Fri, 18 Sep 2026

Package veesa updated to version 0.1.8 with previous version 0.1.7 dated 2025-12-04

Title: Pipeline for Explainable Machine Learning with Functional Data
Description: Implements the Variable importance Explainable Elastic Shape Analysis pipeline for explainable machine learning with functional data inputs. Converts training and testing data functional inputs to elastic shape analysis principal components that account for vertical and/or horizontal variability. Computes feature importance to identify important principal components and visualizes variability captured by functional principal components. See Goode et al. (2025) <doi:10.48550/arXiv.2501.07602> for technical details about the methodology.
Author: Katherine Goode [cre, aut], J. Derek Tucker [aut], Sandia National Laboratories [cph, fnd]
Maintainer: Katherine Goode <kjgoode@sandia.gov>

Diff between veesa versions 0.1.7 dated 2025-12-04 and 0.1.8 dated 2026-09-18

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Package supportR updated to version 1.6.1 with previous version 1.6.0 dated 2025-12-21

Title: Support Functions for Wrangling and Visualization
Description: Suite of helper functions for data wrangling and visualization. The only theme for these functions is that they tend towards simple, short, and narrowly-scoped. These functions are built for tasks that often recur but are not large enough in scope to warrant an ecosystem of interdependent functions.
Author: Nicholas J Lyon [aut, cre, cph]
Maintainer: Nicholas J Lyon <nickjlyon@gmail.com>

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Package multigroup.vaccine updated to version 0.1.2 with previous version 0.1.1 dated 2026-02-09

Title: Analyze Outbreak Models of Multi-Group Populations with Vaccination
Description: Model infectious disease dynamics in populations with multiple subgroups having different vaccination rates, transmission characteristics, and contact patterns. Calculate final and intermediate outbreak sizes, form age-structured contact models with automatic fetching of U.S. census data, and explore vaccination scenarios with an interactive 'shiny' dashboard for a model with two subgroups, as described in Nguyen et al. (2024) <doi:10.1016/j.jval.2024.03.039> and Duong et al. (2026) <doi:10.1093/ofid/ofaf695.217>.
Author: Damon Toth [aut, cre, cph] , Jake Wagoner [aut] , Willy Ray [aut], George Vega Yon [ctb] , Centers for Disease Control and Prevention's Center for Forecasting and Outbreak Analytics [fnd]
Maintainer: Damon Toth <damon.toth@hsc.utah.edu>

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Package markovchain updated to version 1.1.1 with previous version 1.0.0 dated 2026-08-25

Title: Easy Handling Discrete Time Markov Chains
Description: Functions and S4 methods to create and manage discrete time Markov chains more easily. In addition functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of their structural proprieties) analysis are provided. See Spedicato (2017) <doi:10.32614/RJ-2017-036>. Some functions for continuous times Markov chains depend on the suggested ctmcd package.
Author: Giorgio Alfredo Spedicato [aut, cre] , Tae Seung Kang [aut], Sai Bhargav Yalamanchi [aut], Mildenberger Thoralf [ctb] , Deepak Yadav [aut], Ignacio Cordon [aut] , Vandit Jain [ctb], Toni Giorgino [ctb] , Richel J.C. Bilderbeek [ctb] , Daniel Ebbert [ [...truncated...]
Maintainer: Giorgio Alfredo Spedicato <spedicato_giorgio@yahoo.it>

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Package ltertools updated to version 2.1.1 with previous version 2.1.0 dated 2025-09-02

Title: Tools Developed by the Long Term Ecological Research Community
Description: Set of the data science tools created by various members of the Long Term Ecological Research (LTER) community. These functions were initially written largely as standalone operations and have later been aggregated into this package.
Author: Nicholas Lyon [aut, cre] , Angel Chen [aut] , Miguel C. Leon [ctb] , National Science Foundation [fnd] , University of California, Santa Barbara [cph]
Maintainer: Nicholas Lyon <nickjlyon@gmail.com>

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Package finto updated to version 0.1.2 with previous version 0.1.1 dated 2025-11-24

Title: Access the 'Finto' API
Description: Access and retrieve vocabulary data 'Finto' API <https://api.finto.fi/>, which is a centralized service for interoperable thesauri, ontology and classification schemes for different subject areas.
Author: Akewak Jeba [aut, cre] , Leo Lahti [aut]
Maintainer: Akewak Jeba <akewak84@gmail.com>

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Package dndR updated to version 3.1.1 with previous version 3.1.0 dated 2025-06-11

Title: Dungeons & Dragons Functions for Players and Dungeon Masters
Description: The goal of 'dndR' is to provide a suite of Dungeons & Dragons related functions. This package is meant to be useful both to players and Dungeon Masters (DMs). Some functions apply to many tabletop role-playing games (e.g., dice rolling), but others are focused on Fifth Edition (a.k.a. "5e") and where possible both the 2014 and 2024 versions are supported.
Author: Nicholas Lyon [aut, cre, cph] , Tim Schatto-Eckrodt [aut] , Humberto Nappo [aut] , Billy Mitchell [aut]
Maintainer: Nicholas Lyon <nickjlyon@gmail.com>

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Package prais updated to version 1.2.0 with previous version 1.1.4 dated 2025-06-25

