Tue, 22 Sep 2026

Package statgenGWAS updated to version 1.0.14 with previous version 1.0.13 dated 2026-02-19

Title: Genome Wide Association Studies
Description: Fast single trait Genome Wide Association Studies (GWAS) following the method described in Kang et al. (2010), <doi:10.1038/ng.548>. One of a series of statistical genetic packages for streamlining the analysis of typical plant breeding experiments developed by Biometris.
Author: Bart-Jan van Rossum [aut, cre] , Willem Kruijer [aut] , Fred van Eeuwijk [ctb] , Martin Boer [ctb] , Marcos Malosetti [ctb] , Daniela Bustos-Korts [ctb] , Emilie Millet [ctb] , Joao Paulo [ctb] , Maikel Verouden [ctb] , Ron Wehrens [ctb] , Choazhi Zh [...truncated...]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

Diff between statgenGWAS versions 1.0.13 dated 2026-02-19 and 1.0.14 dated 2026-09-22

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Package rjd3tramoseats updated to version 3.9.0 with previous version 3.8.0 dated 2026-07-10

Title: Seasonal Adjustment with TRAMO-SEATS in 'JDemetra+' 3.x
Description: Interface to 'JDemetra+' 3.x (<https://github.com/jdemetra>) time series analysis software. It offers full access to options and outputs of 'TRAMO-SEATS' (Time series Regression with ARIMA noise, Missing values and Outliers - Signal Extraction in ARIMA Time Series), including 'TRAMO' modelling (ARIMA model with outlier detection and trading days adjustment). ARIMA = AutoRegressive Integrated Moving Average.
Author: Jean Palate [aut], Alain Quartier-la-Tente [aut] , Tanguy Barthelemy [aut, cre, art], Anna Smyk [aut], Eulalie Delaune [aut]
Maintainer: Tanguy Barthelemy <timeserieswithjdemetraandr@gmail.com>

Diff between rjd3tramoseats versions 3.8.0 dated 2026-07-10 and 3.9.0 dated 2026-09-22

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Package azr updated to version 0.3.6 with previous version 0.3.5 dated 2026-06-26

Title: Credential Chain for Seamless 'OAuth 2.0' Authentication to 'Azure Services'
Description: Implements a credential chain for 'Azure OAuth 2.0' authentication based on the package 'httr2''s 'OAuth' framework. Sequentially attempts authentication methods until one succeeds. During development allows interactive browser-based flows ('Device Code' and 'Auth Code' flows) and non-interactive flow ('Client Secret') in batch mode.
Author: Pedro Baltazar [aut, cre]
Maintainer: Pedro Baltazar <pedrobtz@gmail.com>

Diff between azr versions 0.3.5 dated 2026-06-26 and 0.3.6 dated 2026-09-22

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Package richCluster updated to version 2.0.1 with previous version 2.0.0 dated 2026-09-16

Title: Fast, Robust Clustering Algorithms for Gene Enrichment Data
Description: Clusters functionally related biological terms from gene set enrichment results. Terms are compared by the overlap of their gene sets using Cohen's kappa, the Jaccard index, or the Dice coefficient, and the resulting similarity matrix is grouped either by agglomerative hierarchical clustering with single, complete, average, or Ward linkage, or by the seed-and-merge procedure of the 'DAVID' functional classification tool. The distance and clustering routines are written in 'C++' for speed. The methods are described in Huang et al. (2007) <doi:10.1186/gb-2007-8-9-r183>, Ward (1963) <doi:10.1080/01621459.1963.10500845>, Cohen (1960) <doi:10.1177/001316446002000104>, and Jaccard (1912) <doi:10.1111/j.1469-8137.1912.tb05611.x>.
Author: Junguk Hur [aut, cre] , Sarah Hong [aut], Jane Kim [aut]
Maintainer: Junguk Hur <hurlabshared@gmail.com>

Diff between richCluster versions 2.0.0 dated 2026-09-16 and 2.0.1 dated 2026-09-22

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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

More information about panglm at CRAN
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Package MorphSim readmission to version 1.2.1 with previous version 1.2.0 dated 2026-05-06

Title: Simulate Discrete Character Data along Phylogenetic Trees
Description: Tools to simulate morphological traits along phylogenetic trees with branch lengths representing evolutionary distance or time. Includes functions for visualizing evolutionary processes along trees and within morphological character matrices. Methods are described in Mulvey et al. (2026) <doi:10.1111/2041-210X.70326>.
Author: Laura Mulvey [aut, cre, cph], Tim Brandler [aut, cph], Alessio Capobianco [aut, cph], Rachel Warnock [aut, cph], Joelle Barido-Sottani [aut, cph]
Maintainer: Laura Mulvey <lauramulvey479@gmail.com>

