that serve as the starting point for the construction of this package. We also acknowledge funding from the Conselleria de Educación, Cultura y Universidades (grant CIACIO/2023/031).
URL: https://doi.org/10.17605/OSF.IO/NP73B
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: stats
Suggests: testthat (>= 3.0.0), usethis
NeedsCompilation: no
Packaged: 2026-09-15 18:36:55 UTC; pavia
Author: Cristina Aybar [aut] , Jose M. Pavia [aut, cre]
Maintainer: Jose M. Pavia <jose.m.pavia@uv.es>
Repository: CRAN
Date/Publication: 2026-09-26 17:00:08 UTC

More information about eiballots at CRAN
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New package drisdiagnostics with initial version 1.0.1
Package: drisdiagnostics
Title: Diagnostic Systems for Plant Nutrient Analysis (DRIS, MDRIS, PASS)
Version: 1.0.1
Description: Provides implementations of the Diagnosis and Recommendation Integrated System (DRIS), the Modified DRIS (MDRIS), and the Plant Analysis with Standardized Scores (PASS) approaches for nutrient diagnosis in crops. These methods allow quantitative evaluation of nutrient imbalances using ratio-based indices and standardized scores, supporting improved fertilizer use efficiency and crop management decisions. The DRIS method is described in Walworth, J.L. and Sumner, M.E. (1987) <doi:10.1007/978-1-4612-4682-4_4>. The MDRIS approach is detailed in Beverly, R.B. (1987) <doi:10.1080/01904168709363672>. The PASS method combining DRIS and sufficiency ranges is presented in Baldock, J.O. and Schulte, E.E. (1996) <doi:10.2134/agronj1996.00021962008800030015x>.
License: GPL-3
Encoding: UTF-8
Imports: ggplot2, stats, rlang
Suggests: readxl, testthat (>= 3.0.0)
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-15 18:54:14 UTC; bejoy
Author: Blesson B. Varghese [aut, cre], Mubashir Sadiq V [aut], Deepthi C [aut], Sowmiya Saravanan [aut], Aparna Mohan V [aut]
Maintainer: Blesson B. Varghese <blessonvarghese1234@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 17:00:16 UTC

More information about drisdiagnostics at CRAN
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New package diy.sem.plot with initial version 1.0.0
Package: diy.sem.plot
Title: Manually Plot Path Diagrams for Structural Equation Models
Version: 1.0.0
Description: Manually plot fully customisable path diagrams for structural equation models (SEM). Map out node positions using simple coordinates and specify where on the perimeter of each node paths begin and end. Extensive fine-tuning options allow the creation of a path diagram exactly as envisioned, entirely within R.
Encoding: UTF-8
Imports: ggplot2, ggtext, ggforce, lavaan, patchwork
Suggests: knitr, rmarkdown, testthat
URL: https://github.com/snagy86/diy.sem.plot
BugReports: https://github.com/snagy86/diy.sem.plot/issues
VignetteBuilder: knitr
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2026-09-15 10:31:57 UTC; snagy
Author: Sebastian Nagy [aut, cre, cph]
Maintainer: Sebastian Nagy <snagy8610@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:20:13 UTC

More information about diy.sem.plot at CRAN
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New package cwad with initial version 0.2.0
Package: cwad
Title: Connectivity-Weighted Allocation and Comparison of Field-Plot Designs
Version: 0.2.0
Date: 2026-09-15
Description: A reproducible mixed-model toolkit for plant-breeding trial design. It evaluates any replication allocation under a known genetic relationship (kinship) matrix using one common linear-mixed-model engine on genotype means. Crucially, allocation and analysis model are crossed rather than confounded: every allocation can be scored both with and without kinship, so the precision gain attributable to a design can be separated from the gain attributable to the kinship-based analysis adopted alongside it. It computes A-optimal, connectivity-aware allocations via rank-1 Sherman-Morrison updates, and provides Monte-Carlo stress tests for outlier shrinkage and for an incorrectly specified kinship matrix, each with a matched control arm.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.0.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/bkpraveenars-del/cwad
BugReports: https://github.com/bkpraveenars-del/cwad/issues
NeedsCompilation: no
Packaged: 2026-09-15 07:43:57 UTC; root
Author: Praveen Kumar [aut, cre]
Maintainer: Praveen Kumar <bkpraveenars@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:10:07 UTC

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New package bslibdash with initial version 0.7.5
Package: bslibdash
Title: 'Bootstrap' 5 Dashboard Framework for 'shiny' Apps
Version: 0.7.5
Description: Provides a dashboard layer for 'shiny' applications built on 'bslib' and 'Bootstrap' 5. Includes a dashboard page shell, sidebar navigation, cards, value boxes, header drop-down menus and feedback components that inherit the active 'bslib' theme and follow 'Bootstrap' design patterns. Function names mirror those of the 'shinydashboard' package wherever the underlying concepts are shared, allowing existing applications to migrate with minimal changes.
License: MIT + file LICENSE
URL: https://github.com/Novartis/bslibdash, https://opensource.nibr.com/bslibdash/
BugReports: https://github.com/Novartis/bslibdash/issues
Depends: R (>= 4.1.0)
Imports: utils, shiny (>= 1.0.5), shinyjs, htmltools, bslib (>= 0.6.0), bsicons, rlang, glue, sass
Suggests: testthat (>= 3.0.0), withr, knitr, lintr, rmarkdown, covr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-15 14:32:17 UTC; KOUREAL2
Author: Alexandros Kouretsis [aut, cre], Ardalan Mirshani [aut], Dominik Rafacz [aut], Novartis Open Source Initiative [cph]
Maintainer: Alexandros Kouretsis <alexandros@appsilon.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:40:19 UTC

More information about bslibdash at CRAN
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New package bgfanalyzer with initial version 1.1.0
Package: bgfanalyzer
Title: Analyze Microbial Biogas Fermentation Data
Version: 1.1.0
Description: Provides a new S3 class object and relevant methods to analyze biogas fermentation data. It includes three workflows. One is specialized to a commercially available lab-scale fermentation system (see e.g. Nwaigwe (2018) <doi:10.1115/ES2018-7553>). The second provides more flexibility and allows to import data from plain text files. The last workflow offers the most flexibility as it doesn't expect external input files but relays on interactive user input. Although the focus is set on biogas fermentations, concepts and workflows may be also applicable to other fermentations even if not a gaseous product is measured. Furthermore, it provides functions that bridge to established plot engines (e.g. 'ggplot2' or 'plotly') for data visualisation. 'bgfanalyzer' catches up an idea of Hafner et al. (2018) <doi:10.1016/j.softx.2018.06.005> of using R to standardize research within the biogas field. For more details on standardization efforts within the biogas research field see Holl [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: stats, utils, rlang, zoo, dplyr, graphics, ggplot2, plotly
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 3.5)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-15 16:47:28 UTC; blacki
Author: Maximilian Strick [aut, cre, cph]
Maintainer: Maximilian Strick <maximilianb.strick@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 16:50:25 UTC

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New package acousticTS with initial version 2.0.6
Package: acousticTS
Title: Physics-Based Models for Acoustic Target Strength
Version: 2.0.6
Copyright: See file inst/COPYRIGHTS.
Description: Acoustic target strength (TS) represents the intensity of an echo returning from an individual scatterer such as bubbles, fish, or zooplankton. TS can be used to convert integrated or volumetric backscatter collected from fisheries acoustic surveys into units of number density (e.g. animals per m^3), abundance (e.g. number of animals), and biomass (e.g. kg). This parameter can also be used to aid in classifying backscatter, such as separating likely echoes of large predatory fish (e.g. adult cod) from smaller prey (e.g. shrimp). One way to estimate TS is to use physics-based models to calculate theoretical TS that comprise exact and approximate solutions as well as analytical approaches. The models provided can help provide TS estimates over broad statistical distributions of model parameters. Applications are described by Lucca et al. (2023) <doi:10.1121/10.0022459>, with fisheries-acoustics principles from Simmonds and MacLennan (2005) <doi:10.1002/9780470995303>.
License: GPL-3
URL: https://brandynlucca.github.io/acousticTS/, https://doi.org/10.5281/zenodo.7600659
BugReports: https://github.com/brandynlucca/acousticTS/issues
Depends: R (>= 4.0.0)
Imports: grDevices, graphics, methods, parallel, pbapply, Rcpp, stats, tools, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
LinkingTo: BH, Rcpp, RcppArmadillo
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
Language: en-US
NeedsCompilation: yes
Packaged: 2026-09-15 19:00:48 UTC; Brandyn
Author: Brandyn Lucca [aut, cre, cph] , Arnie Lee Van Buren [ctb, cph] , Jeffrey E. Boisvert [ctb]
Maintainer: Brandyn Lucca <brandyn.lucca@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-26 17:00:34 UTC

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Fri, 25 Sep 2026

New package DCC with initial version 1.2.1
Package: DCC
Title: Data Cleaning Center for Survey and Assessment Data
Version: 1.2.1
Description: Rule-driven, auditable cleaning of survey and assessment response data, implementing the WeianData Detect-Execute-Report workflow. Provides a multi-format, multi-encoding input layer (CSV, 'Excel', 'SPSS', 'Stata', 'SAS', Parquet, JSON), the dcc_data container with a provenance chain, level-0 structural diagnostics, five built-in response-quality detectors (missing items, straight-lining, response time, trap items, score anomalies), a declarative YAML rule engine, an execution engine with a cell-level audit log, answer-key scoring, multi-form to master item bank mapping, a normalized report model rendered as bilingual staff workbooks and HTML, complete statistical bundles, and versioned machine JSON/JSONL with findings-to-changes reconciliation, cell-level lineage tracing, and manifest-based one-command reproduction. Includes a protected bilingual strict project workbook and matching JSON contract with cell-addressed validation, non-mutating preflight, preview-first execution, and loca [...truncated...]
License: GPL (>= 2)
Copyright: See file inst/COPYRIGHTS.
Encoding: UTF-8
Language: en
Depends: R (>= 4.1)
Imports: arrow, data.table (>= 1.14.0), haven (>= 2.5.5), jsonlite, openxlsx2 (>= 1.28), readODS (>= 2.3.5), readxl (>= 1.5.0), stringi (>= 1.7.0), methods, stats, tools, utils, writexl, yaml
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
URL: https://github.com/weiandata/DCC
BugReports: https://github.com/weiandata/DCC/issues
NeedsCompilation: no
Packaged: 2026-09-02 11:30:25 UTC; makunxiang
Author: Kunxiang Ma [aut, cre], WEIAN DATA TECH Co., Ltd. [cph, fnd]
Maintainer: Kunxiang Ma <makunxiang@weiandata.com>
Repository: CRAN
Date/Publication: 2026-09-25 22:40:07 UTC

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New package churon with initial version 0.1.12
Package: churon
Title: 'ONNX Runtime' Integration
Version: 0.1.12
Description: Provides high-performance R bindings for 'ONNX Runtime' <https://onnxruntime.ai/>, enabling efficient machine learning model inference. Written in 'Rust' for memory safety and speed, the package supports cross-platform model execution with multiple execution providers. Includes comprehensive error handling and validation, with bundled MNIST example model for immediate testing and prototyping. Designed for production use with support for macOS (arm64), Linux (x64/arm64), and Windows (x64). Runtime libraries are downloaded on explicit request from <https://github.com/microsoft/onnxruntime/releases>.
License: MIT + file LICENSE
URL: https://github.com/mrchypark/churon
BugReports: https://github.com/mrchypark/churon/issues
Encoding: UTF-8
SystemRequirements: Cargo (>= 1.88.0), rustc (>= 1.88.0); ONNX Runtime (>= 1.28.0, optional at runtime)
Depends: R (>= 4.0.0)
Imports: digest
Suggests: testthat (>= 3.2.0)
NeedsCompilation: yes
Packaged: 2026-09-10 16:36:56 UTC; cypark
Author: Chanyub Park [aut, cre] , The authors of the dependency Rust crates [ctb] , ONNX Project contributors [ctb, cph] , Microsoft Corporation [cph]
Maintainer: Chanyub Park <mrchypark@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-25 22:40:02 UTC

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New package arity with initial version 0.1.0
Package: arity
Title: Format R Code with Arity
Version: 0.1.0
Description: Provides R bindings to the deterministic, rule-based formatter from 'arity'. Format R source text or individual files using a style based on the tidyverse R style guide.
License: MIT + file LICENSE
URL: https://github.com/jolars/arity-r, https://arity.cc
BugReports: https://github.com/jolars/arity-r/issues
Depends: R (>= 4.2)
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-US
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.89.0
NeedsCompilation: yes
Packaged: 2026-09-01 19:07:21 UTC; jola
Author: Johan Larsson [aut, cre, cph]
Maintainer: Johan Larsson <johan@jolars.co>
Repository: CRAN
Date/Publication: 2026-09-25 22:30:09 UTC

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Thu, 24 Sep 2026

New package screenllm with initial version 0.1.0
Package: screenllm
Title: LLM-Assisted Title/Abstract Screening for Systematic Reviews
Version: 0.1.0
Description: A turn-key workflow for LLM-assisted systematic-review screening. The package ranks a corpus of titles and abstracts with an ensemble of open-source large language models served locally by 'Ollama', then applies the SAFE stopping rule to identify the records a human should screen. Defaults match the four-LLM mean ensemble and the SAFE configuration recommended by Spillias et al. (2026). A companion 'Shiny' app walks the human reviewer through the records above the stopping point. Complementary to the 'AIscreenR' package of Vembye et al. (2025) <doi:10.1037/met0000769>, which targets cloud-hosted 'GPT' models via the 'OpenAI' API; 'screenllm' targets locally-served open-weights ensembles with an integrated stopping rule.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, digest, fs, jsonlite, tibble, dplyr, rlang, httr2, glue
Suggests: shiny, bslib, DT, callr, later, writexl, readxl, testthat (>= 3.0.0), knitr, rmarkdown, readr, withr, mockery, stringdist
VignetteBuilder: knitr
URL: https://github.com/s-spillias/screenllm
BugReports: https://github.com/s-spillias/screenllm/issues
NeedsCompilation: no
Packaged: 2026-09-15 05:47:11 UTC; spi085
Author: Scott Spillias [aut, cre], Laura Avila Turriago [aut], Christopher Brown [aut], Ariane Easton [aut], Jack Roberts [aut], Michael Sievers [aut], Steve Swearer [aut], Andrew Taylor [aut], Brigette Wright [aut], Valeriya Komyakova [aut]
Maintainer: Scott Spillias <scott.spillias@csiro.au>
Repository: CRAN
Date/Publication: 2026-09-24 15:00:02 UTC

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New package rxode2lincmt with initial version 0.1.0
Package: rxode2lincmt
Version: 0.1.0
Title: Linear Compartment Model Solutions and Gradients for 'rxode2'
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>
Depends: R (>= 4.1.0)
Imports: Rcpp (>= 1.0.8), checkmate
Suggests: covr, testthat (>= 3.0.0)
Description: Analytic one, two and three compartment linear pharmacokinetic solutions with their parameter gradients from 'stan' automatic differentiation (Carpenter et al (2015) <doi:10.48550/arXiv.1509.07164>), eigen decompositions and derived-parameter conversions used by 'rxode2' (Wang, Hallow and James (2016) <doi:10.1002/psp4.12052>). Split out of 'rxode2' so its installation does not compile 'stan' AD items which made it take too long to compile by itself. The closed-form solutions follow the idea of the 'wnl' package (Bae, <https://CRAN.R-project.org/package=wnl>), though the implementation here is different.
BugReports: https://github.com/nlmixr2/rxode2lincmt/issues/
NeedsCompilation: yes
License: GPL (>= 3)
URL: https://nlmixr2.github.io/rxode2lincmt/, https://github.com/nlmixr2/rxode2lincmt/
Biarch: true
LinkingTo: Rcpp (>= 1.0.8), RcppEigen (>= 0.3.3.9.2), StanHeaders (>= 2.21.0.7), BH, RcppParallel
Encoding: UTF-8
Language: en-US
Packaged: 2026-09-14 19:46:27 UTC; matt-fidler
Author: Matthew L. Fidler [aut, cre] , Richard Upton [ctb]
Repository: CRAN
Date/Publication: 2026-09-24 14:40:02 UTC

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New package RobustVis with initial version 0.1.2
Package: RobustVis
Title: Visualize ROBUST-RCT Risk of Bias Assessments
Version: 0.1.2
Description: Provides functions to visualize ROBUST-RCT assessments, as introduced by Wang et al. (2025) <doi:10.1136/bmj-2024-081199>. Through a two-step workflow (step 1 and step 2), the package generates bar plots and traffic-light plots that match standard Cochrane styles.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: dplyr (>= 1.2.0), ggplot2 (>= 4.0.2), scales (>= 1.4.0), tidyr (>= 1.3.1)
NeedsCompilation: no
Packaged: 2026-09-14 21:20:09 UTC; xiaobanxia
Author: Guang Chen [aut, cre], Fanrong Liang [aut]
Maintainer: Guang Chen <tcm_chen7410@163.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:50:06 UTC

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New package RCTCovAdj with initial version 0.1.0
Package: RCTCovAdj
Title: Covariate Adjustment for Randomized Controlled Trials
Version: 0.1.0
Description: Implements covariate-adjusted estimation and inference for marginal mean differences in two-arm randomized controlled trials with continuous outcomes. Methods include the unadjusted difference in means, common-slope analysis of covariance, interacted standardization with joint influence-function inference, and cross-fitted augmentation. The package also provides analytic power and sample-size calculations, reproducible simulation designs, and article replication workflows, including tools for verifying and analyzing an authorized local trial-data file. The adjustment methods build on Tsiatis et al. (2008) <doi:10.1002/sim.3113> and Lin (2013) <doi:10.1214/12-AOAS583>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: digest, graphics, grDevices, parallel, stats, tools, utils
Suggests: knitr, medicaldata (>= 0.2.0), rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
NeedsCompilation: no
Packaged: 2026-09-14 20:26:11 UTC; seyoo
Author: Se Yoon Lee [aut, cre, cph]
Maintainer: Se Yoon Lee <seyoonlee.stat.math@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:50:11 UTC

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New package psvr with initial version 0.1.0
Package: psvr
Title: Percentage-Error Support Vector Regression
Version: 0.1.0
Description: Implements four support vector regression (SVR) models derived from a unified mathematical framework for percentage-error loss functions: epsilon-SVR minimizing the mean absolute percentage error (MAPE), its symmetric kernel extension, least-squares SVR (LS-SVR) minimizing the root mean square percentage error (RMSPE), and its symmetric counterpart. All models require strictly positive targets. The epsilon-SVR models are solved via a built-in sequential minimal optimization (SMO) algorithm (with 'osqp' available as an optional alternative backend) and the LS-SVR models via a linear system (base R). See Benavides-Herrera et al. (2026) <doi:10.3390/math14101679> for the mathematical derivations.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: dials, Matrix, parsnip, Rcpp (>= 1.0.10), rlang, scales, stats, tune, utils, workflowsets
LinkingTo: Rcpp
Suggests: dplyr, ggplot2, knitr, osqp, recipes, rmarkdown, rsample, testthat (>= 3.0.0), tibble, workflows, yardstick
VignetteBuilder: knitr
URL: https://pbenavidesh.github.io/psvr/
NeedsCompilation: yes
Packaged: 2026-09-14 19:56:47 UTC; behep
Author: Pablo Benavides-Herrera [aut, cre]
Maintainer: Pablo Benavides-Herrera <pbenavides@iteso.mx>
Repository: CRAN
Date/Publication: 2026-09-24 14:40:08 UTC

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New package funresMech with initial version 1.0.4
Package: funresMech
Title: Mechanistic Functional Response Analysis
Version: 1.0.4
Description: Implements the mechanistic functional response model proposed by Okuyama (2012) <doi:10.1016/j.biocontrol.2011.10.008> for host-parasitoid systems. Provides tools for model fitting, likelihood profiling, stochastic simulation, and visualization of parasitism distributions. Includes an interactive 'shiny' application for complete analysis workflows, built with 'plotly' for interactive graphics and 'rmarkdown' for reproducible reports.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: DEoptim, dplyr, future, ggplot2 (>= 3.4.0), magrittr, parallel, plotly, rlang, rmarkdown, shiny, shinyBS, shinythemes, stats, utils
Suggests: kableExtra, knitr, testthat (>= 3.0.0)
URL: https://github.com/Segon03/funresMech
BugReports: https://github.com/Segon03/funresMech/issues
NeedsCompilation: no
Packaged: 2026-09-15 03:38:09 UTC; Equipo
Author: Segundo Nunez-Campero [aut, cre]
Maintainer: Segundo Nunez-Campero <segundo.nc@conicet.gov.ar>
Repository: CRAN
Date/Publication: 2026-09-24 14:50:02 UTC

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New package foundryR with initial version 0.1.0
Package: foundryR
Title: Data Frame Workflows for 'Microsoft Foundry'
Version: 0.1.0
Description: Work with 'Microsoft Azure AI Foundry' from data-frame-oriented 'R' workflows. Provides data-frame-returning helpers for 'Azure AI Content Safety', 'Azure OpenAI' Responses API calls, strict structured extraction, vector representations, files, batch jobs, audio, media, and chat completions. Supports research annotation, safety gates, semantic search, and 'tidymodels' recipes. Helps teams keep model workflows inside their 'Azure' environment while preserving analyzable outputs. See the Microsoft Foundry REST API documentation <https://learn.microsoft.com/rest/api/microsoft-foundry/> and Azure AI Content Safety documentation <https://learn.microsoft.com/azure/ai-services/content-safety/>.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
URL: https://github.com/farach/foundryR, https://farach.github.io/foundryR/
BugReports: https://github.com/farach/foundryR/issues
Encoding: UTF-8
Imports: cli, curl, digest, dplyr, generics, httr2 (>= 1.0.0), jsonlite, lifecycle, magrittr, purrr, rlang, tibble
Suggests: AzureAuth, base64enc, ellmer, ggplot2, gt, httptest2, irlba, irr, janeaustenr, knitr, recipes, rmarkdown, S7, testthat (>= 3.0.0), tidymodels, tidyr, withr, yardstick
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 01:20:09 UTC; runner
Author: Alex Farach [aut, cre, cph]
Maintainer: Alex Farach <alexfarach@microsoft.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:40:16 UTC

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New package CAbiplot with initial version 0.1.0
Package: CAbiplot
Title: Correspondence Analysis Biplots and Diagnostic Reports
Version: 0.1.0
Description: A convenience wrapper around 'FactoMineR' and 'factoextra' for running Correspondence Analysis (CA) on a numeric data table (e.g. a genotype-by-trait or contingency-style matrix) and producing a full set of publication-ready diagnostic plots: scree plot, symmetric biplot, row-only and column-only plots, row/column contribution plots, and row/column cos2 (quality-of-representation) plots. A single top-level function runs the whole pipeline, prints formatted result tables, and optionally saves every plot as a high-resolution image, mirroring a typical CA reporting workflow used in agronomy and plant-breeding studies. An example genotype-by-trait data set is included.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: FactoMineR, factoextra, ggplot2, gridExtra, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-15 07:00:02 UTC; iasri
Author: Prakash Kumar [aut, cre], Himadri Sekhar Roy [aut], Ranjit Kumar Paul [aut], Md. Yeasin [aut], Sunil Kumar Yadav [aut], Amrit Kumar Paul [aut]
Maintainer: Prakash Kumar <prakash289111@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 15:00:08 UTC

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New package blueycolors with initial version 0.2.2
Package: blueycolors
Title: Provides 'Bluey' Inspired Color Palettes
Version: 0.2.2
Description: Provides 'Bluey'-inspired color palettes and 'ggplot2' scales.
License: MIT + file LICENSE
URL: https://github.com/ekholme/blueycolors, https://ekholme.github.io/blueycolors/
BugReports: https://github.com/ekholme/blueycolors/issues
Encoding: UTF-8
Imports: ggplot2, grDevices
Suggests: scales, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-14 17:34:43 UTC; ekholme
Author: Eric Ekholm [aut, cre, cph]
Maintainer: Eric Ekholm <eric.ekholm@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:40:26 UTC

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New package ZooRisk with initial version 1.0.0
Package: ZooRisk
Title: Quantitative Assessment of Zoonotic Disease Risk
Version: 1.0.0
Description: Provides quantitative tools for assessing zoonotic disease risk across animal, human, environmental, and transmission interfaces. The package supports exposure and transmission risk estimation, spillover risk assessment, risk scoring, cross-species comparison, transmission-network analysis, Monte Carlo uncertainty simulation, and sensitivity analysis. The One Health framework underlying these assessments is described by World Health Organization, Food and Agriculture Organization of the United Nations, United Nations Environment Programme, and World Organisation for Animal Health (2022) <doi:10.4060/cc2289en>.
License: MIT + file LICENSE
URL: https://github.com/vinodhpmd/ZooRisk
BugReports: https://github.com/vinodhpmd/ZooRisk/issues
Encoding: UTF-8
Suggests: igraph, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 16:48:26 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:50:18 UTC

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New package xaiHydro with initial version 0.1.0
Package: xaiHydro
Title: Explainable AI Tools for Hydro-Climate Modelling
Version: 0.1.0
Date: 2026-09-09
Description: Provides a unified workflow for applying Explainable Artificial Intelligence (XAI) methods to hydro-climate predictive models. Functions implement a permutation-based Monte Carlo SHAP estimator (Strumbelj and Kononenko (2014) <doi:10.1007/s10115-013-0679-x>; Lundberg and Lee (2017) <doi:10.48550/arXiv.1705.07874>), a self-contained locally weighted linear surrogate LIME (Ribeiro et al. (2016) <doi:10.1145/2939672.2939778>), and Partial Dependence Plots with Accumulated Local Effects (Friedman (2001) <doi:10.1214/aos/1013203451>; Apley and Zhu (2020) <doi:10.1111/rssb.12377>) with hydrology-specific visualisations and interpretation utilities. Supports any model object compatible with the 'DALEX' explainer interface (Biecek (2018) <doi:10.18637/jss.v097.i01>), including random forests, gradient boosting, and neural networks trained on streamflow, drought indices, flood risk, or evapotranspiration data. Hydrology-standard performance metrics Nash-Sutcl [...truncated...]
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Depends: R (>= 4.1.0)
Imports: DALEX (>= 2.4.0), ggplot2 (>= 3.4.0), dplyr (>= 1.1.0), tidyr (>= 1.3.0), patchwork (>= 1.2.0), cli (>= 3.6.0), rlang (>= 1.1.0)
Suggests: randomForest (>= 4.7.0), xgboost (>= 1.7.0), ranger (>= 0.16.0), testthat (>= 3.0.0), knitr (>= 1.45), rmarkdown (>= 2.25)
VignetteBuilder: knitr
Packaged: 2026-09-13 10:09:33 UTC; Admin
Author: Sadikul Islam [aut, cre] , Shakir Ali [aut], Rajesh Kaushal [aut]
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:30:02 UTC

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New package uqsa with initial version 0.8.0
Package: uqsa
Title: Uncertainty Quantification and Global Sensitivity Analysis
Version: 0.8.0
Description: In the field of systems biology, chemical reaction networks are modeled in various ways, two of those are: (i) stochastic simulations (e.g. Gillespie algorithm) and (ii) ordinary differential equations. In this package we use a simple tabular model description of reaction systems and automatically generate C code for either solver type. We use the ordinary differential equation solvers from the GNU Scientific Library and provide an interface that deals with lists of simulation experiments. Each simulation experiment contains both the data, and instructions for the model to replicate the data. We use approximate Bayesian computation methods (combined with Markov chain Monte Carlo and sequential Monte Carlo, particle filters) as well as classic methods such as Random Walk Metropolis (Gaussian transition kernel) and Simplified Manifold Metropolis adjusted Langevin algorithm for a Bayesian investigation of the model´s parameter space. Experiments can be evaluated in a sequence; intermediat [...truncated...]
Language: en-US
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: stats, methods, parallel, Ryacas, VineCopula, MASS, errors, mvtnorm, digest, colorspace, pracma, cli
Suggests: ks, remotes, pbdMPI, ggplot2, testthat (>= 3.0.0), knitr, rmarkdown, hexbin
SystemRequirements: GSL (>= 2.7)
VignetteBuilder: knitr
URL: https://icpm-kth.github.io/uqsa/
NeedsCompilation: yes
Packaged: 2026-09-14 16:44:28 UTC; andreikr
Author: Alexandra Jauhiainen [aut], Olivia Eriksson [aut, ctb, cph], Federica Milinanni [aut], Andrei Kramer [cre]
Maintainer: Andrei Kramer <andreikr@kth.se>
Repository: CRAN
Date/Publication: 2026-09-24 13:50:02 UTC

