Fri, 11 Sep 2026

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

Title: Access Brazilian National Treasury Open Data APIs
Description: Provides a unified interface to access open data from the Brazilian National Treasury ('Tesouro Nacional') and related government APIs. Covers six data sources: 'SICONFI' <https://apidatalake.tesouro.gov.br/docs/siconfi/> for fiscal reports ('RREO', 'RGF', 'DCA', 'MSC') and entity information; 'CUSTOS' <https://apidatalake.tesouro.gov.br/docs/custos/> for federal government cost data; 'SADIPEM' <https://apidatalake.tesouro.gov.br/docs/sadipem/> for public debt and credit operations; 'Transferencias Constitucionais' <https://apiapex.tesouro.gov.br/aria/v1/transferencias_constitucionais/docs> for constitutional transfers to states and municipalities; 'SIORG' <https://estruturaorganizacional.dados.gov.br> for federal organizational structure; and 'SIOPE' ('FNDE'/'MEC') for education spending data. Features automatic pagination, in-memory caching, retry logic, and tidy output.
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorim [aut], Diogo Bezerra [aut], Tiago Pereira [aut], Fernando Barbalho [aut]
Maintainer: Andre Leite <leite@castlab.org>

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Package RIFanalysis updated to version 0.9.3 with previous version 0.9.2 dated 2026-08-20

Title: Relative Importance Factor Analysis
Description: Tools for estimating, comparing, and visualizing Relative Importance Factor (RIF) indices based on rank-frequency distributions and discrete power-law models. The package provides reproducible workflows for data preparation, model fitting, goodness-of-fit assessment, bootstrap inference, and publication-ready outputs. The implemented methodology is described in Llinas et al. (2026) <doi:10.3390/math14060966>.
Author: Humberto J. Llinas M. [aut, cre], Humberto J. Llinas S. [aut], Javier A. De la Hoz M. [aut], Brian J. Llinas M. [aut], Jose J. Padilla [aut]
Maintainer: Humberto J. Llinas M. <lhumberto@uninorte.edu.co>

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Package wdsmatch updated to version 0.2.0 with previous version 0.1.1 dated 2026-04-21

Title: Weighted Double Score Matching for Survey-Weighted Causal Inference
Description: Implements weighted double score matching (WDSM) for estimating population-level causal effects from complex survey data. Combines propensity scores and prognostic scores with survey design weights for matching, survey-weighted imputation within match sets, and Hajek normalization to target the population average treatment effect (PATE) and the population average treatment effect on the treated (PATT). Supports both retrospective (treatment-dependent) and prospective (treatment-independent) sampling designs. Uses propensity probabilities and arm-specific prognostic scores for matching, with a complete quadratic bias correction in each arm's double score. Provides linearization-based multinomial replication variance estimates and centered normal Wald confidence intervals, retaining the original matching reuse coefficients without re-matching. Supplied scores can be held fixed for inference conditional on those scores. This weight-only interface does not encode survey strata, clusters, o [...truncated...]
Author: Yukang Zeng [aut, cre], Guangyu Tong [aut], Jiaqi Tong [aut], Haidong Lu [aut], Bhramar Mukherjee [aut], Fan Li [aut]
Maintainer: Yukang Zeng <ykzeng2019@gmail.com>

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Package weightflow updated to version 1.3.0 with previous version 1.2.0 dated 2026-08-29

Title: Declarative Recipes for Staged Survey Weighting with Recipe-Aware Replicate Variances
Description: Builds survey analysis weights by declaring the whole weighting process as an ordered recipe of explicit adjustments, estimated in a single call. Steps cover within-cluster selection, subsampling for two-phase designs, nonresponse by weighting classes or response-propensity models (optionally machine-learning, with cross-fitting), calibration to known totals following Deville and Sarndal (1992) <doi:10.2307/2290268>, optionally model-assisted, non-probability samples by pseudo-weighting, mass imputation and doubly robust estimators, and range-restricted trimming. Rotating and pure panels add panel-selection probabilities, attrition, longitudinal weights, gross flows and composite estimation. Variances come from a recipe-aware bootstrap and jackknife that resample or delete primary sampling units and re-apply the entire cascade on each replicate, following Rao and Wu (1988) <doi:10.1080/01621459.1988.10478591>; panel replicates are coordinated across waves, so the sample ove [...truncated...]
Author: Juan Pablo Ferreira [aut, cre, cph] , Andres Gutierrez [aut]
Maintainer: Juan Pablo Ferreira <juanpablo.ferreira@fcea.edu.uy>

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Package shapr updated to version 1.1.0 with previous version 1.0.8 dated 2026-01-20

Title: Prediction Explanation with Dependence-Aware Shapley Values
Description: Complex machine learning models are often hard to interpret. However, in many situations it is crucial to understand and explain why a model made a specific prediction. Shapley values is the only method for such prediction explanation framework with a solid theoretical foundation. Previously known methods for estimating the Shapley values do, however, assume feature independence. This package implements methods which accounts for any feature dependence, and thereby produces more accurate estimates of the true Shapley values. An accompanying 'Python' wrapper ('pyshapr') is available through PyPI.
Author: Martin Jullum [cre, aut] , Lars Henry Berge Olsen [aut] , Annabelle Redelmeier [aut], Jon Lachmann [aut] , Nikolai Sellereite [aut] , Anders Loeland [ctb], Jens Christian Wahl [ctb], Camilla Lingjaerde [ctb], Norsk Regnesentral [cph, fnd]
Maintainer: Martin Jullum <Martin.Jullum@nr.no>

Diff between shapr versions 1.0.8 dated 2026-01-20 and 1.1.0 dated 2026-09-11

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Package lotri updated to version 1.0.5 with previous version 1.0.4 dated 2026-05-14

Title: A Simple Way to Specify Symmetric, Block Diagonal Matrices
Description: Provides a simple mechanism to specify a symmetric block diagonal matrices (often used for covariance matrices). This is based on the domain specific language implemented in 'nlmixr2' but expanded to create matrices in R generally instead of specifying parts of matrices to estimate. It has expanded to include some matrix manipulation functions that are generally useful for 'rxode2' and 'nlmixr2'.
Author: Matthew L. Fidler [aut, cre] , Mauricio Vargas Sepulveda [ctb] , Bill Denney [ctb]
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

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Package gmeans updated to version 0.2.0 with previous version 0.1.0 dated 2026-08-05

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>

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Package echor updated to version 0.1.10 with previous version 0.1.9 dated 2023-06-22

Title: Access EPA 'ECHO' Data
Description: An R interface to United States Environmental Protection Agency (EPA) Environmental Compliance History Online ('ECHO') Application Program Interface (API). 'ECHO' provides information about EPA permitted facilities, discharges, and other reporting info associated with permitted entities. Data are obtained from <https://echo.epa.gov/>.
Author: Michael Schramm [aut, cre, cph]
Maintainer: Michael Schramm <mpschramm@gmail.com>

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Package diffobj updated to version 0.3.9 with previous version 0.3.8 dated 2026-07-17

Title: Diffs for R Objects
Description: Generate a colorized diff of two R objects for an intuitive visualization of their differences.
Author: Brodie Gaslam [aut, cre], Michael B. Allen [ctb, cph]
Maintainer: Brodie Gaslam <brodie.gaslam@yahoo.com>

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Package choroplethr readmission to version 5.0.2 with previous version 5.0.1 dated 2025-10-18

Title: Create Color-Coded Choropleth Maps in R
Description: Easily create color-coded (choropleth) maps in R. No knowledge of cartography or shapefiles needed; go directly from your geographically identified data to a highly customizable map with a single line of code! Supported geographies: U.S. states, counties, census tracts, and zip codes, world countries and sub-country regions (e.g., provinces, prefectures, etc.).
Author: Ari Lamstein [aut], Zhaochen He [ctb, cre], Brian Johnson [ctb], Trulia, Inc. [cph]
Maintainer: Zhaochen He <zhaochen.he@cnu.edu>

This is a re-admission after prior archival of version 5.0.1 dated 2025-10-18

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Package Certara.NLME8 updated to version 3.2.0 with previous version 3.0.2 dated 2025-08-20

Title: Utilities for Certara's Nonlinear Mixed-Effects Modeling Engine
Description: Interface to Certara's Nonlinear Mixed-Effects (NLME) modeling engine ('NLME-Engine') for pharmacokinetic and pharmacodynamic (PK/PD) modeling and simulation. Provides access to the Maximum Likelihood estimation algorithms available in the 'Phoenix' NLME platform for population, individual, and pooled analyses using parametric methods. Includes utilities for setting up NLME installations and parallel settings, running estimation, bootstrap, and covariate search workflows, and updating model files from engine output. Jobs can be executed locally or across high-performance computing resources, including Linux Sun Grid Engine (SGE) and Simple Linux Utility for Resource Management (SLURM) grids as well as multicore Linux and Windows hosts.
Author: Soltanshahi Fred [aut], Michael Tomashevskiy [aut], James Craig [aut, cre], Shuhua Hu [ctb], Certara USA, Inc. [cph, fnd]
Maintainer: James Craig <james.craig@certara.com>

