Sat, 24 Oct 2026

Package yamlet updated to version 1.4.0 with previous version 1.3.4 dated 2026-03-11

Title: Versatile Curation of Table Metadata
Description: A YAML-based mechanism for working with table metadata. Supports compact syntax for creating, modifying, viewing, exporting, importing, displaying, and plotting metadata coded as column attributes. The 'yamlet' dialect is valid 'YAML' with defaults and conventions chosen to improve readability. See ?yamlet, ?decorate, ?modify, ?io_csv, and ?ggplot.decorated.
Author: Tim Bergsma [aut, cre]
Maintainer: Tim Bergsma <bergsmat@gmail.com>

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Package sure updated to version 0.3.1 with previous version 0.2.0 dated 2017-09-19

Title: Surrogate Residuals for Ordinal and General Regression Models
Description: An implementation of the surrogate approach to residuals and diagnostics for ordinal and general regression models; for details, see Liu and Zhang (2018) <doi:10.1080/01621459.2017.1292915> and Greenwell et al. (2018) <doi:10.32614/RJ-2018-004>. These residuals can be used to construct standard residual plots for model diagnostics (e.g., residual-vs-fitted value plots, residual-vs-covariate plots, Q-Q plots, etc.). The package also provides 'plot' methods for producing standard diagnostic plots using lightweight base R graphics (via 'tinyplot'). The package currently supports cumulative link models from packages 'MASS', 'ordinal', 'rms', and 'VGAM', binary and other generalized linear models fit with 'glm', and multinomial models or general classifiers via a matrix of predicted class probabilities.
Author: Brandon Greenwell [aut, cre], Andrew McCarthy [aut], Bradley Boehmke [aut], Liz Glaser [ctb]
Maintainer: Brandon Greenwell <greenwell.brandon@gmail.com>

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Package stratifyR updated to version 2.0-4 with previous version 2.0-3 dated 2026-10-17

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 Dynamic Programming (DP) solver of Reddy and Khan (2020), which is globally optimal for the fitted distribution, as the default. It adds two fast derivative-free solvers, a multi-start 'COBYLA' solver and a two-phase global solver that couples 'DIRECT-L' with 'BOBYQA' refinement, and an exact solver that runs dynamic programming on the sorted data and returns the partition with the smallest empirical Neyman cost. It also provides cost-constrained allocation with unequal per-stratum costs, a desi [...truncated...]
Author: Karuna G. Reddy [aut, cre] , M. G. M. Khan [aut]
Maintainer: Karuna G. Reddy <karuna.reddy@auckland.ac.nz>

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Package pslr updated to version 1.2.2 with previous version 1.2.1 dated 2026-09-14

Title: Public Suffix List Engine
Description: A focused implementation of the Public Suffix List (PSL). Bundles a reproducible, pinned PSL snapshot and implements the official prevailing-rule algorithm to answer public-suffix (eTLD) and registrable-domain (eTLD+1) queries. Distinguishes ICANN and PRIVATE rule sections, accepts Unicode and ASCII hostnames via 'punycoder' canonicalization, and supports an explicit, validated offline refresh path. The matcher is compiled with 'cpp11' and requires no external system library. Used as the PSL engine by the 'rurl' package.
Author: Bart Turczynski [aut, cre, cph]
Maintainer: Bart Turczynski <bartek@turczynski.pl>

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Package enrollcast updated to version 0.2.0 with previous version 0.1.0 dated 2026-08-26

Title: Project School Enrollment with Grade Progression Ratios
Description: Projects school enrollment using the cohort survival / grade progression ratio method described in Webster (1970) <doi:10.1080/00220973.1970.11011238>, implemented as a matrix projection. Works at any level of aggregation and any number of grades. Provides functions to compute progression ratios from historical grade-level enrollment and to project future enrollment forward an arbitrary horizon.
Author: Rory Lawless [aut, cre, cph]
Maintainer: Rory Lawless <rory@rorylawless.com>

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Package contrast updated to version 0.25.0 with previous version 0.24.2 dated 2022-10-05

Title: A Collection of Contrast Methods
Description: One degree of freedom contrasts for 'lm', 'glm', 'gls', and 'geese' objects.
Author: Alan O'Callaghan [cre], Max Kuhn [aut], Steve Weston [aut], Jed Wing [aut], James Forester [aut], Thorn Thaler [aut]
Maintainer: Alan O'Callaghan <alan.ocallaghan@outlook.com>

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Package arrow updated to version 26.0.0 with previous version 25.0.1 dated 2026-08-23

Title: Integration to 'Apache' 'Arrow'
Description: 'Apache' 'Arrow' <https://arrow.apache.org/> is a cross-language development platform for in-memory data. It specifies a standardized language-independent columnar memory format for flat and hierarchical data, organized for efficient analytic operations on modern hardware. This package provides an interface to the 'Arrow C++' library.
Author: Neal Richardson [aut], Ian Cook [aut], Nic Crane [aut], Dewey Dunnington [aut] , Romain Francois [aut] , Jonathan Keane [aut, cre], Bryce Mecum [aut], Dragoș Moldovan-Gruenfeld [aut], Jeroen Ooms [aut], Jacob Wujciak-Jens [aut], Javier Luraschi [ctb], [...truncated...]
Maintainer: Jonathan Keane <jkeane@gmail.com>

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Package windsoraiR updated to version 0.1.3 with previous version 0.1.2 dated 2021-05-10

Title: Access the 'Windsor.ai' API
Description: Collect multichannel marketing data from sources such as Google analytics, Facebook Ads, and many others using the 'Windsor.ai' API <https://windsor.ai/api-documentation/>.
Author: Octavian Corlade [aut, cre], Novica Nakov [aut], Windsor.ai [cph]
Maintainer: Octavian Corlade <octavian.corlade@gmail.com>

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Package TSGenerator updated to version 2.0.1 with previous version 2.0.0 dated 2026-10-21

Title: 'Copernicus' HR-VPP Vegetation Time-Series Processing
Description: Provides tools for acquiring, extracting, quality-assessing, and analysing vegetation time series derived from 'Copernicus' High Resolution Vegetation Phenology and Productivity (HR-VPP) products. Supports Seasonal Trajectories (ST) and Vegetation Phenology and Productivity (VPP) products through native R access to 'WEkEO', geospatial processing, product-quality assessment, temporal completeness analysis, missingness modelling, and integrated graphical workflows. Selected functions from 'TSGenerator' 1.x are retained to support migration and legacy workflows.
Author: Alexey Valero-Jorge [aut, cre] , M. Auxiliadora Casterad Seral [aut] , Jose-Tomas Alcala Nalvaiz [aut]
Maintainer: Alexey Valero-Jorge <avalero@cita-aragon.es>

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Package Rduckhts updated to version 2.0.1.0.1.0 with previous version 2.0.0.0.1.9 dated 2026-10-20

Title: 'DuckDB' High Throughput Sequencing File Formats Reader Extension
Description: Bundles the 'duckhts' 'DuckDB' extension for reading High Throughput Sequencing file formats with 'DuckDB'. The 'DuckDB' C extension API <https://duckdb.org/docs/stable/clients/c/api> and its 'htslib' dependency are compiled from vendored sources during package installation. James K Bonfield and co-authors (2021) <doi:10.1093/gigascience/giab007>. VariantKey / RegionKey support follows Nicola Asuni (2018) <doi:10.1101/473744>.
Author: Sounkou Mahamane Toure [aut, cre], Ryan Ward [aut] , Nurture Bio [cph] , James K Bonfield, John Marshall,Petr Danecek ,Heng Li , Valeriu Ohan, Andrew Whitwham,Thomas Keane , Robert M Davies [ctb] , DuckHTS Contributors [cph] ), RBCFTools Authors [cph [...truncated...]
Maintainer: Sounkou Mahamane Toure <sounkoutoure@gmail.com>