This is a re-admission after prior archival of version 1.2.0 dated 2026-05-06

Diff between MorphSim versions 1.2.0 dated 2026-05-06 and 1.2.1 dated 2026-09-22

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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

More information about iod25 at CRAN
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Package GMTM updated to version 0.2.0 with previous version 0.1.0 dated 2026-09-15

Title: Gaussian Mixture Topic Models
Description: Gaussian mixture models (GMM) and k-means for topic analysis of dense document vectors. The underlying clustering functions rely on the Armadillo library (Sanderson & Curtin, 2017) <doi:10.1109/ICSPCS.2017.8270510>.
Author: Kohei Watanabe [aut, cre, cph] , Sanderson Conrad [ctb, cph] , Curtin Ryan [ctb, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

Diff between GMTM versions 0.1.0 dated 2026-09-15 and 0.2.0 dated 2026-09-22

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Package ggbreak updated to version 0.2.2 with previous version 0.1.7 dated 2026-03-18

Title: Set Axis Break for 'ggplot2'
Description: An implementation of scale functions for setting axis breaks of a 'gg' plot (S Xu (2021) <doi:10.3389/fgene.2021.774846>).
Author: Guangchuang Yu [aut, cre, cph] , Shuangbin Xu [aut]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between ggbreak versions 0.1.7 dated 2026-03-18 and 0.2.2 dated 2026-09-22

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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

More information about EconEvalR at CRAN
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Package drrglm updated to version 0.4.0 with previous version 0.3.2 dated 2026-04-20

Title: Doubly Regularized Matrix-Variate Regression
Description: The doubly regularized matrix-variate regression solves a low-rank-plus-sparse structure for matrix-variate generalized linear models through a weighted combination of nuclear-norm and L1-norm. The methodology implemented by this package is described in the paper "Doubly Regularized Matrix-Variate Regression". See Xu, Luo and Jiang <doi:10.1080/10618600.2026.2702534>.
Author: Zengchao Xu [aut, cre, cph], Shan Luo [aut], Binyan Jiang [aut]
Maintainer: Zengchao Xu <zengc.xu@aliyun.com>

Diff between drrglm versions 0.3.2 dated 2026-04-20 and 0.4.0 dated 2026-09-22

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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

More information about Compositionalcln at CRAN
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Package aplot updated to version 0.3.2 with previous version 0.3.1 dated 2026-07-07

Title: Decorate a 'ggplot' with Associated Information
Description: Supports data-driven composition of a main plot with associated subplots that need precise axis alignment. Unlike general layout-focused tools such as 'cowplot' and 'patchwork', it enables related subplots to be integrated on the top, bottom, left, or right sides of a main plot with matched axes, so that the combined panels can be interpreted as a coherent whole. This design was inspired by the 'Method 2' described in 'ggtree' (G Yu (2018) <doi:10.1093/molbev/msy194>).
Author: Guangchuang Yu [aut, cre] , Shuangbin Xu [ctb] , Thomas Hackl [ctb]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between aplot versions 0.3.1 dated 2026-07-07 and 0.3.2 dated 2026-09-22

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More information about aplot at CRAN
Permanent link

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

More information about zot at CRAN
Permanent link

Package survrec readmission to version 2.0.0 with previous version 1.2-2 dated 2012-03-26

Title: Survival Analysis for Recurrent Event Data
Description: Estimation of the survival function of inter-occurrence times for recurrent event data, using the estimators of Peña, Strawderman and Hollander (2001) <doi:10.1198/016214501753381922> and Wang and Chang (1999) <doi:10.1080/01621459.1999.10473831>, and maximum likelihood estimation under a gamma frailty model. Includes bootstrap comparison of survival quantiles between groups.
Author: Dolors Pelegri-Siso [aut, cre] , Juan R. Gonzalez [aut], Edsel A. Pena [aut], Robert L. Strawderman [aut]
Maintainer: Dolors Pelegri-Siso <dolors.pelegri@isglobal.org>

This is a re-admission after prior archival of version 1.2-2 dated 2012-03-26

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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

More information about sptrends at CRAN
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Package NetSimR updated to version 0.3.1 with previous version 0.3.0 dated 2026-09-15