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Package bacenR updated to version 0.5.0 with previous version 0.4.4 dated 2026-07-03

Title: Access Data from Brazilian Central Bank: IFdata, Active Institutions, Balance Sheets and Normative Acts
Description: Provides functions to query, retrieve, and tidy economic and financial data from Brazilian Central Bank web services for use in R analyses and workflows. Active institutions information, balance sheets and normative acts.
Author: Ricardo Theodoro [aut, cre]
Maintainer: Ricardo Theodoro <rtheodoro@usp.br>

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Package normalblockr updated to version 0.3.0 with previous version 0.2.1 dated 2026-09-03

Title: Gaussian Graphical Models with Latent Clustering Structure
Description: Implements the Normal-Block model, a Gaussian graphical model with a latent clustering structure for the multivariate analysis of continuous data. The model clusters variables and, building on the graphical lasso, infers a network of statistical dependencies between clusters rather than between individual variables, for known or unknown clusterings, with an optional zero-inflation extension for data with an excess of exact zeros. A complementary family clusters variables by their regression response to covariates rather than by their covariance, sharing one profile per cluster. See Tous & Chiquet (2026) <doi:10.1016/j.csda.2026.108347> for the model itself and its variational expectation-maximization estimation procedure.
Author: Jeanne Tous [aut], Nestor Ngalala Manguitini [ctb], Julien Chiquet [aut, cre]
Maintainer: Julien Chiquet <julien.chiquet@inrae.fr>

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Package mvinfluence updated to version 0.9.4 with previous version 0.9.2 dated 2025-07-23

Title: Influence Measures and Diagnostic Plots for Multivariate Linear Models
Description: Computes regression deletion diagnostics for multivariate linear models and provides some associated diagnostic plots. The diagnostic measures include hat-values (leverages), generalized Cook's distance, and generalized squared 'studentized' residuals. Several types of plots to detect influential observations are provided.
Author: Michael Friendly [aut, cre]
Maintainer: Michael Friendly <friendly@yorku.ca>

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Package gllvm updated to version 2.0.15 with previous version 2.0.13 dated 2026-07-09

Title: Generalized Linear Latent Variable Models
Description: Analysis of multivariate data using generalized linear latent variable models (gllvm). Estimation is performed using either the Laplace method, variational approximations, or extended variational approximations, implemented via TMB (Kristensen et al. (2016), <doi:10.18637/jss.v070.i05>).
Author: Jenni Niku [aut, cre], Wesley Brooks [aut], Riki Herliansyah [aut], Francis K.C. Hui [aut], Pekka Korhonen [aut], Sara Taskinen [aut], Bert van der Veen [aut], David I. Warton [aut]
Maintainer: Jenni Niku <jenni.m.e.niku@jyu.fi>

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Package bvartools updated to version 0.3.0 with previous version 0.2.4 dated 2024-01-08

Title: Bayesian Inference of Vector Autoregressive and Error Correction Models
Description: Assists in the set-up of algorithms for Bayesian inference of vector autoregressive (VAR) and error correction (VEC) models. Functions for posterior simulation, forecasting, impulse response analysis and forecast error variance decomposition are largely based on the introductory texts of Chan, Koop, Poirier and Tobias (2019, ISBN: 9781108437493), Koop and Korobilis (2010) <doi:10.1561/0800000013> and Luetkepohl (2006, ISBN: 9783540262398).
Author: Franz X. Mohr [aut, cre]
Maintainer: Franz X. Mohr <franz.x.mohr@outlook.com>

Diff between bvartools versions 0.2.4 dated 2024-01-08 and 0.3.0 dated 2026-09-11

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Permanent link

Package pre updated to version 1.1.1 with previous version 1.1.0 dated 2026-08-31

Title: Prediction Rule Ensembles
Description: Fits prediction rule ensembles (PREs). Largely follows the procedure for deriving PREs as described in Friedman & Popescu (2008; <DOI:10.1214/07-AOAS148>), with adjustments and improvements described in Fokkema (2020; <DOI:10.18637/jss.v092.i12>) and Fokkema & Strobl (2020; <DOI:10.1037/met0000256>). The main function pre() derives prediction rule ensembles consisting of rules and/or linear terms for continuous, binary, count, multinomial, survival and multivariate continuous responses. Function gpe() derives generalized prediction ensembles, consisting of rules, hinge and linear functions of the predictor variables.
Author: Marjolein Fokkema [aut, cre], Benjamin Christoffersen [aut], Giorgio Spadaccini [ctb]
Maintainer: Marjolein Fokkema <m.fokkema@fsw.leidenuniv.nl>

Diff between pre versions 1.1.0 dated 2026-08-31 and 1.1.1 dated 2026-09-11

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Package tmbstan updated to version 1.2.1 with previous version 1.2.0 dated 2026-07-28

Title: MCMC Sampling from 'TMB' Model Object using 'Stan'
Description: Enables all 'rstan' functionality for a 'TMB' model object, in particular MCMC sampling and chain visualization. Sampling can be performed with or without Laplace approximation for the random effects. This is demonstrated in Monnahan & Kristensen (2018) <DOI:10.1371/journal.pone.0197954>.
Author: Kasper Kristensen [aut, cre] , Andrew Johnson [ctb], Cole Monnahan [ctb]
Maintainer: Kasper Kristensen <kaskr@dtu.dk>

Diff between tmbstan versions 1.2.0 dated 2026-07-28 and 1.2.1 dated 2026-09-11

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Package mx.client updated to version 0.2.1 with previous version 0.2.0 dated 2026-08-04

Title: Stateful Matrix Client Helpers
Description: Stateful helpers for building 'Matrix' (<https://matrix.org>) chat clients in R. Builds on the low-level 'mx.api' Client-Server API bindings, adding local configuration persistence, room resolution, sync cursor handling, sync-event extraction, invite acceptance, a conservative Markdown-to-HTML converter for formatted messages, and 'Olm'/'Megolm' end-to-end encryption orchestration over the optional 'mx.crypto' package.
Author: Troy Hernandez [aut, cre] , cornball.ai [cph]
Maintainer: Troy Hernandez <troy@cornball.ai>

Diff between mx.client versions 0.2.0 dated 2026-08-04 and 0.2.1 dated 2026-09-11

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Package fable.bayesRecon updated to version 0.2.1 with previous version 0.2.0 dated 2026-08-21

Title: Bayesian Reconciliation in the 'fable' Framework
Description: Implements the 'bayesRecon' probabilistic reconciliation methods within the 'fable' framework for hierarchical time series forecasting. Bayesian reconciliation (bayesRecon) methods are accessed via the 'reconcile' verb, following 'fable' conventions. For methodological background, see Corani et al. (2021) <doi:10.1007/978-3-030-67664-3_13>, Zambon et al. (2024a) <doi:10.1007/s11222-023-10343-y>, Zambon et al. (2024b) <https://proceedings.mlr.press/v244/zambon24a.html>, and Carrara et al. (2026) <doi:10.1016/j.ijforecast.2026.07.003>.
Author: Dario Azzimonti [aut, cre, cph] , Stefano Damato [aut] , Lorenzo Zambon [aut] , Chiara Carrara [aut] , Giorgio Corani [aut]
Maintainer: Dario Azzimonti <dario.azzimonti@gmail.com>

Diff between fable.bayesRecon versions 0.2.0 dated 2026-08-21 and 0.2.1 dated 2026-09-11

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Package DUToolkit updated to version 1.0.3 with previous version 1.0.2 dated 2025-10-06

Title: Visualizing and Quantifying Decision Uncertainty
Description: A suite of tools to help modelers and decision-makers effectively interpret and communicate decision risk when evaluating multiple policy options. It uses model outputs from uncertainty analysis for baseline scenarios and policy alternatives to generate visual representations of uncertainty and quantitative measures for assessing associated risks. For more details see Wiggins and colleagues (2025) <doi:10.1371/journal.pone.0332522> and <https://dut.ihe.ca/>.
Author: Megan Wiggins [aut, cre] , Marie Betsy Varughese [aut] , Ellen Rafferty [aut] , Sasha van Katwyk [aut] , Christopher McCabe [aut] , Jeff Round [aut] , Erin Kirwin [aut] , Institute of Health Economics [cph, aut], Canadian Network for Modelling Infect [...truncated...]
Maintainer: Megan Wiggins <mwiggins@ihe.ca>

Diff between DUToolkit versions 1.0.2 dated 2025-10-06 and 1.0.3 dated 2026-09-11

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Package wintime updated to version 1.0.0 with previous version 0.4.4 dated 2026-04-23

Title: Win Time Methods for Time-to-Event Data in Clinical Trials
Description: Performs an analysis of time-to-event clinical trial data using various "win time" methods, including 'ewt', 'ewtr', 'rmt', 'ewtp', 'rewtp', 'ewtpr', 'rewtpr', 'max', 'wtr', 'rwtr', 'pwt', and 'rpwt'. These methods are used to calculate and compare treatment effects on ordered composite endpoints. The package handles event times, event indicators, and treatment arm indicators and supports calculations on observed and resampled data. Detailed explanations of each method and usage examples are provided in "Use of win time for ordered composite endpoints in clinical trials," by Troendle et al. (2024)<doi:10.1002/sim.10045>. For more information, see the package documentation or the vignette titled "Introduction to wintime."
Author: James Troendle [aut, cre], Samuel Lawrence [aut]
Maintainer: James Troendle <james.troendle@nih.gov>

