Thu, 10 Sep 2026

Package haplo.stats updated to version 1.9.9.1 with previous version 1.9.8.7 dated 2026-04-25

Title: Statistical Analysis of Haplotypes with Traits and Covariates when Linkage Phase is Ambiguous
Description: Routines for the analysis of indirectly measured haplotypes. The statistical methods assume that all subjects are unrelated and that haplotypes are ambiguous (due to unknown linkage phase of the genetic markers). The main functions are: haplo.em(), haplo.glm(), haplo.score(), and haplo.power(); all of which have detailed examples in the vignette.
Author: Schaid Daniel [aut], Jason P. Sinnwell [aut, cre]
Maintainer: Jason P. Sinnwell <sinnwell.jason@mayo.edu>

Diff between haplo.stats versions 1.9.8.7 dated 2026-04-25 and 1.9.9.1 dated 2026-09-10

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More information about haplo.stats at CRAN
Permanent link

Package CNVScope updated to version 3.7.7 with previous version 3.7.6 dated 2026-07-04

Title: A Versatile Toolkit for Copy Number Variation Relationship Data Analysis and Visualization
Description: Provides the ability to create interaction maps, discover CNV map domains (edges), gene annotate interactions, and create interactive visualizations of these CNV interaction maps.
Author: James Dalgleish [aut, cre] , Yonghong Wang [aut], Jack Zhu [aut], Paul Meltzer [aut, sad]
Maintainer: James Dalgleish <jamesdalg@gmail.com>

Diff between CNVScope versions 3.7.6 dated 2026-07-04 and 3.7.7 dated 2026-09-10

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More information about CNVScope at CRAN
Permanent link

Package spmodel updated to version 0.14.0 with previous version 0.13.0 dated 2026-06-10

Title: Spatial Statistical Modeling and Prediction
Description: Fit, summarize, and predict for a variety of spatial statistical models applied to point-referenced and areal (lattice) data. Parameters are estimated using various methods. Additional modeling features include anisotropy, non-spatial random effects, partition factors, big data approaches, and more. Model-fit statistics are used to summarize, visualize, and compare models. Predictions at unobserved locations are readily obtainable. For additional details, see Dumelle et al. (2023) <doi:10.1371/journal.pone.0282524>.
Author: Michael Dumelle [aut, cre] , Matthew Heaton [ctb] , Matt Higham [aut] , Ryan A. Hill [ctb] , Michael Mahon [ctb] , Jay M. Ver Hoef [aut]
Maintainer: Michael Dumelle <Dumelle.Michael@epa.gov>

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Package ragnar updated to version 0.3.1 with previous version 0.3.0 dated 2026-01-23

Title: Retrieval-Augmented Generation (RAG) Workflows
Description: Provides tools for implementing Retrieval-Augmented Generation (RAG) workflows with Large Language Models (LLM). Includes functions for document processing, text chunking, embedding generation, storage management, and content retrieval. Supports various document types and embedding providers ('Ollama', 'OpenAI'), with 'DuckDB' as the default storage backend. Integrates with the 'ellmer' package to equip chat objects with retrieval capabilities. Designed to offer both sensible defaults and customization options with transparent access to intermediate outputs. For a review of retrieval-augmented generation methods, see Gao et al. (2023) "Retrieval-Augmented Generation for Large Language Models: A Survey" <doi:10.48550/arXiv.2312.10997>.
Author: Tomasz Kalinowski [aut, cre], Daniel Falbel [aut], Posit Software, PBC [cph, fnd]
Maintainer: Tomasz Kalinowski <tomasz@posit.co>

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Package enderecobr updated to version 0.6.0 with previous version 0.5.0 dated 2026-01-10

Title: Padronizador de Endereços Brasileiros (Brazilian Addresses Standardizer)
Description: Padroniza endereços brasileiros a partir de diferentes critérios. Os métodos de padronização incluem apenas manipulações básicas de strings, não oferecendo suporte a correspondências probabilísticas entre strings. (Standardizes brazilian addresses using different criteria. Standardization methods include only basic string manipulation, not supporting probabilistic matches between strings.)
Author: Daniel Herszenhut [aut] , Rafael H. M. Pereira [aut, cre] , Gabriel Garcia de Almeida [aut] , Lucas Mation [aut]
Maintainer: Rafael H. M. Pereira <rafa.pereira.br@gmail.com>

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Package clusterv updated to version 1.1.2 with previous version 1.1.1 dated 2025-05-14

Title: Assessment of Cluster Stability by Randomized Maps
Description: The reliability of clusters is estimated using random projections. A set of stability measures is provided to assess the reliability of the clusters discovered by a generic clustering algorithm. The stability measures are taylored to high dimensional data (e.g. DNA microarray data) (Valentini, G (2005), <doi:10.1093/bioinformatics/bti817>.
Author: Giorgio Valentini [aut], Jessica Gliozzo [cre]
Maintainer: Jessica Gliozzo <jessica.gliozzo@gmail.com>

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Package Rothermel readmission to version 1.4.1 with previous version 1.2 dated 2014-11-10

Title: Surface Fire Spread Model
Description: Implements the surface fire spread model of Rothermel (1972) <doi:10.2737/INT-RP-115> in R. Additional utilities support uncertainty propagation, selection among standard fuel models, optimization of fuel model parameters by genetic algorithms, and example datasets.
Author: Giorgio Vacchiano [aut, cre] , Davide Ascoli [ctb]
Maintainer: Giorgio Vacchiano <gvacchiano@gmail.com>

This is a re-admission after prior archival of version 1.2 dated 2014-11-10

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Package marble updated to version 0.0.4 with previous version 0.0.3 dated 2024-04-04

Title: Robust Marginal Bayesian Variable Selection for Gene-Environment Interactions
Description: Recently, multiple marginal variable selection methods have been developed and shown to be effective in Gene-Environment interactions studies. We propose a novel marginal Bayesian variable selection method for Gene-Environment interactions studies. In particular, our marginal Bayesian method is robust to data contamination and outliers in the outcome variables. With the incorporation of spike-and-slab priors, we have implemented the Gibbs sampler based on Markov Chain Monte Carlo. The core algorithms of the package have been developed in 'C++'.
Author: Xi Lu [aut, cre], Cen Wu [aut]
Maintainer: Xi Lu <xilu0521@gmail.com>

Diff between marble versions 0.0.3 dated 2024-04-04 and 0.0.4 dated 2026-09-10

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Package geostatsp updated to version 2.2.0 with previous version 2.0.10 dated 2026-02-26

Title: Geostatistical Modelling with Likelihood and Bayes
Description: Geostatistical modelling facilities using 'SpatRaster' and 'SpatVector' objects are provided. Non-Gaussian models are fit using 'INLA', and Gaussian geostatistical models use Maximum Likelihood Estimation. For details see Brown (2015) <doi:10.18637/jss.v063.i12>. The 'RandomFields' package is available at <https://web.archive.org/web/20250719184025/https://www.wim.uni-mannheim.de/schlather/publications/software> and <https://github.com/cran/RandomFields>.
Author: Patrick Brown [aut, cre, cph]
Maintainer: Patrick Brown <patrick.brown@utoronto.ca>

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Package Bayenet updated to version 0.4 with previous version 0.3 dated 2025-03-19

Title: Robust Bayesian Elastic Net
Description: As heavy-tailed error distribution and outliers in the response variable widely exist, models which are robust to data contamination are highly demanded. Here, we develop a novel robust Bayesian variable selection method with elastic net penalty. In particular, the spike-and-slab priors have been incorporated to impose sparsity. An efficient Gibbs sampler has been developed to facilitate computation.The core modules of the package have been developed in 'C++' and R.
Author: Xi Lu [aut, cre], Cen Wu [aut]
Maintainer: Xi Lu <xilu0521@gmail.com>

Diff between Bayenet versions 0.3 dated 2025-03-19 and 0.4 dated 2026-09-10

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Package tidylda updated to version 0.1.1 with previous version 0.1.0 dated 2026-08-28

Title: Latent Dirichlet Allocation Using 'tidyverse' Conventions
Description: Implements an algorithm for Latent Dirichlet Allocation (LDA), Blei et al. (2003) <https://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf>, using style conventions from the 'tidyverse', Wickham et al. (2019)<doi:10.21105/joss.01686>, and 'tidymodels', Kuhn et al.<https://tidymodels.github.io/model-implementation-principles/>. Fitting is done via 'warpLDA', a Metropolis-Hastings sampler, Chen et al. (2016) <doi:10.48550/arXiv.1510.08628>. Also implements several novel features for LDA such as guided models and transfer learning.
Author: Tommy Jones [aut, cre] , Brendan Knapp [ctb] , Barum Park [ctb]
Maintainer: Tommy Jones <jones.thos.w@gmail.com>

Diff between tidylda versions 0.1.0 dated 2026-08-28 and 0.1.1 dated 2026-09-10

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Package rextor updated to version 1.2.0 with previous version 1.1.0 dated 2026-05-21

Title: Prepare 'WEXTOR' Data
Description: Facilitate data preparation for data collected on 'WEXTOR' <https://wextor.eu>, created by Reips and Neuhaus (2002) <doi:10.3758/bf03195449>. Perform plausibility and other checks and make use of cool color palettes and themes for data visualization.
Author: Annika Tave Overlander [aut, cre] , Ulf-Dietrich Reips [ths, cph]
Maintainer: Annika Tave Overlander <annika-tave.overlander@uni.kn>