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Package PsychoMatic updated to version 1.0.1 with previous version 1.0.0 dated 2026-10-23

Title: Automated Psychometric Workflows and Reporting Tools
Description: Automates common psychometric workflows for applied researchers, including item descriptives, inter-item correlations, exploratory and confirmatory factor analysis, exploratory structural equation measurement models, reliability, psychometric network analysis, multi-group measurement invariance, and alignment optimization. Decision heuristics are informed by procedures such as parallel analysis (Horn, 1965, <doi:10.1007/BF02289447>), multivariate normality diagnostics (Mardia, 1970, <doi:10.1093/biomet/57.3.519>), measurement-invariance fit-change rules (Chen, 2007, <doi:10.1080/10705510701301834>), and alignment optimization (Asparouhov and Muthen, 2014, <doi:10.1080/10705511.2014.919210>), among others. Results can be returned as structured R objects and exported as bilingual reports for transparent analytical documentation.
Author: Jose Gamarra-Moncayo [aut, cre]
Maintainer: Jose Gamarra-Moncayo <gamarramoncayoj@gmail.com>

Diff between PsychoMatic versions 1.0.0 dated 2026-10-23 and 1.0.1 dated 2026-10-24

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Package newmark updated to version 1.9.0 with previous version 1.3.0 dated 2026-07-16

Title: Uncertainty Analysis in Dynamic Site and Slope Response
Description: Estimates the seismic response of sites and slopes from the results of a seismic hazard analysis. For a site, it computes the fundamental period of the soil profile and the amplification of spectral acceleration. For a slope, it computes the fundamental period, the earthquake-induced displacement, and the pseudostatic coefficient that keeps a selected quantile of the displacement within a given limit. Uncertainty in the soil profile and in the ground motion is represented by Monte Carlo samples. Every result is reported with its representative value, its applicable quantiles or dispersion, and the population or conditioning to which it refers.
Author: Alejandro Verri Kozlowski [aut, cre, cph]
Maintainer: Alejandro Verri Kozlowski <averri@fi.uba.ar>

Diff between newmark versions 1.3.0 dated 2026-07-16 and 1.9.0 dated 2026-10-24

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Package FastRet updated to version 1.5.2 with previous version 1.3.0 dated 2025-12-17

Title: Retention Time Prediction in Liquid Chromatography
Description: A framework for predicting retention times in liquid chromatography. Users can train custom models for specific chromatography columns, predict retention times using existing models, or adjust existing models to account for altered experimental conditions. The provided functionalities can be accessed either via the R console or via a graphical user interface. For details see Fadil et al. (2026) <doi:10.1021/acs.jcim.6c01344>. Related work: Bonini et al. (2020) <doi:10.1021/acs.analchem.9b05765>.
Author: Tobias Schmidt [aut, cre, cph] , Christian Amesoeder [aut, cph] , Marian Schoen [aut, cph], Fadi Fadil [aut, cph] , Katja Dettmer [aut, cph] , Peter Oefner [ths, cph]
Maintainer: Tobias Schmidt <tobias.schmidt331@gmail.com>

Diff between FastRet versions 1.3.0 dated 2025-12-17 and 1.5.2 dated 2026-10-24

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Package origin updated to version 1.2.2 with previous version 1.2.1 dated 2026-01-18

Title: Explicitly Qualifying Namespaces by Automatically Adding 'pkg::' to Functions
Description: Automatically adding 'pkg::' to a function, i.e. mutate() becomes dplyr::mutate(). It is up to the user to determine which packages should be used explicitly, whether to include base R packages or use the functionality on selected text, a file, or a complete directory. User friendly logging is provided in the 'RStudio' Markers pane. Lives in the spirit of 'lintr' and 'styler'. Can also be used for checking which packages are actually used in a project.
Author: Matthias Braun FKA Nistler [aut, cre]
Maintainer: Matthias Braun FKA Nistler <m_nistler@web.de>

Diff between origin versions 1.2.1 dated 2026-01-18 and 1.2.2 dated 2026-10-24

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Package tightenBlock updated to version 0.1.8 with previous version 0.1.7 dated 2023-12-15

Title: Tightens an Observational Block Design by Balanced Subset Matching
Description: Tightens an observational block design into a smaller design with either smaller or fewer blocks while controlling for covariates (Rosenbaum 2025 <doi:10.1080/00031305.2024.2393630>). The method uses fine balance, optimal subset matching (Rosenbaum, 2012 <doi:10.1198/jcgs.2011.09219>) and two-criteria matching (Zhang et al 2023 <doi:10.1080/01621459.2021.1981337>). The main function is tighten(). The suggested 'rrelaxiv' package for solving minimum cost flow problems: (i) derives from Bertsekas and Tseng (1988) <doi:10.1007/BF02288322>, (ii) is not available on CRAN due to its academic license, (iii) may be downloaded from GitHub at <https://github.com/josherrickson/rrelaxiv/>, (iv) is not essential to use the package.
Author: Paul Rosenbaum [aut, cre]
Maintainer: Paul Rosenbaum <rosenbaum@wharton.upenn.edu>

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Package norSTR updated to version 0.3.1 with previous version 0.2.1 dated 2025-05-05

Title: Forensic STR Map and Allele Frequencies
Description: A marker map for 51 forensic short tandem repeat (STR) markers, and allele frequency databases for Norway and several broader regional populations: Europe, Africa, South America, West Asia, Middle Asia, and East Asia. Developed and maintained for use at the Department of Forensic Sciences, Oslo, Norway.
Author: Magnus Dehli Vigeland [aut, cre]
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

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More information about norSTR at CRAN
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Package GRANDpriv updated to version 0.2.0 with previous version 0.1.3 dated 2025-08-22

Title: Graph Release with Assured Node Differential Privacy
Description: Implements a novel method for privatizing network data using differential privacy. Provides functions for generating synthetic networks based on LSM (Latent Space Model), applying differential privacy to network latent positions to achieve overall network privatization, and evaluating the utility of privatized networks through various network statistics. The privatize and evaluate functions support both LSM and RDPG (Random Dot Product Graph). For generating RDPG networks, users are encouraged to use the 'randnet' package <https://CRAN.R-project.org/package=randnet>. For more details, see the "proposed method" section of Liu, Bi, and Li (2025) <doi:10.48550/arXiv.2507.00402>.
Author: Suqing Liu [aut, cre], Xuan Bi [aut], Tianxi Li [aut]
Maintainer: Suqing Liu <liusuqing0123@uchicago.edu>

Diff between GRANDpriv versions 0.1.3 dated 2025-08-22 and 0.2.0 dated 2026-10-24

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Package CopulaSCR updated to version 1.0.4 with previous version 1.0.2 dated 2026-08-21

Title: Analysis of Semi-Competing Risks Data Using Copula-Based Models
Description: Simulate and analyze Semi-competing Risks Data using copula-based models. The Semi-competing Risks Data consist of a terminal event time and single or multiple intermediate event times. The marginal survival functions of these event times are estimated without parametric assumptions. The association parameters measuring dependency among these event times involving the copula model are yielded from solving a concordance estimating equations or maximizing a pseudo-likelihood function. Details can be found in the article by Tonghui Yu and Liming Xiang (2026) <doi:10.1093/biomtc/ujag087>.
Author: Tonghui Yu [aut, cre] , Binhui Zhang [aut]
Maintainer: Tonghui Yu <tonghui_yu@126.com>

Diff between CopulaSCR versions 1.0.2 dated 2026-08-21 and 1.0.4 dated 2026-10-24

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Package starburst updated to version 0.3.10 with previous version 0.3.9 dated 2026-07-22