Diff between wintime versions 0.4.4 dated 2026-04-23 and 1.0.0 dated 2026-09-11

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Package tidytuesdayR updated to version 1.3.3 with previous version 1.3.2 dated 2026-04-12

Title: Access the Weekly 'TidyTuesday' Project Dataset
Description: 'TidyTuesday' is a project by the 'Data Science Learning Community' in which they post a weekly dataset in a public data repository (<https://github.com/rfordatascience/tidytuesday>) for people to analyze and visualize. This package provides the tools to easily download this data and the description of the source.
Author: Jon Harmon [aut, cre] , Ellis Hughes [aut], Thomas Mock [ctb], Data Science Learning Community [dtc]
Maintainer: Jon Harmon <jonthegeek@gmail.com>

Diff between tidytuesdayR versions 1.3.2 dated 2026-04-12 and 1.3.3 dated 2026-09-11

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New package siniaR with initial version 0.1.0
Package: siniaR
Title: Access to Peru's Environmental Statistics ('SINIA' / 'MINAM')
Version: 0.1.0
Description: Provides programmatic access to official environmental statistics and data of Peru from the National Environmental Information System ('SINIA', <https://sinia.minam.gob.pe/>), Ministry of the Environment ('MINAM'). Includes indicator catalogs, technical metadata sheets ('fichas técnicas'), and structured historical series for 'R'.
Language: es
License: MIT + file LICENSE
URL: https://github.com/PaulESantos/siniaR, https://paulesantos.github.io/siniaR/
BugReports: https://github.com/PaulESantos/siniaR/issues
Depends: R (>= 3.6.0)
Imports: cli (>= 3.0.0), curl (>= 4.3.0), jsonlite (>= 1.7.0), tibble (>= 3.0.0)
Suggests: DT, dplyr, ggplot2, htmltools, knitr, rmarkdown, testthat (>= 3.0.0), tidyr
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-09-01 01:25:38 UTC; PC
Author: Paul Efren Santos Andrade [aut, cre, cph]
Maintainer: Paul Efren Santos Andrade <paulefrens@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-11 16:00:02 UTC

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New package sglssnal with initial version 0.1.0
Package: sglssnal
Title: Sparse-Group Lasso via Semismooth Newton Augmented Lagrangian
Version: 0.1.0
Description: Implements the sparse-group lasso method of Zhang et al. (2020) <doi:10.1007/s10107-018-1329-6>. Unlike many widely available methods based on first-order descent, this method uses second-order information to solve the dual optimization problem via a semismooth Newton method.
License: MIT + file LICENSE
URL: https://github.com/roobnloo/sglssnal
BugReports: https://github.com/roobnloo/sglssnal/issues
Depends: R (>= 4.4.0)
Encoding: UTF-8
LazyData: true
Imports: Matrix, Rcpp, RSpectra, methods, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
Language: en-US
VignetteBuilder: knitr
NeedsCompilation: yes
Packaged: 2026-08-31 23:04:17 UTC; boethius
Author: Robin Liu [aut, cre], Yangjing Zhang [ctb]
Maintainer: Robin Liu <robin28liu@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-11 15:30:02 UTC

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Package qrjoint updated to version 2.1-0 with previous version 2.0-11 dated 2025-09-24

Title: Joint Estimation in Linear Quantile Regression
Description: Joint estimation of quantile specific intercept and slope parameters in a linear regression setting.
Author: Surya Tokdar [aut, cre] , Erika Cunningham [aut]
Maintainer: Surya Tokdar <surya.tokdar@duke.edu>

Diff between qrjoint versions 2.0-11 dated 2025-09-24 and 2.1-0 dated 2026-09-11

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Package glasstabs updated to version 0.4.0 with previous version 0.3.4 dated 2026-07-31

Title: Animated Glass-Style Tabs and Select Inputs for 'Shiny'
Description: Tools for creating animated glassmorphism-style tab navigation and select filter widgets in 'Shiny' applications. Provides a tab navigation component with a sliding glass halo animation, a searchable multi-select dropdown, and a single-select dropdown - all with multiple colour themes and server-side update helpers. Tabs support icons, numeric badges, disable/enable toggling, runtime append/remove, reactive rendering via 'renderGlassTabs()', URL bookmarking, responsive overflow modes, optional touch gestures, reduced-motion support, and compact mode for dashboard card layouts. 'glassTabCondition()' generates 'conditionalPanel()' condition strings without needing to recall the internal input key pattern. 'glasstabs_news()' displays the release notes from the R console. Built-in example apps can be launched with 'runGlassExample()'. All widgets are compatible with standard 'Shiny' layouts and 'bs4Dash' dashboards and 'bslib' themed applications. An experimental 'glassPage()' helper prov [...truncated...]
Author: George Arthur [aut, cre]
Maintainer: George Arthur <prigasgenthian48@gmail.com>

Diff between glasstabs versions 0.3.4 dated 2026-07-31 and 0.4.0 dated 2026-09-11

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Package enderecobr updated to version 0.6.1 with previous version 0.6.0 dated 2026-09-10

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>

Diff between enderecobr versions 0.6.0 dated 2026-09-10 and 0.6.1 dated 2026-09-11

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Package commons updated to version 0.1.0 with previous version 0.0.1 dated 2026-08-07

Title: AI Agents for Data Analysis
Description: Implements trustworthy large language model agents. Connect raw data sources, a pool of trusted calculations, and a searchable context layer that demonstrates how to interpret them. Then, deploy data agents that answer questions, log interactions, and can be evaluated and improved over time.
Author: Simon Couch [aut, cre] , Sara Altman [aut], Posit Software, PBC [cph, fnd]
Maintainer: Simon Couch <simon.couch@posit.co>

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Package TreeDist updated to version 2.15.0 with previous version 2.14.1 dated 2026-06-10

Title: Calculate and Map Distances Between Phylogenetic Trees
Description: Implements measures of tree similarity, including information-based generalized Robinson-Foulds distances (Phylogenetic Information Distance, Clustering Information Distance, Matching Split Information Distance; Smith 2020) <doi:10.1093/bioinformatics/btaa614>; Jaccard-Robinson-Foulds distances (Bocker et al. 2013) <doi:10.1007/978-3-642-40453-5_13>, including the Nye et al. (2006) metric <doi:10.1093/bioinformatics/bti720>; the Matching Split Distance (Bogdanowicz & Giaro 2012) <doi:10.1109/TCBB.2011.48>; the Hierarchical Mutual Information (Perotti et al. 2015) <doi:10.1103/PhysRevE.92.062825>; Maximum Agreement Subtree distances; the Kendall-Colijn (2016) distance <doi:10.1093/molbev/msw124>, and the Nearest Neighbour Interchange (NNI) distance, approximated per Li et al. (1996) <doi:10.1007/3-540-61332-3_168>. Includes tools for visualizing mappings of tree space (Smith 2022) <doi:10.1093/sysbio/syab100>, for identifying islands o [...truncated...]
Author: Martin R. Smith [aut, cre, cph, prg] , Roy Jonker [prg, cph] , Yong Yang [ctb, cph] , Yi Cao [ctb, cph] , Neil Kaye [cph]
Maintainer: Martin R. Smith <martin.smith@durham.ac.uk>

Diff between TreeDist versions 2.14.1 dated 2026-06-10 and 2.15.0 dated 2026-09-11

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Package tibblify updated to version 0.4.2 with previous version 0.4.1 dated 2026-05-12

Title: Rectangle Nested Lists
Description: A tool to rectangle a nested list, that is to convert it into a 'tibble'. This is done automatically or according to a given specification. A common use case is for nested lists coming from parsing 'JSON' files, or the 'JSON' responses of 'REST' 'APIs'. 'Rectangling' uses the 'vctrs' package, and therefore offers a wide support of vector types.
Author: Jon Harmon [aut, cre] , Maximilian Girlich [aut, cph], Kirill Mueller [ctb]
Maintainer: Jon Harmon <jonthegeek@gmail.com>

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Package rmsfact updated to version 0.0.4 with previous version 0.0.3 dated 2016-08-04

Title: Amazing Random Facts About the World's Greatest Hacker
Description: Display a randomly selected quote about Richard M. Stallman based on the collection in the 'GNU Octave' function 'fact()' which was aggregated by Jordi Gutiérrez Hermoso based on the (now defunct) site stallmanfacts.com (which is accessible only via <http://archive.org>).
Author: Dirk Eddelbuettel [aut, cre] , Octave Authors [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between rmsfact versions 0.0.3 dated 2016-08-04 and 0.0.4 dated 2026-09-11

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Package LABTNSCPSS updated to version 1.0.5 with previous version 1.0.4 dated 2026-09-10