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New package rsmart with initial version 0.1.0
Package: rsmart
Title: Sequential Multiple Assignment Randomized Trials Design and Analyses
Version: 0.1.0
Description: Implements the interim augmented inverse probability weighted estimator (IAIPWE) for estimating the value of treatment regimes embedded in sequential multiple assignment randomized trials (SMARTs). The IAIPWE subsumes both the inverse probability weighted estimator (IPWE) and the augmented inverse probability weighted estimator (AIPWE), enabling inference at interim and final analyses. The package provides functions for value estimation, sandwich variance computation, group sequential stopping boundaries, and sample size determination for multi-stage SMARTs with up to two treatment options at each stage. See Manschot, Laber, and Davidian (2023) <doi:10.1111/biom.13854> for additional details.
License: GPL (>= 3)
URL: https://MSDLLCpapers.github.io/rsmart/, https://github.com/MSDLLCpapers/rsmart, https://msdllcpapers.github.io/rsmart/
BugReports: https://github.com/MSDLLCpapers/rsmart/issues
Encoding: UTF-8
Suggests: dplyr, knitr, pkgdown, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 3.5)
Imports: data.table, doFuture, foreach, Matrix, MASS, modelObj, mvtnorm, stats
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 14:37:41 UTC; manschoc
Author: Cole Manschot [aut, cre], Tabitha Peter [ctb], Gabriela Piasecki [ctb], Laura Frederick [ctb]
Maintainer: Cole Manschot <cole.manschot@msd.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:40:02 UTC

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New package riskweightedassets with initial version 1.1.1
Package: riskweightedassets
Title: Reproducible Risk-Weighted Asset Calculations
Version: 1.1.1
Description: Provides transparent, deterministic and auditable calculations of risk-weighted assets, own-funds requirements, interest-rate risk in the banking book and related capital metrics. It supports canonical in-memory tables and versioned spreadsheet datasets, strict validation, synthetic reference profiles, bitemporal snapshots, calculation controls and traceable regulatory source metadata. Methods are parameterised against the European Parliament and Council (2013) Capital Requirements Regulation <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32013R0575> and its amending Regulation (EU) 2024/1623 <https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1623>. A granular analyst API exposes individual formulae, domain views, controls, schemas and auditable parameter overrides. The implementation is intended for analytical, educational and model-validation use and does not constitute legal or supervisory advice.
License: GPL-3
Copyright: 2026 RiskDataScience GmbH
URL: https://github.com/rds0001/risk-weighted-assets-r
BugReports: https://github.com/rds0001/risk-weighted-assets-r/issues
Encoding: UTF-8
Date: 2026-09-14
Depends: R (>= 4.1.0)
Imports: digest, jsonlite, openxlsx, readxl, utils, yaml
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 16:20:54 UTC; qwert123
Author: Dimitrios Geromichalos [cre], RiskDataScience GmbH [aut, cph]
Maintainer: Dimitrios Geromichalos <riskdatascience@web.de>
Repository: CRAN
Date/Publication: 2026-09-24 13:50:10 UTC

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New package regstat with initial version 0.1.0
Package: regstat
Title: An Exact Test for a Change in Covariance (Dependence) Structure
Version: 0.1.0
Description: An exact finite-sample test for whether two groups share a covariance matrix, the omnibus form of the differential-network question. Under the Gaussian null the likelihood-ratio statistic has a distribution given by the real Jacobi ensemble that is free of the unknown common covariance, so a single Monte-Carlo calibration at the identity serves every covariance with no estimate of the nuisance covariance; this is the property that survives the dimension barrier, where estimating the covariance is hardest. The max-type high-dimensional test of Cai, Liu and Xia (2013) <doi:10.1080/01621459.2012.758041> is provided for comparison. A pure-C back-end does the numerics and also backs the 'Python' package 'regstat'.
URL: https://github.com/mtloots/regstat
BugReports: https://github.com/mtloots/regstat/issues
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: yes
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Packaged: 2026-09-14 15:44:51 UTC; home
Author: M. Theodor Loots [aut, cre]
Maintainer: M. Theodor Loots <theo.loots@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:40:09 UTC

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New package plasmidplot with initial version 0.1.0
Package: plasmidplot
Title: Publication-Quality Circular and Linear Plasmid Maps
Version: 0.1.0
Description: Draws circular and linear plasmid maps with 'grid' graphics. Features are shown as colored arcs with optional arrowheads, callout labels that are laid out to avoid overlap, an automatic base-pair scale, and the plasmid name and size. A style is built from a handful of shape parameters, with presets as named combinations of them, and the layout follows the molecule's topology. Maps can be built up feature by feature or imported from 'GenBank', 'EMBL', 'FASTA' and 'SnapGene' files, whose format is detected from content rather than file extension. Restriction sites can be located in the sequence and labeled. Ships eight visual styles, including one inspired by the 'AngularPlasmid' JavaScript library, and seven categorical palettes checked for colorblind safety. Palettes from other packages can be used directly, as a color vector or as a palette function, and checked against the same criteria.
License: MIT + file LICENSE
URL: https://github.com/dkturingfz/plasmidplot
BugReports: https://github.com/dkturingfz/plasmidplot/issues
Encoding: UTF-8
Imports: grDevices, grid, tools, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), xml2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 09:44:14 UTC; church
Author: Qiyou Pan [aut, cre]
Maintainer: Qiyou Pan <dkturingfz@outlook.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-09-24 13:30:09 UTC

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New package pacha with initial version 0.1.1
Package: pacha
Title: Reproducible Reporting for ChecklistBank Ethnobotanical Data
Version: 0.1.1
Description: Provides programmatic access to the 'Listado de plantas de uso y aprovechamiento sostenible en Ecuador' <doi:10.48580/dgvrn>. Acts as a client for the 'ChecklistBank' API and for processing 'ColDP' (Catalogue of Life Data Package) files. Supports data retrieval for ethnobotanical records and includes built-in Markdown report generation for reproducible workflows.
License: GPL (>= 3)
Language: en-US
URL: https://github.com/envinatu/pacha
BugReports: https://github.com/envinatu/pacha/issues
Imports: httr2, stats, tools, utils, yaml
Suggests: knitr, quarto, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 17:26:51 UTC; PC
Author: Marcelo F. Amores-Palma [aut, cre, cph]
Maintainer: Marcelo F. Amores-Palma <contacto.envinatu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:00:02 UTC

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New package nlmixr2scm with initial version 0.4
Package: nlmixr2scm
Title: Stepwise Covariate Modeling for 'nlmixr2' Models
Version: 0.4
Description: Stepwise covariate modeling (SCM) for nonlinear mixed-effects models fitted with 'nlmixr2'. Forward inclusion and backward elimination are driven by likelihood-ratio tests, and the covariate terms are generated inside the model body, so continuous covariates are centered and categorical covariates expanded into indicator columns without editing the model by hand. Candidate fits can be cached and resumed, fitted in parallel, and reviewed through per-step and all-candidate summary tables. The approach follows Jonsson and Karlsson (1998) <doi:10.1023/A:1011970125687>, and the implementation in 'Perl-speaks-NONMEM' described by Lindbom, Ribbing and Jonsson (2004) <doi:10.1016/j.cmpb.2003.11.003>.
Depends: R (>= 4.1)
License: GPL (>= 3)
URL: https://github.com/nlmixr2/nlmixr2scm
BugReports: https://github.com/nlmixr2/nlmixr2scm/issues
Imports: checkmate, cli (>= 3.4.0), data.table, lotri, nlme, nlmixr2est (>= 7.0.0), nlmixr2utils (>= 0.3), rxode2 (>= 5.0.0), stats, tools, utils
Suggests: future, knitr, nlmixr2data, pkgload, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-14 09:38:51 UTC; justin
Author: Justin Wilkins [aut, cre, cph] , Matthew Fidler [aut] , Yaping Liu [aut] , Bill Denney [aut] , Vipul Mann [aut], Vishal Sarsani [aut] , Christian Bartels [ctb]
Maintainer: Justin Wilkins <justin.wilkins@occams.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:30:14 UTC

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New package gdam with initial version 0.0.1
Package: gdam
Title: Fast Robust Additive Models using Gamma Divergence
Version: 0.0.1
Date: 2026-09-10
Description: Provides a computationally efficient method (at least at the time of development!) for robust additive modeling based on the gamma divergence, implementing the methodology of Hui, Ding, and Sugasawa (2026) <doi:10.1007/s11222-026-10960-3>. The method assumes an identity link and normally distributed errors, and applies the gamma divergence to the resulting restricted maximum likelihood function so as to obtain a loss function that is less sensitive to outlying responses. Because 'gdam' uses a model fitted via the 'mgcv' package as the starting point for optimization, and leverages many of its existing techniques for estimation and inference, users can take advantage of many of the smoothing options available in the 'mgcv' package for constructing additive models.
Maintainer: Francis KC Hui <fhui28@gmail.com>
License: GPL (>= 3)
Encoding: UTF-8
Imports: colorspace, ggplot2, gratia, Matrix, mgcv, stats
Suggests: spelling, tidyverse
Language: en-US
URL: https://github.com/fhui28/gdam
BugReports: https://github.com/fhui28/gdam/issues
NeedsCompilation: no
Packaged: 2026-09-14 09:46:04 UTC; fkch
Author: Francis KC Hui [aut, cre] , Shonosuke Sugasawa [ctb]
Repository: CRAN
Date/Publication: 2026-09-24 13:30:20 UTC

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New package FIAstemmap with initial version 2.0.0
Package: FIAstemmap
Title: Tree Canopy Modeling for USDA Forest Inventory and Analysis Plots
Version: 2.0.0
Description: Maps individual tree stem locations on field plots of the Forest Inventory and Analysis Program of USDA Forest Service (<https://research.fs.usda.gov/programs/nfi>). Stem locations are mapped in cartesian coordinate space based on field-measured distance and azimuth from subplot and microplot centers. Per-tree crown widths are estimated using a curated set of allometric equations with coverage for the conterminous US. Spatial descriptors of tree point pattern are computed at the whole plot level. Several stand height metrics are also computed and provided in the output. The spatial representation of modeled tree crowns is used to generate estimates of fractional tree canopy cover at the microplot, subplot and whole plot levels. Convenience functions are provided for efficient data processing. Exploratory data analysis is also facilitated via integration with the 'spatstat' packages.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Imports: bit64, cli, gdalraster (>= 2.5.0), grDevices, methods, spatstat.explore, spatstat.geom, stats
Suggests: glue (>= 1.6.0), spelling, testthat (>= 3.0.0), vctrs (>= 0.3.0)
URL: https://firelab.github.io/FIAstemmap/, https://github.com/firelab/FIAstemmap
BugReports: https://github.com/firelab/FIAstemmap/issues
Encoding: UTF-8
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-14 18:04:43 UTC; ctoney
Author: Chris Toney [aut, cre]
Maintainer: Chris Toney <jctoney@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 14:00:15 UTC

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New package bioIOT with initial version 0.2.2
Package: bioIOT
Title: Inverse Optimal Transport for Single-Cell Trajectory Analysis
Version: 0.2.2
Description: Semi-relaxed inverse optimal transport (IOT) for single-cell state-transition and pseudotime analysis: a self-contained R solver (Anderson-accelerated soft Sinkhorn with exact implicit gradients), feature-weight fitting with a two-stage bias-corrected refit and multi-restart, state transition matrices, random-walk pseudotime, 'ggplot2' visualisation, soft-gated 'Seurat' and 'SingleCellExperiment' interfaces, reproducible simulated demo data, and bulk-cohort pathway scoring utilities.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: utils, ggplot2
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, SingleCellExperiment, Seurat, SummarizedExperiment, S4Vectors
URL: https://github.com/XTSgreen/bioIOT-R
BugReports: https://github.com/XTSgreen/bioIOT-R/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-14 15:40:40 UTC; XTS-green
Author: Han Dong [aut, cre]
Maintainer: Han Dong <dh411424@163.com>
Repository: CRAN
Date/Publication: 2026-09-24 13:40:24 UTC

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New package rapsimng.lupin with initial version 0.1.0
Package: rapsimng.lupin
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Lupin Model
Version: 0.1.0
Description: Provides lupin-specific functions, processes and parameter sets used by lupin model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply lupin model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree (>= 0.1.1), tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://lupin.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.lupin
BugReports: https://github.com/byzheng/rapsimng.lupin/issues
NeedsCompilation: no
Packaged: 2026-09-14 08:06:25 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:30:02 UTC

More information about rapsimng.lupin at CRAN
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New package depguard with initial version 0.1.0
Package: depguard
Title: Manifest-Based Dependency Conflict Detection for Sandboxed R Sessions
Version: 0.1.0
Description: Provides lightweight, manifest-based checking of R package dependencies (including transitive dependencies) against the currently installed environment, without requiring a full project lockfile. Designed for sandboxed or ephemeral notebook environments (e.g. Kaggle, Colab, Binder) where 'renv'-style lockfile ownership is impractical. Includes session snapshot/diff tools (building on 'sessioninfo') to detect when an install silently changes the version of a package that is already loaded, and optional single-package version rollback.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: tools, utils, sessioninfo, cli
Suggests: remotes, pak, testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
URL: https://github.com/sunraycodes/depguard
BugReports: https://github.com/sunraycodes/depguard/issues
NeedsCompilation: no
Packaged: 2026-09-14 06:59:13 UTC; Kartik
Author: Samruddhi Amol Shah [aut, cre], Kartik Patel [aut], Amrit Pal [ctb]
Maintainer: Samruddhi Amol Shah <samruddhi.bitnbyte@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:20:02 UTC

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New package RserveTS with initial version 0.8.3
Package: RserveTS
Title: Typed Application Contracts for 'Rserve'
Version: 0.8.3
Description: Defines a typed application contract between R backends and 'TypeScript' clients over 'Rserve'. Users specify the API architecture with typed object capability (Ocap) functions and compile matching 'TypeScript' schemas and deployment scripts for the server. The companion library 'rserve-ts', available on npm <https://www.npmjs.com/package/rserve-ts>, provides the client-side runtime that consumes those schemas.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0), objectProperties, objectSignals
Imports: methods, rlang, Rserve, stats
Suggests: testthat (>= 3.0.0), withr
URL: https://tomelliott.co.nz/RserveTS/, https://github.com/tmelliott/RserveTS
BugReports: https://github.com/tmelliott/RserveTS/issues
NeedsCompilation: no
Packaged: 2026-09-14 03:40:29 UTC; tom
Author: Tom Elliott [aut, cre]
Maintainer: Tom Elliott <tom@inzight.co.nz>
Repository: CRAN
Date/Publication: 2026-09-24 04:40:02 UTC

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New package rapsimng.wheat with initial version 0.1.0
Package: rapsimng.wheat
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Wheat Model
Version: 0.1.0
Description: Provides wheat-specific functions, processes and parameter sets used by wheat model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply wheat model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather
Suggests: testthat (>= 3.0.0)
URL: https://wheat.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.wheat
BugReports: https://github.com/byzheng/rapsimng.wheat/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:16:34 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:02 UTC

More information about rapsimng.wheat at CRAN
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New package rapsimng.lentil with initial version 0.1.0
Package: rapsimng.lentil
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Lentil Model
Version: 0.1.0
Description: Provides lentil-specific functions, processes and parameter sets used by lentil model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply lentil model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree (>= 0.1.1), tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://lentil.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.lentil
BugReports: https://github.com/byzheng/rapsimng.lentil/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:20:20 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:08 UTC

More information about rapsimng.lentil at CRAN
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New package rapsimng.fababean with initial version 0.1.0
Package: rapsimng.fababean
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Fababean Model
Version: 0.1.0
Description: Provides fababean-specific functions, processes and parameter sets used by fababean model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply fababean model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://fababean.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.fababean
BugReports: https://github.com/byzheng/rapsimng.fababean/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:22:07 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:14 UTC

More information about rapsimng.fababean at CRAN
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New package rapsimng.chickpea with initial version 0.1.0
Package: rapsimng.chickpea
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Chickpea Model
Version: 0.1.0
Description: Provides chickpea-specific functions, processes and parameter sets used by chickpea model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply chickpea model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather (>= 0.3.0)
Suggests: testthat (>= 3.0.0)
URL: https://chickpea.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.chickpea
BugReports: https://github.com/byzheng/rapsimng.chickpea/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:24:15 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:19 UTC

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New package rapsimng.canola with initial version 0.1.0
Package: rapsimng.canola
Title: Crop-Specific Functions and Parameters for APSIM Next Generation Canola Model
Version: 0.1.0
Description: Provides canola-specific functions, processes and parameter sets used by canola model in the Agricultural Production Systems sIMulator ('APSIM') Next Generation. Includes tools for crop process calculations, parameter management and customisation, enabling users to explore, modify and apply canola model components.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: optree, tidyweather
Suggests: testthat (>= 3.0.0)
URL: https://canola.rapsimng.bangyou.me/, https://github.com/byzheng/rapsimng.canola
BugReports: https://github.com/byzheng/rapsimng.canola/issues
NeedsCompilation: no
Packaged: 2026-09-14 05:26:29 UTC; zhe00a
Author: Bangyou Zheng [aut, cre]
Maintainer: Bangyou Zheng <zheng.bangyou@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 05:00:25 UTC

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New package genoaligner with initial version 1.0.0
Package: genoaligner
Title: GPU-Portable Pairwise Sequence Alignment (WFA + Smith-Waterman)
Version: 1.0.0
Description: Pairwise sequence alignment from one portable C++17 core: edit-distance (Levenshtein / WFA-equivalent) and Smith-Waterman local alignment, both with score and CIGAR reconstruction. The core builds and runs anywhere (it is the CPU backend, so it needs no GPU toolchain); the wavefront/GPU backend (ROCm/CUDA) computes the same results with acceleration and is tracked in the sibling C++ repository. A batch API aligns many pairs in one call and reports how many were resolved, so silent under-serving is impossible. Designed to slot into data.frame/tibble pipelines.
URL: https://github.com/alrobles/genoaligner-r, https://alrobles.github.io/genoaligner-r/
BugReports: https://github.com/alrobles/genoaligner-r/issues
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: Rcpp
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spelling
SystemRequirements: C++17
NeedsCompilation: yes
Packaged: 2026-09-13 20:33:24 UTC; alrobles
Author: Angel Robles-Fernandez [aut, cre]
Maintainer: Angel Robles-Fernandez <a.l.robles.fernandez@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-24 04:20:02 UTC

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New package gcemod with initial version 0.3.0
Package: gcemod
Title: Generalized Competing Event Models with Lunn-McNeil Testing
Version: 0.3.0
Date: 2026-09-02
Description: Fits generalized competing event (GCE) models and estimates covariate effects on omega-plus, the ratio of the hazard for an event of interest to the hazard for a competing event, on both the cause-specific (Cox) and subdistribution (Fine-Gray) hazard scales. Confidence intervals and p-values are obtained from the Lunn-McNeil (1995) stacked (augmented) data approach. The package builds GCE risk scores from the model linear predictor, identifies risk-score cutpoints that maximize the separation in omega-plus between groups, and produces cumulative incidence ("alligator") plots by risk group and calibration plots of predicted versus observed omega-plus. It also compares covariate effects across the primary, competing, and total (composite) events, and estimates covariate effects on the ratio of cumulative incidence functions (a cumulative-incidence-scale GCE model). Methods follow Carmona et al. (2014) <doi:10.1016/j.ijrobp.2014.03.047>, Mell et al. (2024) <doi:10.1016/j.eururo.2 [...truncated...]
License: GPL (>= 2)
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 3.5.0)
Imports: survival, cmprsk, ggplot2 (>= 3.5.2), patchwork, stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-03 00:37:58 UTC; lorenmell
Author: Loren Mell [aut, cre]
Maintainer: Loren Mell <lmell@ucsd.edu>
Repository: CRAN
Date/Publication: 2026-09-24 04:20:07 UTC

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Wed, 23 Sep 2026

New package funHMM with initial version 0.1.0
Package: funHMM
Title: Hidden Markov Models for Functional Data
Version: 0.1.0
Description: Fits hidden Markov models to time-ordered sequences of curves, such as sample paths of stochastic processes or smoothed functional observations, without projecting the curves onto a finite basis. The emission functions are Onsager-Machlup functionals of Gaussian measures on function spaces, which allows for Brownian motion with drift, fractional Brownian motion, Ornstein-Uhlenbeck processes and non-parametric state means under a choice of Cameron-Martin norm. The Baum-Welch and Viterbi algorithms are implemented in C. Methods are described in Kashlak, Loliencar and Heo (2023) <https://jmlr.org/papers/v24/22-0685.html>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, graphics, grDevices
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-09-11 17:42:01 UTC; adam
Author: Adam B Kashlak [aut, cre]
Maintainer: Adam B Kashlak <kashlak@ualberta.ca>
Repository: CRAN
Date/Publication: 2026-09-24 04:00:02 UTC

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New package shinyreact with initial version 0.1.0
Package: shinyreact
Title: Client-Side 'React' Interface for 'Shiny'
Version: 0.1.0
Description: Server-side plumbing for the 'ui.tsx' pattern in 'Shiny': the user interface is defined in a client 'React' (<https://react.dev/>) bundle, and the 'Shiny' server contains only reactive computation. Provides page builders that discover and serve the client bundle, a render function that publishes any JSON-serializable value to the client, and custom messages to 'React' components. Ships no user interface components, so the app author owns the whole front end. The 'React' runtime and the client hooks are bundled, so no JavaScript build step is required to get started.
License: MIT + file LICENSE
URL: https://posit-dev.github.io/shinyreact/r/, https://github.com/posit-dev/shinyreact
BugReports: https://github.com/posit-dev/shinyreact/issues
Imports: brio, cli, htmltools, jsonlite, rlang, shiny (>= 1.13.0), utils
Suggests: knitr, later, rmarkdown, shinytest2, spelling, testthat (>= 3.0.0), withr
VignetteBuilder: knitr, rmarkdown
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-13 14:22:17 UTC; barret
Author: Barret Schloerke [cre, aut] , Winston Chang [ctb] , Garrick Aden-Buie [ctb] , Carson Sievert [ctb] , Posit Software, PBC [cph, fnd] , Meta Platforms, Inc. [cph]
Maintainer: Barret Schloerke <barret@posit.co>
Repository: CRAN
Date/Publication: 2026-09-23 04:20:02 UTC

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New package HRRI with initial version 1.0.6
Package: HRRI
Title: Diagnostics for Soil-Plant-Microbial Redox Recovery
Version: 1.0.6
Date: 2026-09-12
Description: Provides diagnostic functions for integrating longitudinal soil, plant and microbial observations during redox disturbance and recovery. Functions calculate stoichiometric potential oxygen demand, accessible electron capacity from explicitly supplied inventories and kinetic parameters, recovery signatures, fixed-reference domain scores, and exploratory multiblock scores with observation-coverage diagnostics. Memory is represented as a holobiont state accumulating from mineralogical, plant-acclimation and microbial-community legacies. An illustrative simulator produces closed Fe and Mn inventories alongside synthetic observations; its carbon, nitrogen, sulfur and oxygen budgets are not closed and its parameters are not calibrated to field rates. Simulation benchmarks assess agreement with a prescribed synthetic target and do not constitute empirical validation or parameter identification. Accuracy assessment is cluster-aware: intervals come from resampling whole trajectories, agreement [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: ggplot2 (>= 3.4.0), graphics, grid, igraph (>= 1.5.0), rlang (>= 1.1.0), stats, utils, tidyr, tidyselect
Suggests: ggtern (>= 3.4.0), knitr, patchwork (>= 1.2.0), psych, rmarkdown, testthat (>= 3.0.0), viridis
VignetteBuilder: knitr
URL: https://github.com/mghotbi/HRRI, https://mghotbi.github.io/HRRI/
BugReports: https://github.com/mghotbi/HRRI/issues
NeedsCompilation: no
Packaged: 2026-09-13 14:45:59 UTC; mitraghotbi
Author: Mitra Ghotbi [aut, cre] , Marjan Ghotbi [ctb]
Maintainer: Mitra Ghotbi <mitra.ghotbi@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-23 04:30:02 UTC

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Tue, 22 Sep 2026

New package visATC with initial version 1.0.0
Package: visATC
Title: Visualise the Anatomical Therapeutic Chemical (ATC) Hierarchy
Version: 1.0.0
Description: Visualisation and subsetting of the World Health Organisation Anatomical Therapeutic Chemical (ATC) classification system.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: tidyr, dplyr, rlang, igraph, methods, plotly, graphlayouts
Suggests: knitr, rmarkdown
Depends: R (>= 4.1.0)
URL: https://jnm212.github.io/visATC/
NeedsCompilation: no
Packaged: 2026-09-13 09:47:55 UTC; jmatt
Author: J Matthews [aut, cre, cph]
Maintainer: J Matthews <jnmatt212@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-23 04:00:02 UTC

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New package semeqmodels with initial version 0.1.0
Package: semeqmodels
Title: Equivalent Models in Structural Equation Models
Version: 0.1.0
Description: For identifying the sets of empirically equivalent models for structural equation models fitted by the 'lavaan' package developed by Rosseel (2012) <doi:10.18637/jss.v048.i02>.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), dagitty
Imports: lavaan (>= 0.7.2), modelbpp (>= 0.4.0), digest, manymome (>= 0.3.7), igraph, semPlot, semptools (>= 0.4.0), RColorBrewer, cli
Depends: R (>= 4.1.0)
URL: https://sfcheung.github.io/semeqmodels/
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-13 04:52:57 UTC; shufa
Author: Shu Fai Cheung [aut, cre] , Borui Yang [aut] , Wenting Xu [aut] , Wendie Yang [aut]
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-23 03:50:02 UTC

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New package FSHybridPLS with initial version 0.1.0
Package: FSHybridPLS
Title: Hybrid Penalized Partial Least Squares for Mixed Data
Version: 0.1.0
Description: Fits Penalized Partial Least Squares (PLS) regression when predictors are hybrid objects that combine functional curves (infinite-dimensional 'fda' objects) and scalar covariates (finite-dimensional numeric matrices). The package treats a hybrid predictor as an element of a product Hilbert space formed by the functional and Euclidean components, and implements the arithmetic (addition, scalar multiplication, and inner products, including roughness-penalized inner products) needed to run penalized PLS directly in that space. The algorithm extracts latent components that maximize covariance with a scalar response while penalizing roughness of the estimated functional coefficient curves. Helpers are included for constructing hybrid predictors, two-step within- and between-modality normalization, train/test splitting, synthetic data generation, cross-validated component selection, and prediction. The method is described in Mun and Jang (2026) <doi:10.48550/arXiv.2601.16364>.
License: MIT + file LICENSE
URL: https://github.com/Jong-Min-Moon/FShybridPLS
BugReports: https://github.com/Jong-Min-Moon/FShybridPLS/issues
Imports: fda (>= 6.1.3), stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
VignetteBuilder: knitr
Packaged: 2026-09-13 07:46:25 UTC; jongmin
Author: Jongmin Mun [aut, cre, cph]
Maintainer: Jongmin Mun <jongmin.mun@marshall.usc.edu>
Repository: CRAN
Date/Publication: 2026-09-23 04:00:09 UTC

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New package DACT with initial version 0.1.2
Package: DACT
Version: 0.1.2
Title: Design and Analysis for Clinical Trials
Author: Ping Gao [aut, cre]
Maintainer: Ping Gao <support@innovatiostat.com>
Description: The applications and evaluation of the operating characteristics of many statistical methodologies require the use of sophisticated software or extensive simulations. 'DACT' is designed to serve a wide range of innovative statistical designs and analyses. The primary objective of the 'DACT' software is to promote the understanding and application of cutting-edge statistical solutions in clinical trials. For this reason, the software is free for non-commercial scientific research, including but not limited to academic researchers and research/teaching institutions. Computing codes are available upon request. For more details see P. Gao (2024) <doi:10.1080/10543406.2024.2341673>.
Depends: clinfun, mvtnorm, doParallel
License: MIT + file LICENSE
Encoding: UTF-8
Imports: foreach, dplyr, jsonlite
URL: https://github.com/innovatiostat/rcode
BugReports: https://github.com/innovatiostat/rcode/issues
NeedsCompilation: no
Packaged: 2026-09-13 02:55:24 UTC; chengboqin
Repository: CRAN
Date/Publication: 2026-09-23 03:40:02 UTC