Title: Seamless AWS Cloud Bursting for Parallel R Workloads
Description: A 'future' backend that enables seamless execution of parallel R workloads on 'Amazon Web Services' ('AWS', <https://aws.amazon.com>), including 'EC2' and 'Fargate'. 'staRburst' handles environment synchronization, data transfer, quota management, and worker orchestration automatically, allowing users to scale from local execution to 100+ cloud workers with a single line of code change.
Author: Scott Friedman [aut, cre]
Maintainer: Scott Friedman <help@starburst.ing>

Diff between starburst versions 0.3.9 dated 2026-07-22 and 0.3.10 dated 2026-10-24

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Package ErrorTracer updated to version 1.4.0 with previous version 1.3.1 dated 2026-08-19

Title: Bayesian Error Propagation and Forecast Uncertainty Decomposition
Description: Provides a full pipeline from regularized or standard regression models (elastic net, linear models, generalized linear models, random forests) to informed Bayesian priors, structured forecast uncertainty decomposition (parameter / environmental / residual, plus a temporal component when the model carries an autocorrelation term), and forecast shelf life analysis (the quantification of when a forecast becomes uninformative). Designed for ecological and genomic forecasting with climate or environmental covariates. Methods build on Bürkner (2017) <doi:10.18637/jss.v080.i01> for Bayesian regression via 'Stan', Friedman, Hastie, and Tibshirani (2010) <doi:10.18637/jss.v033.i01> for elastic net regularization, Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01> for random forests, and Vehtari, Gelman, and Gabry (2017) <doi:10.1007/s11222-016-9696-4> for leave-one-out cross-validation.
Author: Luis Javier Madrigal-Roca [aut, cre], John Kelly [aut]
Maintainer: Luis Javier Madrigal-Roca <madrigalrocalj@yahoo.com>

Diff between ErrorTracer versions 1.3.1 dated 2026-08-19 and 1.4.0 dated 2026-10-24

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 22 files changed, 984 insertions(+), 216 deletions(-)

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New package whence with initial version 0.1.0
Package: whence
Title: Explain Where a Number Came from in 'shiny' Apps
Version: 0.1.0
Description: Lets the viewer of a 'shiny' dashboard click a number, a row of a summary table or a bar of a 'ggplot2' plot, and see where it came from. The pipeline that makes the result is split into its steps. Each step is run in turn, and the number of rows after each step is recorded. The result is an attrition waterfall that shows how many rows each step removed, and what share of the rows that was, together with code that reproduces the result. The steps are found from the expression alone, so the pipeline does not need to be rewritten. The rows that contribute to a result, and the rows that a step removed, are found only when the viewer asks for them.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1.0)
Imports: htmltools, rlang, shiny (>= 1.7.0), utils
Suggests: dplyr, ggplot2, reactable, shinytest2, testthat (>= 3.0.0), tidyr, withr
URL: https://github.com/tenmeh/whence, https://tenmeh.github.io/whence/
BugReports: https://github.com/tenmeh/whence/issues
NeedsCompilation: no
Packaged: 2026-10-15 17:49:38 UTC; tchan
Author: Tanmay Chanda [aut, cre, cph]
Maintainer: Tanmay Chanda <tanmaychanda96@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:20:02 UTC

More information about whence at CRAN
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New package SurveySolutionsAPIv2 with initial version 0.1.2
Package: SurveySolutionsAPIv2
Title: Comprehensive API Access to Your 'Survey Solutions' Server Using 'httr2'
Version: 0.1.2
Description: A comprehensive suite of functions for interfacing with the 'Survey Solutions' APIs (<https://demo.mysurvey.solutions/apidocs/index.html> and <https://docs.mysurvey.solutions/>). It supports all the current POST, GET, and PATCH requests of the 'REST' API and extends its capabilities by integrating selected 'GraphQL' API queries and mutations when 'REST' API equivalents are not available. Designed for ease of use, it includes several convenience functions to streamline operations. The package ensures that data retrieved from the API is automatically transformed into a single, easy-to-use data frame or data table, optimizing it for subsequent analysis and processing. Additionally, it is specifically designed to facilitate seamless integration into 'shiny' applications, enhancing the interactive web application development experience. Built on the robust 'httr2' package, this version supersedes the previous 'httr'-based implementation. Recognizing the needs of large-scale data [...truncated...]
License: MIT + file LICENSE
URL: https://michael-cw.github.io/SurveySolutionsAPIv2/, https://github.com/michael-cw/SurveySolutionsAPIv2
BugReports: https://github.com/michael-cw/SurveySolutionsAPIv2/issues
Depends: R (>= 4.1.0)
Imports: cli, curl, data.table, dplyr, foreach, graphics, httr2, jsonlite, lubridate, readr, rlang, shiny, stats, stringr, susographql (>= 0.1.1), tidyjson, tidyr, withr, zip
Encoding: UTF-8
Language: en
Suggests: doFuture, DT, future, future.apply, ggplot2, knitr, progressr, readxl, rmarkdown, sf, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 18:01:47 UTC; michaelwild
Author: Michael Wild [aut, cre, cph]
Maintainer: Michael Wild <michael.wild@me.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:20:13 UTC

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New package soilwatR with initial version 0.1.1
Package: soilwatR
Title: Simulation of Soil Water Flow Based on Darcy's Law
Version: 0.1.1
Description: Provides a simple model to simulate soil water content and water flux changes at multiple soil depths. Calculations mainly follow Allen et al. (1998, ISBN:92-5-104219-5) and Teh (2017, ISBN:9789673447626).
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: dplyr, ggplot2, magrittr, rlang, stringr, tidyr
Suggests: ggpubr, testthat (>= 3.0.0)
Depends: R (>= 4.0)
NeedsCompilation: no
Packaged: 2026-10-15 16:23:27 UTC; liumg
Author: Minguo Liu [aut, cre]
Maintainer: Minguo Liu <liumg@nwafu.edu.cn>
Repository: CRAN
Date/Publication: 2026-10-24 16:10:02 UTC

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New package robotstxtr with initial version 0.3.1
Package: robotstxtr
Title: Engine-Aware 'robots.txt' Policy with Google's Matcher Algorithm
Version: 0.3.1
Language: en-US
Description: Evaluates whether URLs may be crawled according to 'robots.txt' rules. A versioned engine-aware facade keeps neutral fetch evidence, per-engine status policy, robots product tokens, and matcher capabilities separate, returning explicit non-decisions when policy is undocumented or a matcher is unavailable. The available matcher is a bundled, upstream-test-validated snapshot of Google's open-source C++ 'robots.txt' matcher, preserving 'Googlebot' behavior. Fetches use a deterministic, conservative policy built on 'httr2', with fetch origins constructed by 'rurl'. All network access in tests, examples, and vignettes is mocked or served locally, so no internet connection is required to install, test, or check the package. This matcher derives from Google's 'robotstxt' project <https://github.com/google/robotstxt>, distributed under the Apache License 2.0; see the package NOTICE.
License: MIT + file LICENSE
Copyright: file inst/COPYRIGHTS
URL: https://bart-turczynski.gitlab.io/robotstxtr/, https://gitlab.com/bart-turczynski/robotstxtr, https://bart-turczynski.r-universe.dev/robotstxtr
BugReports: https://gitlab.com/bart-turczynski/robotstxtr/-/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: httr2 (>= 1.2.0), rurl (>= 3.0.1)
LinkingTo: cpp11
SystemRequirements: C++17
Suggests: callr, httpuv, jsonlite, knitr, oysteR, rmarkdown, rosv, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-10-15 14:04:24 UTC; bartturczynski
Author: Bart Turczynski [aut, cre, cph] , Google LLC [cph]
Maintainer: Bart Turczynski <bartek@turczynski.pl>
Repository: CRAN
Date/Publication: 2026-10-24 16:10:08 UTC