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 methodology is described in Nikiema, Bayani, and Bally (2026), "A Semantic-Based Carry-Forward Approach: Uncovering Chronic Disease Burden in Real-World Data Analysis", International Journal of Medical Informatics, article 106709 <doi:10.1016/j.ijmedinf.2026.106709>.
Author: Azadeh Bayani [aut, cre] , Jean Noel Nikiema [ctb], Michele Bally [ctb]
Maintainer: Azadeh Bayani <azadeh.bayani@umontreal.ca>

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Package discretes updated to version 0.1.1 with previous version 0.1.0 dated 2026-03-31

Title: Discrete Numeric Series
Description: Provides a framework for representing discrete numeric series (enumerable sets of numbers) that may be finite or infinite. Series can be traversed, combined using arithmetic operations, tested for membership, and queried for limit points ("sinks"), without explicit enumeration of all elements.
Author: Vincenzo Coia [aut, cre, cph] , Carlo De Michele [aut]
Maintainer: Vincenzo Coia <vincenzo.coia@gmail.com>

Diff between discretes versions 0.1.0 dated 2026-03-31 and 0.1.1 dated 2026-09-11

 DESCRIPTION                              |   19 +++++-----
 MD5                                      |   53 +++++++++++++++--------------
 NAMESPACE                                |    1 
 NEWS.md                                  |   13 +++++++
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 29 files changed, 245 insertions(+), 66 deletions(-)

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New package arcstat with initial version 0.2.0
Package: arcstat
Title: Arc-Length Statistics: Goodness of Fit, Distributions and a Bayesian Test
Version: 0.2.0
Description: Inference from the arc length of statistical functions. Three tools share one pure-C back-end: a goodness-of-fit test based on the arc length of the probability plot, with an analytic saddlepoint null and sensitivity to local density structure that the empirical-distribution tests miss; two constructions that build a distribution from the arc length of its defining curve, the arc-length generator and the quantile arc-length family estimated by L-moments; and a Bayesian nonparametric arc-length goodness-of-fit test on the Dirichlet-process posterior. The same C sources back the 'Python' package 'arcstat'.
URL: https://github.com/mtloots/arcstat
BugReports: https://github.com/mtloots/arcstat/issues
License: GPL-3
Encoding: UTF-8
Imports: stats
NeedsCompilation: yes
Suggests: MASS, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Packaged: 2026-08-31 19:10:05 UTC; home
Author: M. Theodor Loots [aut, cre]
Maintainer: M. Theodor Loots <theo.loots@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-11 14:30:13 UTC

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Package adbcsqlite (with last version 0.24.0-1) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-07-29 0.24.0-1
2026-06-03 0.23.0-1
2026-04-08 0.23.0
2026-01-20 0.22.0
2025-11-19 0.21.0
2025-09-16 0.20.0
2025-07-13 0.19.0
2025-05-27 0.18.0
2025-03-07 0.17.0
2025-01-22 0.16.0
2024-11-14 0.15.0
2024-09-06 0.14.0
2024-07-08 0.13.0
2024-05-22 0.12.0
2024-04-17 0.11.0.1
2024-02-22 0.10.0
2024-01-09 0.9.0
2023-11-09 0.8.0
2023-10-11 0.7.0.1
2023-08-30 0.6.0

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Package HRTnomaly (with last version 25.11.22) was removed from CRAN

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2025-11-25 25.11.22
2025-02-26 25.2.25
2025-02-20 25.2.18

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Package imaginarycss (with last version 0.1.0) was removed from CRAN

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2026-03-04 0.1.0

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Package adbi (with last version 0.1.2) was removed from CRAN

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2025-09-03 0.1.2
2024-01-25 0.1.1
2023-12-21 0.1.0
2023-12-11 0.0.2

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Package adbcdrivermanager (with last version 0.24.0-2) was removed from CRAN

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2026-08-23 0.24.0-2
2026-07-30 0.24.0-1
2026-06-04 0.23.0-2
2026-04-09 0.23.0-1
2026-03-25 0.22.0-2
2026-03-09 0.22.0-1
2026-01-21 0.22.0
2025-11-20 0.21.0
2025-09-17 0.20.0
2025-07-20 0.19.0-1
2025-07-13 0.19.0
2025-05-27 0.18.0
2025-03-07 0.17.0
2025-01-22 0.16.0
2024-11-14 0.15.0
2024-09-06 0.14.0
2024-07-09 0.13.0
2024-05-22 0.12.0
2024-04-02 0.11.0
2024-02-22 0.10.0
2024-01-16 0.9.0.1
2023-11-10 0.8.0
2023-10-07 0.7.0.1
2023-09-27 0.7.0
2023-08-30 0.6.0
2023-06-22 0.5.0.1

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Package awdb (with last version 0.1.4) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-08-21 0.1.4
2025-08-23 0.1.3
2025-04-14 0.1.2
2025-02-26 0.1.1

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Package adbcpostgresql (with last version 0.24.0-1) was removed from CRAN

Previous versions (as known to CRANberries) which should be available via the Archive link are:

2026-07-29 0.24.0-1
2026-06-03 0.23.0-1
2026-04-08 0.23.0
2026-01-21 0.22.0
2025-11-19 0.21.0
2025-09-16 0.20.0
2025-07-13 0.19.0
2025-05-27 0.18.0
2025-03-07 0.17.0
2025-01-22 0.16.0
2024-11-14 0.15.0
2024-09-06 0.14.0
2024-07-09 0.13.0
2024-05-22 0.12.0
2024-04-15 0.11.0.1
2024-04-02 0.11.0
2024-02-22 0.10.0
2024-01-21 0.9.0.1
2024-01-09 0.9.0
2023-12-12 0.8.0.1

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Package defm (with last version 0.2.1.0) was removed from CRAN

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2026-02-13 0.2.1.0
2023-09-07 0.1-1
2023-08-08 0.1-0

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Package NetMix (with last version 0.2.0.3) was removed from CRAN

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2025-06-05 0.2.0.3
2023-12-13 0.2.0.2
2022-11-16 0.2.0.1
2021-03-01 0.2.0
2020-01-14 0.1.5
2019-07-26 0.1.4

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Package HDclust (with last version 1.0.4) was removed from CRAN

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2024-09-20 1.0.4
2019-04-11 1.0.3
2018-07-29 1.0

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New package rpsurv with initial version 0.7.1
Package: rpsurv
Title: Fast Royston-Parmar Flexible Parametric Survival Models
Version: 0.7.1
Description: Fits Royston-Parmar flexible parametric survival models (Royston and Parmar, 2002) <doi:10.1002/sim.1203> on the log cumulative hazard, odds, and probit scales, with time-varying (non-proportional) covariate effects via restricted cubic splines in log time. The likelihood and its analytic gradient are evaluated in C++ with 'RcppParallel', giving large speedups over pure-R implementations for large datasets.
License: MIT + file LICENSE
URL: https://github.com/ielbadisy/rpsurv
BugReports: https://github.com/ielbadisy/rpsurv/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp, RcppParallel, survival, stats, graphics, grDevices
LinkingTo: Rcpp, RcppParallel
SystemRequirements: GNU make
Suggests: rstpm2, flexsurv, numDeriv, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
LazyData: true
NeedsCompilation: yes
Packaged: 2026-08-31 17:24:07 UTC; imad-el-badisy
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-11 13:50:02 UTC

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Package HRM readmission to version 1.3.0 with previous version 1.2.1 dated 2020-02-06

Title: High-Dimensional Repeated Measures
Description: Methods for testing main and interaction effects in possibly high-dimensional parametric or nonparametric repeated measures in factorial designs. The observations of the subjects are assumed to be multivariate normal if using the parametric test. The nonparametric version tests with regard to nonparametric relative effects (based on pseudo-ranks). It is possible to use up to 2 whole- and 3 subplot factors. See Happ et al. (2017, <doi:10.1080/15598608.2017.1307792>) for details.
Author: Martin Happ [aut, cre] , Solomon W. Harrar [aut], Arne C. Bathke [aut]
Maintainer: Martin Happ <statistics@happ.co.at>

This is a re-admission after prior archival of version 1.2.1 dated 2020-02-06

Diff between HRM versions 1.2.1 dated 2020-02-06 and 1.3.0 dated 2026-09-11

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New package validateR with initial version 0.2.0
Package: validateR
Title: Simple Data Frame Validation and Quality Checks
Version: 0.2.0
Description: Checks a data frame for common data quality issues, including missing values, outliers, duplicate rows, and type inconsistencies. Results are returned as a structured 'validation_report' object with 'print' and 'plot' methods for quick inspection.
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Imports: graphics, stats
VignetteBuilder: knitr
URL: https://github.com/UgyenNorbu/validateR
BugReports: https://github.com/UgyenNorbu/validateR/issues
NeedsCompilation: no
Packaged: 2026-08-31 13:26:26 UTC; ugyennorbu
Author: Ugyen Norbu [aut, cre]
Maintainer: Ugyen Norbu <unorbu2019@gmail.com>
Depends: R (>= 4.1.0)
Repository: CRAN
Date/Publication: 2026-09-11 12:20:02 UTC