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New package BasicStatsPlots with initial version 0.1.0
Package: BasicStatsPlots
Title: Publication-Ready Data Visualization and Simple Statistical Inference
Version: 0.1.0
Description: Creates publication-ready data visualizations using 'ggplot2', together with tools for common simple statistical analyses (confidence intervals, ANOVA, linear and generalized regression). The package provides common chart types and analyses with built-in validation, customization options, and publication-friendly themes.
License: GPL-3
Encoding: UTF-8
Imports: broom, broom.helpers (>= 1.20.0), car, checkmate, dplyr, ggplot2 (>= 4.0.0), ggridges, gt, gtsummary, lmtest, MASS, nortest, patchwork, pROC, RColorBrewer, rlang, scales, tibble, tidyr
NeedsCompilation: no
Packaged: 2026-09-13 02:43:29 UTC; carce
Author: Quentin Ricros [aut], Theo Roussel [aut], Cedrik Carriere [aut, cre], Bouchra Nasri [aut]
Maintainer: Cedrik Carriere <carced2009@live.ca>
Repository: CRAN
Date/Publication: 2026-09-23 03:30:13 UTC

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New package WSwavelet with initial version 0.1.0
Package: WSwavelet
Title: Bayesian Wavelet Denoising with Wendland-Semicircle Slab Mixture
Version: 0.1.0
Date: 2026-09-12
Maintainer: Nilotpal Sanyal <nsanyal@utep.edu>
Description: Bayesian wavelet denoising using a resolution-adaptive spike-and-slab prior whose continuous slab is a mixture of a compactly supported Wendland-type density and the semicircle density. The package provides Gaussian and Laplace working-likelihood versions, empirical-Bayes fitting of resolution-specific slab weights, robust noise-scale estimation, posterior-mean coefficient shrinkage, reconstruction by the inverse discrete wavelet transform, and diagnostic tools.
License: GPL-2 | GPL-3
URL: https://nilotpalsanyal.github.io/WSwavelet/
BugReports: https://github.com/nilotpalsanyal/WSwavelet/issues
Depends: R (>= 4.1.0)
Imports: wavethresh
Suggests: testthat (>= 3.0.0), knitr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Repository: CRAN
Packaged: 2026-09-12 20:51:20 UTC; nsanyal
Author: Nilotpal Sanyal [aut, cre]
Date/Publication: 2026-09-23 02:40:09 UTC

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New package qapproach with initial version 0.1.1
Package: qapproach
Title: The Q Approach to Consensus Building
Version: 0.1.1
Description: Implements a workflow based on Q method to support consensus-building processes. It prepares participant rankings, selects and fits group perspectives, calculates consensus priority scores, validates results by bootstrap resampling, and produces publication-ready figures. The underlying method is described by Geschke et al. (2022) "The Q approach to consensus building: integrating diverse perspectives to guide decision-making" <doi:10.32942/X2F59S>.
License: GPL-3
URL: https://doi.org/10.5281/zenodo.11518485
BugReports: https://github.com/JonasGeschke/qapproach/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: fmsb, igraph, qmethod, withr
Suggests: hues, knitr, magick, pdftools, rmarkdown, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-12 20:10:10 UTC; geschke
Author: Jonas Geschke [aut, cre]
Maintainer: Jonas Geschke <hallo@qapproach.app>
Repository: CRAN
Date/Publication: 2026-09-23 02:50:02 UTC

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New package panglm with initial version 1.1.4
Package: panglm
Title: Generalized Linear Models for Panel Data
Version: 1.1.4
Description: Provides generalized linear models for panel data, including pooled, fixed-effects, and random-effects estimators for continuous, binary, and count outcomes. Offers a unified interface for fitting and analysing panel regression models, with efficient computation for large datasets. Estimators and tests follow standard panel-data references, including Hausman (1978) <doi:10.2307/1913827>, Chamberlain (1980) <doi:10.2307/2297110>, Allison and Waterman (2002) <doi:10.1111/1467-9531.00117>, and Croissant and Millo (2008) <doi:10.18637/jss.v027.i02>. Core numerical routines are implemented using 'Rcpp', 'RcppArmadillo', and 'RcppParallel'.
License: MIT + file LICENSE
URL: https://CRAN.R-project.org/package=panglm, https://github.com/ielbadisy/panglm
BugReports: https://github.com/ielbadisy/panglm/issues
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: Rcpp, data.table, graphics, stats
LinkingTo: Rcpp, RcppArmadillo, RcppParallel
Suggests: testthat (>= 3.0.0), plm, pglm, fixest, sandwich, survival, MASS, AER, glmmTMB, lme4, pscl, generics, broom, knitr, rmarkdown
SystemRequirements: GNU make
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-09-12 16:25:58 UTC; imad-el-badisy
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-22 07:10:02 UTC

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New package iod25 with initial version 1.0.0
Package: iod25
Title: English Indices of Deprivation (IoD25)
Version: 1.0.0
Description: Set of relative measures of deprivation for small areas (Lower-layer Super Output Areas) across England.
License: CC BY 4.0
URL: https://douglasmunro.github.io/iod25/
BugReports: https://github.com/douglasmunro/iod25/issues
Depends: R (>= 3.5)
Suggests: dplyr, knitr, rmarkdown, spelling, tibble
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-12 18:30:34 UTC; douglas
Author: Douglas Munro [aut, cre, cph]
Maintainer: Douglas Munro <douglas@douglasmunro.co.uk>
Repository: CRAN
Date/Publication: 2026-09-22 07:20:02 UTC

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New package EconEvalR with initial version 0.1.0
Package: EconEvalR
Title: Economic Evaluation Methods for Cost-Benefit, Partial Budgeting, and Cost-Effectiveness Analyses
Version: 0.1.0
Description: Provides functions for economic evaluation, including Cost-Benefit Analysis, Benefit-Cost Ratio, Net Present Value, Internal Rate of Return, Partial Budgeting, Budget Impact Analysis, Cost-Effectiveness Analysis, Decision Tree Analysis, One-Way, Two-Way, Multi-Way, and Probabilistic Sensitivity Analyses, Expected Value of Perfect Information, and Expected Value of Partial Perfect Information. The implemented methods are based on established approaches in economic evaluation and decision analysis; see Drummond et al. (2015, ISBN:9780199665884), Briggs et al. (2006, ISBN:9780198526629), Boardman et al. (2018, ISBN:9781108415996), and van Hout et al. (1994) <doi:10.1002/hec.4730030505>. The package produces summaries, graphical displays, and reproducible workflows for applications in veterinary science, agriculture, public health, epidemiology, health economics, and related fields.
License: MIT + file LICENSE
URL: https://github.com/vinodhpmd/EconEvalR
BugReports: https://github.com/vinodhpmd/EconEvalR/issues
Depends: R (>= 4.3.0)
Imports: cli (>= 3.6.2), mgcv
Suggests: covr, testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-12 17:03:32 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-22 07:10:09 UTC

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New package Compositionalcln with initial version 1.0
Package: Compositionalcln
Title: Modelling Compositional Data with Zero Values
Version: 1.0
Date: 2026-09-12
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: graphics, grDevices, mziln, rangen, Rfast, stats
Suggests: Compositional, Rfast2
Description: Modelling structural zeros in compositional data using a conditional logistic normal model as described by Aitchison (1986), where MLE (Maximum Likelihood Estimation) is performed via the EM (Expectation-Maximization) algorithm. The relevant paper is Alzeley and Tsagris (2026) <doi:10.48550/arXiv.2608.29954>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-09-12 17:50:16 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-09-22 07:10:16 UTC

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New package zot with initial version 0.1.2
Package: zot
Version: 0.1.2
Title: Access 'Zotero' Libraries
Description: Interface to the 'Zotero' reference manager <https://www.zotero.org> through its public web API and local client database. Provides paginated reads, versioned writes, read-only local queries, batch plans and resumable ledgers, bibliographic comparison, metadata mapping, file attachment, and optional semantic-index queries.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
URL: https://averriK.github.io/zot/
Depends: R (>= 4.1.0)
Imports: data.table, DBI, digest, httr2, jsonlite, RSQLite
Suggests: knitr, rmarkdown, testthat (>= 3.2.0)
VignetteBuilder: knitr, rmarkdown
SystemRequirements: Python 3 and zotero-mcp-server (optional, for ztSemantic())
NeedsCompilation: no
Packaged: 2026-09-12 11:49:05 UTC; averrik
Author: Alejandro Verri Kozlowski [aut, cre, cph]
Maintainer: Alejandro Verri Kozlowski <averri@fi.uba.ar>
Repository: CRAN
Date/Publication: 2026-09-22 06:20:02 UTC

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New package sptrends with initial version 1.6.3
Package: sptrends
Title: Statistical Inference for Spatiotemporal Trends in Gridded Data
Version: 1.6.3
Language: en-GB
Description: Provides a unified and reproducible framework for statistical inference of spatiotemporal trends in gridded environmental data. The framework addresses the interconnected challenges of serial correlation, spatial dependence and multiple testing that commonly arise when analysing gridded environmental time series. Its core methods support serial-correlation treatment through trend-preserving prewhitening, pixel-wise and spatially explicit trend inference, slope estimation and multiple-testing correction. These methods may be applied independently or integrated within configurable analytical workflows. Dedicated workflows are also provided to reproduce methodologies published in the scientific literature: Gutiérrez-Hernández and García (2025) <doi:10.1016/j.rsase.2024.101377> for the True Significant Trends workflow, Gutiérrez-Hernández and García (2024) <doi:10.3390/rs16203886> for the Robust Trend Analysis workflow, and Gutiérrez-Hernández and García (2025) <doi:10.3390/ [...truncated...]
License: GPL (>= 3)
URL: https://github.com/Olive-r/sptrends, https://olive-r.github.io/sptrends/
BugReports: https://github.com/Olive-r/sptrends/issues
Depends: R (>= 4.1)
Imports: terra (>= 1.7-0), Matrix, parallel, stats, utils, graphics, grDevices, withr (>= 2.2.0)
Suggests: fields, testthat (>= 3.2.0), knitr, rmarkdown, ncdf4, Kendall, modifiedmk, rkt, robslopes, trend, zyp
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-12 16:07:28 UTC; olive
Author: Oliver Gutierrez-Hernandez [aut, cre] , Luis V. Garcia [aut] , Spanish National Research Council , Seville, Spain)
Maintainer: Oliver Gutierrez-Hernandez <olivergh@uma.es>
Repository: CRAN
Date/Publication: 2026-09-22 07:00:09 UTC

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New package lexsync with initial version 0.1.0
Package: lexsync
Title: Lexical Optimisation and Hardware-Timed Experiment Generation
Version: 0.1.0
Description: A cross-platform toolkit that unifies many-language lexical-corpus access, parallel multidimensional stimulus matching, deterministic pseudoword generation, counterbalancing and the automated generation of experiments from a declarative trial-event model, for 'PsychoPy', 'OpenSesame' and the browser ('jsPsych'). The laboratory targets bind electroencephalography onset triggers to the stimulus flip. It is the R member of a dual-language pair; a structurally identical 'Python' package is also provided. Several paradigms (factorial word contrasts, lexical decision, priming, self-paced reading and cued categorisation) are supported, and each design is accompanied by a machine- and human-readable materials datasheet for reproducibility.
License: MIT + file LICENSE
Copyright: The MIT licence covers the source code only. The example lexica in inst/extdata are derived from third-party data and are distributed under CC BY-SA 4.0; the terms and the attribution they require are in the LICENSE.note file.
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.0.0)
Imports: readr, yaml, stringdist, stringi, jsonlite, digest, stats, tools, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spelling, clue, shiny, bslib, DT, zip
VignetteBuilder: knitr
URL: https://github.com/pablobernabeu/lexsync, https://pablobernabeu.github.io/lexsync/r/
BugReports: https://github.com/pablobernabeu/lexsync/issues
NeedsCompilation: no
Packaged: 2026-09-12 10:10:40 UTC; CodexSandboxOffline
Author: Pablo Bernabeu [aut, cre]
Maintainer: Pablo Bernabeu <pcbernabeu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-22 06:20:09 UTC

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New package Canton with initial version 0.0.8
Package: Canton
Title: Consistent Fonts and Figure Export for Scientific Publication Workflows
Version: 0.0.8
Description: Provides a unified interface for exporting figures created with base graphics, 'ggplot2', 'grid', 'pheatmap', and 'ComplexHeatmap' to PDF, PNG, JPEG, and TIFF files. Selects an appropriate rendering strategy based on the plot object and supports exporting a figure to multiple formats in one call. Also provides font configuration and diagnostics, reusable figure presets, publication-oriented themes, and colour palettes. The 'ggplot2' graphics framework is described by Wickham (2016, ISBN:978-3-319-24277-4).
License: GPL (>= 3)
URL: https://github.com/ScienceAdvances/Canton
BugReports: https://github.com/ScienceAdvances/Canton/issues
Encoding: UTF-8
Depends: R (>= 3.5)
Imports: ggplot2 (>= 3.4.0), systemfonts
Suggests: ComplexHeatmap, pheatmap, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-12 12:09:27 UTC; luther
Author: Tim Holy [aut, cre]
Maintainer: Tim Holy <email@timholy.com>
Repository: CRAN
Date/Publication: 2026-09-22 06:30:02 UTC

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New package BioMixModel with initial version 1.0.0
Package: BioMixModel
Title: Mixed Models for Biological, Clustered and Longitudinal Data
Version: 1.0.0
Description: Fits and interprets mixed-effects models for clustered, longitudinal and heterogeneous biological data. Provides variance partitioning, intraclass correlation, penalized likelihood summaries, a heterogeneous-data information criterion, model comparison, diagnostics, and ensemble-style summaries for multilevel data. The package is designed as a complementary, interpretable workflow around established mixed-model methods. Methods for intraclass correlation and variance partitioning are informed by Nakagawa and Schielzeth (2010) <doi:10.1111/j.1469-185X.2010.00141.x> and Nakagawa et al. (2017) <doi:10.1098/rsif.2017.0213>. Mixed-effects modeling approaches are described by Zuur et al. (2009) <doi:10.1007/978-0-387-87458-6>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0), glmmTMB, nlme, mgcv, survival, coxme, brms
URL: https://github.com/vinodhpmd/BioMixModel
BugReports: https://github.com/vinodhpmd/BioMixModel/issues
NeedsCompilation: no
Packaged: 2026-09-12 15:31:19 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-22 06:50:11 UTC

More information about BioMixModel at CRAN
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New package AI4OfficialStats with initial version 0.1.0
Package: AI4OfficialStats
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 using non-compensatory critical-error rules, weakest-link and geometric fidelity summaries, provenance graphs, and portable SHA-256 proof bundles. The package provides bounded connectors for official statistical services and an extensible HTTPS JSON API registry. Prompt perturbation, statistical red-team generation, minimal-pair tests, and benchmark data support reproducible evaluation of generative, retrieval-augmented, and agentic statistical systems. An embedded alignment layer maps claim-level controls to relevant activities of the Generic Statistical Business Process Model (GSBPM) 5.2, including Analyse, Disseminate, Evaluate, Quality Management, and Metadata Manag [...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: 2026-08-25 11:47:24 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: 2026-09-22 06:20:17 UTC

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New package OPCC with initial version 1.0.1
Package: OPCC
Title: Open Postal Code Correspondence
Version: 1.0.1
Description: An open, fully reproducible alternative to closed postal code conversion files, giving source-qualified many-to-many correspondence between Ontario postal codes and Statistics Canada 2021 census geographies. Every published artifact can be rebuilt step by step from public sources using the included build functions, so any user can reproduce and audit the conversion end to end. Lookup results retain allocation weights, evidence source, lineage, method, and vintage; unmatched postal codes remain explicit, and versioned release artifacts are checksum-verified before use. A built-in 'shiny' application provides a point-and-click interface for joining, mapping, and exporting results. Correspondences are derived from the Statistics Canada National Address Register <https://www150.statcan.gc.ca/n1/pub/46-26-0002/462600022022001-eng.htm>, the 2021 Census Geographic Attribute File <https://www12.statcan.gc.ca/census-recensement/2021/geo/aip-pia/attribute-attribs/index-eng.cfm>, and [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
URL: https://github.com/lennon-li/OPCC
BugReports: https://github.com/lennon-li/OPCC/issues
Depends: R (>= 4.1)
Imports: digest, jsonlite
Suggests: testthat (>= 3.0.0), curl, dplyr, readr, readxl, rlang, sf, knitr, rmarkdown, withr, shiny (>= 1.8.0), bslib (>= 0.6.0), DT, leaflet, htmlwidgets, chromote, processx, httpuv
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 20:33:43 UTC; yeli
Author: Lennon Li [aut, cre, cph]
Maintainer: Lennon Li <yeli@biostats.ai>
Repository: CRAN
Date/Publication: 2026-09-22 05:50:02 UTC

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Mon, 21 Sep 2026

New package summarisebig with initial version 0.1.0
Package: summarisebig
Title: Grouped Summaries for Large 'arrow' Datasets
Version: 0.1.0
Description: Provides a 'dplyr'-like interface for grouped summaries on large 'arrow' datasets. Complete summaries are attempted in 'arrow' first. When a result can be reconstructed from 'arrow'-computable sufficient statistics, an explicit MapReduce-style reduction and 'R' finalization strategy is available. For arbitrary 'R' functions that require raw group observations, complete groups are materialized in bounded chunks, with optional parallel execution and shared-memory processing. The MapReduce strategy follows the programming model described by Dean and Ghemawat (2008) <doi:10.1145/1327452.1327492>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: arrow, dplyr, future, future.mirai, futurize, furrr (>= 0.4.0), purrr, rlang
Suggests: knitr, mori, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
URL: https://github.com/larry77/summarisebig, https://larry77.github.io/summarisebig/
BugReports: https://github.com/larry77/summarisebig/issues
NeedsCompilation: no
Packaged: 2026-09-11 20:15:02 UTC; lorenzo
Author: Lorenzo Isella [aut, cre]
Maintainer: Lorenzo Isella <lorenzo.isella@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 22:30:02 UTC

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New package legendplot with initial version 0.4-1
Package: legendplot
Title: Standard and 'rgl' Plots with Legends
Version: 0.4-1
Date: 2026-09-11
Maintainer: Ruben Fernandez-Casal <rubenfcasal@gmail.com>
Depends: R (>= 2.14.0), graphics
Imports: rgl, grDevices
Suggests: fields, knitr
Description: Provides tools to combine standard R plots or 'rgl' 3D plots with a legend. Facilitates the creation of composite figures that mix 2D or 3D visualizations with a categorical or continuous legend.
License: GPL (>= 2)
URL: https://rubenfcasal.github.io/legendplot/, https://github.com/rubenfcasal/legendplot/
BugReports: https://github.com/rubenfcasal/legendplot/issues/
LazyData: yes
Encoding: UTF-8
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 19:54:33 UTC; ruben.fcasal
Author: Ruben Fernandez-Casal [aut, cre]
Repository: CRAN
Date/Publication: 2026-09-21 22:20:02 UTC

More information about legendplot at CRAN
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New package CLCM with initial version 0.1.1
Package: CLCM
Title: Estimate Confirmatory Latent Class Models
Version: 0.1.1
Description: Estimate confirmatory latent class models for a variety of item response types that are encountered in the clinical field. One or two timepoints are supported. Latent regression estimation can be performed, allowing for comparisons of longitudinal latent class assignments (e.g., treatment success/failure) across observed groups (e.g., treatment arms in clinical trials). Fit statistics C2 (a limited-information goodness-of-fit statistic), Akaike Information Criterion (AIC), and Bayesian Information Criterion (BIC) are available as well. Methods are described in Iaconangelo (2026) <doi:10.5281/zenodo.22663151>.
License: GPL (>= 3)
URL: https://github.com/CJangelo/CLCM, https://cjangelo.github.io/CLCM/
BugReports: https://github.com/CJangelo/CLCM/issues
Encoding: UTF-8
Imports: Matrix, numDeriv, stats, utils
Suggests: ggplot2, knitr, nnet, rmarkdown, scales
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-12 00:53:40 UTC; charl
Author: Charlie Iaconangelo [aut, cre]
Maintainer: Charlie Iaconangelo <charles.iaconangelo@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 22:50:11 UTC

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New package ValCurvaR with initial version 0.1.0
Package: ValCurvaR
Title: Validation of Analytical Calibration Curves
Version: 0.1.0
Description: Provides transparent tools for fitting and evaluating analytical calibration curves. Ordinary and weighted least squares fits are supported, together with lack-of-fit, heteroscedasticity and influence diagnostics, back-calculation, prediction uncertainty and publication-ready base graphics. The workflow is designed to support validation studies rather than rely on a single goodness-of-fit statistic. Methods follow Magnusson and Ornemark (2014) <https://www.eurachem.org/images/stories/Guides/pdf/MV_guide_2nd_ed_EN.pdf> and International Council for Harmonisation (2023) <https://database.ich.org/sites/default/files/ICH_Q2%28R2%29_Guideline_2023_1130_ErrorCorrection_2025.pdf>.
License: MIT + file LICENSE
URL: https://github.com/isaquebrand/ValCurvaR
BugReports: https://github.com/isaquebrand/ValCurvaR/issues
Encoding: UTF-8
Imports: graphics, grDevices, lmtest, nortest, outliers, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 11:43:01 UTC; isaqu
Author: Isaque Wilkson de Sousa Brandao [aut, cre]
Maintainer: Isaque Wilkson de Sousa Brandao <isaquebrand@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 21:20:02 UTC

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New package tbl.now with initial version 1.0.0
Package: tbl.now
Title: Tidy Data and Workflow Layer for Epidemic Nowcasting
Version: 1.0.0
Description: Defines tidy data structures and package-agnostic workflows for epidemiological nowcasting. The 'tbl_now' class records event, report, and revision dates alongside strata, covariates, censoring, and reporting-delay metadata while remaining compatible with 'dplyr'. Tools support validation, manipulation, diagnostics, visualization, format conversion, retrospective evaluation, and multiple modelling engines. The 'tbl_nowcast' class standardizes probabilistic predictions for plotting, scoring, comparison, and ensembling.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Depends: R (>= 4.2.0)
Suggests: almanac, baselinenowcast (>= 0.2.1), diseasenowcasting (>= 2.4.0), data.table, epidist (>= 0.4.1), EpiNow2 (>= 1.9.0), epinowcast (>= 0.7.0), knitr, modifiedmk (>= 1.6.0), NobBS (>= 1.1.1), patchwork, plotly, rmarkdown, scoringutils (>= 2.0.0), surveillance (>= 1.26.1), testthat (>= 3.0.0), tsibble, withr
Additional_repositories: https://epinowcast.r-universe.dev, https://davisvaughan.r-universe.dev, https://rodrigozepeda.r-universe.dev
Imports: cli, generics, grid, dplyr, ggplot2, lifecycle, lubridate, methods, pillar, rlang, S7, scales, stats, tibble, tidyr, tidyselect, utils
URL: https://rodrigozepeda.github.io/tbl.now/, https://github.com/RodrigoZepeda/tbl.now
BugReports: https://github.com/RodrigoZepeda/tbl.now/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 10:38:28 UTC; rodzepeda
Author: Rodrigo Zepeda-Tello [aut, cre] , Rami Yaari [aut] , Matteo Perini [aut] , Teresa Yamana [ctb] , Jeffrey Shaman [ctb] , Columbia University in the City of New York [cph, fnd]
Maintainer: Rodrigo Zepeda-Tello <rzepeda17@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 21:10:02 UTC

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New package spaci with initial version 0.1.1
Package: spaci
Title: Causal Effect Estimation Under Spatial Confounding and Interference
Version: 0.1.1
Description: Implements the distance-adjusted propensity score with interference (iDAPS) and recoverU+ methods for estimating the average treatment effect on the treated (ATT) from spatial observational data in the presence of both spatial confounding and spatial interference. iDAPS matches units on a data-driven composite of propensity-score distance, spatial proximity and neighbourhood-exposure distance. recoverU+ is a doubly robust estimator that augments the propensity-score and control-outcome models with a partially recovered spatial confounder and a neighbourhood-exposure term. The package also provides the naive propensity score, DAPS and recoverU comparators, and a simulator for the spatial confounding/interference data-generating process.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: geoR, ggplot2, readxl, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Ogunsolaia/spaci
BugReports: https://github.com/Ogunsolaia/spaci/issues
NeedsCompilation: no
Packaged: 2026-09-11 12:10:11 UTC; b71225io
Author: Isqeel Ogunsola [aut, cre], Olatunji Johnson [aut], Thomas House [aut]
Maintainer: Isqeel Ogunsola <isqeel.ogunsola@postgrad.manchester.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-21 21:30:02 UTC

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New package risq with initial version 3.0.0
Package: risq
Title: Representativity Indicators for Survey Quality
Version: 3.0.0
Maintainer: Reijer Idema <r.idema@cbs.nl>
Description: Calculate representativity indicators for survey quality based on survey data and response models. Use partial indicators to analyse the impact of individual variables and categories. Monitor changes in representativity during data collection. Improve representativity through adaptive survey design. Supports both R-indicators and coefficients of variation. See also Schouten, Cobben, Bethlehem (2009) <https://api.semanticscholar.org/CorpusID:33654901>, Shlomo, Skinner, Schouten (2012) <doi:10.1016/j.jspi.2011.07.008> and Schouten, Shlomo (2017) <doi:10.1111/insr.12159>.
License: EUPL-1.2
Encoding: UTF-8
Depends: R (>= 2.10)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 11:36:44 UTC; reijer
Author: Reijer Idema [aut, cre], Barry Schouten [aut]
Repository: CRAN
Date/Publication: 2026-09-21 21:10:17 UTC

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New package raddr with initial version 0.1.2
Package: raddr
Title: Show What an IP Address Literal Means Under Every Standard
Version: 0.1.2
Language: en-US
Description: Standards and implementations disagree about what an IP address literal means: the string "0177.0.0.1" is rejected by the dotted-quad grammar, read as 127.0.0.1 by browsers, and read as 177.0.0.1 by some 'inet_pton' implementations. Most libraries pick one reading and discard the rest. This package reports them all, alongside the reason codes that explain each one, and classifies parsed values against the IANA special-purpose address registries. It is pure R, performs no network access, and returns facts rather than allow or deny verdicts.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: rlang (>= 1.1.7), vctrs (>= 0.7.0)
URL: https://gitlab.com/bart-turczynski/raddr
BugReports: https://gitlab.com/bart-turczynski/raddr/-/issues
Suggests: bignum, bit64, digest, hedgehog, knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-10 18:22:52 UTC; bartturczynski
Author: Bart Turczynski [aut, cre] , web-platform-tests contributors [cph]
Maintainer: Bart Turczynski <bartek@turczynski.pl>
Repository: CRAN
Date/Publication: 2026-09-21 21:40:02 UTC

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New package gtstats with initial version 1.0.0
Package: gtstats
Title: Beginner-Friendly Statistics and Publication-Ready Tables
Version: 1.0.0
Description: Provides beginner-friendly functions for common descriptive and inferential statistical analyses, together with tools for creating publication-ready tables. The package includes data description, summary statistics, distribution assessment, group comparisons, effect sizes, correlations, proportions and rates with confidence intervals, crosstabs for epidemiological measures, plots, and modular table-building workflows. Statistical methods include unequal-variance comparisons described by Welch (1947) <doi:10.1093/biomet/34.1-2.28>, score confidence intervals described by Wilson (1927) <doi:10.1080/01621459.1927.10502953>, and robust variance assessment described by Brown and Forsythe (1974) <doi:10.1080/01621459.1974.10482955>.
URL: https://gtstats.thinkdenominator.com/, https://github.com/ThinkDenominator/gtstats
BugReports: https://github.com/thinkdenominator/gtstats/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: dplyr, tibble, gt, flextable, officer, stats, ggplot2, tidyselect
Suggests: shiny, rstudioapi, rio, testthat (>= 3.0.0), knitr, rmarkdown, pkgdown, webshot2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 14:56:33 UTC; drrubesh
Author: Rubeshkumar Polani [aut, cre] , Mogan Kaviprawin [aut] , Manikandanesan Sakthivel [aut] , Salin K Eliyas [aut] , Yuvaraj Krishnamoorthy [aut]
Maintainer: Rubeshkumar Polani <rubesh@thinkdenominator.com>
Repository: CRAN
Date/Publication: 2026-09-21 21:50:02 UTC