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New package p3d with initial version 0.1.0
Package: p3d
Title: Interactive 3D Visualization of p-Value Surfaces
Version: 0.1.0
Description: Provides interactive three-dimensional visualization of p-value surfaces for single-sample t-tests. Enables simultaneous exploration of effect size, sample size, and significance level, making the continuous nature of p-values and the moderating effect of sample size visually apparent. Includes both interactive ('rgl', 'plotly') and static (persp()) rendering options. The p-value surface is based on the approach of Infanger and Schmidt-Trucksäss (2019) <doi:10.1002/sim.8293>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://github.com/ahmetkutuk1/p3d, https://ahmetkutuk1.github.io/p3d/
BugReports: https://github.com/ahmetkutuk1/p3d/issues
Suggests: knitr, plotly, rgl, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 4.1.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 18:17:59 UTC; Ahmet
Author: Ahmet Kutuk [aut, cre]
Maintainer: Ahmet Kutuk <ahmetkutuk@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:30:02 UTC

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New package OptimalFactor with initial version 1.5.0
Package: OptimalFactor
Title: Item Selection in Factor Analysis by Boosting and Specification Search
Version: 1.5.0
Date: 2026-10-05
Description: Provides an iterative optimization algorithm for exploratory and confirmatory factor analysis that follows a boosting approach inspired by machine learning. It uses a composite fit index whose weights adapt to the degrees of freedom and the sample size, following Kenny and McCoach (2003) <doi:10.1207/S15328007SEM1003_1> and Shi, Lee and Maydeu-Olivares (2019) <doi:10.1177/0013164418783530>. It detects and removes problematic items (Heywood cases, cross-loadings, low loadings) with greedy or global search strategies, checks interfactor correlations, and supports ordinal data with WLSMV estimation and several rotation methods. A heuristic specification search for confirmatory models (MacCallum, 1986 <doi:10.1037/0033-2909.100.1.107>) explores move, drop and covariance operations across seed configurations. It also evaluates the resampling stability of the item selection, the recovery of a known or theoretical structure, and offers an optional conceptual analysis of remo [...truncated...]
License: GPL (>= 3)
URL: https://github.com/jventural/OptimalFactor, https://jventural.github.io/OptimalFactor/
BugReports: https://github.com/jventural/OptimalFactor/issues
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: lavaan, psych, dplyr, tidyr, ggplot2, stringr, parallel, stats, utils
Suggests: testthat (>= 3.0.0), httr, jsonlite, R.utils, knitr, rmarkdown, semTools
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 17:35:48 UTC; PC
Author: Jose Ventura-Leon [aut, cre]
Maintainer: Jose Ventura-Leon <jventuraleon@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:30:08 UTC

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New package MAC.address with initial version 0.1.0
Package: MAC.address
Title: Find, Validate and Identify Device MAC Addresses
Version: 0.1.0
Description: Tools to work with MAC (Media Access Control) addresses: list the MAC addresses of the local network interfaces and of the neighbors in the ARP cache on Linux, macOS and Windows, extract MAC addresses from free text, validate and normalize their notation, check the multicast and locally administered bits, generate random addresses, derive IPv6 interface identifiers (modified EUI-64), and identify the manufacturer using the public IEEE (Institute of Electrical and Electronics Engineers) MA-L, MA-M and MA-S registries <https://regauth.standards.ieee.org/standards-ra-web/pub/view.html#registries>.
URL: https://github.com/EnriquePH/mac-address, https://enriqueph.github.io/mac-address/
BugReports: https://github.com/EnriquePH/mac-address/issues
Depends: R (>= 4.0.0)
Imports: stats, tools, utils
Suggests: curl, testthat (>= 3.0.0), withr
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-10-14 19:39:39 UTC; eph
Author: Enrique Perez Herrero [aut, cre]
Maintainer: Enrique Perez Herrero <eph.project1500@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:30:15 UTC

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New package ltvlms with initial version 0.1.0
Package: ltvlms
Title: Linear Time-Variant Logistic Models with a Shape Parameter
Version: 0.1.0
Description: Evaluates and fits the Linear Time-Variant Logistic Model with Shape Parameter (LTVLMS) for dynamic growth processes. The model combines a linearly time-varying growth rate with a shape parameter for asymmetric trajectories and includes numerically stable prediction utilities. Methodological details are provided by Betrouni and Kernane (2026) "Linear Time-Varying Logistic Model With Shape Parameter for Dynamic Epidemic Modeling" <doi:10.1155/jama/4928447>.
Depends: R (>= 4.0.0)
License: MIT + file LICENSE
Copyright: Package code and documentation are copyright the listed authors. The included UNAIDS-derived datasets remain subject to the UNAIDS terms identified in inst/COPYRIGHTS.
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-15 18:03:31 UTC; bander
Author: Redouane Betrouni [aut] , Tewfik Kernane [aut] , Bander Hussein [aut, cre]
Maintainer: Bander Hussein <bshussein@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:20:08 UTC

More information about ltvlms at CRAN
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Package gputools readmission to version 2.1.0 with previous version 1.1 dated 2016-10-26

Title: GPU Drop-Ins for Statistics on Wide Data
Description: GPU versions of base R statistics for data with many variables, using the NVIDIA 'CUDA' toolkit: correlation matrices (Pearson, Spearman and Kendall) and their tests, the strongest correlated pairs among tens of thousands of variables without forming the matrix, association scans with covariates as in expression quantitative trait loci studies (Shabalin 2012 <doi:10.1093/bioinformatics/bts163>), permutation tests with Westfall-Young maxT adjustment, distance matrices, hierarchical and k-means clustering, Granger causality tests, B-spline mutual information, principal components, and least-squares fits. Results agree with the base R functions they replace. Without 'CUDA' the package installs, and its functions explain how to get a 'CUDA' build. Described in Buckner et al. (2010) <doi:10.1093/bioinformatics/btp608>.
Author: Josh Buckner [aut, cre], Mark Seligman [aut], Fan Meng [aut], Justin Wilson [ctb]
Maintainer: Josh Buckner <nullsatz@gmail.com>

This is a re-admission after prior archival of version 1.1 dated 2016-10-26

Diff between gputools versions 1.1 dated 2016-10-26 and 2.1.0 dated 2026-10-24

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New package cdiscdata with initial version 0.2.0
Package: cdiscdata
Title: Versioned CDISC Standards Reference Data
Version: 0.2.0
Description: Provides versioned reference data for the standards of the Clinical Data Interchange Standards Consortium (CDISC) <https://www.cdisc.org/standards>: the CDISC Controlled Terminology (CT) for the Study Data Tabulation Model (SDTM) and the Analysis Data Model (ADaM); variable metadata for the SDTM model and for the families of the SDTM Implementation Guide (SDTMIG), the Standard for Exchange of Nonclinical Data Implementation Guide (SENDIG), and the ADaM Implementation Guide (ADaMIG); the Clinical Data Acquisition Standards Harmonization (CDASH) model and implementation guide; the Questionnaires, Ratings, and Scales (QRS) supplements; and the Define-XML schemas, written in the Extensible Markup Language (XML) Schema Definition (XSD) language, with Extensible Stylesheet Language Transformations (XSLT) stylesheets for them. A validity-date design stores every historical CT version compactly, without duplicating rows. Intended as a shared data dependency for pharmaverse-aligned packag [...truncated...]
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
Suggests: testthat (>= 3.0.0), xml2, withr, covr, pkgdown, knitr, rmarkdown, callr
LazyData: true
LazyDataCompression: xz
Encoding: UTF-8
Language: en-US
URL: https://github.com/humanpred/cdiscdata, https://humanpred.github.io/cdiscdata/
BugReports: https://github.com/humanpred/cdiscdata/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 21:46:07 UTC; bill
Author: Bill Denney [aut, cre] , Clinical Data Interchange Standards Consortium [cph] ), Lex Jansen [cph] ), National Cancer Institute Enterprise Vocabulary Services [dtc] )
Maintainer: Bill Denney <wdenney@humanpredictions.com>
Repository: CRAN
Date/Publication: 2026-10-24 16:40:09 UTC