More information about validateR at CRAN
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Package simplermarkdown updated to version 0.1.0 with previous version 0.0.6 dated 2023-03-24

Title: Simple Engine for Generating Reports using R
Description: Runs R-code present in a pandoc markdown file and includes the resulting output in the resulting markdown file. This file can then be converted into any of the output formats supported by pandoc. The package can also be used as an low dependency engine for writing package vignettes.
Author: Jan van der Laan [aut, cre] , Troy Hernandez [ctb]
Maintainer: Jan van der Laan <jan@ntteloos.nl>

Diff between simplermarkdown versions 0.0.6 dated 2023-03-24 and 0.1.0 dated 2026-09-11

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New package r4subpharma with initial version 0.1.0
Package: r4subpharma
Title: 'pharmaverse' Adapters for R4SUB Submission Readiness Evidence
Version: 0.1.0
Description: Bridges the 'pharmaverse' clinical reporting stack and the R4SUB (Ready for Submission) ecosystem. Converts 'metacore' metadata objects and ADaM (Analysis Data Model) datasets - such as those built with 'admiral' - into standardized R4SUB evidence table rows via 'r4subcore', so that submission readiness can be scored with 'r4subscore' without changing an existing pharmaverse pipeline.
License: MIT + file LICENSE
URL: https://r4sub.github.io/r4subpharma/, https://github.com/R4SUB/r4subpharma
BugReports: https://github.com/R4SUB/r4subpharma/issues
Depends: R (>= 4.2)
Imports: cli, r4subcore, tibble
Suggests: knitr, metacore, pharmaverseadam, r4subdata, r4subprofile, r4subscore, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-08-31 17:07:11 UTC; alpine
Author: Pawan Rama Mali [aut, cre, cph]
Maintainer: Pawan Rama Mali <prm@outlook.in>
Repository: CRAN
Date/Publication: 2026-09-11 13:00:02 UTC

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Package pedFamilias updated to version 0.2.6 with previous version 0.2.5 dated 2026-05-17

Title: Import and Export 'Familias' Files
Description: Tools for exchanging pedigree data between the 'pedsuite' packages and the 'Familias' software for forensic kinship computations (Egeland et al. (2000) <doi:10.1016/s0379-0738(00)00147-x>). These functions were split out from the 'forrel' package to streamline maintenance and provide a lightweight alternative for packages otherwise independent of 'forrel'.
Author: Magnus Dehli Vigeland [aut, cre]
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

Diff between pedFamilias versions 0.2.5 dated 2026-05-17 and 0.2.6 dated 2026-09-11

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 build/partial.rdb           |binary
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 11 files changed, 142 insertions(+), 37 deletions(-)

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New package nbsurv with initial version 0.5.1
Package: nbsurv
Title: Conditional Naive Bayes Survival Modelling for Right-Censored Data
Version: 0.5.1
Description: Fits conditional naive Bayes survival models for right-censored outcomes using inverse-probability of censoring weighting. The package provides model fitting, prediction, resampling-based evaluation, cross-validation, hyper-parameter tuning, and permutation variable importance utilities for horizon-specific survival prediction. The model is the censored naive Bayes classifier of Wolfson et al. (2015) <doi:10.1002/sim.6526>, which combines the marginal Kaplan-Meier survivor function with horizon-specific class-conditional covariate densities and inverse-probability-of-censoring weights. Resampling evaluation uses the inverse-probability-of-censoring-weighted Brier score of Gerds and Schumacher (2006) <doi:10.1002/bimj.200610301>.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: graphics, survival, stats, utils
Suggests: knitr, pkgload, pec, quarto, ranger, rmarkdown, testthat
VignetteBuilder: knitr
URL: https://github.com/ielbadisy/nbsurv
BugReports: https://github.com/ielbadisy/nbsurv/issues
NeedsCompilation: no
Packaged: 2026-08-31 17:09:00 UTC; imad-el-badisy
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-11 12:50:02 UTC

More information about nbsurv at CRAN
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Package segmented updated to version 2.2-2 with previous version 2.2-1 dated 2026-01-29

Title: Regression Models with Break-Points / Change-Points Estimation (with Possibly Random Effects)
Description: Fitting regression models where, in addition to possible linear terms, one or more covariates have segmented (i.e., broken-line or piece-wise linear) or stepmented (i.e. piece-wise constant) effects. Multiple breakpoints for the same variable are allowed. The estimation method is discussed in Muggeo (2003, <doi:10.1002/sim.1545>) and illustrated in Muggeo (2008, <https://www.r-project.org/doc/Rnews/Rnews_2008-1.pdf>). An approach for hypothesis testing is presented in Muggeo (2016, <doi:10.1080/00949655.2016.1149855>), and interval estimation for the breakpoint is discussed in Muggeo (2017, <doi:10.1111/anzs.12200>). Segmented mixed models, i.e. random effects in the change point, are discussed in Muggeo (2014, <doi:10.1177/1471082X13504721>). Estimation of piecewise-constant relationships and changepoints (mean-shift models) is discussed in Fasola et al. (2018, <doi:10.1007/s00180-017-0740-4>).
Author: Vito M. R. Muggeo [aut, cre]
Maintainer: Vito M. R. Muggeo <vito.muggeo@unipa.it>

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Package nuggets updated to version 2.2.4 with previous version 2.2.3 dated 2026-08-20

Title: Fast and Extensible Pattern Discovery in Tabular Data
Description: Fast and extensible framework for discovering interesting patterns in tabular data. The package searches combinations of fuzzy or Boolean predicates and evaluates the resulting subgroups using statistical, logical, or structural measures. It supports a broad range of pattern-discovery tasks, including association rules (Agrawal et al., 1994, <https://www.vldb.org/conf/1994/P487.PDF>), contrast patterns (Chen, 2022, <doi:10.48550/arXiv.2209.13556>), emerging patterns (Dong et al., 1999, <doi:10.1145/312129.312191>), subgroup discovery (Atzmueller, 2015, <doi:10.1002/widm.1144>), and conditional correlations (Hájek, 1978, <doi:10.1007/978-3-642-66943-9>). User-defined functions may be supplied to guide custom pattern searches, making the framework applicable beyond traditional association-rule mining. Efficient implementation enables pattern discovery on large and dense data sets. Package includes methods for visualization and supports interactive explo [...truncated...]
Author: Michal Burda [aut, cre]
Maintainer: Michal Burda <michal.burda@osu.cz>

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Package mx.crypto updated to version 0.2.2 with previous version 0.2.1 dated 2026-08-04

Title: Matrix End-to-End Encryption Primitives
Description: 'Olm' and 'Megolm' encryption ratchet primitives for the 'Matrix' messaging protocol <https://matrix.org/>, wrapping the 'vodozemac' Rust crate. Provides device-key generation, one-time-key management, 1:1 'Olm' sessions, and 'Megolm' group sessions. Pairs with the 'mx.api' package, which handles 'Matrix' HTTP transport.
Author: Troy Hernandez [aut, cre] , cornball.ai [cph], The Matrix.org Foundation C.I.C. [ctb, cph] , Authors of the dependency Rust crates [ctb]
Maintainer: Troy Hernandez <troy@cornball.ai>

Diff between mx.crypto versions 0.2.1 dated 2026-08-04 and 0.2.2 dated 2026-09-11

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New package eidosapi with initial version 1.2.0
Package: eidosapi
Title: Connect to the Taxonomic Services of the Spanish Inventory of Natural Patrimony and Biodiversity
Version: 1.2.0
Description: Provides access to 'EIDOS' <https://iepnb.gob.es/areas-tematicas/especies-silvestres/eidos>, the taxonomic information service from the Spanish Inventory of Natural Patrimony and Biodiversity. This package includes a suite of functions that help retrieve species' taxonomic and conservation information from 'EIDOS' and match taxa names against the checklists available in the database. More information can be found at Miranda Cebrián, H. (2025) <doi:10.7818/ECOS.3134>.
License: GPL (>= 3)
Encoding: UTF-8
Imports: jsonlite, fuzzyjoin, readxl, curl, httr
URL: https://github.com/hmirceb/eidosapi
BugReports: https://github.com/hmirceb/eidosapi/issues
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-08-31 12:09:05 UTC; hector
Author: Hector Miranda-Cebrian [aut, cre, cph]
Maintainer: Hector Miranda-Cebrian <hectorm94@gmail.com>
Repository: CRAN
Date/Publication: 2026-09-11 12:00:09 UTC