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New package CausalLoopAnalytics with initial version 1.0.0
Package: CausalLoopAnalytics
Title: Data-Driven Causal Loop and Feedback Network Analysis
Version: 1.0.0
Description: Provides tools for constructing signed causal-loop models, discovering directed causal relationships from time-series data using Granger-style tests, identifying and classifying reinforcing and balancing feedback loops, quantifying loop strength, assessing loop stability by bootstrap resampling, calculating network centrality and leverage-point scores, comparing causal-loop models, and producing publication-ready base R visualizations and summaries. The package is domain-agnostic and can be used in human medicine, veterinary medicine, agriculture, epidemiology, ecology, public health, and One Health. Methods are based on Granger (1969) <doi:10.2307/1912791> and Efron (1979) <doi:10.1214/aos/1176344552>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0)
URL: https://github.com/vinodhpmd/CausalLoopAnalytics
BugReports: https://github.com/vinodhpmd/CausalLoopAnalytics/issues
NeedsCompilation: no
Packaged: 2026-09-11 14:21:34 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 21:50:17 UTC

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New package nlcs with initial version 1.0
Package: nlcs
Title: N-LCS: Normative Latent Cognitive Structure
Version: 1.0
Description: Provides functions to construct a normative latent cognitive structure (N-LCS) from cognitive test data standardized to healthy controls, and to compute cognitive deviation magnitude (CDM) and cognitive deviation angle (CDA). Methods are described in Chen (2026) <doi:10.1080/23279095.2026.2691088>.
License: GPL-3
Encoding: UTF-8
Imports: EFAtools, psych, stats, utils
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-11 08:13:38 UTC; chenc
Author: Chen Chen [aut, cre]
Maintainer: Chen Chen <chench61@alumni.nu.ac.th>
Repository: CRAN
Date/Publication: 2026-09-21 21:00:02 UTC

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New package GARCHInfoLSTM with initial version 0.1.0
Package: GARCHInfoLSTM
Title: GARCH-Informed LSTM Model for Volatility Forecasting
Version: 0.1.0
Description: The proposed Generalized Autoregressive Conditional Heteroskedasticity (GARCH)-informed Long Short-Term Memory (LSTM) model follows the concept of physics-informed machine learning (PIML) by integrating established econometric knowledge of price volatility into a data-driven forecasting framework. In the model, conditional volatility estimated from the GARCH process is incorporated as an additional explanatory signal or volatility-based weighting component within the LSTM architecture. This enables the LSTM to learn nonlinear temporal dependencies while remaining informed by the underlying characteristics of agricultural price series, including volatility clustering, heteroscedasticity and market uncertainty. The optimized weighting parameter, lambda, controls the contribution of the GARCH-derived volatility information to the final prediction. Thus, the model combines the statistical interpretability of GARCH with the nonlinear learning capability of LSTM, producing a hybrid PIML fram [...truncated...]
Encoding: UTF-8
Imports: torch (>= 0.11.0), rugarch (>= 1.5.0), ggplot2 (>= 3.4.0), cli (>= 3.6.0), coro, stats, utils
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2026-09-08 11:41:08 UTC; YEASIN
Author: Md Yeasin [aut], Ranjit Kumar Paul [aut, cre], Manojit Mandal [aut], Pushkar Bora [aut]
Maintainer: Ranjit Kumar Paul <ranjitstat@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 20:50:08 UTC

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New package exposureEM with initial version 0.3.0
Package: exposureEM
Title: Combined-Exposure Models by EM and Marquardt Optimization
Version: 0.3.0
Description: Fits general two-component combined-exposure models for binary event histories when the event setting is not observed. The observed binary event is represented as the union of two latent component-specific binary events. Known exposure proportions enter as offsets. Parameters can be estimated by expectation-maximization, direct Marquardt-damped Newton-Raphson maximization of the observed likelihood, or a hybrid that uses several expectation-maximization iterations before direct optimization. Uncertainty is estimated with Louis' formula for the expectation-maximization estimator and the inverse observed Hessian for direct and hybrid fits. Complementary log-log, logit, and log component links are available for all three estimation methods.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, utils
NeedsCompilation: no
Packaged: 2026-09-11 07:17:45 UTC; anna
Author: Wenjing Meng [aut, cre]
Maintainer: Wenjing Meng <w2meng@ucsd.edu>
Repository: CRAN
Date/Publication: 2026-09-21 21:00:07 UTC

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New package DMAR with initial version 1.0.0
Package: DMAR
Title: Design, Measurement, and Analysis in R (DMAR)
Version: 1.0.0
Date: 2026-09-07
Imports: grDevices, MASS, generics, parallel, stats, utils, withr
Suggests: boot, car, ggplot2 (>= 3.4.0), ggrain, knitr, lavaan (>= 0.7-2), lme4, lmerTest, mvtnorm, nlme, OpenMx, patchwork, reformulas, rmarkdown, testthat (>= 3.2.0)
Description: Methods for design, measurement, and analysis, with the aim of being user friendly yet methodologically sound. 'DMAR' (pronounced "Dee-Mar") implements many advanced and nonstandard methods and makes them available for straightforward use, with interfaces, defaults, and documentation that are consistent across the package and grounded in the methodological literature, in support of sound and reproducible results. The package emphasizes effect size estimation with confidence intervals; sample size planning through accuracy in parameter estimation (AIPE) and power analysis (including composite power for designs whose conclusions require several results to hold at once), with minimum risk, sequential, and equivalence frameworks; reliability, agreement, and measurement more broadly, from coefficient omega with confidence intervals to measurement invariance; factor analysis and structural equation modeling, in which constructs, latent variables measured by multiple indicators, are modeled d [...truncated...]
Depends: R (>= 4.0.0)
URL: https://kenkelley.org, https://yelleknek.github.io/DMAR/, https://github.com/yelleKneK/DMAR
BugReports: https://github.com/yelleKneK/DMAR/issues
License: GPL (>= 3)
Encoding: UTF-8
Language: en-US
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-07 23:48:51 UTC; kkelley
Author: Ken Kelley [aut, cre]
Maintainer: Ken Kelley <kkelley@nd.edu>
Repository: CRAN
Date/Publication: 2026-09-21 20:50:14 UTC

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New package TaxResolveR with initial version 0.1.0
Package: TaxResolveR
Title: Taxonomic Name Resolution and Validation Tools
Version: 0.1.0
Description: Provides reproducible tools for cleaning, parsing, classifying, standardising, validating and resolving scientific names in ecological and biodiversity datasets. Taxonomic matches can be assessed for match quality and taxonomic status, records requiring manual review can be identified, and resolution results can be summarised, reported and exported. Taxonomic name resolution can use the 'GBIF' species matching service and the GBIF Backbone Taxonomy described by GBIF Secretariat (2023) <doi:10.15468/39omei>.
URL: https://github.com/prdelosriosescalante/TaxResolveR
BugReports: https://github.com/prdelosriosescalante/TaxResolveR/issues
License: GPL-3
Encoding: UTF-8
Language: en-GB
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Imports: httr2
NeedsCompilation: no
Packaged: 2026-09-11 05:40:53 UTC; tarea
Author: Patricio R. De los Rios-Escalante [aut, cre]
Maintainer: Patricio R. De los Rios-Escalante <patricio.delosrios.e@mail.pucv.cl>
Repository: CRAN
Date/Publication: 2026-09-21 18:10:02 UTC

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New package tradeIndices with initial version 0.1.0
Package: tradeIndices
Title: International Trade Intensity, Openness and Diversification Measures
Version: 0.1.0
Description: Calculates commonly used indicators for empirical international trade analysis from user-supplied data. Measures include trade openness, bilateral export and import intensity, the Herfindahl-Hirschman concentration index, normalized and entropy-based diversification, structural diversification relative to a benchmark, export similarity, trade complementarity, revealed comparative advantage, and intra-industry trade. Functions are vectorized where appropriate, validate economically meaningful inputs, and require no external data service. The definition of trade openness follows the World Bank indicator metadata <https://data.worldbank.org/indicator/NE.TRD.GNFS.ZS>. Methodological background for several trade indicators is provided by the World Bank's World Integrated Trade Solution <https://wits.worldbank.org/wits/wits/witshelp/Content/Utilities/e1.trade_indicators.htm> and the World Trade Organization (2012, ISBN:9789287038128).
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-11 05:38:56 UTC; majum
Author: Chiranjit Mazumder [aut, cre], Renjini V. R. [aut]
Maintainer: Chiranjit Mazumder <majumder.chira@icar.org.in>
Repository: CRAN
Date/Publication: 2026-09-21 18:00:02 UTC

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New package tiltdens with initial version 0.1.1
Package: tiltdens
Title: Tilted and Data-Sharpened Nonparametric Density Estimation
Version: 0.1.1
Description: High-order nonparametric density estimators built by perturbing a conventional kernel estimator, either by re-weighting the observations ("tilting") or by moving them ("data sharpening"). The perturbation is chosen so that the estimator inherits the fast convergence rate of an infinite-order kernel estimator, such as the sinc or trapezoidal flat-top estimator, while remaining a proper non-negative density without the oscillatory tails those estimators suffer from. Two criteria are provided: minimising the L2 distance to an infinite-order comparator, following Doosti and Hall (2016) <doi:10.1111/rssb.12112>, and minimising a cross-validation criterion that needs no comparator and is much faster, following Doosti, Hall and Mateu (2018) <doi:10.1016/j.jspi.2017.12.003>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.5.0)
Imports: graphics, stats, quadprog
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/DoostiH/tiltdens
BugReports: https://github.com/DoostiH/tiltdens/issues
NeedsCompilation: no
Packaged: 2026-09-10 23:52:21 UTC; MQ20173444
Author: Hassan Doosti [aut, cre, cph]
Maintainer: Hassan Doosti <hassan.doosti@mq.edu.au>
Repository: CRAN
Date/Publication: 2026-09-21 17:10:02 UTC

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New package peruocc with initial version 0.1.0
Package: peruocc
Title: Query and Standardize Biodiversity Occurrences in Peru
Version: 0.1.0
Description: Facilitates the retrieval, spatial validation, and integration of flora and fauna occurrence records across administrative units (districts and provinces) in Peru. Retrieves official boundary geometries via 'geoperu', queries and consolidates observations from the Global Biodiversity Information Facility (GBIF, <https://www.gbif.org/>) and 'iNaturalist' (<https://www.inaturalist.org/>), and standardizes attributes into a unified Darwin Core aligned structure. Designed for biodiversity assessments and spatial workflows within user-defined areas of interest.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, dplyr, geoperu, ggplot2, jsonlite, readr, rgbif, rinat, sf
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://paulesantos.github.io/peruocc/
BugReports: https://github.com/PaulESantos/peruocc/issues
NeedsCompilation: no
Packaged: 2026-09-11 03:06:36 UTC; PC
Author: Paul E. Santos Andrade [aut, cre, cph]
Maintainer: Paul E. Santos Andrade <paulefrens@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 17:50:02 UTC

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New package mechgraph with initial version 0.0.1
Package: mechgraph
Title: Mechanism Evidence Graph Data Model
Version: 0.0.1
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>
Description: Provides a lightweight graph data model for representing, combining, querying, and summarizing evidence-backed biological mechanism graphs. A mechgraph is an S3 list holding a node table, an edge table, and provenance metadata. The package implements builders that convert STRING and BioGRID interaction tables into mechgraph objects, combiners (mg_bind(), mg_combine()) that merge graphs while preserving duplicate evidence records, accessors (mg_nodes(), mg_edges(), mg_metadata()) and mutators (mg_add_*(), mg_drop_*()) for node and edge tables, filters by type, source, identifier, and score, induced-subgraph construction, structural validation (mg_validate()), and quality-control summaries (mg_qc()). Szklarczyk et al. (2023) <doi:10.1093/nar/gkac1000> Oughtred et al. (2021) <doi:10.1002/pro.3938>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: igraph
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-11 05:02:37 UTC; wang
Repository: CRAN
Date/Publication: 2026-09-21 18:00:08 UTC

More information about mechgraph at CRAN
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New package matsketch with initial version 0.1.0
Package: matsketch
Title: Randomized Matrix Computations from Few Entries and Products
Version: 0.1.0
Description: Implements recent randomized algorithms that answer questions about a large positive-semidefinite matrix while touching only a small part of it. Randomly pivoted Cholesky builds a low-rank approximation from a few rows of a kernel matrix (Chen, Epperly, Tropp and Webber (2025) <doi:10.1002/cpa.22234>), with an accelerated variant based on rejection sampling (Epperly, Tropp and Webber (2025) <doi:10.1137/24m1699048>). The XTrace, XNysTrace and XDiag estimators recover the trace and diagonal of a matrix that is available only through matrix-vector products (Epperly, Tropp and Webber (2024) <doi:10.1137/23m1548323>), alongside the Hutch++ estimator of Meyer, Musco, Musco and Woodruff (2021) <doi:10.1137/1.9781611976496.16>. Randomized Nystrom preconditioning speeds up the conjugate gradient method for regularized linear systems (Frangella, Tropp and Udell (2023) <doi:10.1137/21m1466244>). These pieces are combined to fit restricted maximum likelihood variance [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats
Suggests: knitr, Matrix, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/mqfarooqi1/matsketch, https://mqfarooqi1.github.io/matsketch/
BugReports: https://github.com/mqfarooqi1/matsketch/issues
NeedsCompilation: no
Packaged: 2026-09-11 01:03:34 UTC; faroo
Author: Muhammad Farooqi [aut, cre]
Maintainer: Muhammad Farooqi <mqfarooqi@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-21 17:20:02 UTC

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Fri, 18 Sep 2026

New package attrition with initial version 1.0.0
Package: attrition
Title: Addressing Nonignorable Attrition with Double Sampling and Bounds
Version: 1.0.0
Description: Implements the double-sampling bounds estimator of Coppock, Gerber, Green, and Kern (2017) <doi:10.1017/pan.2016.6> for randomized experiments with nonignorable missing outcomes. Provides worst-case (Manski) bounds, double-sampling bounds with analytic variance and Imbens-Manski confidence intervals, Lee (2009) <doi:10.1111/j.1467-937X.2009.00536.x> trimming bounds with analytic and bootstrap standard errors, covariate adjustment via poststratification, and a sensitivity analysis for violations of the outcome stability assumption.
Depends: R (>= 4.1.0)
Imports: generics, ggplot2, tibble
Encoding: UTF-8
License: GPL-3
URL: https://alexandercoppock.com/attrition/, https://github.com/acoppock/attrition
BugReports: https://github.com/acoppock/attrition/issues
Suggests: dplyr, estimatr, knitr, purrr, rmarkdown, testthat (>= 3.0.0), vayr (>= 1.1.0)
VignetteBuilder: knitr
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-10 20:30:46 UTC; alexandercoppock
Author: Alexander Coppock [aut, cre], Alan S. Gerber [aut], Donald P. Green [aut], Holger L. Kern [aut]
Maintainer: Alexander Coppock <acoppock@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-18 12:00:01 UTC

More information about attrition at CRAN
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New package typedjson with initial version 0.1.0
Package: typedjson
Title: Type-Faithful and Human-Readable JSON for R Values
Version: 0.1.0
Description: Writing an R value as JSON that a human can read, and reading it back unchanged. The 'jsonlite' package offers either a readable but lossy pair of functions or a faithful but verbose one; this package emits ordinary JSON for ordinary values and annotates only what JSON cannot express, namely the distinction between integer and double, typed missing values, non-finite numbers, attributes, and objects from the S3, S4 and S7 systems.
License: MIT + file LICENSE
Copyright: The bundled 'yyjson' code in src/ is Copyright (c) 2020 YaoYuan and distributed under the MIT license. See file YYJSON-LICENSE for its full text.
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.3)
LinkingTo: cpp11
Imports: methods
Suggests: jsonlite, knitr, R6, rmarkdown, S7, testthat (>= 3.0.0), withr
VignetteBuilder: knitr, rmarkdown
URL: https://nbenn.github.io/typedjson/
BugReports: https://github.com/nbenn/typedjson/issues
NeedsCompilation: yes
Packaged: 2026-09-10 11:13:06 UTC; coder
Author: Nicolas Bennett [aut, cre, cph], YaoYuan [ctb, cph]
Maintainer: Nicolas Bennett <nicolas@cynkra.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:20:02 UTC

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New package TrialFlowR with initial version 1.0.0
Package: TrialFlowR
Title: Clinical Trial Flow and Participant Disposition
Version: 1.0.0
Description: Summarizes participant flow and disposition in clinical trials, including CONSORT-style randomized controlled trials, parallel-group, crossover, cluster randomized, and multi-arm trials. Provides functions for screening failures, exclusions and reasons, allocation, follow-up, loss to follow-up, withdrawals, intention-to-treat and per-protocol populations, and participant-disposition summaries. The methods are based on established principles for reporting participant flow and disposition in randomized trials; see Schulz et al. (2010) <doi:10.1136/bmj.c332>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.2.0)
Suggests: testthat (>= 3.0.0), spelling
URL: https://github.com/vinodhpmd/TrialFlowR
BugReports: https://github.com/vinodhpmd/TrialFlowR/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-10 15:18:58 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:40:07 UTC

More information about TrialFlowR at CRAN
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New package SCAtools with initial version 0.4.3
Package: SCAtools
Title: Direction-Aware Sufficiency Condition Analysis
Version: 0.4.3
Date: 2026-09-10
Description: Provides a direction-aware interface for analysing bivariate sufficiency statements from empty-space frontier patterns. Logical sufficiency directions (high or low levels of a condition and outcome) are kept separate from the physical location of the empty corner in the scatter plot. Computation is delegated to version 5 of the 'NCA' package based on Dul (2016) <doi:10.1177/1094428115584005>, using the contraposition between necessity and sufficiency. Threshold tables are computed in actual units and converted by this package, so percentage, percentile and standard-deviation scales follow one stated reporting convention in every sufficiency direction. Includes tidy summaries, threshold rules, plots, random-data generation, permutation tests, and power analysis. An ordinary least-squares line can be drawn beside the frontier as a central-tendency reference; it is an average-effect summary and never a component of a sufficiency claim. An empty-space pattern alone does not establish [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: ggplot2 (>= 3.4.0), NCA (>= 5.0.2), stats, utils
Suggests: testthat (>= 3.0.0)
URL: https://github.com/youngchanresearcher/SCAtools
BugReports: https://github.com/youngchanresearcher/SCAtools/issues
NeedsCompilation: no
Packaged: 2026-09-10 14:17:41 UTC; furfa
Author: Young Chan [aut, cre]
Maintainer: Young Chan <youngchanresearcher@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:40:11 UTC

More information about SCAtools at CRAN
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New package sasctl with initial version 0.9.0
Package: sasctl
Title: Easily Communicate Between the "SAS Viya" Platform and R
Version: 0.9.0
Description: The 'sasctl' (sas control) package enables easy communication between the "SAS Viya" platform APIs <https://developer.sas.com> and the R runtime. It offers convenient wrappers to some most used endpoints.
License: Apache License (>= 2)
Encoding: UTF-8
Suggests: future, furrr, testthat (>= 3.0.0), httptest, knitr, rmarkdown, tidymodels, xgboost, rstudioapi
Imports: jsonlite, httr, uuid, ROCR, utils, reshape2, methods, base64enc, glue
URL: https://sassoftware.github.io/r-sasctl/
BugReports: https://github.com/sassoftware/r-sasctl/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-10 17:57:25 UTC; edhell
Author: Eduardo Hellas [aut, cre], SAS [cph, fnd]
Maintainer: Eduardo Hellas <ehellas@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:50:02 UTC

More information about sasctl at CRAN
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New package mpem with initial version 0.1.0
Package: mpem
Title: Matrix Partial EM for Incomplete Matrix-Normal Data
Version: 0.1.0
Description: Fits single-component and finite-mixture Kronecker-structured matrix-normal models and imputes incomplete matrix-variate data using matrix partial expectation-maximization. General MPEM handles arbitrary missingness, while Rect-MPEM exploits rectangular structural missingness. The methods are described in Lu, Andrews and Browne (2026) "An Efficient EM Algorithm for Both Element-Wise and Structural Missingness in Matrix-Variate Normal Mixture Models" <doi:10.48550/arXiv.2609.00616>.
License: MIT + file LICENSE
URL: https://github.com/LHZMix/MPEM
BugReports: https://github.com/LHZMix/MPEM/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-09-08 18:42:15 UTC; Hanzhang
Author: Hanzhang Lu [aut, cre, cph], Jeffrey L. Andrews [aut, ths], Ryan P. Browne [aut]
Maintainer: Hanzhang Lu <hanzhang.lu@ubc.ca>
Repository: CRAN
Date/Publication: 2026-09-18 11:50:08 UTC

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New package gridHR with initial version 1.0.0
Package: gridHR
Title: Grid-Based Home-Range Analysis and Radial Space-Use Profiles
Version: 1.0.0
Description: Tools for estimating and exploring animal home ranges from geographical locations using regular spatial grids of square or hexagonal cells; see Ford and Krumme (1979) <doi:10.1016/0022-5193(79)90366-7>. The package includes grid-based home-range estimation across different cell sizes, analyses of the relationship between grid-cell size and home-range area and spatial connectivity, and rarefaction analyses to evaluate how home-range estimates change with increasing numbers of locations. It also introduces a novel radial approach for characterizing the internal organization of space use by quantifying how space-use intensity changes with increasing distance from the centre toward the periphery of the home range.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, ggplot2, sf
Depends: R (>= 4.1)
LazyData: true
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-10 08:47:46 UTC; norberello
Author: Norberto Asensio [aut, cre]
Maintainer: Norberto Asensio <norberto.asensio@ehu.eus>
Repository: CRAN
Date/Publication: 2026-09-18 11:20:08 UTC

More information about gridHR at CRAN
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New package gRaphiaExtra with initial version 0.26.9
Package: gRaphiaExtra
Title: An R Package for Integrating 'Seurat' Objects into 'gRaphia'
Version: 0.26.9
Maintainer: Nilabhra R Das <n.das@uq.edu.au>
Description: Utilising graph-based network analysis frameworks, 'Graphia' <https://graphia.app/> is a powerful open source visual analytics application developed to aid the interpretation of large and complex datasets. For more details, see article by Freeman et al. (2022) <doi:10.1371/journal.pcbi.1010310>. 'gRaphia' is an extension of the 'Graphia' application within the R environment, providing tools for network analysis and visualisation. 'gRaphiaExtra' provides additional functionality specifically designed for single-cell RNA-sequencing data, enabling users to seamlessly integrate and utilise existing 'Seurat' analysis outputs in 'gRaphia'. The package also provides supplementary functions to support and enhance the 'gRaphia' analysis framework.
License: GPL-3
Depends: R (>= 4.4.2.0)
Imports: checkmate, dplyr, stats, utils
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-10 19:29:44 UTC; nilabhra.das
Author: Nilabhra R Das [cre, aut] , Kaitlyn A Flynn [aut] , John P Kemp [aut]
Repository: CRAN
Date/Publication: 2026-09-18 11:50:13 UTC

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New package ggrank with initial version 0.1.0
Package: ggrank
Title: Visualise Changes in Rankings with 'ggplot2'
Version: 0.1.0
Description: Calculates, inspects, tabulates, and visualises changes in rankings across two to four ordered states. Creates 'ggplot2'-based rank-transition charts that retain categories entering or leaving a selected top-rank boundary. Supports ranks calculated from numeric values as well as authoritative ranks supplied without values.
License: MIT + file LICENSE
URL: https://thinkdenominator.github.io/ggrank/, https://github.com/ThinkDenominator/ggrank
BugReports: https://github.com/ThinkDenominator/ggrank/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
LazyData: true
Imports: dplyr, ggplot2, rlang, scales
Suggests: knitr, pkgdown, rmarkdown, rstudioapi, shiny, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-10 16:28:24 UTC; drrubesh
Author: Rubeshkumar Polani [aut, cre] , Think Denominator [cph]
Maintainer: Rubeshkumar Polani <rubesh@thinkdenominator.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:40:02 UTC

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New package fibermargin with initial version 0.1.0
Package: fibermargin
Title: Categorical Mask and Spatial Label Refinement
Version: 0.1.0
Description: Implements 'FiberMargin', a deterministic training-free operator for repairing categorical masks and spatial labels from coordinates and labels alone. Its primary multiclass operator uses rotated space-filling-curve charts and two-sided class enclosure at one fixed geometric transport range. A class-balanced, isolation-protected chart-disagreement rule provides pointwise repair decisions and audit scores. An auxiliary nearest-neighbour ballot handles binary masks. The 'C++' engine supports two- and three-dimensional coordinates, removes constant axes independently within each specimen, and reuses one deterministic CPU worker budget without nested process pools. Reproducible mask corruptions, planar and volumetric simulators, damage-aware evaluation, and compact licensed human dorsolateral prefrontal cortex and colorectal cancer benchmarks support assessment.
License: MIT + file LICENSE
URL: https://tkcaccia.github.io/fibermargin/, https://github.com/tkcaccia/fibermargin
BugReports: https://github.com/tkcaccia/fibermargin/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp, parallel
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), ggplot2, dplyr, tidyr, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-09-10 16:52:06 UTC; stefano
Author: Stefano Cacciatore [aut, cre, cph]
Maintainer: Stefano Cacciatore <tkcaccia@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:50:18 UTC

More information about fibermargin at CRAN
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New package biocohort with initial version 0.1.1
Package: biocohort
Title: Cohort Objects for Subjects and Samples in Omics Studies
Version: 0.1.1
Description: Keeps the subjects, samples, and analysis outputs of a study in one validated object. It starts from a sample manifest with one row per sample, which is read, checked, and split into a subject table and a sample map. Species and assay are plain values in those tables rather than fixed types, so the same object serves any organism and any omics assay. From that object the package writes the sample sheet a pipeline expects, pairs tumor and normal samples on demand, and records where each analysis writes its output so the files can be loaded back in by subject or by pair. Manual corrections are kept in an audit trail. Results can also be translated across genome builds or species, with liftover for coordinates and ortholog mapping for genes.
License: MIT + file LICENSE
URL: https://www.samuelbharti.com/biocohort/, https://github.com/samuelbharti/biocohort
BugReports: https://github.com/samuelbharti/biocohort/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: S7, cli, rlang, checkmate, fs, readr, dplyr (>= 1.1.0), tibble
Suggests: testthat (>= 3.0.0), pkgdown, knitr, rmarkdown, rtracklayer, GenomicRanges, IRanges, S4Vectors, babelgene, withr, readxl, writexl, arrow, SummarizedExperiment, SeuratObject, yaml
SystemRequirements: CrossMap (optional, for the CrossMap liftover backend)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-10 09:44:30 UTC; Samuel
Author: Samuel Bharti [aut, cre, cph] , Barret Schloerke [ths] , Carson Sievert [ths] , Posit Software, PBC [cph, fnd]
Maintainer: Samuel Bharti <samuelbharti.io@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-18 11:20:14 UTC

More information about biocohort at CRAN
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Thu, 17 Sep 2026

New package spatstat.convert with initial version 1.0-1
Package: spatstat.convert
Title: Extension to 'spatstat' for Converting Data Formats
Version: 1.0-1
Date: 2026-09-10
Depends: R (>= 3.4.0), spatstat (>= 3.6-2), spatstat.geom (>= 3.8-2), spatstat.linnet (>= 3.5-3), sp (>= 2.1), stats, graphics, methods
Imports: spatstat.utils (>= 3.2-4), spatstat.univar (>= 3.2-0)
Suggests: terra (>= 1.7-83), sf (>= 1.0-21)
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>
Description: Extension to the 'spatstat' package, enabling the user to convert spatial data between formats defined in `spatstat' and formats defined in 'sp', 'sf' and 'terra'.
License: GPL (>= 2)
ByteCompile: true
NeedsCompilation: no
Packaged: 2026-09-10 02:20:12 UTC; adrian
Author: Adrian Baddeley [aut, cre], Ege Rubak [aut], Rolf Turner [aut], Edzer Pebesma [aut], Roger Bivand [aut], Michael Sumner [ctb], Matthew Lewis [ctb], Mathieu Rajerison [ctb], Mehdi Moradi [ctb]
Repository: CRAN
Date/Publication: 2026-09-17 14:40:02 UTC