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New package boltzrosen with initial version 0.1.0
Package: boltzrosen
Title: Boltzmann-Rosenbrock Distribution and Associated Copula
Version: 0.1.0
Description: Provides the probability density function, cumulative distribution function, quantile function, and random sample generation for the Boltzmann-Rosenbrock distribution. The package also includes functions for the marginal distributions of X and Y, the mutual information between the two components, and the copula associated with the distribution, including its density, distribution function, and sampling routines. The use of Boltzmann distribution in objective functions, such as the Rosenbrock function, is described in Segovia-Domínguez, I., Valdez, S.I. and Hernández-Aguirre, A. (2014) <doi:10.5220/0005079902510258>.
License: GPL-3
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-15 14:48:35 UTC; rogel
Author: Rogelio Salinas Gutierrez [aut, cre, cph] , Jhon Daniel Aguilar Payares [aut, cph] , Alejandro Fausto Cortes Salinas [aut, cph] , Sofia Isabel Soledad Limon [aut, cph] , Rogelio Emiliano Salinas Gutierrez [aut, cph] , Juan Pablo Salinas Munoz [aut, c [...truncated...]
Maintainer: Rogelio Salinas Gutierrez <rogelio.salinas@edu.uaa.mx>
Repository: CRAN
Date/Publication: 2026-10-24 16:10:14 UTC

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New package paretoinfer with initial version 0.1.0
Package: paretoinfer
Title: Sequential Identification of Approximately Pareto-Optimal Alternatives under Noise
Version: 0.1.0
Description: Sequential identification of epsilon-Pareto-optimal alternatives among a finite set with noisy, possibly correlated objectives. Simultaneous anytime-valid confidence sequences for every objective of every alternative (Waudby-Smith and Ramdas, 2024, <doi:10.1093/jrsssb/qkad009>) certify, at any time, which alternatives are epsilon-dominated and which are not, report the estimated frontier, the plausible Pareto set and the certified-dominated set, propose the next alternative to evaluate, and record an auditable result contract.
License: GPL (>= 3)
URL: https://castlaboratory.github.io/paretoinfer/, https://github.com/castlaboratory/paretoinfer
BugReports: https://github.com/castlaboratory/paretoinfer/issues
Encoding: UTF-8
Language: en-GB
Depends: R (>= 4.1)
Imports: cli (>= 3.6.0), generics, ggplot2 (>= 3.5.0), rlang (>= 1.1.0), seqbench (>= 0.1.0), stats, tibble (>= 3.2.0), utils
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 10:47:31 UTC; leite
Author: Andre Leite [aut, cre] , Raydonal Ospina [aut] , Cristiano Ferraz [aut]
Maintainer: Andre Leite <leite@castlab.org>
Repository: CRAN
Date/Publication: 2026-10-24 15:50:01 UTC

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Package metabodeconplus updated to version 0.22.4 with previous version 0.22.0 dated 2026-08-09

Title: Deconvolution, Alignment and Model Fitting of 1d NMR Spectra
Description: An integrated framework for deconvolution, alignment and postprocessing of 1-dimensional (1d) nuclear magnetic resonance (NMR) spectra, extended with end-to-end model fitting that turns the resulting matrix of aligned signal integrals into classification models. The deconvolution part uses the algorithm described in Koh et al. (2009) <doi:10.1016/j.jmr.2009.09.003>. The alignment part is based on functions from the 'speaq' package, described in Beirnaert et al. (2018) <doi:10.1371/journal.pcbi.1006018> and Vu et al. (2011) <doi:10.1186/1471-2105-12-405>. A detailed description and evaluation of an early version of the package can be found in Haeckl et al. (2021) <doi:10.3390/metabo11070452>. The current package, including the model fitting workflow, is described in Schmidt et al. (2026) <doi:10.3390/metabo16090604>. 'metabodeconplus' is the actively developed successor to the 'metabodecon' package and introduces backwards-incompatible API changes.
Author: Tobias Schmidt [aut, cre, cph], Martina Haeckl [aut, cph], Yanren Linda Hu [ctb], Wolfram Gronwald [aut, cph]
Maintainer: Tobias Schmidt <tobias.schmidt331@gmail.com>

Diff between metabodeconplus versions 0.22.0 dated 2026-08-09 and 0.22.4 dated 2026-10-24

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Package gmeans updated to version 0.3.0 with previous version 0.2.0 dated 2026-09-11

Title: G-means Clustering
Description: Gaussian-means (G-means) clustering is a clustering algorithm that extends the k-means algorithm by automatically determining the number of clusters.
Author: Maximilian Muecke [aut, cre]
Maintainer: Maximilian Muecke <muecke.maximilian@gmail.com>

Diff between gmeans versions 0.2.0 dated 2026-09-11 and 0.3.0 dated 2026-10-24

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Package Analitica updated to version 2.3.0 with previous version 2.2.0 dated 2025-12-03

Title: Exploratory Data Analysis, Group Comparison Tools, and Other Procedures
Description: Provides a comprehensive set of tools for descriptive statistics, graphical data exploration, outlier detection, homoscedasticity testing, and multiple comparison procedures. Includes manual implementations of Levene's test, Bartlett's test, and the Fligner-Killeen test, as well as post hoc comparison methods such as Tukey, Scheffé, Games-Howell, Brunner-Munzel, and others. This version introduces two new procedures: the Jonckheere-Terpstra trend test and the Jarque-Bera test with Glinskiy's (2024) correction. Designed for use in teaching, applied statistical analysis, and reproducible research. Additionally you can find a post hoc Test Planner, which helps you to make a decision on which procedure is most suitable.
Author: Carlos Jimenez-Gallardo [aut, cre]
Maintainer: Carlos Jimenez-Gallardo <carlos.jimenez@ufrontera.cl>

Diff between Analitica versions 2.2.0 dated 2025-12-03 and 2.3.0 dated 2026-10-24

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Package trend updated to version 1.1.10 with previous version 1.1.9 dated 2026-10-12

Title: Non-Parametric Trend Tests and Change-Point Detection
Description: The analysis of environmental data often requires the detection of trends and change-points. This package includes tests for trend detection (Cox-Stuart Trend Test, Mann-Kendall Trend Test, (correlated) Hirsch-Slack Test, partial Mann-Kendall Trend Test, multivariate (multisite) Mann-Kendall Trend Test, (Seasonal) Sen's slope, partial Pearson and Spearman correlation trend test), change-point detection (Lanzante's test procedures, Pettitt's test, Buishand Range Test, Buishand U Test, Standard Normal Homogeinity Test), detection of non-randomness (Wallis-Moore Phase Frequency Test, Bartels rank von Neumann's ratio test, Wald-Wolfowitz Test) and the two sample Robust Rank-Order Distributional Test.
Author: Thorsten Pohlert [aut, cre]
Maintainer: Thorsten Pohlert <thorsten.pohlert@gmx.de>

Diff between trend versions 1.1.9 dated 2026-10-12 and 1.1.10 dated 2026-10-24

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New package DistLagHet with initial version 0.1.0
Package: DistLagHet
Title: Treatment Effect Estimation in Complex Designs
Version: 0.1.0
Description: Implements estimation methods for treatment effects in complex designs under parallel-trends assumptions. Based on the methodology of de Chaisemartin and D'Haultfoeuille (2025) <doi:10.48550/arXiv.2508.07808>. Provides three model specifications: base model with K lags, full dynamics model using all available periods, and interactions model with lag interaction terms. Includes C++ optimizations for faster bootstrap estimation.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: MASS, Rcpp (>= 1.0.0)
LinkingTo: Rcpp, RcppEigen
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-10-15 09:34:12 UTC; henrifabre
Author: Clement de Chaisemartin [aut], Xavier D'Haultfoeuille [aut], Henri Fabre [cre, ctb]
Maintainer: Henri Fabre <henri.fabre@ensae.fr>
Repository: CRAN
Date/Publication: 2026-10-24 11:50:07 UTC