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New package danlex with initial version 0.1.0
Package: danlex
Title: Access Danish Legislation from Retsinformation
Version: 0.1.0
Description: Provides access to Danish acts, regulations and treaties published by Retsinformation via its European Legislation Identifier (ELI) service. Part of the lexverse family of packages for legal and regulatory data.
License: MIT + file LICENSE
Depends: R (>= 4.1.0)
URL: https://github.com/KristianVepsalainen/danlex
BugReports: https://github.com/KristianVepsalainen/danlex/issues
Encoding: UTF-8
Imports: httr2, rlang, tibble, xml2
Suggests: knitr, rmarkdown, spelling, testthat (>= 3.0.0)
VignetteBuilder: knitr
Language: en-US
NeedsCompilation: no
Packaged: 2026-08-31 12:08:00 UTC; kristianvepsalainen
Author: Kristian Vepsaelaeinen [aut, cre]
Maintainer: Kristian Vepsaelaeinen <kristian.vepsalainen@proton.me>
Repository: CRAN
Date/Publication: 2026-09-11 12:00:15 UTC

More information about danlex at CRAN
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Package c3dr updated to version 0.2.1 with previous version 0.2.0 dated 2025-08-21

Title: Read and Write C3D Motion Capture Files
Description: A wrapper for the 'EZC3D' library to work with C3D motion capture data.
Author: Simon Nolte [aut, cre] , Benjamin Michaud [cph] , German Sport University Cologne [fnd] , Aymeric Stamm [rev] for rOpenSci, see <https://github.com/ropensci/software-review/issues/686>), July Pilowsky [rev] for rOpenSci, see <https://github.com/rop [...truncated...]
Maintainer: Simon Nolte <s.nolte@dshs-koeln.de>

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Package ipr updated to version 1.0.0 with previous version 0.1.0 dated 2020-03-20

Title: Iterative Proportional Repartition Algorithm
Description: Let us consider a sample of patients who can suffer from several diseases simultaneously, in a given set of diseases. The goal of the implemented algorithm is to estimate the individual average cost of each disease, starting from the global health costs available for each patient.
Author: Jean-Benoit Rossel [aut, cre], Valentin Rousson [aut], Yves Eggli [aut]
Maintainer: Jean-Benoit Rossel <jean-benoit.rossel@unisante.ch>

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Package htmlreportR updated to version 2.0.1 with previous version 1.0.0 dated 2024-08-19

Title: 'HTML' Reporting Made Simple(R)
Description: Create compressed, interactive 'HTML' (Hypertext Markup Language) reports with embedded 'Python' code, custom 'JS' ('JavaScript') and 'CSS' (Cascading Style Sheets), and wrappers for 'CanvasXpress' plots, networks and more. Based on <https://pypi.org/project/py-report-html/>, its sister project.
Author: Alvaro Esteban Martos [aut, cph, cre] , Jose Cordoba Caballero [aut, cph] , James Perkins [aut, cph] , Pedro Seoane Zonjic [aut, cph] , Jesus Perez Garcia [aut, cph]
Maintainer: Alvaro Esteban Martos <alvaroesteban@uma.es>

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Package cooltools updated to version 2.33 with previous version 2.18 dated 2025-07-23

Title: Practical Tools for Scientific Computation and Visualisation
Description: Provides utilities for scientific computation and visualisation, with an emphasis on applications in physics and astrophysics. Functionality includes random sampling from spherical and custom distributions, information and entropy analysis, Fourier transforms, two-point correlation estimation, binning and gridding of point sets, two-dimensional interpolation, Monte Carlo integration, vector operations, coordinate transformations, physical constants, and cosmological conversions. Graphics tools support the creation and export of publication-quality plots, animations, colour scales, map projections, and bitmap images. Several of these tools were used by Obreschkow et al. (2020) <doi:10.1093/mnras/staa445>.
Author: Danail Obreschkow [aut, cre]
Maintainer: Danail Obreschkow <danail.obreschkow@gmail.com>

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Package cABCanalysis updated to version 1.0.2 with previous version 1.0.1 dated 2026-06-09

Title: Computed ABC Analysis
Description: Identify the most relative data points by dividing a numeric data set into three classes A, B, and C, where class A items are the "import few", class C items are the "trivial many" with class B items being something in between, resembling the idea of the Pareto principle. This ABC classification is done using an ABC curve, which plots cumulative "Yield" against "Effort", similar to a Lorenz curve. Class borders are then precisely mathematically defined on that curve, aiding in interpretation. Based on: Ultsch A, Lotsch J (2015) "Computed ABC Analysis for rational Selection of most informative Variables in multivariate Data". PLoS ONE 10(6): e0129767. <doi:10.1371/journal.pone.0129767>.
Author: Jorn Lotsch [aut] , Andre Himmelspach [aut, cre]
Maintainer: Andre Himmelspach <himmelspach@med.uni-frankfurt.de>

Diff between cABCanalysis versions 1.0.1 dated 2026-06-09 and 1.0.2 dated 2026-09-11

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Package ENMeval updated to version 2.0.6 with previous version 2.0.5.2 dated 2025-05-01

Title: Automated Tuning and Evaluations of Ecological Niche Models
Description: Runs ecological niche models over all combinations of user-defined settings (i.e., tuning), performs cross validation to evaluate models, and returns data tables to aid in selection of optimal model settings that balance goodness-of-fit and model complexity. Also has functions to partition data spatially (or not) for cross validation, to plot multiple visualizations of results, to run null models to estimate significance and effect sizes of performance metrics, and to calculate range overlap between model predictions, among others. The package was originally built for Maxent models (Phillips et al. 2006, Phillips et al. 2017), but the current version allows possible extensions for any modeling algorithm. The extensive vignette, which guides users through most package functionality but unfortunately has a file size too big for CRAN, can be found here on the package's Github Pages website: <https://jamiemkass.github.io/ENMeval/articles/ENMeval-2.0-vignette.html>.
Author: Jamie M. Kass [aut, cre], Gonzalo E. Buitrago-Pinilla [aut], Robert Muscarella [aut], Peter J. Galante [aut], Corentin Bohl [aut], Robert A. Boria [aut], Mariano Soley-Guardia [aut], Robert P. Anderson [aut]
Maintainer: Jamie M. Kass <jamie.m.kass@gmail.com>

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Package pedprobr updated to version 1.1.1 with previous version 1.1.0 dated 2026-06-22

Title: Probability Computations on Pedigrees
Description: An implementation of the Elston-Stewart algorithm for calculating pedigree likelihoods given genetic marker data (Elston and Stewart (1971) <doi:10.1159/000152448>). The standard algorithm is extended to allow inbred founders. 'pedprobr' is part of the 'pedsuite', a collection of packages for pedigree analysis in R. In particular, 'pedprobr' depends on 'pedtools' for pedigree manipulations and 'pedmut' for mutation modelling. For more information, see 'Pedigree Analysis in R' (Vigeland, 2021, ISBN:9780128244302).
Author: Magnus Dehli Vigeland [aut, cre]
Maintainer: Magnus Dehli Vigeland <m.d.vigeland@medisin.uio.no>

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Package NetworkComparisonTest updated to version 2.2.4 with previous version 2.2.3 dated 2026-02-18

Title: Statistical Comparison of Two Networks Based on Several Invariance Measures
Description: This permutation based hypothesis test, suited for several types of data supported by the estimateNetwork function of the bootnet package (Epskamp & Fried, 2018), assesses the difference between two networks based on several invariance measures (network structure invariance, global strength invariance, edge invariance, several centrality measures, etc.). Network structures are estimated with l1-regularization. The Network Comparison Test is suited for comparison of independent (e.g., two different groups) and dependent samples (e.g., one group that is measured twice). See van Borkulo et al. (2021), available from <doi:10.1037/met0000476>.
Author: Claudia van Borkulo [aut], Sacha Epskamp [aut], Payton Jones [aut], Jonas Haslbeck [ctb], Alex Millner [ctb], Karoline Huth [ctb], Don van den Bergh [cre]
Maintainer: Don van den Bergh <D.vandenBergh@tilburguniversity.edu>

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Package ivdtools updated to version 0.2.5 with previous version 0.1.3 dated 2026-08-23

Title: Statistical Tools for Evaluation of in Vitro Diagnostic Reagents
Description: Provides statistical workflows used in the evaluation of in vitro diagnostic reagents. Facilities include method comparison, commutability assessment, Bland-Altman and receiver operating characteristic analysis, qualitative agreement, C5 and C95 estimation, precision and variance-component analysis, linearity, interference, dilution and spiking studies, high-dose hook assessment, measurement uncertainty, reference-material bias, reference intervals, stability studies, quality-control charts, curve fitting, analytical sensitivity, outlier and normality assessment, and sample-size calculations. For methodological details, see Bland and Altman (1986) <doi:10.1016/S0140-6736(86)90837-8>, Passing and Bablok (1983) <doi:10.1515/cclm.1983.21.11.709>, Linnet (1993) <doi:10.1093/clinchem/39.3.424>, Hawkins and Kraker (2026) <doi:10.1093/jalm/jfaf183>, Hanley and McNeil (1982) <doi:10.1148/radiology.143.1.7063747>, Horn et al. (1998) <doi:10.1093/clinchem/44.3.62 [...truncated...]
Author: hiox-tech [cph, aut, cre]
Maintainer: hiox-tech <GeorgeBinDragon@outlook.com>

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Package hdf5r updated to version 1.3.16 with previous version 1.3.15 dated 2026-09-07