Diff between rextor versions 1.1.0 dated 2026-05-21 and 1.2.0 dated 2026-09-10

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New package mathr with initial version 0.1.3
Package: mathr
Version: 0.1.3
Title: Scientific Computation Using R
Description: A collection of undergraduate level mathematical routines for quantitative work, covering calculus, distribution functions, random variate generation, linear algebra, differential equations and optimization, sized for one semester.
Depends: R (>= 3.0.0)
Copyright: 2018-2026, Kyun-Seop Bae
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
URL: https://github.com/ksbae/mathr
BugReports: https://github.com/ksbae/mathr/issues
Packaged: 2026-08-31 05:38:17 UTC; Kyun-SeopBae
Author: Kyun-Seop Bae [aut, cre]
Maintainer: Kyun-Seop Bae <k@acr.kr>
Repository: CRAN
Date/Publication: 2026-09-10 15:10:02 UTC

More information about mathr at CRAN
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New package intraclass with initial version 0.1.0
Package: intraclass
Title: Modern Intraclass Correlation Coefficients
Version: 0.1.0
Description: Estimates interrater-reliability intraclass correlation coefficients (ICCs) within the generalizability-theory framework using modern variance-component estimation (linear mixed models) rather than the classical analysis-of-variance mean-squares approach. Provides the full ICC family (absolute agreement versus consistency, single versus average, fixed versus random raters, one-way versus two-way) with boundary-aware Monte-Carlo confidence intervals, support for imbalanced, incomplete, and multilevel (nested) designs, decision-study projection to other numbers of raters, and an interactive helper for choosing the correct coefficient. Multilevel methods follow ten Hove, Jorgensen and van der Ark (2022) <doi:10.1037/met0000391>.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: cli, generics, glmmTMB, lifecycle, rlang, stats, tibble
Suggests: brms, coda, covr, ggplot2, irr, irrICC, knitr, lavaan, lme4, merDeriv, posterior, psych, rmarkdown, spelling, testthat (>= 3.0.0), withr
VignetteBuilder: knitr
Language: en-US
URL: https://github.com/jmgirard/intraclass, https://jmgirard.github.io/intraclass/
BugReports: https://github.com/jmgirard/intraclass/issues
Depends: R (>= 4.5.0)
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-31 01:00:17 UTC; jmgirard
Author: Jeffrey Girard [aut, cre]
Maintainer: Jeffrey Girard <me@jmgirard.com>
Repository: CRAN
Date/Publication: 2026-09-10 15:10:10 UTC

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Package hours2lessons updated to version 1.0.0 with previous version 0.1.5 dated 2026-09-05

Title: Alocă Pe Ore Lecțiile Zilei
Description: Lecțiile prof/cls trebuie completate cu un câmp "ora", astfel ca oricare două lecții prof/cls/ora să nu se suprapună într-o aceeași oră. The prof/cls lessons must be completed with a "hour" field ('ora), so that any two prof/cls/ora lessons do not overlap in the same hour. <https://vlad.bazon.net/>.
Author: Vlad Bazon [aut, cre]
Maintainer: Vlad Bazon <vlad.bazon@gmail.com>

Diff between hours2lessons versions 0.1.5 dated 2026-09-05 and 1.0.0 dated 2026-09-10

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New package icebergr with initial version 0.1.0
Package: icebergr
Title: Read and Write 'Apache Iceberg' Tables
Version: 0.1.0
Description: A native client for 'Apache Iceberg', the open table format used by 'Snowflake', 'Databricks', 'BigQuery', 'AWS' and 'Dremio'. R has otherwise been able to read 'Iceberg' tables only by routing through 'DuckDB' as an intermediary, which rules out writes, snapshot management and catalog integration. This package talks to 'Iceberg' directly: it connects to REST and 'AWS Glue' catalogs, lists namespaces and tables, reads the schema and partition specification of a table, scans data with predicates and projections pushed down, travels back through snapshot history, and appends new data. 'Apache Arrow' is the interchange layer throughout, so scan results arrive in R without a serialisation round trip. Built on 'iceberg-rust', the Apache-governed 'Rust' implementation, via 'extendr'. Supports table spec versions 1 and 2; see the 'README' for the full matrix of supported and unsupported features. This is a community package, not affiliated with or endorsed by The Apache Software Foundation; ' [...truncated...]
License: GPL (>= 3)
URL: https://github.com/PursuitOfDataScience/icebergr
BugReports: https://github.com/PursuitOfDataScience/icebergr/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.2)
Imports: nanoarrow (>= 0.4.0), rlang (>= 1.1.0), tibble
Suggests: bit64, dplyr, knitr, rmarkdown, testthat (>= 3.1.7), vctrs, withr (>= 2.3.0)
VignetteBuilder: knitr
SystemRequirements: Cargo (Rust's package manager), rustc >= 1.92, xz
NeedsCompilation: yes
Packaged: 2026-08-28 19:12:45 UTC; youzhi
Author: Youzhi Yu [aut, cre], The Apache Software Foundation [cph]
Maintainer: Youzhi Yu <yuyouzhi666@icloud.com>
Repository: CRAN
Date/Publication: 2026-09-10 15:30:16 UTC

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Package GetTDData updated to version 1.7.1 with previous version 1.7.0 dated 2026-08-29

Title: Get Data for Brazilian Bonds (Tesouro Direto)
Description: Downloads and aggregates data for Brazilian government issued bonds directly from the website of Tesouro Direto <https://www.tesourodireto.com.br/>.
Author: Marcelo Perlin [aut, cre]
Maintainer: Marcelo Perlin <marceloperlin@gmail.com>

Diff between GetTDData versions 1.7.0 dated 2026-08-29 and 1.7.1 dated 2026-09-10

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Package wordvector updated to version 0.6.4 with previous version 0.6.3 dated 2026-07-28

Title: Word and Document Vector Models
Description: Create dense vector representation of words and documents using 'quanteda'. Implements Word2vec (Mikolov et al., 2013) <doi:10.48550/arXiv.1310.4546>, Doc2vec (Le & Mikolov, 2014) <doi:10.48550/arXiv.1405.4053> and Latent Semantic Analysis (Deerwester et al., 1990) <doi:10.1002/(SICI)1097-4571(199009)41:6%3C391::AID-ASI1%3E3.0.CO;2-9>.
Author: Kohei Watanabe [aut, cre, cph] , Jan Wijffels [aut] , BNOSAC [cph] , Max Fomichev [ctb, cph]
Maintainer: Kohei Watanabe <watanabe.kohei@gmail.com>

Diff between wordvector versions 0.6.3 dated 2026-07-28 and 0.6.4 dated 2026-09-10

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New package tvbounds with initial version 0.1.1
Package: tvbounds
Title: Sensitivity Analysis and Bounds under Total Variation Neighborhoods
Version: 0.1.1
Description: Implements the sensitivity analysis framework of Palomba (2026) "Sensitivity Analysis in Population Shares" <https://filippopalomba.github.io/#jmp> for randomized experiments with attrition, counterfactuals in structural models, and recentered instrumental variables. Computes and plots sensitivity bounds together with their confidence intervals and robustness summary measures.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2 (>= 3.4.0), stats, utils, withr
Suggests: JuliaCall, testthat (>= 3.1.5), knitr, rmarkdown
SystemRequirements: For tvbounds_counterfactual(): Julia (>= 1.9) and the Artelys KNITRO solver with a valid license.
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-30 17:10:06 UTC; fpalomba
Author: Filippo Palomba [aut, cre, cph]
Maintainer: Filippo Palomba <fpalomba@princeton.edu>
Repository: CRAN
Date/Publication: 2026-09-10 14:20:02 UTC

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Package stratifyR updated to version 2.0-1 with previous version 1.0-5 dated 2026-06-23

Title: Optimal Stratification of Univariate Populations
Description: Determines Optimum Strata Boundaries (OSB) and Optimum Sample Sizes (OSS) for univariate stratified sampling designs under Neyman allocation. The stratification variable is described by a best-fitting parametric distribution, selected automatically by AIC from a set of continuous families (normal, log-normal, gamma, Weibull, exponential, Cauchy, uniform, Pareto, triangular and right-triangular), and the optimum boundaries are obtained by minimising the Neyman objective. Version 2.0 keeps the original globally optimal Dynamic Programming (DP) solver of Reddy and Khan (2020) as the default and adds two faster derivative-free alternatives for interactive and large-scale use: a multi-start 'COBYLA' solver and a two-phase 'global' solver that couples 'DIRECT-L' with 'COBYLA' refinement. It also provides cost-constrained allocation with unequal per-stratum costs, a design-efficiency comparison (compare_designs), two- and three-dimensional and interactive visualisations, solution-quality di [...truncated...]
Author: Karuna G. Reddy [aut, cre], M. G. M. Khan [aut]
Maintainer: Karuna G. Reddy <karuna.reddy@auckland.ac.nz>

Diff between stratifyR versions 1.0-5 dated 2026-06-23 and 2.0-1 dated 2026-09-10

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Package shadowVIMP updated to version 1.0.3 with previous version 1.0.2 dated 2025-06-19

Title: Covariate Selection Based on VIMP Permutation-Like Testing
Description: A statistical method for reducing the number of covariates in an analysis by evaluating Variable Importance Measures (VIMPs) derived from the Random Forest algorithm. It performs statistical tests on the VIMPs and outputs whether the covariate is significant along with the p-values.
Author: Tim Mueller [aut, cre], Oktawia Miluch [aut], Staburo GmbH [cph, fnd]
Maintainer: Tim Mueller <mueller@staburo.de>

Diff between shadowVIMP versions 1.0.2 dated 2025-06-19 and 1.0.3 dated 2026-09-10

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Package sentopics updated to version 1.0.1 with previous version 1.0.0 dated 2026-08-21