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New package agriTradeRisk with initial version 0.1.0
Package: agriTradeRisk
Title: Agricultural Export Competitiveness and Risk Analysis
Version: 0.1.0
Description: An integrated and reproducible workflow for analysing the competitiveness and risk of agricultural and horticultural exports. It measures destination and product concentration (Herfindahl-Hirschman, entropy and equivalent-number indices), revealed comparative advantage (Balassa, 1965) <doi:10.1111/j.1467-9957.1965.tb00050.x> and its symmetric form, relative unit values, and constant market share decomposition of export growth. It tests vertical price transmission between export and domestic prices with Engle-Granger cointegration (Engle and Granger, 1987) <doi:10.2307/1913236> using MacKinnon (2010) critical values and symmetric or asymmetric error correction models. It quantifies exchange-rate exposure of a multi-currency export portfolio (volatility, diversification ratio, risk contributions and value at risk), screens destination markets with composite entry-risk scores, and identifies risk-efficient destination mixes by mean-variance portfolio optimisation (Markowitz, 1 [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 3.5.0)
Imports: graphics, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 09:10:53 UTC; root
Author: Anbukkani Perumal [aut, cre, cph]
Maintainer: Anbukkani Perumal <anbueconomic@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 11:50:02 UTC

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New package agriEquity with initial version 0.1.0
Package: agriEquity
Title: Equity and Sustainability Assessment of Agricultural Subsidies
Version: 0.1.0
Description: An integrated framework for evaluating whether agricultural support measures reach smallholders, women farmers and resource-poor regions, and at what productivity and environmental cost. It provides survey-weighted benefit incidence analysis by landholding class, gender, region or income quantile; concentration, Kakwani and Reynolds-Smolensky progressivity measures (Kakwani, 1977) <doi:10.2307/2230485> with bootstrap confidence intervals; multi-dimensional equity scorecards with parity ratios and Theil decomposition of benefit inequality; effects of subsidies on income inequality and Foster-Greer-Thorbecke poverty (Foster, Greer and Thorbecke, 1984) <doi:10.2307/1913475>; budget-neutral reallocation of a subsidy budget under alternative allocation rules, including a welfare-optimal allocation that combines diminishing productivity returns, Atkinson (1970) <doi:10.1016/0022-0531(70)90039-6> inequality aversion and environmental damage costs; and productivity-equity-sus [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 3.5.0)
Imports: graphics, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 10:08:23 UTC; root
Author: Anbukkani Perumal [aut, cre, cph]
Maintainer: Anbukkani Perumal <anbueconomic@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 12:00:02 UTC

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Package proxymix updated to version 0.17.0 with previous version 0.16.0 dated 2026-10-08

Title: Gaussian Mixture Proxies for Densities and Characteristic Functions
Description: Fits multivariate Gaussian-mixture proxies to target distributions on real Euclidean space, given by a density, by samples, or by a characteristic function. Four fitting regimes are unified under one verb: (i) closed-form moment matching for a single component, (ii) classical expectation-maximisation when independent samples are available, (iii) importance-sampled expectation-maximisation that minimises the Kullback-Leibler divergence when the target can be evaluated point-wise but not (cheaply) sampled, and (iv) a least-squares fit to the characteristic function when only that is known, with numerical bounds on the Kolmogorov distance along one-dimensional projections. Closed-form Gaussian-mixture operators (density, sampling, marginalisation, conditioning, divergence) round out the toolkit. The conditioning operator drives multiple imputation of data missing at random, covering the multimodal and heteroscedastic cases a single-Gaussian model cannot represent. Implements the regime hi [...truncated...]
Author: Max Moldovan [aut, cre] , John van der Hoek [aut]
Maintainer: Max Moldovan <max.moldovan@gmail.com>

Diff between proxymix versions 0.16.0 dated 2026-10-08 and 0.17.0 dated 2026-10-24

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New package fpoValue with initial version 0.1.0
Package: fpoValue
Title: Farmer Producer Organisation Economics and Member Benefit Accounting
Version: 0.1.0
Description: Tools to determine when collective marketing, aggregation, grading and bulk input procurement through farmer producer organisations (FPOs) and agricultural cooperatives improve member-farmer returns. The package provides channel-level transaction cost accounting (transport, commissions, market fees, time, rejection and payment-delay costs), estimation of scale economies from consolidated transport, tiered bulk input discounts and grading premiums, break-even throughput and procurement-price analysis, and comparison of individual and collective marketing scenarios. Its core is a member-level distributional accounting framework that separates the total surplus generated by an FPO from the benefits actually received by farmers through prices, transaction cost savings, input savings and dividends, and summarises their distribution across members with Gini and concentration indices and farm-size group shares.
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
Depends: R (>= 3.5.0)
Imports: graphics
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-15 04:40:01 UTC; root
Author: Anbukkani Perumal [aut, cre, cph]
Maintainer: Anbukkani Perumal <anbueconomic@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 11:00:15 UTC

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New package controlledburn with initial version 0.3.1
Package: controlledburn
Title: Sparse Geometry Rasterization with Exact Coverage Fractions
Version: 0.3.1
Description: Rasterize polygon, line, and point geometry without materializing any pixel values. For polygons it computes exact coverage fractions for polygon-grid intersections, returning sparse tables: run-length encoded interior cells and individually weighted boundary cells. The scanline algorithm is O(perimeter) in both time and memory, using the scan line fill attributed to Wylie et al. (1967) <doi:10.1145/1465611.1465619>. Exact coverage fractions use the 'exactextract' algorithm by Daniel Baston, vendored from the 'exactextractr' package <doi:10.32614/CRAN.package.exactextractr>. Derived from the 'fasterize' package by Noam Ross.
License: Apache License (== 2.0)
Copyright: See file COPYRIGHTS
Encoding: UTF-8
LinkingTo: cpp11
Imports: wk
Suggests: geos, testthat (>= 3.0.0), knitr, rmarkdown, fasterize, terra, raster, ggplot2
URL: https://github.com/hypertidy/controlledburn
BugReports: https://github.com/hypertidy/controlledburn/issues
VignetteBuilder: knitr
Depends: R (>= 3.5)
NeedsCompilation: yes
Packaged: 2026-10-15 04:19:00 UTC; mdsumner
Author: Michael Sumner [aut, cre] , Noam Ross [aut] , EcoHealth Alliance [cph] , Jim Hester [ctb] , Daniel Baston [cph] ), ISciences, LLC [cph] )
Maintainer: Michael Sumner <mdsumner@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 11:00:21 UTC

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New package smak with initial version 0.1.0
Package: smak
Maintainer: Steven E. Pav <shabbychef@gmail.com>
Version: 0.1.0
Date: 2026-10-13
License: LGPL-3
Title: Scalable Model Averageing Kit
BugReports: https://github.com/shabbychef/smak/issues
Description: Supports frequentist model averaging on linear regression problems via the scalable method of Zhu et. al. (2022) <doi:10.1080/07350015.2022.2116442>. The scalable model averaging technique projects to singular vectors, performs one linear regression per singular vector, then combines the estimates to optimize either Mallows' criterion, or the jackknife estimate of error.
Depends: R (>= 4.0)
Imports: generics, methods, quadprog
Suggests: broom, testthat, knitr
URL: https://github.com/shabbychef/smak
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-14 21:54:30 UTC; spav
Author: Steven E. Pav [aut, cre]
Repository: CRAN
Date/Publication: 2026-10-24 09:20:02 UTC