Title: Interface to the 'HDF5' Binary Data Format
Description: 'HDF5' is a data model, library and file format for storing and managing large amounts of data. This package provides a nearly feature complete, object oriented wrapper for the 'HDF5' API <https://support.hdfgroup.org/documentation/hdf5/latest/_r_m.html> using R6 classes. Additionally, functionality is added so that 'HDF5' objects behave very similar to their corresponding R counterparts.
Author: Holger Hoefling [aut, cre], Mario Annau [aut], Novartis Institute for BioMedical Research [cph]
Maintainer: Holger Hoefling <hhoeflin@gmail.com>

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Package wcswatin updated to version 0.2.0 with previous version 0.1.1 dated 2026-07-19

Title: Weather and Climate Inputs for 'SWAT'
Description: Provides workflows to prepare weather and climate time series from gridded and station data for 'SWAT' ('Soil and Water Assessment Tool'). Supports data extraction, aggregation, interpolation, quality control, unit conversion, and export of per-location model input files. For the underlying model, see Arnold et al. (1998) "Large Area Hydrologic Modeling and Assessment Part I: Model Development" <doi:10.1111/j.1752-1688.1998.tb05961.x>.
Author: Reginal Exavier [aut, cre] , Fernando Shinji Kawakubo [aut] , Peter Zeilhofer [aut]
Maintainer: Reginal Exavier <reginalexavier@rocketmail.com>

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Package VIM updated to version 7.3.1 with previous version 7.3.0 dated 2026-09-02

Title: Visualization and Imputation of Missing Values
Description: Provides methods for imputation and visualization of missing values. It includes graphical tools to explore the amount, structure and patterns of missing and/or imputed values, supporting exploratory data analysis and helping to investigate potential missingness mechanisms (details in Alfons, Templ and Filzmoser, <doi:10.1007/s11634-011-0102-y>). The quality of imputations can be assessed visually using a wide range of univariate, bivariate and multivariate plots. The package further provides several imputation methods, including efficient implementations of k-nearest neighbour and hot-deck imputation (Kowarik and Templ 2013, <doi:10.18637/jss.v074.i07>), iterative robust model-based multiple imputation (Templ 2011, <doi:10.1016/j.csda.2011.04.012>; Templ 2023, <doi:10.3390/math11122729>), and machine learning–based approaches such as robust GAM-based multiple imputation (Templ 2024, <doi:10.1007/s11222-024-10429-1>) as well as random forest and gradient b [...truncated...]
Author: Matthias Templ [aut, cre], Alexander Kowarik [aut] , Andreas Alfons [aut], Johannes Gussenbauer [aut], Nina Niederhametner [aut], Eileen Vattheuer [aut], Gregor de Cillia [aut], Bernd Prantner [ctb], Wolfgang Rannetbauer [aut]
Maintainer: Matthias Templ <matthias.templ@gmail.com>

Diff between VIM versions 7.3.0 dated 2026-09-02 and 7.3.1 dated 2026-09-11

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Package spatstat.utils updated to version 3.2-5 with previous version 3.2-4 dated 2026-07-16

Title: Utility Functions for 'spatstat'
Description: Contains utility functions for the 'spatstat' family of packages which may also be useful for other purposes.
Author: Adrian Baddeley [aut, cre] , Rolf Turner [aut] , Ege Rubak [aut]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.utils versions 3.2-4 dated 2026-07-16 and 3.2-5 dated 2026-09-11

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Package simr updated to version 1.0.11 with previous version 1.0.10 dated 2026-08-01

Title: Power Analysis for Generalised Linear Mixed Models by Simulation
Description: Calculate power for generalised linear mixed models, using simulation. Designed to work with models fit using the 'lme4' package. Described in Green and MacLeod, 2016 <doi:10.1111/2041-210X.12504>.
Author: Peter Green [aut, cre] , Catriona MacLeod [aut], Phillip Alday [ctb]
Maintainer: Peter Green <simr.peter@gmail.com>

Diff between simr versions 1.0.10 dated 2026-08-01 and 1.0.11 dated 2026-09-11

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New package ICESat2VegR with initial version 0.0.1
Package: ICESat2VegR
Title: ICESat-2 Data Analysis for Land and Vegetation
Version: 0.0.1
Description: Provides tools for downloading, reading, processing, visualizing, and exporting NASA's ICESat-2 ATL03 (Global Geolocated Photon Data) and ATL08 (Land and Vegetation Height) products. Supports photon- and segment-level analysis, spatial sampling, gridding, statistical and machine-learning modeling, and integration with 'Google Earth Engine' (<https://earthengine.google.com/>) for wall-to-wall mapping of vegetation structure and other land attributes.
Depends: R (>= 4.1.0)
Imports: curl, data.table, sf, fs, getPass, geojsonsf, googledrive, googleCloudStorageR, grDevices, jsonlite, httr2, magrittr, mathjaxr, methods, Rcpp, Rdpack, R6, randomForest, reticulate, terra, dplyr, servr, stringr, xml2
Encoding: UTF-8
URL: https://github.com/carlos-alberto-silva/ICESat2VegR
BugReports: https://github.com/carlos-alberto-silva/ICESat2VegR/issues
NeedsCompilation: yes
BuildManual: TRUE
Suggests: chromote, devtools, ggplot2, grid, gridExtra, hdf5r, htmlwidgets, knitr, leaflet, leafsync, lwgeom, mapview, png, rmarkdown, rstudioapi, signal, stars, testthat (>= 3.0.0), webshot, viridis, withr
LinkingTo: Rcpp
SystemRequirements: - GDAL (>= 3.0.0) - PROJ (>= 6.0.0) - HDF5 (>= 1.8.13)
License: GPL (>= 3)
Packaged: 2026-09-10 17:24:06 UTC; carlo
Author: Carlos Alberto Silva [aut, cph, cre], Caio Hamamura [aut, cph], Cesar Alvites [aut, ctb], Alexander J. Gaskins [aut, ctb], Sunil Arya [ctb, cph] ), David Mount [ctb, cph] ), University of Maryland [cph] ), Chuck Gantz [ctb] , Cole Krehbiel [ctb]
Maintainer: Carlos Alberto Silva <c.silva@ufl.edu>
Repository: CRAN
Date/Publication: 2026-09-11 07:10:09 UTC

More information about ICESat2VegR at CRAN
Permanent link

Package grattanInflators updated to version 0.6.0 with previous version 0.5.7 dated 2026-01-12

Title: Inflators for Australian Policy Analysis
Description: Using Australian Bureau of Statistics indices, provides functions that convert historical, nominal statistics to real, contemporary values without worrying about date input quality, performance, or the ABS catalogue.
Author: Hugh Parsonage [aut, cre]
Maintainer: Hugh Parsonage <hugh.parsonage@gmail.com>

Diff between grattanInflators versions 0.5.7 dated 2026-01-12 and 0.6.0 dated 2026-09-11

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More information about grattanInflators at CRAN
Permanent link

Package crmn updated to version 0.0.22 with previous version 0.0.21 dated 2020-02-10

Title: CCMN and Other Normalization Methods for Metabolomics Data
Description: Implements the Cross-contribution Compensating Multiple standard Normalization (CCMN) method described in Redestig et al. (2009) Analytical Chemistry <doi:10.1021/ac901143w> and other normalization algorithms.
Author: Henning Redestig [aut, cre]
Maintainer: Henning Redestig <henning.red@gmail.com>

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Package afc updated to version 1.5.0 with previous version 1.4.0 dated 2017-05-18

Title: Generalized Discrimination Score
Description: This is an implementation of the Generalized Discrimination Score (also known as Two Alternatives Forced Choice Score, 2AFC) for various representations of forecasts and verifying observations. The Generalized Discrimination Score is a generic forecast verification framework which can be applied to any of the following verification contexts: dichotomous, polychotomous (ordinal and nominal), continuous, probabilistic, and ensemble. A comprehensive description of the Generalized Discrimination Score, including all equations used in this package, is provided by Mason and Weigel (2009).
Author: Andreas Weigel [aut], MeteoSwiss [cph], Jonas Bhend [cre, aut]
Maintainer: Jonas Bhend <jonas.bhend@meteoswiss.ch>

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Package spatialkit updated to version 2.0.0 with previous version 1.0.0 dated 2026-08-07

Title: Spatial Tessellation, Modeling, and Cross-Validation Toolkit
Description: Constructs analysis regions from the distribution of the data itself, as an alternative to aggregating onto administrative boundaries that were drawn for unrelated purposes. Seeds and builds Voronoi, Delaunay, hexagonal and square tessellations with reproducible identifiers, selects a cell count from the spatial structure of the observations, assigns features to cells, and aggregates to cell level with optional design-effect corrections so that standard errors account for within-cell autocorrelation. Also manages coordinate reference systems. Fits geographically weighted regression (via 'GWmodel'; Lu et al. (2014) <doi:10.1080/10095020.2014.917453>), Bayesian spatial Gaussian process regression (via 'brms', using the Hilbert space approximation of Riutort-Mayol et al. (2023) <doi:10.1007/s11222-022-10167-2>) and random forests (via 'ranger', with the permutation importance of Strobl et al. (2007) <doi:10.1186/1471-2105-8-25>), each behind one S3 class with consistent [...truncated...]
Author: Justin Chase [aut, cre, cph]
Maintainer: Justin Chase <jchase.msu@gmail.com>