Title: Tools for Joint Sentiment and Topic Analysis of Textual Data
Description: A framework that joins topic modeling and sentiment analysis of textual data. The package implements a fast Gibbs sampling estimation of Latent Dirichlet Allocation (Griffiths and Steyvers (2004) <doi:10.1073/pnas.0307752101>) and Joint Sentiment/Topic Model (Lin, He, Everson and Ruger (2012) <doi:10.1109/TKDE.2011.48>). It offers a variety of helpers and visualizations to analyze the result of topic modeling. The framework also allows enriching topic models with dates and externally computed sentiment measures. A flexible aggregation scheme enables the creation of time series of sentiment or topical proportions from the enriched topic models. Moreover, a novel method jointly aggregates topic proportions and sentiment measures to derive time series of topical sentiment.
Author: Olivier Delmarcelle [aut, cre] , Samuel Borms [ctb] , Chenghua Lin [cph] , Yulan He [cph] , Jose Bernardo [cph] , David Robinson [cph] ), Julia Silge [cph] , ORCID: <https://orcid.org/0000-0002-3671-836X>)
Maintainer: Olivier Delmarcelle <delmarcelle.olivier@gmail.com>

Diff between sentopics versions 1.0.0 dated 2026-08-21 and 1.0.1 dated 2026-09-10

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Package mosclust updated to version 1.0.3 with previous version 1.0.2 dated 2025-05-27

Title: Model Order Selection for Clustering
Description: Stability based methods for model order selection in clustering problems (Valentini, G (2007), <doi:10.1093/bioinformatics/btl600>). Using multiple perturbations of the data the stability of clustering solutions is assessed. Different perturbations may be used: resampling techniques, random projections and noise injection. Stability measures for the estimate of clustering solutions and statistical tests to assess their significance are provided.
Author: Giorgio Valentini [aut], Jessica Gliozzo [cre]
Maintainer: Jessica Gliozzo <jessica.gliozzo@gmail.com>

Diff between mosclust versions 1.0.2 dated 2025-05-27 and 1.0.3 dated 2026-09-10

 DESCRIPTION |   10 +++++-----
 MD5         |    2 +-
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Package LABTNSCPSS updated to version 1.0.4 with previous version 1.0.3 dated 2026-09-05

Title: Calculation of Comorbidity and Frailty Scores
Description: Computes comorbidity indices and combined frailty scores for multiple ICD coding systems, including ICD-10-CA, ICD-10-CM, and ICD-11. The package provides tools to preprocess episode data, map diagnosis codes to chronic categories, propagate conditions across episodes, and generate comorbidity and frailty measures. The methods implemented are original to this package and were developed by the authors for research applications; a manuscript describing the methodology is currently in preparation.
Author: Azadeh Bayani [aut, cre] , Jean Noel Nikiema [ctb], Michele Bally [ctb]
Maintainer: Azadeh Bayani <azadeh.bayani@umontreal.ca>

Diff between LABTNSCPSS versions 1.0.3 dated 2026-09-05 and 1.0.4 dated 2026-09-10

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 MD5                       |   11 +++++++----
 R/setup_package.R         |only
 README.md                 |   43 +++++++++++++++++++++++++++++++------------
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Package GenHMM1d updated to version 0.2.8 with previous version 0.2.6 dated 2025-09-07

Title: Goodness-of-Fit for Zero-Inflated Univariate Hidden Markov Models
Description: Inference, goodness-of-fit tests, and predictions for continuous and discrete univariate Hidden Markov Models (HMM), including zero-inflated distributions. The goodness-of-fit test is based on a Cramer-von Mises statistic and uses parametric bootstrap to estimate the p-value. The description of the methodology is taken from Nasri et al (2020) <doi:10.1029/2019WR025122>.
Author: Bouchra R. Nasri [aut, cre, cph], Mamadou Yamar Thioub [aut, cph], Bruno N. Remillard [aut, cph]
Maintainer: Bouchra R. Nasri <bouchra.nasri@umontreal.ca>

Diff between GenHMM1d versions 0.2.6 dated 2025-09-07 and 0.2.8 dated 2026-09-10

 DESCRIPTION      |   10 +--
 MD5              |   26 ++++----
 R/CDF.R          |   39 ++++++-------
 R/CDF_est.R      |   31 ++++++----
 R/EstHMMGen.R    |  161 +++++++++++++++++++++++++++++++------------------------
 R/GofHMMGen.R    |    4 +
 R/PDF.R          |   29 ++++++---
 R/PDF_unc.R      |   43 +++++++++-----
 R/QUANTILE.R     |   22 +++----
 R/SimHMMGen.R    |   37 +++++++-----
 R/alpha2theta.R  |   46 +++++++++------
 R/theta2alpha.R  |   49 ++++++++++------
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 14 files changed, 291 insertions(+), 215 deletions(-)

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Package GADAG updated to version 0.99.1 with previous version 0.99.0 dated 2017-04-11

Title: A Genetic Algorithm for Learning Directed Acyclic Graphs
Description: Learns sparse large Directed Acyclic Graphs with a combination of a convex program and a tailored genetic algorithm.
Author: Magali Champion [aut, cre], Victor Picheny [aut], Matthieu Vignes [aut]
Maintainer: Magali Champion <magali.champion@u-paris.fr>

Diff between GADAG versions 0.99.0 dated 2017-04-11 and 0.99.1 dated 2026-09-10

 GADAG-0.99.0/GADAG/src/registerDynamicSymbol.c |only
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 GADAG-0.99.1/GADAG/NAMESPACE                   |   42 -
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 GADAG-0.99.1/GADAG/R/GADAG_Run.R               |  680 +++++++++++--------------
 GADAG-0.99.1/GADAG/R/RcppExports.R             |   14 
 GADAG-0.99.1/GADAG/R/chrom.R                   |   72 +-
 GADAG-0.99.1/GADAG/R/create.population.R       |   70 +-
 GADAG-0.99.1/GADAG/R/crossover.R               |  145 ++---
 GADAG-0.99.1/GADAG/R/evaluation.R              |  234 ++++----
 GADAG-0.99.1/GADAG/R/fitness.R                 |  114 ++--
 GADAG-0.99.1/GADAG/R/generateToyData.R         |  256 ++++-----
 GADAG-0.99.1/GADAG/R/mutation.R                |  115 ++--
 GADAG-0.99.1/GADAG/R/selection.R               |  111 ++--
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 GADAG-0.99.1/GADAG/man/evaluation.Rd           |  174 +++---
 GADAG-0.99.1/GADAG/man/fitness.Rd              |  120 ++--
 GADAG-0.99.1/GADAG/man/generateToyData.Rd      |  135 ++--
 GADAG-0.99.1/GADAG/man/toy_data.Rd             |   34 -
 GADAG-0.99.1/GADAG/src/RcppExports.cpp         |   17 
 27 files changed, 1868 insertions(+), 1791 deletions(-)

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Package flextable updated to version 0.10.1 with previous version 0.10.0 dated 2026-07-07

Title: Functions for Tabular Reporting
Description: Use a grammar for creating and customizing pretty tables. The following formats are supported: 'HTML', 'PDF', 'Typst', 'RTF', 'Microsoft Word', 'Microsoft PowerPoint', R 'Grid Graphics' and 'patchwork'. 'R Markdown', 'Quarto' and the package 'officer' can be used to produce the result files. The syntax is the same for the user regardless of the type of output to be produced. A set of functions allows the creation, definition of cell arrangement, addition of headers or footers, formatting and definition of cell content with text and or images. The package also offers a set of high-level functions that allow tabular reporting of statistical models and the creation of complex cross tabulations.
Author: David Gohel [aut, cre], ArData [cph], Clementine Jager [ctb], Eli Daniels [ctb], Panagiotis Skintzos [aut], Quentin Fazilleau [ctb], Maxim Nazarov [ctb], Titouan Robert [ctb], Michael Barrowman [ctb], Atsushi Yasumoto [ctb], Paul Julian [ctb], Sean B [...truncated...]
Maintainer: David Gohel <david.gohel@ardata.fr>

Diff between flextable versions 0.10.0 dated 2026-07-07 and 0.10.1 dated 2026-09-10

 DESCRIPTION                             |    8 
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 NAMESPACE                               |  367 +++++++++++++++++---------------
 NEWS.md                                 |   23 ++
 R/docx_str.R                            |   15 -
 R/html_str.R                            |   16 +
 R/pptx_str.R                            |    9 
 R/read_structure.R                      |  101 +++++++-
 R/rtf_str.R                             |    6 
 R/runs_as_functions.R                   |   15 -
 R/typst_str.R                           |   29 ++
 R/xtable_to_flextable.R                 |    2 
 tests/testthat/test-cell_content.R      |    6 
 tests/testthat/test-deterministic-css.R |only
 tests/testthat/test-footers.R           |    2 
 tests/testthat/test-headers.R           |    4 
 tests/testthat/test-typst.R             |   43 +++
 17 files changed, 427 insertions(+), 250 deletions(-)