Title: Actuarial Functions for Non-Life Insurance Modelling
Description: Assists actuaries and other insurance modellers in pricing, reserving and capital modelling for non-life insurance and reinsurance modelling. Provides functions that help model excess levels, capping and pure Incurred but not reported claims (pure IBNR). Includes capped mean, exposure curves and increased limit factor curves (ILFs) for LogNormal, Gamma, Pareto, Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes mean, probability density function (pdf), cumulative probability function (cdf) and inverse cumulative probability function for Sliced LogNormal-Pareto and Sliced Gamma-Pareto distributions. Includes calculating pure IBNR exposure with LogNormal and Gamma distribution for reporting delay. Includes three 'shiny' tools: a claims simulator with reinsurance structures, a generalised linear model fitting tool, and a claims frequency and severity distribution fitting tool. Methods used in the package refer to Free for All by Yiannis Parizas (2023) <https://www. [...truncated...]
Author: Yiannis Parizas [aut, cre]
Maintainer: Yiannis Parizas <yiannis.parizas@gmail.com>

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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

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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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Package OSCARS updated to version 0.2.1 with previous version 0.1.2 dated 2026-05-06

Title: Global Bounded Optimization by the OSCARS-II Algorithm
Description: A collection of general optimization routines based on variants of the One Side Cut Accelerated Random Search (OSCARS-II) algorithm (Price et al., 2020, <doi:10.1007/s10898-020-00928-6>). The main function , 'oscars()', performs black-box optimization of a general (including nonsmooth or discontinuous) function subject to simple bounds on the unknowns. If all bounds are finite, oscars searches globally. The main method implements a stochastic direct search method and is derivative free. Testing shows the OSCARS-II algorithm usually finds extrema with fewer function evaluations than similar global derivative-free methods.
Author: Chris Price [aut, cre], Trent McDonald [aut, ctb]
Maintainer: Chris Price <chrisj.price@canterbury.ac.nz>

Diff between OSCARS versions 0.1.2 dated 2026-05-06 and 0.2.1 dated 2026-09-22

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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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Package fragility updated to version 2.0 with previous version 1.6.1 dated 2025-01-23

Title: Assessing and Visualizing Fragility of Clinical Results
Description: A collection of user-friendly functions for assessing fragility of clinical results with binary and survival outcomes. For binary outcomes, the package assesses and visualizes fragility of individual studies (Walsh et al., 2014 <doi:10.1016/j.jclinepi.2013.10.019>; Lin, 2021 <doi:10.1111/jep.13428>), conventional pairwise meta-analyses (Atal et al., 2019 <doi:10.1016/j.jclinepi.2019.03.012>), and network meta-analyses of multiple treatments with binary outcomes (Xing et al., 2020 <doi:10.1016/j.jclinepi.2020.07.003>). The functions for binary outcomes are designed to: 1) calculate the fragility index (i.e., the minimal event status modifications that can alter the significance or non-significance of the original result) and fragility quotient (i.e., fragility index divided by sample size) at a specific significance level; 2) give the cases of event status modifications for altering the result's significance or non-significance and visualize these cases; 3) visua [...truncated...]
Author: Lifeng Lin [aut, cre] , Xing Xing [aut] , Jiayi Tong [aut] , Haitao Chu [aut]
Maintainer: Lifeng Lin <lifenglin@arizona.edu>

Diff between fragility versions 1.6.1 dated 2025-01-23 and 2.0 dated 2026-09-22

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Package binest updated to version 0.3-0 with previous version 0.2-1 dated 2026-06-08

Title: Estimation of Group Means and SDs from Binned Count Data
Description: Estimates group-level means and standard deviations from binned (coarsened) data, where only the number of cases in each of several ordered bins is observed and the underlying values are not. The main function, fast_hetop(), fits the heteroskedastic ordered probit model of Reardon, Shear, Castellano and Ho (2017) <doi:10.3102/1076998616666279> one group at a time, solving closed-form truncated-normal score equations instead of optimizing jointly over all groups. Runtime is therefore linear in the number of groups, so thousands of schools, districts or subgroups can be fitted in under a second. Cut scores may be supplied when an agency publishes them, or estimated from the data when it does not. Output includes standard errors and confidence intervals, an optional empirical Bayes shrinkage estimator, and a per-group goodness-of-fit test of the within-group normality assumption. Also included, and deprecated, are mle_hetop() and fh_hetop(), which fit the same model by joint maxim [...truncated...]
Author: Paul T. von Hippel [aut, cre], David J. Hunter [aut], J.R. Lockwood [aut]
Maintainer: Paul T. von Hippel <ph3828@eid.utexas.edu>

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