More information about spatstat.convert at CRAN
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New package rGrSPTT with initial version 0.1.0
Package: rGrSPTT
Title: Group Sampling Inspection Plan for Time Truncated Life Test
Version: 0.1.0
Description: Designing group acceptance sampling inspection plans under time-truncated life tests. The package calculates the required minimum number of groups subject to a consumer's risk constraint on the probability of acceptance. Users can supply failure probabilities obtained from any lifetime distribution, allowing the methodology to be applied without restricting the analysis to a particular probability model. The package also provides a function for plotting the required minimum number of groups against the termination ratio. Saha et al. (2025) <doi:10.1007/s41872-025-00305-w>; Tripathi et al. (2020) <doi:10.1080/02664763.2020.1759031>; Tripathi and Aslam (2024) <doi:10.1285/i20705948v17n3p636>.
License: GPL-3
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-10 06:03:11 UTC; Admin
Author: Harsh Tripathi [aut, cre], Mahendra Saha [aut]
Maintainer: Harsh Tripathi <rsearchstat21@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 14:40:28 UTC

More information about rGrSPTT at CRAN
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New package rgrpc with initial version 0.1.1
Package: rgrpc
Title: Asynchronous 'gRPC' Client and Server Runtime
Version: 0.1.1
Date: 2026-09-09
Description: A first-class asynchronous 'gRPC' <https://grpc.io/> runtime built on the generic asynchronous 'C++' API ('GenericStub', 'AsyncGenericService') <https://grpc.github.io/grpc/cpp/>. Requests and responses cross the native boundary as method names plus opaque byte buffers; 'RProtoBuf' supplies and consumes the bytes, so schemas are loaded at runtime and no generated service stubs are required. Native completion threads never call the R API: completions are queued natively and delivered in batches on the R main thread. Complements 'RProtoBuf' rather than replacing it. Links against the system 'gRPC' library for 'C++'.
License: Apache License (>= 2)
URL: https://github.com/cornball-ai/rgrpc
BugReports: https://github.com/cornball-ai/rgrpc/issues
Depends: R (>= 4.3.0)
Imports: methods
Suggests: RProtoBuf, tinytest
SystemRequirements: gRPC C++ and protobuf libraries with development headers, found via 'pkg-config grpc++ protobuf' (Ubuntu/Debian: 'libgrpc++-dev', 'libprotobuf-dev'; on Windows both ship with Rtools 4.3 and later).
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-09-10 01:55:42 UTC; troy
Author: Troy Hernandez [aut, cre] , cornball.ai [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-09-17 14:40:21 UTC

More information about rgrpc at CRAN
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New package rcxl with initial version 0.1.0
Package: rcxl
Title: Read xlsx Files with a Native Parser
Version: 0.1.0
Description: Reads tabular data from xlsx files with a specialized C parser. Worksheet XML is scanned in a single pass and decoded directly into R vectors, with no intermediate document model. Bundles the 'miniz' and 'libdeflate' decompressors to read the underlying archive.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://github.com/vlshields/rcxl
BugReports: https://github.com/vlshields/rcxl/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Suggests: readxl, cellranger
NeedsCompilation: yes
Packaged: 2026-09-09 23:03:10 UTC; pots
Author: Vincent Shields [aut, cre, cph], Rich Geldreich [ctb, cph] , Tenacious Software LLC [cph] , RAD Game Tools and Valve Software [cph] , Martin Raiber [ctb, cph] , Alex Evans [ctb] , Alistair Moffat [ctb] , Jyrki Katajainen [ctb] , Eric Biggers [ctb, cp [...truncated...]
Maintainer: Vincent Shields <vince.shields913@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 14:20:02 UTC

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New package Coreset with initial version 1.0.0
Package: Coreset
Title: Discrete Diversity, Dispersion, and Coverage Subset Selection
Version: 1.0.0
Description: Solves discrete location objectives on a distance matrix or Euclidean coordinate set. The Max-Min Diversity (MMDP / p-dispersion) objective, which maximizes the minimum pairwise distance within a selection of k items, is solved by farthest-first selection (Gonzalez 1985) <doi:10.1016/0304-3975(85)90224-5>; the DropAdd tabu-search heuristic (Porumbel, Hao & Glover 2011) <doi:10.1007/s10479-011-0898-z>, GRASP with path-relinking (Resende, Marti, Gallego & Duarte 2010) <doi:10.1016/j.cor.2008.05.011>, and an exact node-packing integer program (Sayyady & Fathi 2016) <doi:10.1016/j.ejor.2016.02.026>. The Max-Mean Dispersion objective, which selects a subset of unrestricted size maximising the sum of its pairwise distances divided by the number of selected elements, is solved by reinforcement-learning-guided tabu search (Nijimbere et al. 2020) <doi:10.3934/jimo.2020115>. The discrete k-centre (min-max covering / facility location) objective, which ch [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: cli (>= 3.0.0), Rcpp, Rdpack (>= 0.7), stats
Suggests: highs, knitr, Matrix, quarto, rprojroot, spelling, testthat (>= 3.0.0)
VignetteBuilder: quarto
LinkingTo: Rcpp
URL: https://ms609.github.io/Coreset/
BugReports: https://github.com/ms609/Coreset/issues
ByteCompile: true
NeedsCompilation: yes
Packaged: 2026-09-10 06:44:59 UTC; pjjg18
Author: Martin R. Smith [aut, cre, cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-17 14:50:29 UTC

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New package OmopIndices with initial version 0.1.0
Package: OmopIndices
Title: Patient-Level Indices from the OMOP Common Data Model
Version: 0.1.0
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>
Description: Provides tools to derive standardised, reproducible patient-level indices and covariates from Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) databases. Functions calculate comorbidity and frailty scores, including the Charlson Comorbidity Index, Electronic Frailty Index, and Hospital Frailty Risk Score, as well as body mass index, polypharmacy, ethnicity, location, and socioeconomic status measures.
License: Apache License (>= 2)
Encoding: UTF-8
Suggests: CDMConnector, CodelistGenerator, CohortConstructor, DBI, duckdb, gt, here, htmltools, knitr, odbc, omock, PhenotypeR, rmarkdown, RPostgres, testthat, visOmopResults
URL: https://OHDSI.github.io/OmopIndices/
BugReports: https://github.com/OHDSI/OmopIndices/issues
Imports: cli, clock, dplyr, omopgenerics (>= 1.4.0), PatientProfiles, purrr, rlang
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-09-09 17:30:20 UTC; martics
Author: Marti Catala [aut, cre] , Marta Alcalde-Herraiz [aut] , Maria T Sanchez-Santos [aut]
Repository: CRAN
Date/Publication: 2026-09-17 13:20:27 UTC

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New package iPEB with initial version 0.1.1
Package: iPEB
Title: Improved Parametric Empirical Bayes for Longitudinal Biomarker Analysis
Version: 0.1.1
Description: Extends parametric empirical Bayes (PEB) for longitudinal biomarker screening with a time-gap-aware standardization layer, covariate adjustment, and objective-driven multi-marker weighting. The layer models each subject's biomarker history with a random intercept (and an optional random slope) and autocorrelated, gap-scaled residuals, so that prediction uncertainty grows with the time between visits and per-visit specificity is preserved under irregular sampling. Marker weights are learned to optimize a user-selected clinical objective -- maximizing sensitivity at a fixed specificity, extending detection lead time, or a combined objective -- with optional feature selection and a choice of scalar or multivariate combiner. Functions for fitting, prediction, and evaluation (sensitivity, lead time, and specificity at chosen operating points) are provided. A manuscript describing the method is in preparation.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: nlme, stats, graphics, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, shiny
VignetteBuilder: knitr
URL: https://github.com/bitansa/iPEB
BugReports: https://github.com/bitansa/iPEB/issues
NeedsCompilation: no
Packaged: 2026-09-09 18:47:02 UTC; bitansarkar
Author: Bitan Sarkar [aut, cre, cph] , Ana Maria Kenney [aut], James P. Long [aut], Johannes F. Fahrmann [aut], Samir Hanash [aut], Kim-Anh Do [aut], Ehsan Irajizad [aut]
Maintainer: Bitan Sarkar <bitansarkar010899@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 13:20:08 UTC

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New package ggbipart with initial version 0.1.3
Package: ggbipart
Title: Plots for Bipartite Networks in R
Version: 0.1.3
Description: Provides functions to plot bipartite ecological networks using 'ggplot2' graphics, including interaction webs, node-link layouts, and matrix representations. Species interaction data in the form of adjacency matrices, or 'network' and 'igraph' graph objects, can be plotted directly.
Depends: R (>= 3.1), ggplot2 (>= 2.0.0)
License: GPL-3
Imports: network, igraph, GGally
Suggests: knitr, rmarkdown, bipartite, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: http://pjordanolab.ebd.csic.es/resources/
BugReports: https://github.com/pedroj/bipartite_plots/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-09 15:27:03 UTC; pedro
Author: Pedro Jordano [aut, cre]
Maintainer: Pedro Jordano <jordano@ebd.csic.es>
Repository: CRAN
Date/Publication: 2026-09-17 13:20:15 UTC

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New package filters.trade with initial version 0.0.1
Package: filters.trade
Title: A Filter System for Selecting Trading Instruments
Version: 0.0.1
Description: Enables filtering datasets of tradable instruments by prior specified identifiers which correspond to saved filter expressions. A filter is a named expression bound to a target dataset, stored once in a package level registry, and later applied to select trading codes such as tickers or symbols out of a universe, price or signal dataset. The design follows the `filters` package, replacing the clinical study dataset convention with a trading instrument convention.
Depends: R (>= 4.1.0)
Imports: yaml
Suggests: roxygen2 (>= 7.0.0), testthat (>= 3.0.0)
Encoding: UTF-8
License: Apache License (>= 2.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-09 15:55:59 UTC; joezhu-hp
Author: Joe Zhu [aut, cre]
Maintainer: Joe Zhu <sha.joe.zhu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 13:20:20 UTC

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New package coOpenData with initial version 0.1.0
Package: coOpenData
Title: A Lightweight Interface to Colorado Open Data APIs
Version: 0.1.0
Description: Provides a unified set of helper functions to access datasets from the Colorado Open Data platform <https://data.colorado.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 Colorado 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/nyc-open-data-lab/coOpenData, https://nyc-open-data-lab.github.io/coOpenData/
BugReports: https://github.com/nyc-open-data-lab/coOpenData/issues
VignetteBuilder: knitr
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-09-09 18:53:40 UTC; christianmartinez
Author: Shelby Lyn Gomes [aut] , Christian Martinez [aut, cre]
Maintainer: Christian Martinez <c.martinez0@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-17 13:30:15 UTC

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New package midasINLA with initial version 0.1.0
Package: midasINLA
Title: Spatial MIDAS Models Using INLA
Version: 0.1.0
Description: Provides tools for fitting spatial Mixed Data Sampling (MIDAS) regression models using Integrated Nested Laplace Approximation (INLA). The package is designed for settings where responses and explanatory variables are observed at different temporal frequencies and supports both constant and spatially varying regression coefficients.
License: GPL-3
Encoding: UTF-8
Imports: matrixStats, Matrix, stats
Suggests: INLA, knitr, rmarkdown, testthat (>= 3.0.0), dplyr, ggplot2, tidyr
Additional_repositories: https://inla.r-inla-download.org/R/stable
VignetteBuilder: knitr
Depends: R (>= 4.2)
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-09 09:52:04 UTC; stephenjunvillejo
Author: Stephen Jun Villejo [aut, cre]
Maintainer: Stephen Jun Villejo <s.villejo@imperial.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-17 12:30:02 UTC

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New package maposm with initial version 0.5.1
Package: maposm
Title: Get Map Layers from 'OpenStreetMap'
Version: 0.5.1
Description: The 'OpenStreetMap' database provides a wide range of highly detailed geographic layers on a global scale. To obtain synthetic information for cartographic purposes, layers must be selected, simplified, merged, or modified. 'maposm' downloads 'OpenStreetMap' extracts and performs these operations to create a set of composite layers of urban areas, buildings, green spaces, main roads, secondary roads, railways, and water bodies.
URL: https://codeberg.org/riatelab/maposm, https://riatelab.r-universe.dev/maposm
BugReports: https://codeberg.org/riatelab/maposm/issues
License: GPL-3
Depends: R (>= 4.2.0)
Imports: sf, lwgeom, tools, mapsf, graphics, osmextract
Suggests: tinytest
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-09 15:29:54 UTC; tim
Author: Timothee Giraud [cre, aut] , Matthieu Viry [ctb] , Louis Laurian [ctb]
Maintainer: Timothee Giraud <timothee.giraud@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-09-17 13:00:02 UTC

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New package rankimp with initial version 1.0.0
Package: rankimp
Title: Consensus Ranking of Variable Importance with Uncertainty
Version: 1.0.0
Description: Variable importance rankings depend on the method, the random seed and the resample used to compute them. This package treats every source of importance as a judge expressing a ranking over the predictors, and synthesises those rankings into a Kemeny median ranking with ties. Uncertainty about the consensus is quantified through bootstrap rank confidence sets, top-k probabilities and clustering of disagreeing judges.
License: MIT + file LICENSE
URL: https://github.com/agostinognasso/rankimp
BugReports: https://github.com/agostinognasso/rankimp/issues
Depends: R (>= 3.5)
Imports: ConsRank, ggplot2, stats, tibble, utils
Suggests: cluster, covr, kernelshap, knitr, randomForest, ranger, rmarkdown, rsample, stabm, testthat (>= 3.1.7)
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-09 09:34:03 UTC; agostinognasso
Author: Agostino Gnasso [aut, cre, cph]
Maintainer: Agostino Gnasso <agostino.gnasso@unina.it>
Repository: CRAN
Date/Publication: 2026-09-17 11:30:02 UTC

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New package Proximum with initial version 1.1.0
Package: Proximum
Title: Statistical Analysis of Ensemble Proximity Matrices
Version: 1.1.0
Description: Treats the proximity matrices produced by tree ensembles as first-class statistical objects rather than as model by-products. Provides a unified extractor across ensemble engines, in-bag and out-of-bag definitions, transformations to dissimilarities with metric diagnostics, corrections that make an indefinite proximity usable as a kernel, and permutation inference for comparing two proximity matrices or partitioning one across the terms of a design. Also provides a Nystrom approximation, a thresholded sparse representation and a streaming form that never allocates the matrix at all, for samples too large to hold it, measures how far the proximity moves between replicates of the ensemble, and draws each object through 'ggplot2': the seriated matrix, the configuration it implies, and the thresholded graph with its communities.
License: MIT + file LICENSE
URL: https://github.com/agostinognasso/Proximum
BugReports: https://github.com/agostinognasso/Proximum/issues
Depends: R (>= 3.5)
Imports: ggplot2, Matrix, rlang, stats, utils
Suggests: covr, e2tree, igraph, knitr, randomForest, ranger, rmarkdown, seriation, testthat (>= 3.2.0), vegan
VignetteBuilder: knitr
LazyData: true
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-09 08:28:22 UTC; agostinognasso
Author: Agostino Gnasso [aut, cre, cph]
Maintainer: Agostino Gnasso <agostino.gnasso@unina.it>
Repository: CRAN
Date/Publication: 2026-09-17 11:40:02 UTC

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New package datadict with initial version 0.1.0
Package: datadict
Title: Validate Data Against a 'data-dict.yaml' Data Dictionary
Version: 0.1.0
Description: A data dictionary describes a collection of related tables: their columns, types, constraints, relationships, and glossary. Validate a dataset against its dictionary and read the findings as an HTML report. Reference: <https://data-dict.tidyverse.org>.
License: MIT + file LICENSE
URL: https://data-dict.tidyverse.org, https://github.com/tidyverse/data-dict
BugReports: https://github.com/tidyverse/data-dict/issues
Depends: R (>= 4.1)
Imports: cli (>= 3.2.0), processx, tools, utils
Suggests: nanoparquet, testthat (>= 3.0.0), withr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-09 08:51:05 UTC; gaborcsardi
Author: Gabor Csardi [aut, cre] , Hadley Wickham [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <gabor@posit.co>
Repository: CRAN
Date/Publication: 2026-09-17 11:20:02 UTC

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New package corsym with initial version 1.0.1
Package: corsym
Title: Correlation Estimation for Exchangeable/Symmetrical Variables
Version: 1.0.1
Description: We implement a new correlation estimator, CorSym, designed for exchangeable variables, where the ordering of the two values in the pair is arbitrary. This kind of data arises frequently in the study of assortative pairing (for example, income in a couple). The standard Pearson estimator is sensitive to such ordering and can be highly biased when the order is biased (when the first value tends to have lower or higher values than the second value). CorSym gives the same estimate deterministically for all orders within each pair, and estimates the desired correlation without bias (variables must be exchangeable). The package also includes utilities to simulate biased orders and test for order bias. Described in Kennedy and Ochoa (2026) <doi:10.64898/2026.08.22.746446>.
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), ggplot2
VignetteBuilder: knitr
URL: https://github.com/OchoaLab/corsym
BugReports: https://github.com/OchoaLab/corsym/issues
NeedsCompilation: no
Packaged: 2026-09-09 13:13:19 UTC; viiia
Author: Alejandro Ochoa [aut, cre] , Gabriel Kennedy [aut]
Maintainer: Alejandro Ochoa <alejandro.ochoa@duke.edu>
Repository: CRAN
Date/Publication: 2026-09-17 11:50:02 UTC

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New package carwatch with initial version 1.0.1
Package: carwatch
Title: Processing of 'CARWatch' Sampling Logs and Saliva Data
Version: 1.0.1
Description: Import and reconstruct saliva-sampling studies recorded by the 'CARWatch' application. Registration metadata and raw barcode events are converted into auditable study days and scheduled sample positions using a two-pass issue-review workflow. Functions assess sampling-time compliance, merge laboratory saliva measurements, calculate response features, and create quality-control visualizations. The application is described by Richer et al. (2023) <doi:10.1016/j.psyneuen.2023.106073>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.3)
Imports: boot, clock (>= 0.7.0), digest (>= 0.6.0), dplyr (>= 1.1.0), fs (>= 1.6.0), ggplot2 (>= 3.5.0), grid, jsonlite (>= 1.8.0), readr (>= 2.1.0), rlang (>= 1.1.0), tibble (>= 3.2.0), vctrs (>= 0.6.0), withr (>= 3.0.0)
Suggests: covr, DT, knitr, pkgdown, rmarkdown, roxygen2, shiny, shinytest2, testthat (>= 3.2.0)
VignetteBuilder: knitr
URL: https://carwatch-tools.github.io/carwatch-r/, https://github.com/carwatch-tools/carwatch-r
BugReports: https://github.com/carwatch-tools/carwatch-r/issues
NeedsCompilation: no
Packaged: 2026-09-09 12:43:54 UTC; richer
Author: Robert Richer [aut, cre]
Maintainer: Robert Richer <robert.richer@fau.de>
Repository: CRAN
Date/Publication: 2026-09-17 11:50:08 UTC

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New package arimasel with initial version 0.2.0
Package: arimasel
Title: Cartesian Product-Based ARIMA Model Identification and Selection
Version: 0.2.0
Description: Provides an alternative algorithm for ARIMA and seasonal ARIMA model identification based on Cartesian products of user-supplied parameter sets. Rather than relying on ACF/PACF plots or stepwise search (as in auto.arima()), the package exhaustively evaluates every candidate (p,d,q)(P,D,Q)[m] combination in the requested index sets, ranks all converged models by AIC, AICc, BIC, and HQIC simultaneously, computes Akaike weights for model uncertainty quantification, supports exogenous regressors, produces ensemble forecasts, evaluates candidate models by rolling-origin (expanding window) cross-validation, and provides publication-quality diagnostic and comparison plots. A feature-based exploratory data analysis suite computes scale-free time series characteristics (trend and seasonal strength, spectral entropy, autocorrelation, lumpiness, stability) in the spirit of Hyndman, Wang and Laptev (2015), and a feature-guided automatic search narrows the Cartesian product model space before the e [...truncated...]
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: stats, graphics, grDevices, utils, parallel
Suggests: tseries, forecast, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/Olawaleawe/arimasel
BugReports: https://github.com/Olawaleawe/arimasel/issues
NeedsCompilation: no
Packaged: 2026-09-09 12:59:40 UTC; root
Author: Olushina Olawale Awe [aut, cre]
Maintainer: Olushina Olawale Awe <olawaleawe@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 12:00:02 UTC

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New package modelskill with initial version 0.1.1
Package: modelskill
Title: Assessing and Visualising the Performance of Prediction Models
Version: 0.1.1
Description: Provides tools for evaluating continuous predictions and their associated predictive uncertainty from statistical, machine-learning, geostatistical, and process-based models. It implements complementary measures of prediction error, association, agreement, efficiency, uncertainty calibration, and predictive-distribution performance, together with Taylor, solar, target, coverage, probability integral transform, and quantile-coverage diagnostics. Methods include the integrated evaluation approach of Wadoux, Walvoort and Brus (2022) <doi:10.1016/j.geoderma.2021.115332> and the uncertainty-validation framework of Schmidinger and Heuvelink (2023) <doi:10.1016/j.geoderma.2023.116585>.
License: MIT + file LICENSE
URL: https://github.com/AlexandreWadoux/modelskill, https://alexandrewadoux.github.io/modelskill/
BugReports: https://github.com/AlexandreWadoux/modelskill/issues
Encoding: UTF-8
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, pkgdown
Imports: ggplot2 (>= 3.5.0), ggrepel, viridis
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-09 07:47:43 UTC; jd189549
Author: Alexandre M.J.-C. Wadoux [aut, cre, cph]
Maintainer: Alexandre M.J.-C. Wadoux <alexandre.wadoux@yahoo.fr>
Repository: CRAN
Date/Publication: 2026-09-17 11:00:02 UTC

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New package charport with initial version 0.1.0
Package: charport
Title: ALTREP String Interoperability
Version: 0.1.0
Date: 2026-09-08
Description: Provides infrastructure for interoperable ALTREP character vectors. Producers of ALTREP string classes can register access methods, allowing consumers to read supported character vectors through a common interface without materializing them as ordinary R strings. Also provides 'charvec', a reference ALTREP string implementation backed by stable memory slices, with support for efficient and multithreaded construction.
License: MIT + file LICENSE
Copyright: Benchmark measurements use the enwik8 corpus, the first 10^8 bytes of the English Wikipedia XML dump of 2006-03-03, whose text carries Wikipedia's own terms: the Creative Commons Attribution-ShareAlike License and the GNU Free Documentation License. No Wikipedia data is included in this package.
Encoding: UTF-8
Suggests: cpp11, quarto, Rcpp
VignetteBuilder: quarto
Depends: R (>= 3.6.0)
URL: https://github.com/charbase/charport, https://charbase.github.io/charport/
BugReports: https://github.com/charbase/charport/issues
NeedsCompilation: yes
Packaged: 2026-09-09 07:15:06 UTC; ted
Author: Travers Ching [aut, cre, cph], R Consortium [fnd]
Maintainer: Travers Ching <traversc@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 10:50:02 UTC

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New package sleeper with initial version 0.5.0
Package: sleeper
Title: Estimate Sleep Status from Accelerometry Data
Version: 0.5.0
Description: Wraps the classifier from the Sundararajan (2021) <doi:10.1038/s41598-020-79217-x> to estimate sleep using a random forest. Users must download the model files from Sundararajan (2020) <doi:10.5281/zenodo.3752645> in order to use this method.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: assertthat, curl, dplyr, methods, reticulate, rlang
Suggests: callr, readr, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-08 16:50:58 UTC; johnmuschelli
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:10:02 UTC

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New package rmoriedata with initial version 0.3.2
Package: rmoriedata
Title: Integrated Datasets for the 'rmorie' Package
Version: 0.3.2
Description: Integrated open data fixtures used by the 'rmorie' package for examples, vignettes, and tests. Split out so 'rmorie' itself stays within the 'CRAN' package-size soft cap. Contains snapshots of publicly available datasets from open-data portals built on the Comprehensive Knowledge Archive Network ('CKAN', <https://ckan.org/>), 'Socrata' (<https://dev.socrata.com/>), and 'Opendatasoft' (<https://www.huwise.com/>) (Chicago, New York City, Toronto, Vancouver, and others), Statistics Canada Canadian Centre for Justice and Community Safety Statistics ('CCJS') tables, a multi-agent-reviewed corpus of Ontario Special Investigations Unit ('SIU', <https://www.siu.on.ca/>) director's reports, and synthetic fixtures for unit tests. Also ships a small set of analyst-facing helpers for releasing aggregate statistics without re-identification risk: Laplace and Gaussian differential privacy mechanisms and k-anonymity, l-diversity, and cell suppression verifiers.
License: AGPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: stats, rmoriebricklayer (>= 0.2.1)
LinkingTo: rmoriebricklayer
Suggests: testthat (>= 3.0.0), nanoparquet, tibble, curl, jsonlite, knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
URL: https://github.com/rootcoder007/rmoriedata
BugReports: https://github.com/rootcoder007/rmoriedata/issues
NeedsCompilation: yes
Packaged: 2026-09-08 20:29:29 UTC; rootcoder
Author: Vansh Singh Ruhela [aut, cre]
Maintainer: Vansh Singh Ruhela <vsruhela@proton.me>
Repository: CRAN
Date/Publication: 2026-09-17 10:00:02 UTC

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New package pmsims with initial version 1.0.0
Package: pmsims
Title: Simulation-Based Sample Size Tools for Prediction Models
Version: 1.0.0
Description: Provides a flexible, simulation-based toolkit for exploring how much data are needed to develop reliable prediction models. It works by repeatedly generating data, fitting models, and evaluating performance to show how sample size affects predictive accuracy, calibration, and overfitting. The package supports continuous, binary, and time-to-event outcomes and can be used with both regression-based modelling approaches and machine-learning methods. It is designed to help researchers plan studies, assess feasibility, and build more robust and generalisable models. The methods are described in Olaniran et al. (2026) <doi:10.1186/s12874-026-02935-9> and Shamsutdinova et al. (2026) <doi:10.48550/arXiv.2602.23507>.
License: GPL (>= 3)
URL: https://pmsims-package.github.io/pmsims/, https://github.com/pmsims-package/pmsims
BugReports: https://github.com/pmsims-package/pmsims/issues
Depends: R (>= 4.1.0)
Imports: cli, ggplot2, lifecycle, mlpwr, pROC, stats, survival, timeROC, utils
Suggests: covr, DescTools, doParallel, foreach, glmnet, knitr, mlbench, mlr, randomForestSRC, ranger, rmarkdown, synthpop, testthat (>= 3.0.0), tuneRanger, xgboost
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-08 19:30:59 UTC; k1644956
Author: Ewan Carr [aut, cre] , Gordon Forbes [aut] , Ridwan Olaniran [aut] , Diana Shamsutdinova [aut] , Daniel Stahl [aut] , Sarah Markham [aut] , Felix Zimmer [aut]
Maintainer: Ewan Carr <ewan.carr@kcl.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-17 09:30:02 UTC

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New package nowcaster with initial version 1.0.0
Package: nowcaster
Title: Statistical Models for Notification Delay Correction of Epidemiological Data
Version: 1.0.0
Description: Statistical models for correcting notification delays of epidemiological data. The package wraps statistical models to estimate not yet reported data using empirical delay distribution either from individual-level data or from the differences of aggregated time series of cases. For more details see Bastos et al. (2019) <doi:10.1002/sim.8303>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://covid19br.github.io/nowcaster/
BugReports: https://github.com/covid19br/nowcaster/issues
Suggests: INLA (>= 22.5.3), ggplot2, knitr, rmarkdown, vroom, parallel, lubridate, lme4, sn, stringr
Depends: R (>= 4.1.0)
LazyData: true
Additional_repositories: https://inla.r-inla-download.org/R/stable/
Imports: dplyr, tidyr, tibble, mgcv
NeedsCompilation: no
Packaged: 2026-09-08 16:59:17 UTC; lbastos
Author: Rafael Lopes [aut] , Tatiana Portella [aut] , Leo Bastos [aut, cre]
Maintainer: Leo Bastos <leonardo.bastos@fiocruz.br>
Repository: CRAN
Date/Publication: 2026-09-17 09:20:02 UTC

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New package latentState with initial version 1.0.0
Package: latentState
Title: Simulate Outcomes of a Latent State Reinforcement Learning Model
Version: 1.0.0
Description: Simulates outcomes of an updated version of the latent state reinforcement learning model originally described in Cochran and Cisler (2019) <doi:10.1371/journal.pcbi.1007331>. The package is designed to create results under all reasonable experiment setups, including different reinforcement schedules, number of cues, number of phases, and number of options per trial. Participants can be simulated using either fixed parameters or parameters drawn from a distribution.
License: GPL (>= 3)
URL: https://osf.io/2whcu
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-08 19:41:12 UTC; marti
Author: Martin Benada [aut, cre]
Maintainer: Martin Benada <martinibenada@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:30:09 UTC