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New package exnexSurv with initial version 1.3.0
Package: exnexSurv
Title: Bayesian EXNEX Models for Survival Analysis in Basket Trials
Version: 1.3.0
Description: Implements the Bayesian Exchangeable Non-Exchangeable (EXNEX) framework for right-censored log-normal survival data in basket trials. Based on 'Rcpp' and 'RcppArmadillo', the package provides a fast Gibbs sampler supporting EXNEX, complete pooling, and no pooling models to facilitate methodological comparisons and simulation studies.
License: MIT + file LICENSE
URL: https://github.com/victorney/exnexSurv, https://victorney.github.io/exnexSurv/
BugReports: https://github.com/victorney/exnexSurv/issues
Imports: Rcpp (>= 1.1.1), hardhat (>= 1.4.0), checkmate (>= 2.1.0)
Suggests: testthat (>= 3.3.0), survival (>= 3.8), knitr, rmarkdown, ggplot2, bayesplot, viridisLite
VignetteBuilder: knitr
LinkingTo: Rcpp, RcppArmadillo
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2026-08-30 15:53:41 UTC; victo
Author: Victor Ney [aut, cre]
Maintainer: Victor Ney <victorney@ime.usp.br>
Repository: CRAN
Date/Publication: 2026-09-10 14:20:15 UTC

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New package co2e with initial version 0.1.0
Package: co2e
Title: Global Warming Potential Lookups and CO2-Equivalent Conversion
Version: 0.1.0
Description: Provides curated Global Warming Potential (GWP) values from IPCC Assessment Reports 4 through 6, gas name standardization across documented naming variants (IUPAC/common names, per-report naming changes, and EPA/data.gov naming), and CO2-equivalent conversion utilities. Values are drawn from official IPCC source tables, with corrections applied for two substances where the published table is known to contain errors; see the package vignette for details and source-by-source provenance notes.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: dplyr, tibble, stringr
Suggests: tidyr, readr, testthat (>= 3.0.0), knitr, rmarkdown, spelling
Depends: R (>= 4.1.0)
LazyData: true
VignetteBuilder: knitr
Language: en-US
URL: https://github.com/joewcorra/co2e
BugReports: https://github.com/joewcorra/co2e/issues
NeedsCompilation: no
Packaged: 2026-08-30 16:21:11 UTC; joewc
Author: Joe Corra [aut, cre, cph]
Maintainer: Joe Corra <Joewcorra@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 14:10:02 UTC

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Package liver updated to version 1.30 with previous version 1.29 dated 2026-05-04

Title: Toolkit and Datasets for Data Science
Description: Provides a collection of helper functions and illustrative datasets to support learning and teaching of data science with R. The package is designed as a companion to the book <https://book-data-science-r.netlify.app>, making key data science techniques accessible to individuals with minimal coding experience. Functions include tools for data partitioning, performance evaluation, and data transformations (e.g., z-score and min-max scaling). The included datasets are curated to highlight practical applications in data exploration, modeling, and multivariate analysis. An early inspiration for the package came from an ancient Persian idiom about "eating the liver", symbolizing deep and immersive engagement with knowledge.
Author: Reza Mohammadi [aut, cre] , Jeroen van Raak [aut] , Kevin Burke [aut]
Maintainer: Reza Mohammadi <a.mohammadi@uva.nl>

Diff between liver versions 1.29 dated 2026-05-04 and 1.30 dated 2026-09-10

 DESCRIPTION                 |    6 -
 MD5                         |   10 -
 NEWS.md                     |    4 
 R/partition.R               |  259 ++++++++++++++++++++++++++++++++++++++------
 inst/doc/liver-example.html |   14 +-
 man/partition.Rd            |   31 +++--
 6 files changed, 268 insertions(+), 56 deletions(-)

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Package immunaut updated to version 1.0.3 with previous version 1.0.2 dated 2025-04-09

Title: Machine Learning Immunogenicity and Vaccine Response Analysis
Description: Used for analyzing immune responses and predicting vaccine efficacy using machine learning and advanced data processing techniques. 'Immunaut' integrates both unsupervised and supervised learning methods, managing outliers and capturing immune response variability. It performs multiple rounds of predictive model testing to identify robust immunogenicity signatures that can predict vaccine responsiveness. The platform is designed to handle high-dimensional immune data, enabling researchers to uncover immune predictors and refine personalized vaccination strategies across diverse populations.
Author: Ivan Tomic [aut, cre, cph] , Adriana Tomic [aut, ctb, cph, fnd] , Stephanie Hao [aut]
Maintainer: Ivan Tomic <info@ivantomic.com>

Diff between immunaut versions 1.0.2 dated 2025-04-09 and 1.0.3 dated 2026-09-10

 DESCRIPTION                |   24 +-
 MD5                        |   27 +-
 NAMESPACE                  |    2 
 NEWS.md                    |   23 ++
 R/functions.R              |  465 ++++++++++++++++++++++++---------------------
 R/immunaut.R               |  119 +++++++----
 R/utils.R                  |  308 +++++++++++++++++++----------
 README.md                  |  416 ++++++++++++++++++++--------------------
 man/auto_simon_ml.Rd       |   98 ++++-----
 man/immunaut.Rd            |    8 
 man/plot_clustered_tsne.Rd |    2 
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 man/preProcessResample.Rd  |   27 +-
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 14 files changed, 883 insertions(+), 670 deletions(-)

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New package epkde with initial version 0.1.0
Package: epkde
Title: Bayesian Bandwidth Selection for Multivariate KDE via Expectation Propagation
Version: 0.1.0
Author: Maurizio Filippone [aut, cre]
Maintainer: Maurizio Filippone <maurizio.filippone@kaust.edu.sa>
Description: Implements the approximate Bayesian method for bandwidth selection in multivariate kernel density estimation (KDE) proposed in Filippone & Sanguinetti (2011) <doi:10.1016/j.csda.2011.05.023>. The method uses the Expectation Propagation (EP) algorithm to approximate the posterior distribution of the inverse bandwidth (precision matrix) under a leave-one-out cross-validated likelihood. Three covariance structures are supported: isotropic (scalar precision), diagonal, and full precision matrix. Online Bayesian updating is supported for the isotropic case. The approximate posterior can be used for bandwidth selection, model comparison (via the model evidence / Bayes factor), and online learning.
Depends: R (>= 4.0.0)
License: GPL-3
Encoding: UTF-8
Imports:
Suggests: ks, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/mauriziofilippone/epkde
BugReports: https://github.com/mauriziofilippone/epkde/issues
NeedsCompilation: no
Packaged: 2026-08-30 09:29:08 UTC; filippm
Repository: CRAN
Date/Publication: 2026-09-10 13:10:08 UTC

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Package CompositionalRF updated to version 1.7 with previous version 1.6 dated 2026-02-28

Title: Multivariate Random Forest with Compositional Responses
Description: Multivariate random forests with compositional responses and Euclidean predictors is performed. The compositional data are first transformed using the additive log-ratio transformation, or the alpha-transformation of Tsagris, Preston and Wood (2011), <doi:10.48550/arXiv.1106.1451>, and then the multivariate random forest of Rahman R., Otridge J. and Pal R. (2017), <doi:10.1093/bioinformatics/btw765>, is applied.
Author: Michail Tsagris [aut, cre], Christos Adam [aut]
Maintainer: Michail Tsagris <mtsagris@uoc.gr>

Diff between CompositionalRF versions 1.6 dated 2026-02-28 and 1.7 dated 2026-09-10

 DESCRIPTION                    |    8 ++++----
 MD5                            |    8 ++++----
 R/alfa.comp.rf.R               |   21 +++++++++++++++------
 R/cv.alfacomprf.R              |    6 +++---
 man/CompositionalRF-package.Rd |    4 ++--
 5 files changed, 28 insertions(+), 19 deletions(-)

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Package RDieHarder updated to version 0.2.8 with previous version 0.2.7 dated 2025-03-26

Title: R Interface to the 'DieHarder' RNG Test Suite
Description: The 'RDieHarder' package provides an R interface to the 'DieHarder' suite of random number generators and tests that was developed by Robert G. Brown and David Bauer, extending earlier work by George Marsaglia and others. The 'DieHarder' library code is included.
Author: Dirk Eddelbuettel [aut, cre] , Robert G Brown [aut], David Bauer [aut], DieHarder Contributors [ctb]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between RDieHarder versions 0.2.7 dated 2025-03-26 and 0.2.8 dated 2026-09-10

 ChangeLog                |   32 ++++++++++++++++++++++++++++++++
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 MD5                      |   22 +++++++++++-----------
 build/vignette.rds       |binary
 configure                |   18 +++++++++---------
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 inst/doc/RDieHarder.R    |    3 +--
 inst/doc/RDieHarder.Rnw  |   18 +++++++++---------
 inst/doc/RDieHarder.pdf  |binary
 man/dieharder.Rd         |    4 ++--
 vignettes/RDieHarder.Rnw |   18 +++++++++---------
 vignettes/RDieHarder.bib |   31 ++++++++++++++++++-------------
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New package infometrics with initial version 0.3.0
Package: infometrics
Title: Information-Theoretic Methods for Econometric Estimation
Version: 0.3.0
Date: 2026-08-29
Description: Implements the class of Information-Theoretic (IT) estimators for econometric models, following the unified framework of Golan (2008) <doi:10.1561/0800000004>. Provides Generalized Maximum Entropy (GME) and Generalized Cross-Entropy (GCE) estimators for linear regression, instrumental variables, one-way error-component panel data, multinomial response, matrix balancing, and first-order Markov transition matrices, together with pure and noisy inverse-problem solvers. All estimators use the concentrated (dual) formulation for computational efficiency and report normalized-entropy, entropy-ratio, and Fano-bound diagnostics.
License: GPL-3
URL: https://github.com/GenMaxEnt/infometrics_R
BugReports: https://github.com/GenMaxEnt/infometrics_R/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: bookdown, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-30 08:32:06 UTC; gnbtr
Author: Ganbaatar Jambal [aut, cre]
Maintainer: Ganbaatar Jambal <jg3169a@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 13:00:02 UTC

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Package datawizard updated to version 1.4.0 with previous version 1.3.1 dated 2026-04-26