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Package sommer updated to version 4.4.7 with previous version 4.4.6 dated 2026-07-09

Title: Solving Mixed Model Equations in R
Description: Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>; Jensen et al., 1997). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number of records) or using the Henderson-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available.
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>

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Package sf updated to version 1.1-3 with previous version 1.1-2 dated 2026-07-23

Title: Simple Features for R
Description: Support for simple feature access, a standardized way to encode and analyze spatial vector data. Binds to 'GDAL' <doi:10.5281/zenodo.5884351> for reading and writing data, to 'GEOS' <doi:10.5281/zenodo.11396894> for geometrical operations, and to 'PROJ' <doi:10.5281/zenodo.5884394> for projection conversions and datum transformations. Uses by default the 's2' package for geometry operations on geodetic (long/lat degree) coordinates.
Author: Edzer Pebesma [aut, cre] , Roger Bivand [ctb] , Etienne Racine [ctb], Michael Sumner [ctb], Ian Cook [ctb], Tim Keitt [ctb], Robin Lovelace [ctb], Hadley Wickham [ctb], Jeroen Ooms [ctb] , Kirill Mueller [ctb], Thomas Lin Pedersen [ctb], Dan Baston [c [...truncated...]
Maintainer: Edzer Pebesma <edzer.pebesma@uni-muenster.de>

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Package RCppAD updated to version 1.20260000.0-1 with previous version 1.20260000.0 dated 2026-08-07

Title: 'CppAD' C++ Header Files for Automatic Differentiation
Description: Provides the 'CppAD' C++ header library for automatic differentiation, for use by R packages via LinkingTo. Headers are vendored with CRAN-safe defaults and R-safe error handling that does not call std::cerr or std::exit. The two final components of the version number are the 'CppAD' release number.
Author: Patrick Brown [aut, cre, cph], Bradley M. Bell [aut, cph] , COIN-OR Foundation [cph]
Maintainer: Patrick Brown <patrick.borgnine@gmail.com>

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Package MBHdesign readmission to version 2.3.22 with previous version 2.3.15 dated 2023-09-25

Title: Spatial Designs for Ecological and Environmental Surveys
Description: Provides spatially survey balanced designs. Information about the package itself is given in Foster (2021) <doi:10.1111/2041-210X.13535>. Designs using MBHdesign can: 1) accommodate, without substantial detrimental effects on spatial balance, legacy sites (Foster et al., 2017 <doi:10.1111/2041-210X.12782>); 2) be based on points or transects (foster et al. 2020 <doi:10.1111/2041-210X.13321> and produce clustered samples (Foster et al. (in press). The base idea that these designs stem from is the quasi-random number method described Robinson et al. (2013) <doi:10.1111/biom.12059> and adjusted in Robinson et al. (2017) <doi:10.1016/j.spl.2017.05.004>.
Author: Scott D. Foster [aut], Scott Foster [cre]
Maintainer: Scott Foster <scott.foster@csiro.au>

This is a re-admission after prior archival of version 2.3.15 dated 2023-09-25

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Package lme4breeding updated to version 1.1.4 with previous version 1.1.3 dated 2026-07-12

Title: Breeding-Related Mixed-Effects Models
Description: Fit relationship-based and customized mixed-effects models with complex variance-covariance structures using the 'lme4' machinery. The core computational algorithms are implemented using the 'Eigen' 'C++' library for numerical linear algebra and 'RcppEigen' 'glue'.
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>

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Package healthiar updated to version 0.2.6 with previous version 0.2.5 dated 2026-08-21

Title: Quantifying and Monetizing Health Impacts Attributable to Exposure
Description: This R package has been developed with a focus on air pollution and noise but can be applied to other exposures. The initial development has been funded by the European Union project BEST-COST. Disclaimer: It is work in progress and the developers are not liable for any calculation errors or inaccuracies resulting from the use of this package. Selection of relevant references (in chronological order): WHO (2003) <https://www.who.int/publications/i/item/9241546204>, Murray et al. (2003) <doi:10.1186/1478-7954-1-1>, Miller & Hurley (2003) <doi:10.1136/jech.57.3.200>, Steenland & Armstrong (2006) <doi:10.1097/01.ede.0000229155.05644.43>, WHO (2011) <https://iris.who.int/items/723ab97c-5c33-4e3b-8df1-744aa5bc1c27>, GBD 2019 Risk Factors Collaborators (2020) <doi:10.1016/S0140-6736(20)30752-2>.
Author: Alberto Castro [cre, aut] , Axel Luyten [aut] , Arno Pauwels [ctb] , Liliana Vazquez Fernandez [ctb] , Gianni Ardielli [ctb] , Iracy Pimenta [ctb] , Susanne Breitner [ctb] , Carl Baravelli [ctb] , Vanessa Gorasso [ctb] , Maria Lepnurm [ctb] , Andreia [...truncated...]
Maintainer: Alberto Castro <alberto.castrofernandez@swisstph.ch>

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Package ggscribe updated to version 1.0.0 with previous version 0.2.0 dated 2026-07-06

Title: Publication-Quality 'ggplot2' Annotation
Description: Annotation helper functions for publication-quality 'ggplot2' visualisation. These functions make it easier to annotate plots in a way that stays consistent with the set theme.
Author: David Hodge [aut, cre, cph]
Maintainer: David Hodge <davidhodge931@gmail.com>

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Package ggRandomForests updated to version 3.5.3 with previous version 3.5.2 dated 2026-08-21

Title: Visually Exploring Random Forests
Description: Graphic elements for exploring Random Forests using the 'randomForest' or 'randomForestSRC' package for survival, regression and classification forests and 'ggplot2' package plotting. Implements visualizations of the methods described in Breiman (2001) <doi:10.1023/A:1010933404324> and Ishwaran, Kogalur, Blackstone, and Lauer (2008) <doi:10.1214/08-AOAS169>.
Author: John Ehrlinger [aut, cre]
Maintainer: John Ehrlinger <john.ehrlinger@gmail.com>

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Package gcTensor updated to version 1.0.1 with previous version 1.0.0 dated 2023-07-06

Title: Generalized Coupled Tensor Factorization
Description: Multiple matrices/tensors can be specified and decomposed simultaneously by Probabilistic Latent Tensor Factorisation (PLTF). See the reference section of GitHub README.md <https://github.com/rikenbit/gcTensor>, for details of the method.
Author: Koki Tsuyuzaki [aut, cre]
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

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Package evola updated to version 1.0.9 with previous version 1.0.8 dated 2026-07-20

Title: Evolutionary Algorithm
Description: Runs an evolutionary algorithm using the 'AlphaSimR' machinery <doi:10.1093/g3journal/jkaa017> .
Author: Giovanny Covarrubias-Pazaran [aut, cre]
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>

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Package LiblineaR updated to version 2.10-25 with previous version 2.10-24 dated 2024-09-13

Title: Linear Predictive Models Based on the LIBLINEAR C/C++ Library
Description: A wrapper around the LIBLINEAR C/C++ library for machine learning (available at <https://www.csie.ntu.edu.tw/~cjlin/liblinear/>). LIBLINEAR is a simple library for solving large-scale regularized linear classification and regression. It currently supports L2-regularized classification (such as logistic regression, L2-loss linear SVM and L1-loss linear SVM) as well as L1-regularized classification (such as L2-loss linear SVM and logistic regression) and L2-regularized support vector regression (with L1- or L2-loss). The main features of LiblineaR include multi-class classification (one-vs-the rest, and Crammer & Singer method), cross validation for model selection, probability estimates (logistic regression only) or weights for unbalanced data. The estimation of the models is particularly fast as compared to other libraries.
Author: Thibault Helleputte [cre, aut, cph], Jerome Paul [aut], Pierre Gramme [aut], Chih-Jen Lin [cph] ; see LICENSE.note)
Maintainer: Thibault Helleputte <thibault.helleputte@dnalytics.com>

Diff between LiblineaR versions 2.10-24 dated 2024-09-13 and 2.10-25 dated 2026-09-11

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More information about LiblineaR at CRAN
Permanent link

Package arules updated to version 1.7.15 with previous version 1.7.14 dated 2026-03-29

Title: Mining Association Rules and Frequent Itemsets
Description: Provides the infrastructure for representing, manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides C implementations of the association mining algorithms Apriori and Eclat. Hahsler, Gruen and Hornik (2005) <doi:10.18637/jss.v014.i15>.
Author: Michael Hahsler [aut, cre, cph] , Christian Buchta [aut, cph], Bettina Gruen [aut, cph], Kurt Hornik [aut, cph] , Christian Borgelt [ctb, cph], Ian Johnson [ctb], Makhlouf Ledmi [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>

Diff between arules versions 1.7.14 dated 2026-03-29 and 1.7.15 dated 2026-09-11

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More information about arules at CRAN
Permanent link


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