More information about latentState at CRAN
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New package actimetrics with initial version 0.4.0
Package: actimetrics
Title: Create Metrics Actigraphy and Activity Analysis
Version: 0.4.0
Description: Provides functions for calibrating, counting, and summarizing actigraphy and activity data into specific metrics and sleep measures. The metrics include activity counts, step counts, activity index, Monitor Independent Movement Summary Unit (MIMS), mean amplitude deviation (MAD), and provides wrappers for sleep estimation from activity counts using Tudor-Locke (2014) <doi:10.1139/apnm-2013-0173> and Sadeh (1994) <doi:10.1093/sleep/17.3.201>.
License: GPL-3
Depends: R (>= 4.1.0)
Suggests: testthat, utils, covr, knitr, httr, rmarkdown, MIMSunit, data.table, reticulate, stepcount (>= 0.6.0), actigraph.sleepr (>= 0.3.1), agcounts (>= 0.6.7), callr
Encoding: UTF-8
VignetteBuilder: knitr
Imports: actibase, actiread, dplyr, lubridate, assertthat, purrr, tibble, rlang, stats, tidyr, walking (>= 0.8.0), methods
LazyData: true
URL: https://jhuwit.github.io/actimetrics/
BugReports: https://github.com/jhuwit/actimetrics/issues
NeedsCompilation: no
Packaged: 2026-09-08 16:17:38 UTC; johnmuschelli
Author: John Muschelli [aut, cre]
Maintainer: John Muschelli <muschellij2@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-17 09:10:15 UTC

More information about actimetrics at CRAN
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New package bonsaisitter with initial version 0.1.2
Package: bonsaisitter
Title: Bindings to the 'Tree-Sitter' Parsing Library
Version: 0.1.2
Date: 2026-09-08
Description: A runtime for the 'Tree-sitter' parsing library <https://tree-sitter.github.io/tree-sitter/> that mirrors the API of the 'treesitter' package, so it can serve as a drop-in replacement. Parses source code into concrete syntax trees and updates them incrementally as the source changes. Grammars are supplied by separate packages such as 'treesitter.r', so the runtime itself depends on nothing beyond base R.
License: MIT + file LICENSE
Copyright: cornball.ai, except the bundled tree-sitter sources under src/tree-sitter, whose holders are listed in inst/COPYRIGHTS.
URL: https://github.com/cornball-ai/bonsaisitter
BugReports: https://github.com/cornball-ai/bonsaisitter/issues
Encoding: UTF-8
NeedsCompilation: yes
Suggests: tinytest, treesitter, treesitter.r
Packaged: 2026-09-08 16:12:58 UTC; troy
Author: Troy Hernandez [aut, cre] , cornball.ai [cph], Max Brunsfeld [ctb, cph] , International Business Machines Corporation [cph] , Unicode, Inc. [cph] , Mathias Panzenboeck [ctb]
Maintainer: Troy Hernandez <troy@cornball.ai>
Repository: CRAN
Date/Publication: 2026-09-17 09:00:09 UTC

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Wed, 16 Sep 2026

New package ggmosaic2 with initial version 0.5.1
Package: ggmosaic2
Title: Mosaic Plots in the 'ggplot2' Framework, Extended
Version: 0.5.1
Date: 2026-09-15
Description: Mosaic plots in the 'ggplot2' framework. Mosaic plot functionality is provided in a single 'ggplot2' layer by calling the geom 'mosaic'. This extends the now-defunct 'ggmosaic' package by allowing fitted loglinear models which can be used to show patterns of association among variables in frequency tables.
License: GPL (>= 2)
Language: en-US
URL: https://friendly.github.io/ggmosaic2/, https://github.com/friendly/ggmosaic2
BugReports: https://github.com/friendly/ggmosaic2/issues
Depends: ggplot2 (>= 4.0.0), R (>= 4.1.0)
Imports: productplots, dplyr, plotly (>= 4.9.3), purrr, rlang, tidyr, ggrepel, scales, withr (>= 2.5.0)
Suggests: gridExtra, knitr, rmarkdown, shiny (>= 1.1.0), patchwork, vcdExtra
VignetteBuilder: knitr
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-15 14:27:34 UTC; friendly
Author: Michael Friendly [aut, cre, cph] , Gavin Klorfine [aut] , Haley Jeppson [aut] , Heike Hofmann [aut] , Di Cook [aut] , Hadley Wickham [ctb]
Maintainer: Michael Friendly <friendly@yorku.ca>
Repository: CRAN
Date/Publication: 2026-09-16 12:30:02 UTC

More information about ggmosaic2 at CRAN
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New package dplyneage with initial version 0.3.1
Package: dplyneage
Title: Column Lineage Visualization for 'dplyr' Pipelines
Version: 0.3.1
Description: Implements column lineage visualizations using 'React Flow' for 'dplyr' and 'dbplyr' pipelines. Provides a tidyverse-style interface for tracking data transformations through pipeline operations.
License: MIT + file LICENSE
URL: https://tgerke.github.io/dplyneage/, https://github.com/tgerke/dplyneage
BugReports: https://github.com/tgerke/dplyneage/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: htmlwidgets, jsonlite
Suggests: DBI, dbplyr, dplyr, duckdb, igraph, knitr, reticulate, rlang, rmarkdown, RSQLite, shiny, testthat (>= 3.2.0), withr, xml2
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-08 14:02:39 UTC; tgerke
Author: Travis Gerke [aut, cre, cph], Meta Platforms, Inc. and affiliates [cph] , xyflow GmbH [cph]
Maintainer: Travis Gerke <travisgerke@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-16 12:10:02 UTC

More information about dplyneage at CRAN
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New package ARInfoLSTM with initial version 0.1.0
Package: ARInfoLSTM
Title: ARIMA-Informed LSTM for Time Series Forecasting
Version: 0.1.0
Description: Implements an ARIMA-Informed Long Short-Term Memory (LSTM) framework for univariate time series forecasting. The package integrates statistical information extracted from AutoRegressive Integrated Moving Average (ARIMA) models with deep learning-based LSTM architectures to improve forecasting accuracy, stability, and interpretability. Inspired by the philosophy of Physics-Informed Machine Learning (PIML), the proposed framework incorporates information from classical statistical models into neural network learning, creating a hybrid forecasting approach that combines domain knowledge with data-driven intelligence. The methodology is motivated by hybrid forecasting framework proposed by Yeasin and Paul (2024) <doi:10.1007/s11227-023-05542-3>.
License: GPL-3
Encoding: UTF-8
Imports: torch (>= 0.11.0), forecast (>= 8.21), ggplot2 (>= 3.4.0), cli (>= 3.6.0), coro, stats, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-08 11:50:21 UTC; YEASIN
Author: Md Yeasin [aut], Ranjit Kumar Paul [aut, cre], Pushkar Bora [aut]
Maintainer: Ranjit Kumar Paul <ranjitstat@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-16 11:40:02 UTC

More information about ARInfoLSTM at CRAN
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Tue, 15 Sep 2026

New package landmarked with initial version 0.2.0
Package: landmarked
Title: Plot Adjusted Kaplan-Meier Estimates from a Landmark Time
Version: 0.2.0
Description: Plots contextual landmark Kaplan-Meier curves. An extension of the 'survminer::ggsurvplot()' function that allows the specification of a landmark time and an optional label. The period before the landmark is displayed as a pooled survival curve, while curves beyond the landmark are presented according to the groups defined in the supplied 'survival::survfit' object.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/CStats/landmarked
Imports: dplyr, ggplot2, survival, survminer
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 4.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-08 10:31:38 UTC; christopherb
Author: Chris Brown [aut, cre, cph]
Maintainer: Chris Brown <c.brown@sydney.edu.au>
Repository: CRAN
Date/Publication: 2026-09-15 14:30:02 UTC

More information about landmarked at CRAN
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New package hdcce with initial version 0.1.0
Package: hdcce
Title: Estimation and Inference for High-Dimensional Panel Data Models with Interactive Fixed Effects
Version: 0.1.0
Description: Estimation and inference for panel data models with interactive fixed effects. The methods cover i) the linear specification of Ruecker, M., Vogt, M., Linton, O. and Walsh, C. (2025) "Estimation and Inference in High-Dimensional Panel Data Models with Interactive Fixed Effects" <doi:10.3982/QE2308>, and ii) the dictionary design of Ruecker, M., Vogt, M. and Linton, O. (2026) "High-Dimensional Panel Data Models with Interactive Fixed Effects: Beyond the Linear Case" <doi:10.48550/arXiv.2608.02055>.
License: GPL (>= 2)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, graphics, glmnet, mvtnorm
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
LazyDataCompression: xz
URL: https://github.com/RueckerM/hdcce
NeedsCompilation: no
Packaged: 2026-09-08 08:39:45 UTC; maximilianrucker
Author: Maximilian Ruecker [aut, cre], Michael Vogt [aut], Oliver Linton [aut], Christopher Walsh [aut]
Maintainer: Maximilian Ruecker <maximilian.ruecker@uni-ulm.de>
Repository: CRAN
Date/Publication: 2026-09-15 14:20:02 UTC

More information about hdcce at CRAN
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New package autorelevate with initial version 0.1.0
Package: autorelevate
Title: The Autorelevated Family of Probability Distributions and Estimation Methods
Version: 0.1.0
Description: Implements the autorelevated family of probability distributions, obtained by applying the autorelevation transformation of Krakowski (1973) <doi:10.1051/ro/197307V201071> and Dileepkumar and Sankaran (2022) to ten baseline probability distributions: Weibull, Lomax, Burr XII, Gompertz, Log-Logistic, Chen, Exponentiated Exponential, Power Lindley, Log-normal, and Gamma. The Weibull member of the family is studied in detail by Dileep Kumar, Shabeer, and Sankaran (2025) <doi:10.1080/01966324.2026.2665479>. The Lomax member is studied by Sharma, Pal, Bhardwaj, and Tyagi (2026, submitted), who establish its upside-down bathtub hazard shape. Supplies vectorized density, distribution, survival, hazard, quantile (via the negative branch of the Lambert W function), and random-generation functions for all ten members of the family. It also implements Maximum Likelihood, Maximum Product of Spacings, Least Squares, Weighted Least Squares, and Cramer-von Mises estimation methods along w [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
URL: https://github.com/vksharma-bhu/autorelevate
BugReports: https://github.com/vksharma-bhu/autorelevate/issues
LazyData: true
Depends: R (>= 3.5)
Imports: stats, graphics, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, spelling
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-08 07:26:52 UTC; vishu
Author: Vikas Kumar Sharma [aut, cre]
Maintainer: Vikas Kumar Sharma <vksharma@bhu.ac.in>
Repository: CRAN
Date/Publication: 2026-09-15 14:10:02 UTC

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New package oneway with initial version 0.0.2
Package: oneway
Title: One-Way Statistical Analyses
Version: 0.0.2
Description: Performs one-way tests of assumptions (normality and homoscedasticity), analysis of variance, robust and nonparametric alternatives, multiple comparison procedures, effect size estimators, confidence intervals, and descriptive summaries. Functions are designed with a consistent interface to support reproducible and user-friendly statistical workflows. For more details see Howell (2010, ISBN:978-0-495-59784-1), Zar (2014, ISBN:978-0-13-100846-5), Hollander et al. (2014, ISBN:978-0-470-38737-5), Montgomery (2017, ISBN:978-1-119-11347-8), Lakens (2013) <doi:10.3389/fpsyg.2013.00863>, and Piepho (2004) <doi:10.1198/1061860043515>.
License: MIT + file LICENSE
URL: https://github.com/P10911004-NPUST/oneway
BugReports: https://github.com/P10911004-NPUST/oneway/issues
Encoding: UTF-8
Imports: normality, outlying, varequal
Suggests: ggplot2, testthat (>= 3.0.0)
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-08 03:40:01 UTC; ABRC
Author: Joon-Keat Lai [aut, cre, cph]
Maintainer: Joon-Keat Lai <p10911004@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 13:20:02 UTC

More information about oneway at CRAN
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New package netDFI with initial version 1.2.0
Package: netDFI
Title: Dynamic Fit Index for Network Models
Version: 1.2.0
Description: Implement methods to determine the dynamic fit index cutoffs for network models. The package allows users to evaluate model fit based on their own model statement, model type, and sample size. Methods are described in Du and Epskamp (2026) <doi:10.31234/osf.io/5wj2y_v2>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/xinkaidupsy/netDFI
BugReports: https://github.com/xinkaidupsy/netDFI/issues
Imports: bootnet, dplyr, future, future.apply, progressr, psychonetrics, qgraph, ggplot2, patchwork
Suggests: psych
NeedsCompilation: no
Packaged: 2026-09-08 03:09:18 UTC; K
Author: Xinkai Du [aut, cre]
Maintainer: Xinkai Du <xinkai.du.xd@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 13:20:08 UTC

More information about netDFI at CRAN
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New package ggicons with initial version 0.1.0
Package: ggicons
Title: Icon Geometries for 'ggplot2'
Version: 0.1.0
Description: Provides icon geometries for 'ggplot2', using vector icon sets from the 'icons' package. Icons can be drawn as points in place of ordinary markers, styled with the usual colour, size, alpha and angle aesthetics, and mapped from discrete values or passed through directly. Icons also appear in legend keys, as fixed-position annotations, and as axis, strip and legend labels. Pictograms extend this to isotype-style unit charts, waffle/percentage charts and rating widgets, encoding a value as a grid of repeated icons.
License: MIT + file LICENSE
URL: https://pkg.mitchelloharawild.com/ggicons/, https://github.com/mitchelloharawild/ggicons
BugReports: https://github.com/mitchelloharawild/ggicons/issues
Imports: cli, ggplot2 (>= 4.0.0), grid, grImport2, icons (>= 1.0.0), rlang (>= 1.1.0), rsvg, scales, vctrs
Suggests: spelling, testthat (>= 3.0.0)
Encoding: UTF-8
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-08 00:13:07 UTC; mitchell
Author: Mitchell O'Hara-Wild [aut, cre]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>
Repository: CRAN
Date/Publication: 2026-09-15 13:10:02 UTC

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New package FCtools with initial version 2.3.1
Package: FCtools
Title: Functional Connectivity Tools
Version: 2.3.1
Date: 2026-09-08
Maintainer: Charly Billaud <charly.billaud@ntu.edu.sg>
Description: Analyzing and visualizing brain connectivity data, including network-based statistics (NBS) for linear and linear mixed models, both at edge level and functional network level (Yeo's 7-networks (Schaefer et al. (2017) <doi:10.1093/cercor/bhx179>)). Plots include edge-wise connectograms, chord diagrams, network connectograms, heatmaps, and 3D glass brain connectivity plots. 'FCtools' works with vectors of edges (derived from connectivity/adjacency matrices) from the 'Brainnetome' (Fan et al. (2016) <doi:10.1093/cercor/bhw157>), 'Schaefer' (100 or 200, each with 19 'ASeg' subcortices) (Schaefer et al. (2017) <doi:10.1093/cercor/bhx179>, Fischl et al. (2002) <doi:10.1016/S0896-6273(02)00569-X>), and 'Automated Anatomical Labeling' (AAL) atlases (Tzourio-Mazoyer et al. (2002) <doi:10.1006/nimg.2001.0978>).
License: GPL-3
Encoding: UTF-8
LazyData: true
URL: https://cogbrainhealthlab.github.io/FCtools/
Depends: R (>= 4.1.0)
Imports: Rfast, circlize, cowplot, doParallel, doSNOW, foreach, ggplot2, ggplotify, ggraph, grid, gridExtra, igraph, parallel, plotly, png, reshape2
NeedsCompilation: no
Packaged: 2026-09-08 00:58:08 UTC; charly.billaud
Author: Junhong Yu [aut] , Charly Billaud [aut, cre]
Repository: CRAN
Date/Publication: 2026-09-15 13:10:08 UTC

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New package evaluatellm with initial version 0.1.0
Package: evaluatellm
Title: Statistical Inference for Language Model Evaluations
Version: 0.1.0
Description: Treats language model evaluations as statistical experiments and supplies the inference they require. Provides central limit theorem and cluster-robust standard errors for evaluation scores, paired and unpaired model comparisons, variance decomposition when several responses are drawn per question, control-variate variance reduction, multiplicity adjustment across benchmark suites, and power and minimum detectable effect calculations for planning evaluations, following Miller (2024) <doi:10.48550/arXiv.2411.00640>. For evaluations scored by a model judge, implements agreement statistics against a human gold standard and prediction-powered inference (Angelopoulos et al. 2023) <doi:10.1126/science.adi6000> with the power-tuned estimator of Angelopoulos, Bates and Jordan (2023) <doi:10.48550/arXiv.2311.01453>, so a small set of human labels debiases a large set of judge scores. Leaderboards are supported through bootstrap rank intervals and Bradley-Terry ratings (Bradley [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
URL: https://charlescoverdale.github.io/evaluatellm/, https://github.com/charlescoverdale/evaluatellm
BugReports: https://github.com/charlescoverdale/evaluatellm/issues
Depends: R (>= 4.1.0)
Imports: cli (>= 3.6.0), graphics, grDevices, stats, utils
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, sandwich
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-08 07:19:25 UTC; charlescoverdale
Author: Charles Coverdale [aut, cre, cph]
Maintainer: Charles Coverdale <charlesfcoverdale@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 13:40:02 UTC

More information about evaluatellm at CRAN
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New package Entropic.Scree with initial version 1.0.1
Package: Entropic.Scree
Title: Information-Theoretic Dimensionality Estimation
Version: 1.0.1
Copyright: Terrence J. Lee-St. John (Enli)
Description: An information-theoretic diagnostic technique for estimating the intrinsic dimensionality of tabular datasets. Evaluates shared probability mass via a transformed mutual information metric. Aims to extract the Intrinsic Generative Rank (r) and structural topology. For full methodological details, see the preprint by Lee-St. John (2026) <https://zenodo.org/records/22028087>.
URL: https://zenodo.org/records/22028087
License: Apache License 2.0
Encoding: UTF-8
Imports: data.table, ggplot2, infotheo, parallel, patchwork, Rcpp
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-09-08 08:12:20 UTC; tjlee
Author: Terrence J. Lee-St. John [aut, cre]
Maintainer: Terrence J. Lee-St. John <terry@enli.com.au>
Repository: CRAN
Date/Publication: 2026-09-15 14:00:02 UTC

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New package simPsyStudy with initial version 1.1.8
Package: simPsyStudy
Title: Simulation of Ordinal Responses for Psychometric Studies
Version: 1.1.8
Date: 2026-09-07
Description: Provides tools to define factorial simulation conditions and generate binary or ordinal item responses under common-factor and probit graded response model parameterizations. Supports multivariate normal and correlated gamma latent traits, reproducible replications, parameter conversion, and structured storage of generated datasets. The graded response model follows Samejima (1969).
License: MIT + file LICENSE
Encoding: UTF-8
Imports: MASS, moments, MultiRNG, Rdpack
Suggests: testthat (>= 3.0.0)
URL: https://github.com/Boklauth/simPsyStudy
BugReports: https://github.com/Boklauth/simPsyStudy/issues
NeedsCompilation: no
Packaged: 2026-09-07 23:03:46 UTC; BKlauth
Author: Bo Klauth [aut, cre]
Maintainer: Bo Klauth <bklauth@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 13:00:02 UTC

More information about simPsyStudy at CRAN
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New package ConsTree with initial version 1.0.0
Package: ConsTree
Title: Fast Algorithms for Phylogenetic Consensus Trees
Version: 1.0.0
License: GPL (>= 3)
Copyright: Incorporates C++ code from 'FACT' (GPL-3, doi:10.1145/2925985), 'FACT2' and 'FDCT', by kind permission of Jesper Jansson and colleagues.
Description: Efficient construction of phylogenetic consensus trees. Methods include strict, majority-rule, majority-rule (+), loose (combinable component / semi-strict), greedy, Adams, frequency difference, R*, and local consensus.
URL: https://constree.github.io/
BugReports: https://github.com/ms609/ConsTree/issues/
Depends: R (>= 4.1.0),
Imports: ape (>= 5.6), Rcpp (>= 1.0.0), Rdpack (>= 2.6), TreeTools (>= 2.3.0),
LinkingTo: Rcpp, TreeTools (>= 2.1.0),
SystemRequirements: C++17
Suggests: knitr, Quartet, rmarkdown, spelling, testthat (>= 3.0), TreeSearch (>= 2.0.0),
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-GB
NeedsCompilation: yes
Packaged: 2026-09-07 16:42:01 UTC; pjjg18
Author: Martin R. Smith [aut, cre, cph] , Jesper Jansson [cph] ), Chuanqi Shen [cph] ), Wing-Kin Sung [cph] )
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-15 12:10:19 UTC

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New package bioclients with initial version 0.1.1
Package: bioclients
Title: Clients for Biological Database Web Services
Version: 0.1.1
Description: Look up genes, variants and proteins from R, without writing a client for every biological web service. Each service gets one client that makes the request and returns a table. Parsing is a separate function that needs no network, so it can run on a saved response and be tested offline. Transport, retries, caching and error handling are left to the 'biohttp' package. Dependencies for single services are optional, so you do not install what you will not use. The services covered include 'Ensembl', described in Dyer et al. (2025) <doi:10.1093/nar/gkae1071>, 'UniProt', in The UniProt Consortium (2025) <doi:10.1093/nar/gkae1010>, 'gnomAD', in Chen et al. (2024) <doi:10.1038/s41586-023-06045-0>, 'Open Targets', in Buniello et al. (2025) <doi:10.1093/nar/gkae1128>, and the 'AlphaFold' Protein Structure Database, in Varadi et al. (2024) <doi:10.1093/nar/gkad1011>. Each client's help page cites the service it calls.
License: MIT + file LICENSE
URL: https://github.com/samuelbharti/bioclients, https://www.samuelbharti.com/bioclients/
BugReports: https://github.com/samuelbharti/bioclients/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: biohttp (>= 0.1.2), httr2, tibble
Suggests: jsonlite, knitr, rmarkdown, testthat (>= 3.0.0), withr
NeedsCompilation: no
Packaged: 2026-09-07 22:57:13 UTC; Samuel
Author: Samuel Bharti [aut, cre, cph] , Barret Schloerke [ths] , Carson Sievert [ths] , Posit Software, PBC [cph, fnd]
Maintainer: Samuel Bharti <samuelbharti.io@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 13:00:08 UTC

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New package ardldml with initial version 0.1.0
Package: ardldml
Title: Bounds Testing for Cointegration with Many Persistent Controls
Version: 0.1.0
Description: An implementation of the DML-Bounds procedure of Villena (2026) <doi:10.2139/ssrn.6472826> for testing cointegration in data-rich time-series settings. The Autoregressive Distributed Lag (ARDL) bounds test of Pesaran, Shin and Smith (2001) <doi:10.1002/jae.616> avoids pretesting the integration order of the regressors but is not designed for a high-dimensional conditioning set. Residualising the lagged levels against persistent controls can absorb stochastic trends and thereby change the finite-sample null distribution, so what governs the null is the effective number of stochastic trends surviving residualisation rather than the integration order of the original regressors. The procedure combines h-block cross-fitting, a balanced nuisance projection in the Double Machine Learning (DML) style of Chernozhukov and others (2018) <doi:10.1111/ectj.12097>, adaptive weighting after Zou (2006) <doi:10.1198/016214506000000735>, and a restricted system wild bootstrap tha [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: glmnet, stats, graphics, grDevices, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tseries
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/merwanroudane/ardldml
BugReports: https://github.com/merwanroudane/ardldml/issues
NeedsCompilation: no
Packaged: 2026-09-07 18:36:46 UTC; HP
Author: Merwan Roudane [aut, cre, cph]
Maintainer: Merwan Roudane <merwanroudane920@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 12:20:09 UTC

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New package xnicher with initial version 1.0.0
Package: xnicher
Title: Estimates Ecological Niche Models Using Ellipses
Version: 1.0.0
Description: Ecological niche model estimation using ellipsoidal geometry under an M hypothesis. Fits nine likelihood families (presence-only, weighted, inverse-probability-weighted, skew-normal, skew-normal-weighted, skew-t, skew-t-weighted, ncst, and ncst-weighted) via multi-start optimisation with Sobol sequences. Methods for the optimisation of ellipses parameters are as described in Jimenez et al. (2022) <doi:10.1016/j.ecolmodel.2021.109823>.
URL: https://github.com/alrobles/xnicher
BugReports: https://github.com/alrobles/xnicher/issues
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: checkmate, Rcpp (>= 1.1.0), RcppParallel, stats, terra, ucminfcpp, utils
Suggests: ggplot2 (>= 3.0.0), knitr, pomp, rmarkdown, testthat (>= 3.0.0)
LinkingTo: Rcpp, RcppEigen, RcppParallel
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2026-09-07 03:46:00 UTC; alrobles
Author: Angel Robles [aut, cre], Laura Jimenez [aut, ctb]
Maintainer: Angel Robles <a.l.robles.fernandez@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 11:20:02 UTC

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New package staggeredGMM with initial version 0.1.0
Package: staggeredGMM
Title: GMM Estimation of Treatment Effects Under Staggered Adoption
Version: 0.1.0
Description: Estimates cohort-by-time average treatment effects under staggered treatment adoption by the generalized method of moments. Three weighting schemes are provided, corresponding to a pooled stationary covariance, a cohort-specific stationary covariance, and an unrestricted within-cohort covariance. Optional adjustment for baseline covariates by outcome regression, and a serial-correlation robust over-identification test of parallel trends and no anticipation, are also supported. The methods are described in Arora and Bijani (2026) <doi:10.2139/ssrn.6558759>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: fixest, MASS, stats, utils
Suggests: covr, data.table, knitr, rmarkdown, testthat (>= 3.1.5)
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/RishabhBijani/staggeredGMM
BugReports: https://github.com/RishabhBijani/staggeredGMM/issues
NeedsCompilation: no
Packaged: 2026-09-06 17:00:22 UTC; rishabhbijani
Author: Rishabh Bijani [aut, cre, cph] , Parush Arora [aut, cph]
Maintainer: Rishabh Bijani <rishabhbijani@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 11:00:10 UTC

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New package SAMPLE with initial version 1.0.1
Package: SAMPLE
Title: Estimate Sampling Effort for Species Occurrence Rates
Version: 1.0.1
Maintainer: Henrique Bravo <henrique.bravo@rug.nl>
Description: Estimates the sampling effort needed to obtain stable species occurrence and prevalence rates from presence-absence data. The method repeatedly subsamples observations, evaluates changes in estimated rates, and reports the minimum stable sample size. For methodological details, see Bravo et al. (2025) <doi:10.1002/ece3.70998>.
URL: https://github.com/yacinebenchehida/SAMPLE
BugReports: https://github.com/yacinebenchehida/SAMPLE/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: ggplot2 (>= 3.4.2), Rmisc (>= 1.5.1), RColorBrewer (>= 1.1-3), dplyr (>= 1.1.4), magrittr (>= 2.0.3)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), tibble (>= 3.2.1)
NeedsCompilation: no
Packaged: 2026-09-06 09:17:18 UTC; yacinebenchehida
Author: Henrique Bravo [aut, cre] , Yacine Ben Chehida [aut] , Sancia E. T. van der Meij [aut]
Repository: CRAN
Date/Publication: 2026-09-15 11:30:08 UTC

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New package phdid with initial version 0.1.0
Package: phdid
Title: Partial Homogeneity in Staggered Difference-in-Differences
Version: 0.1.0
Description: In staggered difference-in-differences designs the treatment effect is a vector of cohort-time effects rather than a single number. Estimating each separately is unbiased but imprecise when some are equal, while pooling them all is precise but biased under genuine heterogeneity. This package treats the choice as a partition-selection problem on the cohort-time cells and provides two estimators for it: a Dirichlet process mixture fitted by a collapsed Gibbs sampler, whose posterior marginalises over the unknown partition and reports co-clustering probabilities, and an 'L0'-penalised estimator that returns a single partition and arises as the fixed-variance maximum a posteriori solution of the same model. Also provides tests for whether the cohort-time effects carry recoverable heterogeneity at all, sampler diagnostics including exact enumeration of the partition posterior for small designs, regularisation paths for both estimators, and a calibrated data-generating process. All estimator [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats, utils
Suggests: did (>= 2.1.0), knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr, rmarkdown
URL: https://github.com/ronwag2005/phdid
BugReports: https://github.com/ronwag2005/phdid/issues
NeedsCompilation: no
Packaged: 2026-09-07 12:58:30 UTC; rohanwagle
Author: Rohan Wagle [aut, cre, cph], Parush Arora [aut, cph]
Maintainer: Rohan Wagle <rohan.wagle_ug2023@ashoka.edu.in>
Repository: CRAN
Date/Publication: 2026-09-15 12:00:02 UTC