Title: Easy Data Wrangling and Statistical Transformations
Description: A lightweight package to assist in key steps involved in any data analysis workflow: (1) wrangling the raw data to get it in the needed form, (2) applying preprocessing steps and statistical transformations, and (3) compute statistical summaries of data properties and distributions. It is also the data wrangling backend for packages in 'easystats' ecosystem. References: Patil et al. (2022) <doi:10.21105/joss.04684>.
Author: Indrajeet Patil [aut] , Etienne Bacher [aut, cre] , Dominique Makowski [aut] , Daniel Luedecke [aut] , Mattan S. Ben-Shachar [aut] , Brenton M. Wiernik [aut] , Remi Theriault [ctb] , Elin Waring [ctb], Thomas J. Faulkenberry [rev], Robert Garrett [rev [...truncated...]
Maintainer: Etienne Bacher <etienne.bacher@protonmail.com>

Diff between datawizard versions 1.3.1 dated 2026-04-26 and 1.4.0 dated 2026-09-10

 DESCRIPTION                                    |   26 
 MD5                                            |  266 +--
 NAMESPACE                                      |   10 
 NEWS.md                                        |   26 
 R/assign_labels.R                              |  362 ++--
 R/center.R                                     |  708 ++++----
 R/contrs.R                                     |  201 +-
 R/convert_na_to.R                              |  434 ++---
 R/data.R                                       |   42 
 R/data_addprefix.R                             |  148 -
 R/data_arrange.R                               |  308 +--
 R/data_codebook.R                              | 1144 +++++++-------
 R/data_duplicated.R                            |  210 +-
 R/data_extract.R                               |  310 +--
 R/data_group.R                                 |  158 -
 R/data_partition.R                             |  326 ++--
 R/data_peek.R                                  |  304 +--
 R/data_read.R                                  |   10 
 R/data_relocate.R                              |  354 ++--
 R/data_rescale.R                               |  718 ++++-----
 R/data_restoretype.R                           |  100 -
 R/data_reverse.R                               |  624 +++----
 R/data_rotate.R                                |  206 +-
 R/data_seek.R                                  |  380 ++--
 R/data_select.R                                |   88 -
 R/data_separate.R                              |  876 +++++------
 R/data_tabulate.R                              |   94 +
 R/data_to_long.R                               |  764 ++++-----
 R/data_to_wide.R                               |  946 +++++------
 R/data_unique.R                                |  308 +--
 R/data_unite.R                                 |  238 +-
 R/data_xtabulate.R                             |    9 
 R/datawizard-package.R                         |   42 
 R/demean.R                                     |    4 
 R/describe_distribution.R                      | 1640 ++++++++++----------
 R/descriptives.R                               |  426 ++---
 R/extract_column_names.R                       |  360 ++--
 R/format.R                                     |  214 +-
 R/labels_to_levels.R                           |  216 +-
 R/makepredictcall.R                            |  166 +-
 R/mean_sd.R                                    |  192 +-
 R/means_by_group.R                             |   19 
 R/ranktransform.R                              |  404 ++---
 R/remove_empty.R                               |  254 +--
 R/replace_nan_inf.R                            |  126 -
 R/rescale_weights.R                            |  950 +++++------
 R/row_count.R                                  |  266 +--
 R/row_means.R                                  |  428 ++---
 R/select_nse.R                                 | 1516 +++++++++----------
 R/slide.R                                      |  210 +-
 R/smoothness.R                                 |  270 +--
 R/standardize.R                                |  874 +++++-----
 R/to_factor.R                                  |  284 +--
 R/to_numeric.R                                 |  674 ++++----
 R/unnormalize.R                                |  332 ++--
 R/unstandardize.R                              |  686 ++++----
 R/utils-cols.R                                 |  188 +-
 R/utils_standardize_center.R                   | 1056 ++++++-------
 R/visualisation_recipe.R                       |  184 +-
 R/weighted_mean_median_sd_mad.R                |  328 ++--
 R/winsorize.R                                  |  298 +--
 build/partial.rdb                              |binary
 build/vignette.rds                             |binary
 man/assign_labels.Rd                           |  296 +--
 man/categorize.Rd                              |  528 +++---
 man/center.Rd                                  |  400 ++---
 man/coef_var.Rd                                |  186 +-
 man/coerce_to_numeric.Rd                       |   44 
 man/colnames.Rd                                |  100 -
 man/contr.deviation.Rd                         |   22 
 man/convert_na_to.Rd                           |  344 ++--
 man/convert_to_na.Rd                           |  252 +--
 man/data_arrange.Rd                            |   70 
 man/data_duplicated.Rd                         |  218 +-
 man/data_extract.Rd                            |  294 +--
 man/data_merge.Rd                              |  412 ++---
 man/data_partition.Rd                          |  168 +-
 man/data_peek.Rd                               |  210 +-
 man/data_prefix_suffix.Rd                      |  214 +-
 man/data_read.Rd                               |    6 
 man/data_relocate.Rd                           |  310 +--
 man/data_replicate.Rd                          |  200 +-
 man/data_restoretype.Rd                        |   70 
 man/data_rotate.Rd                             |  136 -
 man/data_seek.Rd                               |  136 -
 man/data_separate.Rd                           |  454 ++---
 man/data_tabulate.Rd                           |   10 
 man/data_unique.Rd                             |  214 +-
 man/data_unite.Rd                              |  232 +-
 man/datawizard-package.Rd                      |  103 -
 man/distribution_mode.Rd                       |   68 
 man/efc.Rd                                     |   24 
 man/extract_column_names.Rd                    |  398 ++---
 man/labels_to_levels.Rd                        |  240 +--
 man/makepredictcall.dw_transformer.Rd          |  106 -
 man/mean_sd.Rd                                 |   98 -
 man/means_by_group.Rd                          |    4 
 man/nhanes_sample.Rd                           |   28 
 man/normalize.Rd                               |   10 
 man/ranktransform.Rd                           |  288 +--
 man/recode_into.Rd                             |  252 +--
 man/reexports.Rd                               |    2 
 man/replace_nan_inf.Rd                         |   64 
 man/rescale.Rd                                 |  390 ++--
 man/reverse.Rd                                 |  300 +--
 man/row_count.Rd                               |  274 +--
 man/row_means.Rd                               |  336 ++--
 man/rownames.Rd                                |  110 -
 man/skewness.Rd                                |  296 +--
 man/slide.Rd                                   |  288 +--
 man/smoothness.Rd                              |   74 
 man/standardize.Rd                             |  584 +++----
 man/standardize.default.Rd                     |  200 +-
 man/text_format.Rd                             |  162 +-
 man/to_factor.Rd                               |  268 +--
 man/to_numeric.Rd                              |  290 +--
 man/visualisation_recipe.Rd                    |   60 
 man/weighted_mean.Rd                           |  112 -
 man/winsorize.Rd                               |  196 +-
 tests/testthat/_snaps/data_read.md             |  240 +--
 tests/testthat/_snaps/data_summary.md          |  134 -
 tests/testthat/_snaps/data_tabulate.md         | 1990 ++++++++++++-------------
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 tests/testthat/test-standardize_models.R       |  910 +++++------
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More information about datawizard at CRAN
Permanent link

Package TreeTools updated to version 2.4.1 with previous version 2.4.0 dated 2026-06-02

Title: Create, Modify and Analyse Phylogenetic Trees
Description: Efficient implementations of functions for the creation, modification and analysis of phylogenetic trees. Applications include: generation of trees with specified shapes; tree rearrangement; analysis of tree shape; rooting of trees and extraction of subtrees; calculation and depiction of split support; plotting the position of rogue taxa (Klopfstein & Spasojevic 2019) <doi:10.1371/journal.pone.0212942>; calculation of ancestor-descendant relationships, of 'stemwardness' (Asher & Smith, 2022) <doi:10.1093/sysbio/syab072>, and of tree balance (Mir et al. 2013, Lemant et al. 2022) <doi:10.1016/j.mbs.2012.10.005>, <doi:10.1093/sysbio/syac027>; artificial extinction (Asher & Smith, 2022) <doi:10.1093/sysbio/syab072>; import and export of trees from Newick, Nexus (Maddison et al. 1997) <doi:10.1093/sysbio/46.4.590>, and TNT <https://www.lillo.org.ar/phylogeny/tnt/> formats; and analysis of splits and cladistic information.
Author: Martin R. Smith [aut, cre, cph] , Emmanuel Paradis [cph] , Robert Noble [cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Diff between TreeTools versions 2.4.0 dated 2026-06-02 and 2.4.1 dated 2026-09-10

 DESCRIPTION                                            |   15 
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 NAMESPACE                                              | 1036 +--
 NEWS.md                                                |   24 
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More information about TreeTools at CRAN
Permanent link

Package synthpop updated to version 1.9-3 with previous version 1.9-2 dated 2025-07-12

Title: Generating Synthetic Versions of Sensitive Microdata for Statistical Disclosure Control
Description: A tool for producing synthetic versions of microdata containing confidential information so that they are safe to be released to users for exploratory analysis. The key objective of generating synthetic data is to replace sensitive original values with synthetic ones causing minimal distortion of the statistical information contained in the data set. Most synthesising methods available in the package synthesise from conditional distributions where variables, which can be categorical or continuous, are synthesised one-by-one using sequential modelling. Replacements are generated by drawing from conditional distributions fitted to the original data using parametric or classification and regression trees models. Methods that are not sequential, but synthesise all variables at once, are 'sample', 'ipf', and 'catall'. Data are synthesised via the function syn() which can be largely automated, if default settings are used, or with methods defined by the user. Optional parameters can be used [...truncated...]
Author: Beata Nowok [aut, cre], Gillian Raab [aut], Chris Dibben [ctb], Joshua Snoke [ctb], Caspar van Lissa [ctb], Lotte Pater [ctb], Timon Huijser [ctb]
Maintainer: Beata Nowok <beata.nowok@gmail.com>