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New package LMDT with initial version 0.1.0
Package: LMDT
Title: Local Manifold Dispersion Test for Heteroskedasticity
Version: 0.1.0
Description: Implements the Local Manifold Dispersion Test (LMDT) for detecting complex, non-linear, and high-dimensional heteroskedasticity in linear regression models. LMDT measures the spectral smoothness (Dirichlet energy) of robust log-dispersion residuals over a self-tuning k-nearest neighbors graph Laplacian, as formulated in Jabbar (2026). The test statistic is asymptotically distribution-free with respect to error kurtosis and accommodates high-dimensional covariates (p > 50) via Gavish-Donoho optimal hard thresholding and supervised metric learning.
License: GPL (>= 3)
URL: https://amjed-droid.github.io/LMDT/, https://github.com/amjed-droid/LMDT
BugReports: https://github.com/amjed-droid/LMDT/issues
Depends: R (>= 4.0.0)
Imports: stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-14 23:29:15 UTC; intel
Author: Ahmed Sattar Jabbar [aut, cre]
Maintainer: Ahmed Sattar Jabbar <ahmed.state.me@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 09:30:02 UTC

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New package LAGOtrials with initial version 1.1.0
Package: LAGOtrials
Title: Learn-as-You-Go Adaptive Trial Optimization
Version: 1.1.0
Description: Optimizes interventions for adaptive "Learn-As-you-GO" (LAGO) trials, in which the intervention package is updated between stages using accumulating data. Given data from completed stages, lago_optimization() fits the outcome model (via 'stats' generalized linear models or, for clustered designs, cluster-robust variance) and computes the cost-optimal recommended intervention for the next stage that is expected to reach a target mean outcome and/or a desired statistical power. get_confidence_set() constructs confidence sets for the optimal intervention, and visualize_cost() and lago_report() summarize the cost surface and results. Methods are described in Nevo, Lok and Spiegelman (2021) <doi:10.1214/20-aos1978> and Bing, Spiegelman, Nevo and Lok (2025) <doi:10.1093/biomtc/ujaf061>.
License: GPL-3
Copyright: This package bundles the D3 v7 library (inst/js/d3.v7.min.js), which is ISC-licensed and Copyright 2010-2023 Mike Bostock. See inst/COPYRIGHTS and inst/js/d3-LICENSE. All other code is Copyright the LAGO authors under GPL-3.
URL: https://correspondmerchant.github.io/LAGO-R-Package/, https://github.com/correspondMerchant/LAGO-R-Package
BugReports: https://github.com/correspondMerchant/LAGO-R-Package/issues
Encoding: UTF-8
LazyData: true
Imports: rje, NlcOptim, cli, bslib, shiny, ggplot2, shinyjs, Rcpp
LinkingTo: Rcpp
Suggests: testthat (>= 3.0.0), tibble, knitr, rmarkdown, jsonlite, spelling
VignetteBuilder: knitr
Depends: R (>= 2.10)
Language: en-US
NeedsCompilation: yes
Packaged: 2026-10-14 21:28:13 UTC; antebing
Author: Ante Bing [aut, cre], Minh Bui [aut], Jingyu Cui [aut], Mike Bostock [cph]
Maintainer: Ante Bing <abing@bu.edu>
Repository: CRAN
Date/Publication: 2026-10-24 09:10:02 UTC

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New package DoExp with initial version 0.1.0
Package: DoExp
Title: Design of Experiments with Hasse Diagrams and Anatomy Tables
Version: 0.1.0
Depends: R (>= 4.1.0)
Description: Constructs Hasse diagrams and anatomy tables from structural formulas and experimental data sets. Hasse diagrams may display sources of variation and their degrees of freedom for general experimental structures. For orthogonal designs, the package can also compute core matrices associated with quadratic forms for sums of squares and contributions to the expected mean squares. Anatomy tables display the degrees of freedom and A-efficiencies associated with the sources of variation.
License: GPL (>= 3)
Encoding: UTF-8
Imports: dplyr, ggplot2, knitr, psych, purrr, rlang, stringr, tibble, utils
Suggests: dae, patchwork, rmarkdown
NeedsCompilation: no
Packaged: 2026-10-14 22:32:07 UTC; Leo Peressim
Author: Leonardo Peressim [aut, cre] , Renata Sermarini [aut]
Maintainer: Leonardo Peressim <leonardoperessim@usp.br>
Repository: CRAN
Date/Publication: 2026-10-24 09:30:08 UTC

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New package tidyfault with initial version 0.1.0
Package: tidyfault
Title: Tidy Fault Tree Analysis
Version: 0.1.0
Description: Fault tree analysis with tidy data. Represent a fault tree as two tables, one of nodes (the top event, gates and basic events) and one of edges, so the whole workflow stays in ordinary data frames. Derive the Boolean equation of the top event, enumerate the truth table, and find minimal cut sets with the Method of Obtaining Cut Sets (MOCUS) algorithm of Fussell and Vesely (1972), implemented in 'R' and, by default, in C++ through 'Rcpp'. Evaluate thousands of binary or probabilistic scenarios in one vectorized call, put uncertainty intervals around the top-event probability, follow it over time, and rank which component fix lowers it most. Lay out and draw the tree with 'tidygraph', 'igraph' and 'ggplot2'. Methods follow the "Fault Tree Handbook" of Vesely, Goldberg, Roberts and Haasl (1981) <https://www.nrc.gov/docs/ML1007/ML100780465.pdf>. A 'Python' port with the same functions ships in the same repository.
URL: https://tidyfault.netlify.app, https://github.com/timothyfraser/tidyfault
BugReports: https://github.com/timothyfraser/tidyfault/issues
License: GPL-3
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1)
Imports: dplyr, ggplot2, graphics, igraph, methods, purrr, Rcpp, rlang, scales, stats, stringr, tibble, tidyr, tidygraph
LinkingTo: Rcpp
Suggests: ggraph, knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-10-14 20:12:31 UTC; tmf77
Author: Timothy Fraser [aut, cre, cph] , Jingyao Tong [aut, cph] , Cornell University [cph]
Maintainer: Timothy Fraser <tmf77@cornell.edu>
Repository: CRAN
Date/Publication: 2026-10-24 09:00:02 UTC

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New package RQK with initial version 1.0.0
Package: RQK
Title: Rational Quadratic Kriging
Version: 1.0.0
Description: Fits the rational quadratic kriging models of Song and Joseph (2026) <doi:10.48550/arXiv.2610.18077> for deterministic and noisy responses using a rational quadratic kernel with anisotropic factor weights. Provides leave-one-out tuning, fast 'C++' prediction routines, and conformal prediction intervals. This work is supported by a U.S. NSF grant DMS-2310637.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.3.0)
Imports: Rcpp (>= 1.0.14), nloptr
LinkingTo: Rcpp, RcppArmadillo, nloptr
Suggests: testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-10-14 19:59:39 UTC; Difan
Author: Difan Song [aut, cre], V. Roshan Joseph [aut]
Maintainer: Difan Song <dfsong96@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 08:50:11 UTC

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New package RCPA4 with initial version 1.0.0
Package: RCPA4
Title: Data and Functions for "An R Companion to Political Analysis, Fourth Edition"
Version: 1.0.0
Description: Provides teaching-oriented functions and datasets for "An R Companion to Political Analysis, Fourth Edition" (forthcoming 2026). Functions produce readable tables and graphics for descriptive statistics, data transformation, confidence intervals, hypothesis testing, comparisons, cross-tabulation, and linear and logistic regression. Sampling weights are supported where appropriate, and analysis functions return reusable results for further examination. The package also includes curated political datasets designed for classroom instruction and independent practice. See Edwards and Pollock (forthcoming 2026) <https://www.poliscidata.com/textbooks/r_companion_4e.php>.
License: CC0
URL: https://www.poliscidata.com/textbooks/r_companion_4e.php
LazyData: TRUE
Encoding: UTF-8
Depends: R (>= 4.0)
Imports: beepr, car, graphics, grDevices, haven, Hmisc, knitr, lmtest, methods, stats, survey, utils
Suggests: hexbin, rgl, scatterplot3d, gdata, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-09 13:32:27 UTC; Barry Edwards
Author: Barry C. Edwards [aut, cre] , Philip H. Pollock III [ctb]
Maintainer: Barry C. Edwards <bce@uga.edu>
Repository: CRAN
Date/Publication: 2026-10-24 08:20:02 UTC