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New package NSC with initial version 1.1.8
Package: NSC
Title: Format Student Data for the National Student Clearinghouse
Version: 1.1.8
Date: 2026-09-07
Description: Formats student records for submission to the National Student Clearinghouse. The package creates the required header, detail, and trailer rows and writes tab-delimited TXT and CSV files.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: readxl, stringi
NeedsCompilation: no
Packaged: 2026-09-07 14:00:58 UTC; BKlauth
Author: Bo Klauth [aut, cre]
Maintainer: Bo Klauth <bklauth@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 12:00:18 UTC

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New package multiCorr with initial version 0.1.0
Package: multiCorr
Title: Multicovariance and Multicorrelation for p-Variables
Version: 0.1.0
Description: Implements the multicorrelation coefficient for p-variables as described in Cankaya (2023). The package provides a numerically stable implementation using logarithmic transformations and a log-sum-exp approach to reduce numerical overflow and underflow when calculations involve a large number of variables.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-07 08:16:08 UTC; mehmet.cankaya
Author: Mehmet Niyazi Cankaya [aut, cre]
Maintainer: Mehmet Niyazi Cankaya <mehmet.cankaya@usak.edu.tr>
Repository: CRAN
Date/Publication: 2026-09-15 11:50:08 UTC

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New package GMTM with initial version 0.1.0
Package: GMTM
Title: Gaussian Mixture Text Models for Topic Analysis
Version: 0.1.0
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>
Description: Gaussian mixture models and k-means for topic analysis of dense document vectors. The underlying clustering functions rely on the Armadillo library.
License: Apache License (>= 2.0)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: quanteda (>= 4.0.0), proxyC, wordvector, Rcpp, RcppArmadillo
Suggests: testthat, spelling, rmarkdown, knitr
LinkingTo: Rcpp, RcppArmadillo (>= 0.7.600.1.0), quanteda, testthat
Language: en-US
NeedsCompilation: yes
Packaged: 2026-09-06 02:28:38 UTC; watan
Author: Kohei Watanabe [aut, cre, cph]
Repository: CRAN
Date/Publication: 2026-09-15 11:20:09 UTC

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New package drmTMB with initial version 0.7.0
Package: drmTMB
Title: Distributional Regression Models Using Template Model Builder
Version: 0.7.0
Description: Fast distributional regression models for univariate and bivariate responses using Template Model Builder. The current implementation focuses on Gaussian, Student-t, and skew-normal location-scale models, known sampling covariance, phylogenetic location effects, random-effect scale models, bivariate residual correlation, positive-continuous, 'Tweedie' semi-continuous, strict-proportion, zero-one bounded, and denominator-aware proportion families, fixed-effect Bernoulli/binomial event-probability models, and fixed-effect Poisson, negative-binomial, zero-inflated, zero-truncated, hurdle count, and ordinal cumulative-logit models. Additional response-family models are staged for later phases. Every fitted family also exposes a distributional-output and adequacy layer: randomized quantile-residual worm and QQ plots that detect fixed-effect shape and atom misspecification, and conditional-quantile, exceedance, and centile outputs with plug-in (uncalibrated) intervals.
License: GPL (>= 3)
URL: https://itchyshin.github.io/drmTMB/, https://github.com/itchyshin/drmTMB
BugReports: https://github.com/itchyshin/drmTMB/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: cli, lifecycle, Matrix (>= 1.6.0), methods, stats, TMB (>= 1.9.6), utils
LinkingTo: RcppEigen, TMB
Suggests: ape, callr, detectseparation (>= 0.4.0), emmeans, extraDistr, fmesher, glmmTMB, ggplot2, JuliaCall, knitr, lme4, MASS, metadat, metafor, mvtnorm, nlme, numDeriv, ordinal, palmerpenguins, pkgload, rmarkdown, sf, spelling, statmod, testthat (>= 3.0.0), tweedie, withr
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-09-05 19:15:32 UTC; z3437171
Author: Shinichi Nakagawa [aut, cre, cph]
Maintainer: Shinichi Nakagawa <itchyshin@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 11:00:29 UTC

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New package detectPanel with initial version 0.1.3
Package: detectPanel
Title: Leakage-Aware Discovery of Small Biomarker Panels
Version: 0.1.3
Author: Fuhao Jiang [aut, cre]
Maintainer: Fuhao Jiang <emr39515@gmail.com>
Description: Discovers small binary-classification biomarker panels from count or expression matrices while prioritizing detectability, expression stability, and univariate discrimination. Candidate filtering and panel selection can be repeated inside nested cross-validation to reduce information leakage. The package provides shared resampling splits, exhaustive small-panel search, logistic model fitting with an automatic ridge fallback for unstable separation-prone fits, out-of-fold evaluation, selection-frequency summaries, and optional 'DESeq2' differential-expression support. The nested model-selection workflow follows Varma and Simon (2006) <doi:10.1186/1471-2105-7-91>, and the optional differential-expression analysis uses Love, Huber, and Anders (2014) <doi:10.1186/s13059-014-0550-8>.
License: MIT + file LICENSE
URL: https://github.com/Emr-27/detectPanel
BugReports: https://github.com/Emr-27/detectPanel/issues
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: ggplot2, graphics, stats, utils
Suggests: DESeq2, knitr, rmarkdown, pheatmap, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-05 18:45:46 UTC; 24791
Repository: CRAN
Date/Publication: 2026-09-15 11:00:41 UTC

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New package coinclp with initial version 0.1.0
Package: coinclp
Title: R Interface to the 'COIN-OR' 'Clp' Linear Programming Solver
Version: 0.1.0
Description: Solves linear programs with 'Clp', the simplex and interior point code of the 'COIN-OR' project <https://github.com/coin-or/Clp>. Provides a one-call solver interface for dense and sparse constraint matrices, and complete low level bindings to the 'Clp' callable library covering problem construction, warm starts, presolve options, basis access and 'MPS' files. A compatibility layer reproduces the interface of the archived 'clpAPI' package so that existing code keeps working. 'Clp' itself is not bundled and must be installed on the system; the 'Rtools' toolchain supplies it on 'Windows'.
License: EPL
URL: https://github.com/SamLovick/coinclp
BugReports: https://github.com/SamLovick/coinclp/issues
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: methods, stats, utils
Suggests: Matrix, slam, knitr, rmarkdown
VignetteBuilder: knitr
SystemRequirements: COIN-OR Clp (>= 1.16) with development headers, and a C++17 compiler. Debian/Ubuntu: coinor-libclp-dev, Fedora: coin-or-Clp-devel, macOS: brew install clp, Windows: supplied by Rtools.
NeedsCompilation: yes
Packaged: 2026-09-05 23:26:06 UTC; samlo
Author: Sam Lovick [aut, cre]
Maintainer: Sam Lovick <sam@lovickconsulting.com>
Repository: CRAN
Date/Publication: 2026-09-15 11:10:02 UTC

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New package cdmeta with initial version 1.1-1
Package: cdmeta
Title: Confidence-Distribution-Based Inference for Random-Effects Meta-Analysis
Version: 1.1-1
Date: 2026-09-07
Maintainer: Hisashi Noma <noma@ism.ac.jp>
Description: Computational tools for confidence-distribution-propagation-based inference in random-effects meta-analysis. Implements confidence-distribution propagation for frequentist inference in random-effects meta-analysis. The package samples the between-study variance from a confidence distribution based on the exact distribution of Cochran's Q, samples the average effect conditionally on each draw, and generates the true effect in a future study. It provides prediction intervals and confidence intervals for the average effect, between-study variance, between-study standard deviation, and I2. The methods are described in Noma and Schwarzer (2026) <doi:10.48550/arXiv.2608.26527>.
Depends: R (>= 3.5.0)
Imports: stats, graphics, pimeta (>= 1.1.3)
Suggests: metafor
URL: https://github.com/guido-s/cdmeta
BugReports: https://github.com/guido-s/cdmeta/issues
License: GPL-3
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-07 10:00:30 UTC; nomah
Author: Hisashi Noma [aut, cre] , Guido Schwarzer [aut]
Repository: CRAN
Date/Publication: 2026-09-15 11:50:13 UTC

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New package campsisnca with initial version 1.7.1
Package: campsisnca
Title: Non-Compartmental Analysis for Campsis Simulation Platform
Version: 1.7.1
Description: A flexible and user-friendly non-compartmental analysis (NCA) toolkit designed to work seamlessly with simulated pharmacokinetic data generated using the 'campsis' ecosystem. The package provides a comprehensive framework to compute standard and custom NCA metrics, including exposure (AUC), peak/trough concentrations, half-life and time-above/below thresholds, with support for configurable time windows and summary statistics. 'campsisnca' integrates tightly with 'campsis' and 'campsismod', enabling streamlined workflows from simulation to analysis. In addition, the package provides a JSON-based interface to define NCA analyses, metrics and options using formal schemas, allowing analyses to be created, validated and executed outside of R and facilitating reproducibility, automation and system integration. The package also includes utilities for generating formatted summary tables and exporting results in multiple formats suitable for reporting. Trapezoidal rule implementation for AUC ca [...truncated...]
License: GPL (>= 3)
URL: https://github.com/Calvagone/campsisnca
BugReports: https://github.com/Calvagone/campsisnca/issues
Depends: campsismod, R (>= 4.0.0)
Imports: assertthat, campsis, cards, dplyr, glue, gt, gtsummary, jsonlite, jsonvalidate, lifecycle, magrittr, methods, purrr, rlang, stringr, tibble, tidyr
Suggests: devtools, ggplot2, mrgsolve, pkgdown, rmarkdown, roxygen2, rxode2, testthat
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-07 12:16:58 UTC; nicolas
Author: Nicolas Luyckx [aut, cre]
Maintainer: Nicolas Luyckx <nicolas.luyckx@calvagone.com>
Repository: CRAN
Date/Publication: 2026-09-15 12:00:10 UTC

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New package T1FF with initial version 0.1.0
Package: T1FF
Title: Type-1 Fuzzy Functions for Classification, Regression, and Forecasting
Version: 0.1.0
Description: Fits Type-1 Fuzzy Function models for binary classification, numeric regression, and time-series forecasting with user-supplied temporal predictors. The package combines fuzzy C-means memberships, nonlinear membership transformations, cluster-specific linear or support vector machine models, and membership-weighted predictions. It also provides model evaluation, validation, K-fold and stratified K-fold tuning, and repeated nested cross-validation with task-appropriate metrics. The regression workflow can be used for forecasting when temporal dependence is represented by lagged or seasonal predictors and assessment partitions preserve chronological order.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: e1071, kernlab, stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-05 18:32:29 UTC; nihattak
Author: Nihat Tak [aut, cre]
Maintainer: Nihat Tak <nihattak@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 10:50:33 UTC

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New package sTiles with initial version 2026.9.4
Package: sTiles
Title: Tile-Based Sparse Cholesky Factorization and Selected Inverse
Version: 2026.9.4
Description: Interface to the 'sTiles' framework for tile-based sparse Cholesky factorization: log-determinants, selected inverse (marginal variances) and triangular solves, with symbolic reuse so that repeated factorization of matrices sharing one sparsity pattern pays the ordering cost only once, as in a hyperparameter sweep. The compiled glue in this package resolves its symbols at run time against the 'sTiles' solver library ('libstiles'), which is a separate component distributed under its own terms and is not part of this package. Install it once with 'sTiles_install_library()', or point the package at a copy you already have with the 'STILES_LIB' environment variable.
License: MIT + file LICENSE
URL: https://esmail-abdulfattah.github.io/sTiles/
BugReports: https://github.com/esmail-abdulfattah/sTiles/issues
Imports: methods, Matrix, tools, utils
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
SystemRequirements: the 'sTiles' solver library (libstiles.so on Linux, libstiles.dylib on macOS, libstiles.dll on Windows), obtained with sTiles_install_library() or supplied by the user
Encoding: UTF-8
Packaged: 2026-09-06 15:22:22 UTC; abdulfe
Author: Esmail Abdul Fattah [aut, cre, cph]
Maintainer: Esmail Abdul Fattah <esmail.abdulfattah@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 10:50:02 UTC

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New package sezgi with initial version 0.1.1
Package: sezgi
Title: Metaheuristic Optimization with a 'Rust' Core
Version: 0.1.1
Description: Build and run metaheuristic optimization algorithms as serializable component graphs executed by a 'Rust' core, with reproducible, bit-exact trajectories shared across the 'R' and 'Python' frontends. Includes population and local-search algorithm presets, standard benchmark suites (BBOB, CEC 2014/2017/2022, TSP), multi-objective indicators, structural-bias diagnostics and statistical comparison tools.
License: MIT + file LICENSE
Copyright: sezgi authors, except as documented in inst/COPYRIGHTS (bundled benchmark data and quoted reference excerpts)
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: R6 (>= 2.4.0)
Suggests: testthat (>= 3.0.0), jsonlite
SystemRequirements: Cargo (Rust's package manager), rustc (>= 1.88)
URL: https://github.com/tdelphi1981/sezgi
BugReports: https://github.com/tdelphi1981/sezgi/issues
NeedsCompilation: yes
Packaged: 2026-09-05 13:03:59 UTC; tolgaberber
Author: Tolga Berber [aut, cre] , Beyzanur Siyah [aut] , Emir Karayagiz [aut] , The authors of the dependency Rust crates [ctb]
Maintainer: Tolga Berber <tolga.berber@fen.ktu.edu.tr>
Repository: CRAN
Date/Publication: 2026-09-15 10:40:02 UTC

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New package SelectionTools with initial version 26.3
Package: SelectionTools
Version: 26.3
Date: 2026-09-05
Title: Simulation and Data Analysis for Plant Breeders
Description: Provides tools for simulation of plant breeding programs as described, for example, by Melchinger and Frisch (2023) <doi:10.1007/s00122-023-04446-3>, prediction of segregation variance (Osthushenrich, Frisch and Herzog (2017) <doi:10.1371/journal.pone.0188839>), genomic prediction (Hofheinz and Frisch (2014) <doi:10.1534/g3.113.010025>), linkage disequilibrium based haplotype construction, and planning of marker assisted back crossing programs.
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 4.0.0)
License: CC0
NeedsCompilation: yes
Packaged: 2026-09-05 11:22:03 UTC; frisch-m
Author: Matthias Frisch [aut, cre], Hans Peter Maurer [ctb], Philipp Heilmann [ctb]
Maintainer: Matthias Frisch <matthias.frisch@uni-giessen.de>
Repository: CRAN
Date/Publication: 2026-09-15 10:40:21 UTC

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New package refuginator with initial version 1.0.2
Package: refuginator
Title: An Interactive Tool for Identifying Refugia
Version: 1.0.2
Description: A 'shiny'-based browser application for reconstructing organismal distributions and identifying historical and geohistorical refugia using the methods published by Morley et al. (2026) <doi:10.1038/s43247-026-03563-3>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: dplyr, gganimate, ggplot2, leaflet, neotoma2, plotly, rlang, rnaturalearth, rnaturalearthdata, scales, sf, shiny, shinycssloaders, shinyjs, stringr, tidyr, viridis
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/nathanielmorley2000/refuginator
BugReports: https://github.com/nathanielmorley2000/refuginator/issues
NeedsCompilation: no
Packaged: 2026-09-05 05:34:30 UTC; dinom
Author: Nathaniel E. D. Morley [aut, cre, cph]
Maintainer: Nathaniel E. D. Morley <nathaniel.morley2000@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 10:30:02 UTC

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New package raiseR with initial version 0.1.0
Package: raiseR
Title: Raise Regression and Robust Methods for Multicollinearity
Version: 0.1.0
Description: Implements Raise Regression as an inference-preserving alternative to Ridge Regression for combating multicollinearity in linear models, including the classical single-variable Raise Regression, the Simultaneous Raise Regression (SRR) based on QR decomposition and the Sequential Variance Inflation Factor (SVIF) of Jacob and Varadharajan (2022) <doi:10.1007/s11135-022-01557-9>, and the original raise parameter selection strategy of Jacob and Varadharajan (2023) <doi:10.13189/ms.2023.110106>. Also implements Robust Raise Regression for data contaminated by outliers, with exact finite-sample inference (sandwich standard errors, Wald tests, Satterthwaite-corrected degrees of freedom) obtained by down-weighting observations using Stahel-Donoho projection outlyingness and Tukey's biweight function. Provides ordinary and robust Ridge Regression (Hoerl and Kennard, 1970, <doi:10.1080/00401706.1970.10488634>), ordinary and robust Liu Regression (Liu, 1993, <doi:10.1080/0361 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, graphics, grDevices, mrfDepth, MASS, withr
Suggests: testthat (>= 3.0.0), lmtest, car
URL: https://github.com/jinsejacob/raiseR
BugReports: https://github.com/jinsejacob/raiseR/issues
Author: Jinse Jacob [aut, cre]
Maintainer: Jinse Jacob <jinsejacob@hotmail.com>
NeedsCompilation: no
Packaged: 2026-09-05 05:56:09 UTC; root
Repository: CRAN
Date/Publication: 2026-09-15 10:50:07 UTC

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New package orange with initial version 0.1.0
Package: orange
Title: Spherical Descriptors of Geographic Distributions
Version: 0.1.0
Maintainer: Adam T. Kocsis <adam.t.kocsis@gmail.com>
Description: Characterization of distribution data on the surface of a sphere. The primary group of these metrics describe the extent of a distribution, geographic ranges. The calculation of geographic descriptors can be executed using point coordinate data, vector polygons, as well as cells on a discretized sphere. Besides using spherical implementations, the package offers the exploration of partial results for visual diagnostics.
License: GPL-3
Date: 2026-08-23
BugReports: https://github.com/adamkocsis/orange/issues
Encoding: UTF-8
LazyData: false
URL: https://adamtkocsis.com/orange/
Depends: R (>= 4.0.0), icosa (>= 0.12.0)
Imports: igraph, methods
NeedsCompilation: no
Suggests: sf, knitr, rmarkdown, vegan
Packaged: 2026-09-05 18:18:47 UTC; adam
Author: Adam T. Kocsis [cre, aut] , Elizabeth M. Dowding [ctb] , FAU GeoZentrum Nordbayern [fnd]
Repository: CRAN
Date/Publication: 2026-09-15 10:50:14 UTC

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New package nonnet with initial version 1.0.0
Package: nonnet
Title: Generate and Analyze Nonlinear Networks
Version: 1.0.0
Maintainer: Lindley Slipetz <ddj6tu@virginia.edu>
Description: Creates and detects nonlinear relations using the methods described in Slipetz, Qiu, Sun, and Henry (2026) <doi:10.48550/arXiv.2411.02763>. Use the netgen() function to generate a nonlinear network and the dcor_res() function for a residualization procedure for detecting nonlinear relations.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: energy, mgcv, stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-05 14:55:45 UTC; ddj6tu
Author: Lindley Slipetz [aut, cre], Teague Henry [ctb]
Repository: CRAN
Date/Publication: 2026-09-15 10:40:11 UTC

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New package imply with initial version 0.1.0
Package: imply
Version: 0.1.0
Date: 2026-09-05
Title: Efficiently Apply Functions to Images
Description: Infrastructure for handling generalised two and three dimensional images, which may hold multiple values at each spatial location, and efficiently applying functions to them. Dense, compacted and sparse pixel/voxel representations are supported, with one core engine for processing them all. Parallelism is supported via the 'parallel' package, 'libdispatch' and 'OpenMP'.
Imports: Rcpp, S7, methods
LinkingTo: Rcpp, RcppArray
Suggests: tinytest
Encoding: UTF-8
License: BSD_3_clause + file LICENCE
URL: https://github.com/jonclayden/imply
BugReports: https://github.com/jonclayden/imply/issues
NeedsCompilation: yes
Packaged: 2026-09-05 14:10:31 UTC; jon
Author: Jon Clayden [cre, aut]
Maintainer: Jon Clayden <code@clayden.org>
Repository: CRAN
Date/Publication: 2026-09-15 10:40:16 UTC

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New package genpca with initial version 0.2.0
Package: genpca
Title: Generalized Principal Component Analysis
Version: 0.2.0
Description: Generalized PCA and related matrix decompositions in weighted inner-product spaces. Methods are based on Allen, G. I., Grosenick, L., and Taylor, J. (2014) <doi:10.1080/01621459.2013.852978>, "A generalized least-square matrix decomposition", Journal of the American Statistical Association, 109(505), 145-159; and Abdi, H. (2007), "Singular value decomposition (SVD) and generalized singular value decomposition" <https://personal.utdallas.edu/~herve/Abdi-SVD2007-pretty.pdf>, in "Encyclopedia of Measurement and Statistics", 907-912.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: Rcpp, eigencore (>= 1.0.3), FNN, Matrix, multivarious (>= 0.3.0), assertthat, methods, digest
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Suggests: testthat (>= 3.0.0), adjoin, irlba, matrixStats, clue, knitr, rmarkdown, ggplot2, albersdown, ragg, systemfonts
VignetteBuilder: knitr
URL: https://bbuchsbaum.github.io/genpca/, https://github.com/bbuchsbaum/genpca
BugReports: https://github.com/bbuchsbaum/genpca/issues
NeedsCompilation: yes
Packaged: 2026-09-05 19:18:39 UTC; bbuchsbaum
Author: Brad Buchsbaum [aut, cre, cph]
Maintainer: Brad Buchsbaum <brad.buchsbaum@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 10:50:19 UTC

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New package dtlog with initial version 0.1.0
Package: dtlog
Title: Logging for 'data.table' Operations
Version: 0.1.0
Description: Provides feedback about 'data.table' operations. 'dtlog' redefines the subsetting method for data tables as well as several functions exported by 'data.table' so that each operation prints a short message describing what it did: how many rows were removed, which columns were added, updated or dropped, how many groups an aggregation produced, and so on. The operations themselves are left untouched, including modification by reference. It also provides dttable(), which describes the variables a single data table holds and passes every other call on to base::table() unchanged. Inspired by the 'tidylog' package.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 3.5.0)
Imports: data.table (>= 1.14.0), stats, utils
Suggests: testthat (>= 3.0.0), dplyr, tidyr, tidylog, tibble, knitr, rmarkdown
VignetteBuilder: knitr, rmarkdown
URL: https://github.com/AkiShiroshita/dtlog, https://akishiroshita.github.io/dtlog/
BugReports: https://github.com/AkiShiroshita/dtlog/issues
NeedsCompilation: no
Packaged: 2026-09-05 22:13:16 UTC; shiroa1
Author: Akihiro Shiroshita [aut, cre, cph]
Maintainer: Akihiro Shiroshita <akihirokun8@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-15 10:50:27 UTC

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Mon, 14 Sep 2026

New package rSSP with initial version 0.1.0
Package: rSSP
Title: Single Acceptance Sampling Plans for Time-Truncated Life Test
Version: 0.1.0
Description: Designing single acceptance sampling inspection plans under time-truncated life tests and calculates the minimum required sample size subject to a consumer's risk constraint on the probability of acceptance. Failure probabilities can be supplied from any lifetime distribution, allowing the methodology to be applied without restricting the analysis to a particular probability model. The package also provides plot of the required sample size against the termination ratio. Tripathi et al. (2023) <doi:10.1007/s41872-023-00221-x>; Hu and Gui (2018) <doi:10.1080/09720510.2017.1413044>.
License: GPL-3
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-09-03 06:47:19 UTC; Admin
Author: Harsh Tripathi [aut, cre]
Maintainer: Harsh Tripathi <rsearchstat21@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 20:00:02 UTC

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New package p2oncology with initial version 0.1.1
Package: p2oncology
Version: 0.1.1
Title: Single Arm Phase 2 Oncology Trial
Author: Ping Gao [aut, cre]
Maintainer: Ping Gao <support@innovatiostat.com>
Description: Single arm phase 2 oncology trial. For more details see P. Gao (2024) <doi:10.1080/10543406.2024.2341673>.
Depends: clinfun, mvtnorm, doParallel
License: MIT + file LICENSE
Encoding: UTF-8
Imports: foreach, dplyr, jsonlite
URL: https://github.com/innovatiostat/rcode
BugReports: https://github.com/innovatiostat/rcode/issues
NeedsCompilation: no
Packaged: 2026-09-04 01:08:02 UTC; chengboqin
Repository: CRAN
Date/Publication: 2026-09-14 19:50:02 UTC

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New package ZINB.GP with initial version 1.0.0
Package: ZINB.GP
Title: Bayesian Zero-Inflated Negative Binomial Gaussian Process Models
Version: 1.0.0
Description: Fits Bayesian zero-inflated negative binomial regression models with Gaussian process random effects for spatial, temporal, or spatiotemporal count data. Provides Markov chain Monte Carlo sampling, configurable random effects in the zero-inflation and count components, and posterior predictive draws. Implements a full GP version of the methods described by He and Huang (2024) <doi:10.1016/j.jspi.2023.106098>.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/KingJMS1/GP_ZINB_R, https://kingjms1.github.io/GP_ZINB_R/
BugReports: https://github.com/KingJMS1/GP_ZINB_R/issues
Imports: BayesLogit, LaplacesDemon, MASS, Matrix, msm, mvtnorm, stats
Suggests: coda, knitr, posterior, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-04 15:46:22 UTC; 1king
Author: Mahlon Scott [aut], Qing He [aut], Hsin-Hsiung Huang [aut, cre, cph]
Maintainer: Hsin-Hsiung Huang <hsin.huang@ucf.edu>
Repository: CRAN
Date/Publication: 2026-09-14 15:40:10 UTC

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New package SensoryDataSets with initial version 0.1.0
Package: SensoryDataSets
Title: A Collection of Sensory Evaluation and Consumer Science Datasets
Version: 0.1.0
Description: Provides a curated collection of datasets for sensory evaluation, consumer research, and related statistical applications. The collection includes consumer acceptance and liking scores, sensory profiles, descriptive evaluations, physical and chemical measurements, wine quality and bitterness assessments, and data from products such as bread, olive oil, orange juice, grape blends, wine, cocktails, and perfume. The package is intended for teaching, exploratory data analysis, statistical modeling, multivariate analysis, consumer studies, and methodological research in sensory and consumer science. The original sources and applicable licensing terms are documented in the 'LICENSES_DETAILS.md' file.
License: GPL (>= 2) | GPL-3
URL: https://github.com/dianarebaza/sensorydatasets, https://dianarebaza.github.io/sensorydatasets/
BugReports: https://github.com/dianarebaza/sensorydatasets/issues
Depends: R (>= 4.1.0)
Imports: utils
Suggests: dplyr, ggplot2, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-04 19:03:47 UTC; ADMIN
Author: Diana Rebaza Fernandez [aut, cre, cph]
Maintainer: Diana Rebaza Fernandez <drebazaf@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:40:17 UTC

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New package mardist with initial version 1.0.1
Package: mardist
Title: Calculation of Maritime Distances
Version: 1.0.1
Encoding: UTF-8
Date: 2026-09-03
Description: Tools and utilities for calculating distances and visualising maritime routes.
License: EUPL
Depends: R (>= 3.5)
Imports: data.table, dplyr, leaflet, igraph
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-04 13:47:20 UTC; chrisps@delta.europa.eu
Author: Panayotis Christidis [cre, aut]
Maintainer: Panayotis Christidis <Panayotis.Christidis@ec.europa.eu>
Repository: CRAN
Date/Publication: 2026-09-14 15:30:02 UTC

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New package koopman.dmd with initial version 0.2.2
Package: koopman.dmd
Title: Koopman Operator and Dynamic Mode Decomposition for Dynamical Systems
Version: 0.2.2
Description: Dynamic Mode Decomposition (DMD) with Koopman operator theory extensions, powered by a Rust backend via 'extendr'. Provides standard DMD as described in Schmid (2010) <doi:10.1017/S0022112010001217>, DMD with control for forced linear systems following Proctor, Brunton, and Kutz (2016) <doi:10.1137/15M1013857>, Extended DMD with lifting functions, Hankel-DMD via time-delay embedding, Generalized Laplace Analysis for direct eigenfunction computation, and harmonic time averages and mesochronic harmonic plots for phase space analysis as developed in Mezic (2020) <doi:10.48550/arXiv.2009.05883>. Includes built-in area-preserving and chaotic maps for experimentation.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: Cargo (Rust's package manager), rustc (>= 1.85)
Depends: R (>= 4.0)
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/jimeharrisjr/rust-dmd, https://jimeharrisjr.github.io/rust-dmd/
BugReports: https://github.com/jimeharrisjr/rust-dmd/issues
NeedsCompilation: yes
Biarch: false
Packaged: 2026-09-03 23:59:34 UTC; jimharris
Author: James Harris [aut, cre, cph], The authors of the dependency Rust crates [ctb]
Maintainer: James Harris <jimeharrisjr@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:20:02 UTC