Diff between synthpop versions 1.9-2 dated 2025-07-12 and 1.9-3 dated 2026-09-10

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More information about synthpop at CRAN
Permanent link

Package kde1d updated to version 1.2.0 with previous version 1.1.1 dated 2025-06-12

Title: Univariate Kernel Density Estimation
Description: Provides an efficient implementation of univariate local polynomial kernel density estimators that can handle bounded, discrete, and zero-inflated data. See Geenens and Wang (2018) <doi:10.48550/arXiv.1602.04862>, Geenens (2014) <doi:10.48550/arXiv.1303.4121>, Nagler (2018a) <doi:10.48550/arXiv.1704.07457>, Nagler (2018b) <doi:10.48550/arXiv.1705.05431>.
Author: Thomas Nagler [aut, cre], Thibault Vatter [aut]
Maintainer: Thomas Nagler <mail@tnagler.com>

Diff between kde1d versions 1.1.1 dated 2025-06-12 and 1.2.0 dated 2026-09-10

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More information about kde1d at CRAN
Permanent link

Package easybgm updated to version 0.5.0 with previous version 0.4.0 dated 2026-04-02

Title: Extracting and Visualizing Bayesian Graphical Models
Description: Fit and visualize the results of a Bayesian analysis of networks commonly found in psychology. The package supports cross-sectional network models for ordinal, binary, continuous, and mixed data, fitted using the packages 'bgms' (default), 'BDgraph', and 'BGGM', as well as network comparison tests fitted using the packages 'bgms' and 'BGGM'. The package provides the parameter estimates, posterior inclusion probabilities, inclusion Bayes factor, and the posterior density of the parameters. In addition, for 'BDgraph' and 'bgms' it allows to assess the posterior structure space. Furthermore, the package comes with an extensive suite for visualizing results.
Author: Karoline Huth [aut, cre] , Sara Keetelaar [ctb], Nikola Sekulovski [ctb], Gali Geller [ctb]
Maintainer: Karoline Huth <k.huth@uva.nl>

Diff between easybgm versions 0.4.0 dated 2026-04-02 and 0.5.0 dated 2026-09-10

 DESCRIPTION                      |   26 -
 MD5                              |   59 +-
 NEWS.md                          |only
 R/AuxiliaryFunctions.R           |  506 +++++++++++++++++++---
 R/bgm_plot_class.R               |   48 +-
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 README.md                        |    6 
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 tests/testthat/test-easybgm.R    |  887 ++++++++++++++++++++++++++-------------
 31 files changed, 2817 insertions(+), 1408 deletions(-)

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Package BayesRTMB updated to version 0.4.0 with previous version 0.3.0 dated 2026-08-20

Title: Bayesian Inference Using 'RTMB'
Description: Provides tools for Markov chain Monte Carlo (MCMC) and Maximum A Posteriori (MAP) estimation utilizing the 'RTMB' package. It supports various statistical models including generalized linear mixed models, factor analysis, item response theory, and multidimensional unfolding. The package allows users to easily transition between frequentist and Bayesian paradigms using a unified interface. Automatic differentiation and Laplace approximation follow Kristensen et al. (2016) <doi:10.18637/jss.v070.i05>, and MCMC sampling uses the No-U-Turn Sampler described by Hoffman and Gelman (2014) <https://jmlr.org/papers/v15/hoffman14a.html>.
Author: Hiroshi Shimizu [aut, cre]
Maintainer: Hiroshi Shimizu <simizu706@gmail.com>

Diff between BayesRTMB versions 0.3.0 dated 2026-08-20 and 0.4.0 dated 2026-09-10

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 vignettes/ja-wrapper_functions.Rmd         |   22 +--
 41 files changed, 887 insertions(+), 290 deletions(-)

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Package approximator updated to version 1.3-0 with previous version 1.2-8 dated 2023-08-24

Title: Bayesian Prediction of Complex Computer Codes
Description: Performs Bayesian prediction of complex computer codes when fast approximations are available. It uses a hierarchical version of the Gaussian process, originally proposed by Kennedy and O'Hagan (2000), Biometrika 87(1):1.
Author: Robin K. S. Hankin [aut, cre]
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>

Diff between approximator versions 1.2-8 dated 2023-08-24 and 1.3-0 dated 2026-09-10

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 15 files changed, 59 insertions(+), 61 deletions(-)

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Package performance updated to version 0.18.2 with previous version 0.18.1 dated 2026-09-01

Title: Assessment of Regression Models Performance
Description: Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models. References: Lüdecke et al. (2021) <doi:10.21105/joss.03139>.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Remi Theriault [aut, ctb] , Vincent Arel-Bundock [ctb] , Martin J [...truncated...]
Maintainer: Daniel Luedecke <officialeasystats@gmail.com>

Diff between performance versions 0.18.1 dated 2026-09-01 and 0.18.2 dated 2026-09-10

 DESCRIPTION                                    |    8 ++++----
 MD5                                            |   12 ++++++------
 NEWS.md                                        |   12 ++++++++++++
 R/check_heteroscedasticity.R                   |    2 +-
 R/check_singularity.R                          |    2 +-
 tests/testthat/test-check_heteroskedasticity.R |   21 +++++++++++++++++++++
 tests/testthat/test-check_outliers.R           |    3 ++-
 7 files changed, 47 insertions(+), 13 deletions(-)

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Package BayesNSGP updated to version 0.3.1 with previous version 0.3.0 dated 2026-08-19

Title: Bayesian Analysis of Non-Stationary Gaussian Process Models
Description: Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling. The approach to nonstationary modeling involves a closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes can be specified either deterministically (using covariates or basis functions) or stochastically (using approximate Gaussian processes). Stationary Gaussian processes are a special case of our methodology, and we furthermore implement approximate Gaussian process inference to account for very large spatial data sets (Finley, et al (2017) <doi:10.48550/arXiv.1702.00434>). Bayesian inference is carried out using Markov chain Monte Carlo methods via the "nimble" package, and posterior prediction for the Gaussian process at unobserved locations is provided as a post-processing step. Also provided are nearest-neighbor Gaussian process components for use directly in user-written model code, where the spatial process is retained as [...truncated...]
Author: Daniel Turek [aut, cre], Mark Risser [aut], Fabian Ketwaroo [aut]
Maintainer: Daniel Turek <danielturek@gmail.com>

Diff between BayesNSGP versions 0.3.0 dated 2026-08-19 and 0.3.1 dated 2026-09-10

 DESCRIPTION            |   13 ++++++++-----
 MD5                    |   15 ++++++++++-----
 R/v03_NNGP_density.R   |   13 ++++++++++---
 R/v03_NNGP_neighbors.R |   14 ++++++++------
 build/partial.rdb      |binary
 man/NNGP.pred.Rd       |   13 ++++++++++---
 tests                  |only
 7 files changed, 46 insertions(+), 22 deletions(-)

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New package RSEML with initial version 0.1.0
Package: RSEML
Title: Case-Based Least Squares Estimation of Nonlinear Structural Equation Models
Version: 0.1.0
Date: 2026-08-28
Description: Estimates structural equation models by case-based least squares: the latent scores of every observation are treated as free variables of a constrained optimization problem, so that arbitrary nonlinear model equations, bounds and constraints on latent variables and inequality constraints on parameters become possible. Model equations are specified as plain text (e.g. "y == a*exp(b*eta)"). Gradients are obtained by automatic differentiation via 'RTMB', and the constrained problem is solved with 'nloptr' (SLSQP or augmented Lagrangian). Missing data are handled case-wise. The methodology is described in Oldenburg (2024) <doi:10.19139/soic-2310-5070-1868> and Oldenburg (2025) <doi:10.19139/soic-2310-5070-2324>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: RTMB, nloptr, stats
Suggests: knitr, rmarkdown
NeedsCompilation: no
Packaged: 2026-08-29 12:48:31 UTC; root
Author: Reinhard Oldenburg [aut, cre]
Maintainer: Reinhard Oldenburg <reinhard.oldenburg@math.uni-augsburg.de>
Repository: CRAN
Date/Publication: 2026-09-10 09:20:12 UTC

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New package otter with initial version 0.1.0
Package: otter
Title: Ott's Utility Functions
Version: 0.1.0
Description: A growing collection of personal utility functions. Currently provides tools to parse Rich Text Format (RTF) files and extract their tables into data frames, automatically detecting header rows, merging multi-page tables, and resolving merged cells. Particularly useful for tables produced by SAS or by the 'r2rtf' package, which are commonly used for clinical trial and regulatory reporting.
License: MIT + file LICENSE
URL: https://github.com/ottvahtrik/otter, https://ottvahtrik.github.io/otter/
BugReports: https://github.com/ottvahtrik/otter/issues
Encoding: UTF-8
Suggests: lintr, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-08-28 16:48:57 UTC; ottvahtrik
Author: Ott Vahtrik [aut, cre]
Maintainer: Ott Vahtrik <ott.vahtrik@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:20:02 UTC