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New package PheValuator with initial version 2.2.18
Package: PheValuator
Title: Rapid Phenotype Evaluation
Version: 2.2.18
Date: 2026-10-7
Description: Evaluates phenotype algorithms by developing a diagnostic prediction model using a set of noisy positives and noisy negatives. It can then apply the model to a large cohort to create a set of subjects each with a predicted probability for the health outcome of interest. This cohort can then be used to evaluate phenotype algorithms through the calculation of the necessary performance characteristics - sensitivity, specificity, and positive and negative predictive value. Based on work by Swerdel (2022) <doi:10.1016/j.jbi.2022.104177> and Swerdel (2019) <doi:10.1016/j.jbi.2019.103258>.
License: Apache License 2.0
VignetteBuilder: knitr
Depends: R (>= 4.1.1)
Imports: DatabaseConnector, PatientLevelPrediction (>= 6.0.4), FeatureExtraction (>= 2.1.5), SqlRender (>= 1.5.2), dplyr (>= 0.7.8), methods, ParallelLogger, tibble
Suggests: knitr, rmarkdown, shiny, shinydashboard, DT, htmltools, qpdf, testthat, Eunomia, withr, CohortGenerator
URL: https://ohdsi.github.io/PheValuator/, https://github.com/OHDSI/PheValuator
BugReports: https://github.com/OHDSI/PheValuator/issues
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-10-12 17:16:15 UTC; Admin_WObrien8
Author: William J. O'Brien [aut, cre], Joel Swerdel [aut], Martijn Schuemie [aut]
Maintainer: William J. O'Brien <wobrien8@its.jnj.com>
Repository: CRAN
Date/Publication: 2026-10-24 08:40:02 UTC

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New package flexsdm with initial version 1.4.2
Package: flexsdm
Title: Flexible Species Distribution Modeling Workflow
Version: 1.4.2
Maintainer: Santiago J.E. Velazco <sjevelazco@gmail.com>
URL: https://sjevelazco.github.io/flexsdm/, https://github.com/sjevelazco/flexsdm
BugReports: https://github.com/sjevelazco/flexsdm/issues
Depends: R (>= 3.5.0)
Imports: doParallel, dplyr, foreach, gbm, grDevices, kernlab, maxnet, mgcv, nnet, randomForest, spThin, terra (>= 1.5-21), methods, utils, ggplot2, patchwork, Rcpp
Description: Provides a flexible and comprehensive workflow for species distribution modeling, from data preparation (occurrence filtering, calibration areas, pseudo-absence and background sampling, data partitioning, and collinearity reduction) to model fitting, tuning, evaluation, prediction, ensemble modeling, and post-processing. The package is described in Velazco et al. (2022) <doi:10.1111/2041-210X.13874>. Implemented methods include the Shape metric to measure model extrapolation of Velazco et al. (2023) <doi:10.1111/ecog.06992>, ensembles of small models of Breiner et al. (2015) <doi:10.1111/2041-210X.12403> and Breiner et al. (2018) <doi:10.1111/2041-210X.12957>, Gaussian process models of Golding and Purse (2016) <doi:10.1111/2041-210X.12523>, and occurrence-based constraints for post-processing predictions of Mendes et al. (2020) <doi:10.1016/j.ecolmodel.2020.109180>.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Suggests: covr, fs, knitr, rmarkdown, testthat (>= 3.0.0), tibble, tidyr
VignetteBuilder: knitr
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2026-10-14 19:07:17 UTC; sjevelazco
Author: Santiago J.E. Velazco [aut, cre] , Brooke Rose [aut] , Andre F.A. Andrade [aut] , Ignacio Minoli [aut] , Janet Franklin [aut]
Repository: CRAN
Date/Publication: 2026-10-24 08:50:02 UTC

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New package esgcalc with initial version 0.2.0
Package: esgcalc
Title: Offline Environmental, Social and Governance Calculations
Version: 0.2.0
Description: Native, deterministic calculations for selected environmental, social and governance metrics. Provides granular taxonomy criteria, non-financial taxonomy indicators, principal adverse impact components, portfolio calculations and configurable performance ratings. Versioned local resources, explicit assumptions and structured results support reproducible offline use. Does not determine legal applicability or provide a complete regulatory reporting system. Selected methods reference EU Regulations 2020/852, 2022/1288 and 2023/2772; exact editions and provision locators are supplied in the bundled source contracts. For background on the taxonomy framework, see the European Commission <https://finance.ec.europa.eu/sustainable-finance/tools-and-standards/eu-taxonomy-sustainable-activities_en>.
License: GPL (>= 3)
Copyright: RiskDataScience GmbH
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: jsonlite, digest
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-10-09 10:34:42 UTC; qwert123
Author: Dimitrios Geromichalos [aut, cre], RiskDataScience GmbH [cph]
Maintainer: Dimitrios Geromichalos <riskdatascience@web.de>
Repository: CRAN
Date/Publication: 2026-10-24 08:10:02 UTC

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New package coiR with initial version 0.1.0
Package: coiR
Title: Analysis of Canopy Openness Index from Fisheye Images
Version: 0.1.0
Description: Tools to estimate the Canopy Openness Index (COI) from hemispherical (fisheye) canopy photographs. The package imports canopy images, crops them to the circular area delimited by the fisheye lens, binarizes them to separate sky from vegetation pixels, and computes the index as the proportion of sky pixels in the cropped image. Canopy openness is a measure related to canopy closure, canopy cover and understorey illumination, as discussed in Jennings, Brown and Sheil (1999) "Assessing forest canopies and understorey illumination: canopy closure, canopy cover and other measures" <doi:10.1093/forestry/72.1.59>. Example canopy images are included so users can test the workflow.
URL: https://github.com/Edbbioeco/coiR
BugReports: https://github.com/Edbbioeco/coiR/issues
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: ggplot2, dplyr, terra, tidyterra, rlang
Suggests: testthat (>= 3.0.0), purrr
NeedsCompilation: no
Packaged: 2026-10-14 21:17:24 UTC; LENOVO
Author: Edson Nilton de Moura Silva-Junior [aut, cre]
Maintainer: Edson Nilton de Moura Silva-Junior <edsonbbiologia@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 09:00:10 UTC

More information about coiR at CRAN
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New package AdaptiveGlasso with initial version 1.0.0
Package: AdaptiveGlasso
Title: Adaptive Graphical Lasso for Sparse Network Estimation
Version: 1.0.0
Description: Implements an adaptive graphical lasso method for sparse precision matrix and network estimation. The method combines ridge stabilization, cross-validated regularization, an initial graphical lasso estimate, and adaptive edge-specific penalties to estimate sparse conditional dependence structures. The method supports settings where the sample size is smaller than, equal to, or larger than the number of variables.
URL: https://github.com/elizabethamona/AdaptiveGlasso
BugReports: https://github.com/elizabethamona/AdaptiveGlasso/issues
License: MIT + file LICENSE
Encoding: UTF-8
Imports: CVglasso, glasso
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-10-13 04:39:31 UTC; amona
Author: Elizabeth B. Amona [aut, cre, cph]
Maintainer: Elizabeth B. Amona <amonaelizabeth1@gmail.com>
Repository: CRAN
Date/Publication: 2026-10-24 08:40:09 UTC

More information about AdaptiveGlasso at CRAN
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