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New package featR with initial version 0.1.0
Package: featR
Title: A Unified Toolkit for Feature Selection
Version: 0.1.0
Description: Filter, wrapper, and embedded feature-selection methods behind a consistent set of functions that share one calling convention and one return type: correlation and chi-squared filters, information gain, LASSO and elastic net, Bayesian model comparison, Boruta, recursive feature elimination, random forest importance, multivariate adaptive regression splines, support vector machine recursive feature elimination, stepwise selection, and principal component / singular value decomposition helpers. The implemented methods follow Tibshirani (1996) <doi:10.1111/j.2517-6161.1996.tb02080.x>, Zou and Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, Friedman (1991) <doi:10.1214/aos/1176347963>, Breiman (2001) <doi:10.1023/A:1010933404324>, Guyon, Weston, Barnhill and Vapnik (2002) <doi:10.1023/A:1012487302797>, Kursa and Rudnicki (2010) <doi:10.18637/jss.v036.i11>, and Vehtari, Gelman and Gabry (2017) <doi:10.1007/s11222-016-9696-4>. Heavy modeling en [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: data.table, parallel, stats, utils, withr
Suggests: bigstatsr, Boruta, brms, caret, doParallel, e1071, earth, foreach, furrr, future, ggplot2, glmnet, kernlab, knitr, loo, MASS, Matrix, MLmetrics, pbapply, polycor, pROC, PRROC, randomForest, rmarkdown, RSpectra, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/elkronos/featR
BugReports: https://github.com/elkronos/featR/issues
NeedsCompilation: no
Packaged: 2026-09-04 21:00:35 UTC; appleair
Author: Justin Chase [aut, cre, cph]
Maintainer: Justin Chase <jchase.msu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:40:02 UTC

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New package cureAssess with initial version 0.1.0
Package: cureAssess
Title: Assessing Cure Model Appropriateness for Survival Data
Version: 0.1.0
Description: Assesses whether cure models are appropriate for right-censored survival data, where a fraction of subjects may never experience the event of interest. Implements a two-stage workflow combining Kaplan-Meier visualization and comparison of parametric cure and non-cure models by the Akaike information criterion with formal diagnostics for sufficient follow-up and for the presence of a cured fraction. The diagnostics include the statistics of Maller and Zhou (1992) <doi:10.1093/biomet/79.4.731> and Maller and Zhou (1994) <doi:10.1080/01621459.1994.10476889>, the test of Shen (2000) <doi:10.1016/S0167-7152(00)00063-8>, and the ratio estimation of censored uncured subjects ('RECeUS') method of Selukar and Othus (2023) <doi:10.1002/sim.9610>.
License: MIT + file LICENSE
URL: https://github.com/GeethanjaleeM/cureAssess
BugReports: https://github.com/GeethanjaleeM/cureAssess/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: survival, flexsurv, flexsurvcure, survminer, ggplot2, dplyr, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-02 19:48:52 UTC; durbadal
Author: Geethanjalee Mudunkotuwa [aut, cre, cph], Durbadal Ghosh [aut]
Maintainer: Geethanjalee Mudunkotuwa <geethanjaleem@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 15:50:02 UTC

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New package xplaineff with initial version 0.1.0
Package: xplaineff
Title: Decomposing Global Feature Effects Based on Feature Interactions
Version: 0.1.0
Description: Implements the GADGET (Generalized Additive Decomposition of Global EffecTs) algorithm for interpretable machine learning. The package recursively partitions the feature space to minimize heterogeneity of feature effects (e.g., Accumulated Local Effects or Partial Dependence), producing a tree of regions where effects are more stable. It supports both ALE and PD strategies, works with 'mlr3' learners and provides visualization of the interaction tree and regional effect plots. The method is described in Herbinger, J., Wright, M. N., Nagler, T., Bischl, B., and Casalicchio, G. (2024), "Decomposing Global Feature Effects Based on Feature Interactions" <https://jmlr.org/papers/volume25/23-0699/23-0699.pdf>.
License: MIT + file LICENSE
Depends: R (>= 4.3.0)
URL: https://github.com/mlr-org/xplaineff
BugReports: https://github.com/mlr-org/xplaineff/issues
Encoding: UTF-8
Imports: checkmate (>= 2.3.2), cli (>= 3.0.0), data.table (>= 1.14.0), ggplot2 (>= 3.5.2), ggraph (>= 2.2.1), igraph (>= 2.1.4), mlr3misc (>= 0.14.0), patchwork (>= 1.3.0), R6 (>= 2.6.1), Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat (>= 3.0.0), iml (>= 0.11.4), mlr3, mlr3learners, ranger, ISLR2, rpart, withr, xgboost
NeedsCompilation: yes
Packaged: 2026-09-04 08:21:15 UTC; zzz
Author: Zizheng Zhang [aut, cre]
Maintainer: Zizheng Zhang <Zizheng.Zhang@stat.uni-muenchen.de>
Repository: CRAN
Date/Publication: 2026-09-14 15:00:02 UTC

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New package AutoViz with initial version 1.0.0
Package: AutoViz
Title: Automated Data Visualization and Exploratory Dashboarding
Version: 1.0.0
Description: Provides automated exploratory data analysis, visualization recommendation, summary statistics, missing-value assessment, outlier screening, and HTML dashboard generation for rectangular data. The package automatically identifies variable types and common analytical relationships and recommends appropriate visualization methods based on data structure, cardinality, and analytical objectives. It provides a transparent, reproducible workflow for data profiling and visualization that can be used independently or as a component within interactive applications.
License: MIT + file LICENSE
Language: en-US
Encoding: UTF-8
Imports: ggplot2, htmltools, rlang
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, shiny
VignetteBuilder: knitr
URL: https://github.com/vinodhpmd/AutoViz
BugReports: https://github.com/vinodhpmd/AutoViz/issues
NeedsCompilation: no
Packaged: 2026-09-04 05:14:50 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-14 14:50:02 UTC

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Sat, 12 Sep 2026

New package qpost with initial version 1.0.0
Package: qpost
Title: Create a 'Quarto' Blog Post
Version: 1.0.0
Description: Provides an interactive 'RStudio' dialog for creating 'Quarto' blog posts with correctly structured YAML front matter. The dialog collects title, author, date, categories, and other metadata, then scaffolds the post directory, creates the 'index.qmd' file, and optionally copies an image. A companion function appends COinS (ContextObjects in Spans) metadata to posts for automatic bibliographic import into reference managers such as 'Zotero'.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
URL: https://github.com/petzi53/qpost, https://www.peter-baumgartner.net/qpost/
BugReports: https://github.com/petzi53/qpost/issues
Imports: fs, glue, here, htmltools, lubridate, miniUI, purrr, readr, rlang, rstudioapi, shiny, shinyFeedback, stringi, stringr, urltools, yesno, yaml
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-03 15:33:56 UTC; petzi
Author: Peter Baumgartner [aut, cre, cph]
Maintainer: Peter Baumgartner <petzi53@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 15:20:02 UTC

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New package chestR with initial version 0.1.0
Package: chestR
Title: Kernel-Weighted Cox Regression for Treatment Effect Heterogeneity
Version: 0.1.0
Description: Explores treatment effect heterogeneity and candidate predictive biomarkers by re-fitting weighted Cox proportional hazards models on a biomarker grid. Kernel weights centred at each grid point produce local coefficient estimates that can be visualised across biomarker space. Builds on ideas related to graphical Cox treatment-covariate interaction methods [see Bonetti and Gelber (2004) <doi:10.1093/biostatistics/kxh002> and local partial-likelihood approaches Fan, Lin and Zhou (2006) <doi:10.1214/009053605000000796>].
License: MIT + file LICENSE
Encoding: UTF-8
VignetteBuilder: knitr
Imports: survival, ggplot2, scales
Suggests: knitr, rmarkdown, mvtnorm, testthat (>= 3.0.0)
Language: en-GB
NeedsCompilation: no
Packaged: 2026-09-03 15:15:40 UTC; richardjackson
Author: Richard Jackson [aut, cre], Caroline Jeffery [aut]
Maintainer: Richard Jackson <richj23@liverpool.ac.uk>
Repository: CRAN
Date/Publication: 2026-09-12 15:10:02 UTC

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New package USPopulationSampler with initial version 0.1.1
Package: USPopulationSampler
Title: Population-Weighted Sampling of Geographic Locations in the United States
Version: 0.1.1
Description: Generate geospatial locations within census block groups (BG; the smallest geographic unit for which population counts are available) within target counties, states, or across the entirety of the U.S. randomly selected according to population counts by using the Census Bureau reference data and optionally allow users to conduct temporal assignments on sampled locations using Covid-19 data.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: curl, parallel, sf, arrow, data.table, utils, stats
Suggests: dplyr, usmap, ggplot2, tigris, patchwork, lubridate, lwgeom, testthat (>= 3.0.0), spelling
URL: https://github.com/Techavoan/USPopulationSampler
BugReports: https://github.com/Techavoan/USPopulationSampler/issues
Depends: R (>= 3.5)
LazyData: true
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-03 11:57:27 UTC; techa
Author: Rithy Techavoan Yean [aut, cre, cph], Andrew Holbrook [aut, cph], Jasen Zhang [ctb]
Maintainer: Rithy Techavoan Yean <techavoan@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:20:16 UTC

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New package spconform with initial version 0.1.0
Package: spconform
Title: Conformal Prediction for Spatially and Spatio-Temporally Dependent Data
Version: 0.1.0
Description: Provides distribution-free, model-agnostic prediction intervals for spatially and spatio-temporally dependent data using localized conformal calibration. Implements locally weighted split conformal prediction for geostatistical (point-referenced) data based on spatial-distance kernels, and a neighbourhood-weighted conformal procedure for areal (lattice) data based on graph adjacency structures. Relaxes the standard exchangeability assumption using spatial proximity, following the localized conformal framework of Mao, Martin and Reich (2024) <doi:10.1080/01621459.2022.2147531>. Includes comprehensive spatial diagnostic tools to audit empirical coverage, conditional spatial strata, and boundary proximity effects.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.6.0)
Imports: graphics, grDevices, stats
Suggests: bmstdr, knitr, mgcv, ranger, rmarkdown, sp, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/amjed-droid/spconform, https://amjed-droid.github.io/spconform/, https://doi.org/10.5281/zenodo.21862024
BugReports: https://github.com/amjed-droid/spconform/issues
Language: en-US
NeedsCompilation: no
Packaged: 2026-09-03 14:57:20 UTC; intel
Author: Ahmed Sattar Jabbar [aut, cre]
Maintainer: Ahmed Sattar Jabbar <ahmed.state.me@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:40:02 UTC

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New package soReta with initial version 0.1.0
Package: soReta
Title: Ready-to-Analyze Datasets from Camera Trap Data
Version: 0.1.0
Description: Functions to build datasets ready for statistical analysis from camera trap data: GLMM/GAMM on counts/RAI at various temporal levels, group size, occupancy, kernel/circular analysis of activity patterns, temporal interactions between species, hierarchical diel models, and classic capture-mark-recapture. Input data must be formatted in the style produced by 'camtrapR', the standard convention in the field.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: dplyr, lubridate, tidyr
Suggests: camtrapR, GLMMadaptive, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
URL: https://github.com/OrlandoTomassini/soReta
BugReports: https://github.com/OrlandoTomassini/soReta/issues
NeedsCompilation: no
Packaged: 2026-09-03 09:47:18 UTC; orlan
Author: Orlando Tomassini [aut, cre]
Maintainer: Orlando Tomassini <orlando.tomassini@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:10:03 UTC

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New package rzig with initial version 0.2.3
Package: rzig
Title: Safe Zig Bindings
Version: 0.2.3
Description: Scaffolds packages backed by Zig and generates a safe native boundary for plain Zig functions. The generated integration converts objects at the language boundary, registers native routines, propagates errors, and compiles across platforms without requiring C++.
License: MIT + file LICENSE
URL: https://github.com/MarekDejaUJ/rzig
BugReports: https://github.com/MarekDejaUJ/rzig/issues
Encoding: UTF-8
SystemRequirements: Zig (>= 0.16.0), see https://ziglang.org/download/
NeedsCompilation: no
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Packaged: 2026-09-03 06:18:10 UTC; runner
Author: Marek Deja [aut, cre]
Maintainer: Marek Deja <marek.deja@uj.edu.pl>
Repository: CRAN
Date/Publication: 2026-09-12 14:40:08 UTC

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New package rdatagouv with initial version 0.1.0
Package: rdatagouv
Title: Tools to Download and Explore Datasets from Data.gouv.fr
Version: 0.1.0
Description: Provides a client for the public API of data.gouv.fr, the French government's open data platform. It helps you find a dataset that matches your interests, judge whether it is usable, download it, and re-fetch the exact same table later in a reproducible way. You can search the catalog and filter by producer or theme (dg_find_datasets(), dg_find_organization(), dg_find_topics()), pull a dataset's tabular resources into tidy tibbles (dg_pull_dataset()), inspect the documented variables of its data schema (dg_schema()), and compute summary metrics such as size, number of columns and missing-value rate (dg_summary(), dg_summarise()). Each returned table carries a stable identifier (dg_table_id(), dg_refetch()) so it can be re-fetched later. Requests are built on top of 'httr2'.
License: MIT + file LICENSE
URL: https://astamm.github.io/rdatagouv/, https://github.com/astamm/rdatagouv
BugReports: https://github.com/astamm/rdatagouv/issues
Encoding: UTF-8
VignetteBuilder: quarto
Imports: cli, httr2, jsonlite, nanoparquet, readxl, tibble, vroom
Suggests: dplyr, gt, knitr, pkgdown, quarto, testthat (>= 3.0.0), withr, writexl
NeedsCompilation: no
Packaged: 2026-09-03 11:05:38 UTC; stamm-a
Author: Magali Berland [aut], Pierre Gloaguen [aut], Arthur Leroy [aut], Mahendra Mariadassou [aut], Cedric Midoux [aut], Jean-Francois Rey [aut], Aymeric Stamm [aut, cre]
Maintainer: Aymeric Stamm <aymeric.stamm@cnrs.fr>
Repository: CRAN
Date/Publication: 2026-09-12 14:20:02 UTC

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New package ProMetaR with initial version 1.0.0
Package: ProMetaR
Title: Meta-Analysis of Proportions and Prevalence
Version: 1.0.0
Description: Tools for meta-analysis of proportions and prevalence from studies reporting event counts and sample sizes. Provides transformed and untransformed inverse-variance models, random-effects estimation, heterogeneity statistics, prediction intervals, subgroup analysis, meta-regression, leave-one-out sensitivity analysis, influence diagnostics, forest plots, funnel plots, and an optional binomial generalized linear mixed model interface. The package is designed for epidemiological, veterinary, medical, and One Health applications, including antimicrobial resistance prevalence studies.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: stats, graphics
Suggests: testthat (>= 3.0.0), metafor, knitr, rmarkdown
URL: https://github.com/vinodhpmd/ProMetaR
BugReports: https://github.com/vinodhpmd/ProMetaR/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-03 09:26:33 UTC; m
Author: Vinodhkumar Obli Rajendran [aut, cre], Keerthi Aaradhana [aut]
Maintainer: Vinodhkumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:10:33 UTC

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New package OptOR with initial version 0.1.0
Package: OptOR
Title: Optimal Hyperrectangular Operating Regions
Version: 0.1.0
Language: en-US
Description: Computes optimal axis-aligned hyperrectangles for discrete binary arrays and continuous regions defined by quadratic response functions. The package provides methods for discrete optimization, grid classification, continuous refinement, and exact global extrema calculations. Applications include the identification of practical operating regions within multivariate design spaces, including pharmaceutical development settings related to ICH Q8.
License: MIT + file LICENSE
Encoding: UTF-8
NeedsCompilation: yes
Imports: stats
Suggests: ggplot2, grid, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Packaged: 2026-09-03 09:33:33 UTC; chris
Author: Christian Palmes [aut, cre], Bayer AG [cph], Raluca Ilinca Schmitt [ctb], Adrian Funke [ctb]
Maintainer: Christian Palmes <christian.palmes@bayer.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:10:39 UTC

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New package normanR with initial version 1.8.79
Package: normanR
Title: Client for the 'Norman Network Database System' REST API
Version: 1.8.79
Description: Offers a programmatic interface to the 'NORMAN Network' REST API, facilitating the systematic query, retrieval, and parsing of environmental chemistry data, emerging substance registries, and mass spectrometry workflows. All data structures are tailored to support downstream environmental data analysis and ecotoxicological modelling.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2, jsonlite
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/urniaz/normanR
BugReports: https://github.com/urniaz/normanR/issues
NeedsCompilation: no
Packaged: 2026-09-03 21:48:08 UTC; urniaz
Author: Rafal Urniaz [aut, cre]
Maintainer: Rafal Urniaz <rafal.urniaz@cantab.net>
Repository: CRAN
Date/Publication: 2026-09-12 15:00:02 UTC

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New package MatchAlign with initial version 0.1.2
Package: MatchAlign
Title: Parsing GFA and GAF Alignment Files
Version: 0.1.2
Maintainer: Camille R. Mazurek <camillemazurek23@gmail.com>
Description: Provides tools for extracting segment paths from Graphical Fragment Assembly ('GFA') and Graph Alignment Format ('GAF') files. parse_paths_gfa() reads P (path) and W (walk) records and returns a named list of segment identifiers for each accession. parse_paths_gaf() parses the path string from each alignment and returns a named list of segments traversed by each query. parse_segment_lengths_gfa() reads S records and returns a named list of segment lengths keyed by segment identifier. These tools are intended to simplify downstream interpretation and analysis of pangenome graphs.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
URL: https://github.com/cromazurek/MatchAlign
BugReports: https://github.com/cromazurek/MatchAlign/issues
NeedsCompilation: no
Packaged: 2026-09-03 21:10:48 UTC; camillemazurek2025
Author: Camille R. Mazurek [aut, cre], Michael J. Tisza [ctb]
Repository: CRAN
Date/Publication: 2026-09-12 15:00:12 UTC

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New package marcxmlr with initial version 0.1.0
Package: marcxmlr
Title: Faithful and Scalable MARCXML Parsing
Version: 0.1.0
Description: Parses Machine-Readable Cataloging ('MARC 21') XML <https://www.loc.gov/standards/marcxml/> into a canonical tidy long representation while preserving leaders, control fields, data fields, indicators, repeated fields, repeated subfields, and source order. Provides an in-memory reader for manageable catalogues and a bounded-memory converter that writes larger collections as 'Parquet' datasets, with optional local parallel processing.
License: MIT + file LICENSE
URL: https://github.com/larry77/marcxmlr
BugReports: https://github.com/larry77/marcxmlr/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: purrr (>= 1.0.0), stats, tibble (>= 3.0.0), xml2 (>= 1.3.0)
Suggests: arrow, dplyr, future (>= 1.69.0), future.mirai, futurize, furrr, mori, testthat (>= 3.0.0), XML
NeedsCompilation: no
Packaged: 2026-09-03 12:52:42 UTC; lorenzo
Author: Lorenzo Isella [aut, cre]
Maintainer: Lorenzo Isella <lorenzo.isella@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:30:02 UTC

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New package krt with initial version 0.1.0
Package: krt
Title: Author, Validate, and Export Key Resources Tables
Version: 0.1.0
Description: A toolkit for creating, importing, validating, enriching, rendering, and depositing Key Resources Tables (KRTs). A KRT lists the resources used and generated in a study (antibodies, cell lines, organisms, chemicals, software, datasets, protocols, and more), each paired with a persistent identifier such as a Research Resource Identifier (RRID), a Digital Object Identifier (DOI), a repository accession, or a catalog number, so that resources are unambiguously identifiable and machine-actionable. The package models resources as typed, validated records around a neutral core schema and maps them to journal or funder output profiles, following the FAIR (Findable, Accessible, Interoperable, Reusable) principles of Wilkinson et al. (2016) <doi:10.1038/sdata.2016.18>. It normalizes and optionally resolves identifiers against public registries, extracts resources from manuscripts, and renders tables both in the STAR (Structured, Transparent, Accessible Reporting) Methods style used by Cel [...truncated...]
License: GPL-3
URL: https://github.com/choxos/krt, https://choxos.github.io/krt/
BugReports: https://github.com/choxos/krt/issues
Depends: R (>= 4.1)
Imports: digest, httr2, jsonlite, methods, stats, tools, utils, xml2, yaml
Suggests: bslib, covr, DT, knitr, officer, openxlsx, pdftools, rdflib, rmarkdown, S4Vectors, shiny, spelling, testthat (>= 3.0.0), tibble
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-03 11:34:08 UTC; choxos
Author: Ahmad Sofi-Mahmudi [aut, cre] , Aligning Science Across Parkinson's [cph] from which the bundled ASAP profile is derived. ASAP does not endorse this package.)
Maintainer: Ahmad Sofi-Mahmudi <a.sofimahmudi@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:20:08 UTC

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New package geosmooth with initial version 0.1.0
Package: geosmooth
Title: Geometric Smoothing and Conditional Expectation Methods
Version: 0.1.0
Description: Provides geometric methods for nonparametric regression and density estimation on data represented as coordinate matrices or weighted graphs. Methods include local polynomial smoothing, model-averaged local polynomial smoothing, local polynomial lifting trend filtering, synchronized local polynomial lifting trend filtering, graph low-pass filtering, and Hessian-energy regression. Methodological references include Gajer and Ravel (2025) "Adaptive Geometric Regression for High-Dimensional Structured Data" <doi:10.48550/arXiv.2511.03817>, Fan and Gijbels (1996, ISBN:9780412983214), Wang et al. (2016) "Trend Filtering on Graphs" <https://www.jmlr.org/papers/v17/15-147.html>, and Kim et al. (2009) "Semi-Supervised Regression Using Hessian Energy" <https://papers.nips.cc/paper/3741-semi-supervised-regression-using-hessian-energy-with-an-application-to-semi-supervised-dimensionality-reduction>.
Copyright: file inst/COPYRIGHTS
License: GPL (>= 3)
URL: https://github.com/pgajer/geosmooth
BugReports: https://github.com/pgajer/geosmooth/issues
Encoding: UTF-8
Language: en-US
SystemRequirements: GNU make
LinkingTo: Rcpp
Depends: R (>= 3.5.0)
Imports: dgraphs (>= 0.1.0), digest, jsonlite, MASS, Matrix, methods, Rcpp, stats, utils
Suggests: genlasso, grip, knitr, rmarkdown, testthat (>= 3.0.0), waldo
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-31 21:42:50 UTC; pgajer
Author: Pawel Gajer [aut, cre], Gael Guennebaud [ctb] , Benoit Jacob [ctb] , Authors of Eigen [cph] , Yixuan Qiu [ctb, cph] , Contributors to Spectra [cph] , Sunil Arya [ctb, cph] , David M. Mount [ctb, cph] , University of Maryland [cph]
Maintainer: Pawel Gajer <pgajer@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:10:10 UTC

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New package foresty with initial version 0.1.0
Package: foresty
Title: Forest Plots and Subgroup Effects from Fitted Regression Models
Version: 0.1.0
Description: Draws forest plots of exposure effects from fitted regression models. Name an exposure and 'foresty' plots its effect. Name an effect modifier as well and it refits the model with the interaction term, estimates the exposure effect within each level of the modifier as a linear combination of the coefficients, and reports the joint interaction test beside those estimates. It takes one exposure and one modifier at a time, so the interaction is always a two-way one. Rows of the plot and of the table beside it share one scale, in a layout that can follow a journal's house style. The same results go to a self-contained HTML page holding the subgroup estimates, the joint test and the coefficient table. The 'car' package computes the linear combinations and their tests. Models fitted by stats::glm(), stats::lm(), the 'survival' package, the 'lme4' package and the 'geepack' package are supported, as is any fit supplying coef() and vcov(). Ordinal outcomes are supported through the 'MASS' packa [...truncated...]
License: GPL-3
URL: https://github.com/AkiShiroshita/foresty, https://akishiroshita.github.io/foresty/
BugReports: https://github.com/AkiShiroshita/foresty/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: car (>= 3.1.0), checkmate (>= 2.1.0), ggplot2 (>= 3.4.0), grDevices, grid, patchwork (>= 1.1.0), scales (>= 1.2.0), stats, utils
Suggests: base64enc, broom (>= 1.0.0), bslib (>= 0.5.0), data.table, geepack, gt (>= 0.9.0), Hmisc, knitr, lme4, MASS, nnet, ragg, rmarkdown, rms, sandwich (>= 3.0.0), shiny (>= 1.7.0), survival (>= 3.2.0), svglite, tibble, testthat (>= 3.0.0), zip
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: no
Packaged: 2026-09-03 16:56:17 UTC; shiroa1
Author: Akihiro Shiroshita [aut, cre, cph], Yuki Kataoka [aut]
Maintainer: Akihiro Shiroshita <akihirokun8@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:40:22 UTC

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New package fdic with initial version 0.1.2
Package: fdic
Title: Interface to 'BankFind Suite API'
Version: 0.1.2
Description: Provides a convenient interface to the 'BankFind Suite API' made available by the Federal Deposit Insurance Corporation (FDIC). Contains functions to retrieve data related to qualitative institution information, branch and office locations, Summary of Deposit reporting, financial information, failed financial institutions, structural change events, historic aggregate industry data, and demographics information. See <https://api.fdic.gov/banks/docs/> for the official 'BankFind Suite API' documentation published by the FDIC.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), withr
Depends: R (>= 4.1)
LazyData: true
Imports: cli, httr2, tibble
URL: https://github.com/ketchbrookanalytics/fdic, https://ketchbrookanalytics.github.io/fdic/
BugReports: https://github.com/ketchbrookanalytics/fdic/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-09-03 19:46:41 UTC; root
Author: Dylan Hughes [aut, cre], Michael Thomas [aut], Ketchbrook Analytics [cph, fnd]
Maintainer: Dylan Hughes <dhughes@ketchbrookanalytics.com>
Repository: CRAN
Date/Publication: 2026-09-12 14:50:02 UTC

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New package cauchyreg with initial version 1.0
Package: cauchyreg
Title: Cauchy Regression
Version: 1.0
Date: 2026-09-03
Author: Michail Tsagris [aut, cre]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>
Depends: R (>= 4.0)
Imports: Compositional, glmnet, Rfast, stats
Description: Cauchy regression modelling and LASSO to perform variable selection are included in this package. Cross-validation is performed to choose the optimal value of the lambda parameter. LASSO is based on the IRLS algorithm. A relevant paper is <doi:10.1109/ICIST.2014.6920341>.
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2026-09-03 20:45:39 UTC; mtsag
Repository: CRAN
Date/Publication: 2026-09-12 15:00:07 UTC

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New package badcontrols with initial version 1.0.1
Package: badcontrols
Title: Difference-in-Differences with Bad Controls
Version: 1.0.1
Description: Implements methods for difference-in-differences with bad controls, i.e., time-varying covariates that are affected by the treatment. Provides imputation, doubly robust, and machine learning estimators that are based on Caetano, Callaway, Payne, and Sant'Anna (2026) <doi:10.48550/arXiv.2608.03881>.
URL: https://github.com/hugosantanna/badcontrols
BugReports: https://github.com/hugosantanna/badcontrols/issues
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ptetools (>= 1.0.1), stats
Suggests: grf (>= 2.0.0), testthat (>= 3.0.0), knitr, quarto
VignetteBuilder: quarto
NeedsCompilation: no
Packaged: 2026-09-03 18:22:11 UTC; hsantanna
Author: Carolina Caetano [aut], Brantly Callaway [aut], Stroud Payne [aut], Hugo Sant'Anna [aut, cre]
Maintainer: Hugo Sant'Anna <hsantanna@uab.edu>
Repository: CRAN
Date/Publication: 2026-09-12 14:40:30 UTC

More information about badcontrols at CRAN
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