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New package oesir with initial version 0.3.2
Package: oesir
Title: Online Sliced Inverse Regression for Elliptical Model with Streaming Data
Version: 0.3.2
Author: Sirui Yan [aut], Guangbao Guo [aut, cre]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Description: For high-dimensional streaming heavy-tailed elliptical data, traditional sliced inverse regression methods require full offline data and cannot adapt to incremental data arrival. This package implements Online Sliced Inverse Regression for Elliptical Model with Streaming Data (OE-SIR) algorithm with two recursive updating strategies, including offline batch SIR as benchmark, elliptical heavy-tailed data simulator, subspace evaluation metric and batch simulation tools for numerical experiments. Cai, Z., Li, R., & Zhu, L. (2020) <doi:10.48550/arXiv.2002.02795>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: stats, Matrix, MASS
NeedsCompilation: no
Language: en-US
Packaged: 2026-08-05 09:27:43 UTC; Lenovo
Repository: CRAN
Date/Publication: 2026-09-10 09:20:08 UTC

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New package cudaverse with initial version 0.4.1
Package: cudaverse
Title: Lightweight 'CUDA' Numerical Computing
Version: 0.4.1
Description: Provides a lightweight interface to graphics processing unit (GPU)-accelerated numerical computing using 'CUDA'. Dense tensors, sparse matrices, decompositions, distances, exact nearest neighbours, clustering, graph workflows, and embeddings share one consistent interface. The native backend discovers the 'NVIDIA CUDA Driver API', 'cuBLAS', and 'cuSOLVER' libraries at runtime without bundling 'LibTorch' or the 'CUDA Runtime'. Stage-level provenance records the backend, device, and data transfers used by each result. A portable implementation supports package validation on systems without 'CUDA'. Background for the included Leiden community detection and uniform manifold approximation and projection methods is given by Traag, Waltman and van Eck (2019) <doi:10.1038/s41598-019-41695-z> and McInnes et al. (2018) <doi:10.21105/joss.00861>, respectively.
License: MIT + file LICENSE
URL: https://cudaverse.github.io/cudaverse/, https://github.com/cudaverse/cudaverse
BugReports: https://github.com/cudaverse/cudaverse/issues
Encoding: UTF-8
Language: en-US
Imports: Matrix, methods, stats
Suggests: igraph (>= 2.0.0), knitr, rmarkdown, RSpectra, Rtsne, S4Vectors, SingleCellExperiment, testthat (>= 3.0.0), torch, uwot
VignetteBuilder: knitr
SystemRequirements: For GPU execution on Windows or Linux: NVIDIA CUDA-capable GPU, NVIDIA driver with CUDA Driver API, NVIDIA cuBLAS 12, and NVIDIA cuSOLVER 11
NeedsCompilation: yes
Packaged: 2026-08-29 06:34:48 UTC; Li
Author: Yaoxiang Li [aut, cre]
Maintainer: Yaoxiang Li <liyaoxiang@outlook.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:30:02 UTC

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Package bvarnet updated to version 1.0.3 with previous version 1.0.2 dated 2026-08-31

Title: Bayesian Estimation of Dynamic VAR Models using Stan
Description: Bayesian estimation of multilevel Vector Autoregression (VAR) models using Stan. Supports Gaussian, Binary, and Ordinal (adjacent category) outcome variables with random effects and customizable priors.
Author: Florian Metwaly [aut, cre, cph]
Maintainer: Florian Metwaly <f.j.metwaly@uva.nl>

Diff between bvarnet versions 1.0.2 dated 2026-08-31 and 1.0.3 dated 2026-09-10

 DESCRIPTION                            |    6 -
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 R/helpers.R                            |  152 +++++++++++++++++++++++---
 R/set_priors.R                         |    7 -
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 R/to_stan_data.R                       |    2 
 inst/doc/MCMC-Diagnostics.Rmd          |    2 
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 man/bvarnet-package.Rd                 |    2 
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 tests/testthat/test-prior-scaling.R    |    2 
 tests/testthat/test-sim_bvarnet.R      |    6 -
 tests/testthat/test-stan-likelihood.R  |only
 vignettes/MCMC-Diagnostics.Rmd         |    2 
 vignettes/MCMC-Diagnostics.Rmd.orig    |    2 
 27 files changed, 491 insertions(+), 111 deletions(-)

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New package AlleloBin with initial version 1.0.0
Package: AlleloBin
Title: A Shiny Application for Allele Binning in Microsatellite Markers
Version: 1.0.0
Description: Provides allele binning functionality for SSR/microsatellite markers using least-squares minimization (Idury & Cardon (1997) <doi:10.1101/gr.7.11.1104>). Includes a 'Shiny' application for interactive use, summary statistics, and visualization.
License: GPL-3
Encoding: UTF-8
Imports: shiny, readxl, stats, utils, openxlsx
Suggests: testthat (>= 3.0.0), roxygen2
URL: https://github.com/vpprasanth/AlleloBin
BugReports: https://github.com/vpprasanth/AlleloBin/issues
NeedsCompilation: no
Packaged: 2026-08-29 08:07:51 UTC; vppra
Author: VP Prasanth [aut, cre], Subhash Chandra [aut], DA Hoisington [aut], B Jayashree [aut]
Maintainer: VP Prasanth <prasanth.stat@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:10:02 UTC

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New package agriPAM with initial version 0.1.0
Package: agriPAM
Title: Agricultural Policy Analysis Matrix Toolkit
Version: 0.1.0
Description: Builds and analyses Policy Analysis Matrices ('PAMs') for agricultural production systems. Computes private and social profitability, policy transfers, the domestic resource cost ratio, nominal protection coefficients for outputs and inputs, the effective protection coefficient, the private cost ratio, the profitability coefficient, subsidy ratios, and social cost-benefit ratios. Supports itemised farm budgets, parity prices, grouped analysis, deterministic sensitivity analysis, switching values, and correlated Monte Carlo simulation. Methods follow Monke and Pearson (1989, ISBN:0801419530) and the Food and Agriculture Organization of the United Nations (2007, ISBN:9789251057476).
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: graphics, grDevices, stats, utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Classification/JEL: Q12, Q18
NeedsCompilation: no
Packaged: 2026-08-29 20:12:24 UTC; majum
Author: Chiranjit Mazumder [aut, cre], Himadri Sekhar Roy [aut], Utkarsh Tiwari [aut], Pramit Pandit [aut], Bikramjeet Ghose [aut]
Maintainer: Chiranjit Mazumder <majumder.chira@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:30:09 UTC

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New package aanova with initial version 1.0.1
Package: aanova
Title: Robust Ecological and Fisheries Data Analysis and Visualization
Version: 1.0.1
Description: A comprehensive statistical and visualization toolkit tailored for fisheries science, stock assessment workflows, and aquatic ecology. It provides streamlined wrappers for univariate and factorial ANOVA, ANCOVA, MANOVA, generalized linear models (GLMs) for count data, non-linear morphometric regressions, custom correlation heatmaps, and integrated Mantel test network linkages.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: RColorBrewer, dplyr, emmeans, ggplot2, ggpubr, multcomp, tidyr, stringr, MASS, vegan
Suggests: knitr, multcompView, rmarkdown
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2026-08-29 20:52:15 UTC; User
Author: Ataher Ali [aut, cre]
Maintainer: Ataher Ali <ataher.cu.ms@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:30:15 UTC

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New package socketR with initial version 1.0.4
Package: socketR
Title: POSIX Socket Programming for R
Version: 1.0.4
Description: Provides a small, type-safe interface to POSIX sockets on Linux.
License: Apache License (>= 2)
Encoding: UTF-8
SystemRequirements: Linux operating system with POSIX socket APIs and C++17 compiler
Imports: R6
Suggests: arrow, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://sassoftware.github.io/socketr/
BugReports: https://github.com/sassoftware/socketr/issues
NeedsCompilation: yes
Packaged: 2026-08-28 16:18:47 UTC; edhell
Author: Eduardo Hellas [aut, cre], SAS [cph, fnd]
Maintainer: Eduardo Hellas <ehellas@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 08:30:02 UTC

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New package IndFarmCost with initial version 0.1.0
Package: IndFarmCost
Title: Indian Farm Cost Concepts for Agricultural Economic Analysis
Version: 0.1.0
Description: Implements commonly used Indian farm cost concepts for agricultural economic analysis, including Cost A1, A2, B1, B2, C1, C2, and C3. Tools are provided to calculate cost concepts from farm-level input data, aggregate costs across groups, summarize distributions, compute returns and benefit-cost ratios, estimate cost of production and break-even values, decompose cost shares, conduct one-way sensitivity analysis, and visualize concept-wise costs. The implementation is designed for reproducible farm management and cost-of-cultivation studies.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-28 14:57:35 UTC; majum
Author: Chiranjit Mazumder [aut, cre], Mrinmoy Ray [aut], Utkarsh Tiwari [aut]
Maintainer: Chiranjit Mazumder <majumder.chira@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 08:30:08 UTC

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Package gamlss.dist updated to version 6.1-11 with previous version 6.1-1 dated 2023-08-23

Title: Distributions for Generalized Additive Models for Location Scale and Shape
Description: A set of distributions which can be used for modelling the response variables in Generalized Additive Models for Location Scale and Shape, Rigby and Stasinopoulos (2005), <doi:10.1111/j.1467-9876.2005.00510.x>. The distributions can be continuous, discrete or mixed distributions. Extra distributions can be created, by transforming, any continuous distribution defined on the real line, to a distribution defined on ranges 0 to infinity or 0 to 1, by using a 'log' or a 'logit' transformation respectively.
Author: Mikis Stasinopoulos [aut, cre, cph] , Robert Rigby [aut] , Calliope Akantziliotou [ctb], Vlasios Voudouris [ctb], Gillian Heller [ctb] , Fernanda De Bastiani [ctb] , Raydonal Ospina [ctb] , Nicoletta Motpan [ctb], Fiona McElduff [ctb], Majid Djennad [...truncated...]
Maintainer: Mikis Stasinopoulos <d.stasinopoulos@gre.ac.uk>

Diff between gamlss.dist versions 6.1-1 dated 2023-08-23 and 6.1-11 dated 2026-09-10

 gamlss.dist-6.1-1/gamlss.dist/R/plottingDist.R            |only
 gamlss.dist-6.1-11/gamlss.dist/DESCRIPTION                |   32 
 gamlss.dist-6.1-11/gamlss.dist/MD5                        |  283 ++---
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New package EpiQuestionR with initial version 0.1.1
Package: EpiQuestionR
Title: Questionnaire Analysis for Epidemiology and One Health Research
Version: 0.1.1
Description: Provides tools for the analysis of questionnaire and survey data in epidemiological and One Health research. The package supports data preparation, reliability assessment, exploratory factor analysis, Kaiser-Meyer-Olkin assessment, parallel analysis, visualization, reporting, and export of results using a consistent analysis workflow. The methods are based on established approaches to psychometric and multivariate analysis; see Kaiser (1974) <doi:10.1007/BF02291575>, Horn (1965) <doi:10.1007/BF02289447>, and Tabachnick and Fidell (2019, ISBN:9780134790541).
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.3.0)
Imports: ggplot2, Matrix, graphics, lavaan, psych, stats, generics, withr, tibble
Suggests: broom, broom.helpers, car, corrplot, covr, dplyr, DT, flextable, forcats, gt, gtsummary, haven, janitor, knitr, leaflet, ltm, MASS, mirt, MBESS, nnet, officer, plotly, purrr, readr, readxl, rlang, rmarkdown, semPlot, sf, shiny, shinydashboard, spdep, spelling, stringr, testthat (>= 3.0.0), tidyr, tmap, e1071, jsonlite, openxlsx, reshape2, scales, yaml
VignetteBuilder: knitr
URL: https://github.com/vinodhpmd/EpiQuestionR
BugReports: https://github.com/vinodhpmd/EpiQuestionR/issues
NeedsCompilation: no
Packaged: 2026-08-29 04:03:20 UTC; m
Author: Vinodh Kumar Obli Rajendran [aut, cre] , Keerthi Aaradhana [aut]
Maintainer: Vinodh Kumar Obli Rajendran <vinodhkumar.rajendran@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-10 09:00:18 UTC

More information about EpiQuestionR at CRAN
Permanent link

Package DEA readmission to version 1.0.0 with previous version 0.1-2 dated 2008-02-19

Title: Data Envelopment Analysis
Description: Nonparametric efficiency measurement by data envelopment analysis. Provides radial (Charnes-Cooper-Rhodes and Banker-Charnes-Cooper) technical efficiency under constant, variable, non-increasing and non-decreasing returns to scale, the slacks-based measure of Tone (2001), the additive model of Charnes and others (1985), and the directional distance function of Chambers, Chung and Fare (1996), all through one interface and one result object. Efficiency estimates are accompanied by peers, slacks, returns-to-scale classification, scale efficiency and the optimal multipliers, and by bias-corrected estimates and confidence intervals from the smoothed homogeneous bootstrap of Simar and Wilson (1998). Where prices are known, cost, revenue and Nerlovian profit efficiency separate the technical component from the allocative one; where they are not, cross-efficiency with the secondary goals of Doyle and Green (1994) ranks units that a self-appraisal leaves tied. This package succeeds the arch [...truncated...]
Author: David Bernstein [aut, cre] , Zuleyka Diaz-Martinez [aut], Jose Fernandez-Menendez [aut]
Maintainer: David Bernstein <davebernstein1@gmail.com>

This is a re-admission after prior archival of version 0.1-2 dated 2008-02-19

Diff between DEA versions 0.1-2 dated 2008-02-19 and 1.0.0 dated 2026-09-10

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New package AHTauDesign with initial version 0.1.0
Package: AHTauDesign
Title: Truncation Time Selection for Average Hazard Analyses
Version: 0.1.0
Description: Implements a two-stage, design-informed framework for selecting the truncation time in time-to-event trials analyzed with the average hazard estimand, motivated by pediatric oncology settings with small samples, slow accrual, and limited follow-up. Stage 1 validates a clinically proposed truncation time against the planned design using simulation-based diagnostics for risk-set support, follow-up coverage, estimability, and estimator stability, classifying it as Pass, Borderline, or Fail. Stage 2 performs constrained optimization over a grid of candidate truncation times within a clinical-distance window, maximizing a utility subject to feasibility constraints, with an independent evaluation run to assess the selected time. Supports proportional-hazards, early-, and delayed-effect patterns, uniform accrual with administrative censoring, and calibrated exponential random censoring.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: survival, stats, utils
Suggests: ggplot2, knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-08-25 04:01:27 UTC; xinyueyue
Author: Xinyue Zhao [aut, cre], Haitao Pan [aut]
Maintainer: Xinyue Zhao <xinyuezhao27@gwu.edu>
Repository: CRAN
Date/Publication: 2026-09-10 08:40:08 UTC

More information about AHTauDesign at CRAN
Permanent link

Package manynet updated to version 2.3.4 with previous version 2.3.1 dated 2026-08-28

Title: Many Ways to Make, Manipulate, and Modify Myriad Networks
Description: Many tools for making, manipulating, and modifying many different types of networks. All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, on directed, multiplex, multimodal, signed, and other networks. The package includes functions for importing and exporting, creating and generating networks, modifying networks and node and tie attributes, and describing networks with sensible defaults.
Author: James Hollway [cre, aut, ctb] , Tomas Diviak [ctb], Henrique Sposito [ctb] , Christian Steglich [ctb], Alvaro Uzaheta [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

Diff between manynet versions 2.3.1 dated 2026-08-28 and 2.3.4 dated 2026-09-10

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More information about manynet at CRAN
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Package HAPTRACE updated to version 0.1.2 with previous version 0.1.1 dated 2026-07-30

Title: Haplotype-Based Tracking of Admixed Population for Breed Composition Estimation
Description: Simulate populations and track haplotypes over generations to evaluate population admixture. The 'HAPTRACE' supports customisable population parameters, including size, number of markers, mutation rates and recombination.
Author: Shweta Sahoo [aut, cre] , Sara de las Heras-Saldana [aut] , Julius H. J. van der Werf [aut] , Mohammad H. Ferdosi [aut]
Maintainer: Shweta Sahoo <queryhap01@gmail.com>

Diff between HAPTRACE versions 0.1.1 dated 2026-07-30 and 0.1.2 dated 2026-09-10

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More information about HAPTRACE at CRAN
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Package GerminaR updated to version 2.1.7 with previous version 2.1.6 dated 2025-10-21

Title: Indices and Graphics for Assess Seed Germination Process
Description: A collection of different indices and visualization techniques for evaluate the seed germination process in ecophysiological studies (Lozano-Isla et al. 2019) <doi:10.1111/1440-1703.1275>.
Author: Flavio Lozano-Isla [aut, cre] , Omar Benites Alfaro [aut] , Marcelo F. Pompelli [aut, ths] , Denise Garcia de Santana [aut], Marli A. Ranal [aut], Federal University of Pernambuco [cph] , Federal Rural University of Pernambuco [cph] , Inkaverse [ctb]
Maintainer: Flavio Lozano-Isla <flozanoisla@gmail.com>

Diff between GerminaR versions 2.1.6 dated 2025-10-21 and 2.1.7 dated 2026-09-10

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 GerminaR-2.1.7/GerminaR/DESCRIPTION                                                        |   13 
 GerminaR-2.1.7/GerminaR/MD5                                                                |   98 
 GerminaR-2.1.7/GerminaR/NAMESPACE                                                          |   50 
 GerminaR-2.1.7/GerminaR/NEWS.md                                                            |  249 
 GerminaR-2.1.7/GerminaR/R/GerminaQuant.R                                                   |    2 
 GerminaR-2.1.7/GerminaR/R/ger_summary.R                                                    |   16 
 GerminaR-2.1.7/GerminaR/README.md                                                          |   12 
 GerminaR-2.1.7/GerminaR/build/vignette.rds                                                 |binary
 GerminaR-2.1.7/GerminaR/inst/CITATION                                                      |    2 
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 GerminaR-2.1.7/GerminaR/man/ger_CVG.Rd                                                     |   50 
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 GerminaR-2.1.7/GerminaR/man/ger_GRS.Rd                                                     |   52 
 GerminaR-2.1.7/GerminaR/man/ger_GSP.Rd                                                     |   50 
 GerminaR-2.1.7/GerminaR/man/ger_MGR.Rd                                                     |   64 
 GerminaR-2.1.7/GerminaR/man/ger_MGT.Rd                                                     |   70 
 GerminaR-2.1.7/GerminaR/man/ger_SDG.Rd                                                     |   50 
 GerminaR-2.1.7/GerminaR/man/ger_SYN.Rd                                                     |   72 
 GerminaR-2.1.7/GerminaR/man/ger_UNC.Rd                                                     |   70 
 GerminaR-2.1.7/GerminaR/man/ger_VGT.Rd                                                     |   50 
 GerminaR-2.1.7/GerminaR/man/ger_boxp.Rd                                                    |  146 
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 GerminaR-2.1.7/GerminaR/man/osmp.Rd                                                        |   54 
 GerminaR-2.1.7/GerminaR/man/prosopis.Rd                                                    |   56 
 GerminaR-2.1.7/GerminaR/man/reexports.Rd                                                   |   32 
 GerminaR-2.1.7/GerminaR/man/rep_row.Rd                                                     |   38 
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More information about GerminaR at CRAN
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