Title: Prais-Winsten Estimator for AR(1) Serial Correlation
Description: The Prais-Winsten estimator (Prais & Winsten, 1954) takes into account AR(1) serial correlation of the errors in a linear regression model. The procedure recursively estimates the coefficients and the error autocorrelation of the specified model until sufficient convergence of the AR(1) coefficient is attained.
Author: Franz X. Mohr [aut, cre] , Michael Skvrňak [ctb]
Maintainer: Franz X. Mohr <franz.x.mohr@outlook.com>

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Package OptSurvCutR updated to version 0.11.1 with previous version 0.10.0 dated 2026-06-30

Title: Optimal Survival Cut-Point Discovery for Time-to-Event Analysis with 'OptSurvCutR'
Description: Provides a robust workflow for optimal cut-point analysis in time-to-event ('survival') data. Functions determine the optimal number of cut-points via find_cutpoint_number(), find their precise locations via find_cutpoint() using systematic or genetic algorithms (via the 'rgenoud' package), and validate stability via bootstrapping using validate_cutpoint(). Features include covariate adjustment, parallel processing, and an extensible S3 plotting engine for clinical dashboards and diagnostics.
Author: Payton Yau [aut, cre, cph] , Suhirthakumar Puvanendran [aut]
Maintainer: Payton Yau <tungon@gmail.com>

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Package getRad updated to version 0.4.0 with previous version 0.3.0 dated 2026-06-11

Title: Download Radar Data for Biological Research
Description: Load polar volume and vertical profile data for aeroecological research directly into R. With 'getRad' you can access data from several sources in Europe and the US and standardize it to facilitate further exploration in tools such as 'bioRad'.
Author: Bart Kranstauber [aut, cre] , Pieter Huybrechts [aut] ), Peter Desmet [aut] ), Cecilia Nilsson [ctb] , Alexander Tedeschi [ctb] , Hidde Leijnse [ctb] , Bart Hoekstra [ctb] , University of Amsterdam [cph] , Biodiversa+ [fnd]
Maintainer: Bart Kranstauber <b.kranstauber@uva.nl>

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Package csmbuilder updated to version 0.1.1 with previous version 0.1.0 dated 2026-04-03

Title: A Collection of Tools for Building Cropping System Models
Description: A collection of tools for designing, implementing, testing, documenting and visualizing dynamic simulation cropping system models. Models are specified as a combination of state variables, parameters, intermediate factors and input data that define a system of ordinary differential equations. Specified models can be used to simulate dynamic processes using numerical integration algorithms.
Author: Phillip D Alderman [aut, cre], Pratishtha Poudel [aut]
Maintainer: Phillip D Alderman <phillip.alderman@okstate.edu>

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Package oenb updated to version 0.1.0 with previous version 0.0.2 dated 2021-03-22

Title: Tools for the OeNB Data Web Service
Description: Tools to access data from the data web service of the Oesterreichische Nationalbank (OeNB), <https://www.oenb.at/en/Statistics/User-Defined-Tables/webservice.html>.
Author: Franz X. Mohr [aut, cre]
Maintainer: Franz X. Mohr <franz.x.mohr@outlook.com>

Diff between oenb versions 0.0.2 dated 2021-03-22 and 0.1.0 dated 2026-09-18

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Package jmastats updated to version 0.3.1 with previous version 0.3.0 dated 2025-01-27

Title: Download Weather Data from Japan Meteorological Agency Website
Description: Provides features that allow users to download weather data published by the Japan Meteorological Agency (JMA) website (<https://www.jma.go.jp/jma/index.html>). The data includes information dating back to 1976 and aligns with the categories available on the website. Additionally, users can process the best track data of typhoons and easily handle earthquake record files.
Author: Shinya Uryu [aut, cph, cre]
Maintainer: Shinya Uryu <suika1127@gmail.com>

Diff between jmastats versions 0.3.0 dated 2025-01-27 and 0.3.1 dated 2026-09-18

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Package fastkmedoids updated to version 1.7 with previous version 1.6 dated 2026-03-26

Title: Faster K-Medoids Clustering Algorithms: FastPAM, FastCLARA, FastCLARANS
Description: R wrappers of C++ implementation of Faster K-Medoids clustering algorithms (FastPAM, FastCLARA and FastCLARANS) proposed in Erich Schubert, Peter J. Rousseeuw 2019 <doi:10.1007/978-3-030-32047-8_16>.
Author: Xun Li [aut, cre]
Maintainer: Xun Li <lixun910@gmail.com>

Diff between fastkmedoids versions 1.6 dated 2026-03-26 and 1.7 dated 2026-09-18

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Package ctreeMI updated to version 1.1.0 with previous version 1.0.1 dated 2026-08-26

Title: Conditional Inference Trees with Stacked Multiple Imputation
Description: Implements the stacked-imputation workflow for conditional inference trees ('ctree') described in Sherlock et al. (2026) <doi:10.1080/00273171.2026.2661244>. When data contain missing values, multiply imputed datasets (e.g., from 'mice') are stacked vertically and a single 'ctree' is fit on the combined data. To correct for the artificially inflated sample size introduced by stacking, every node-level test statistic is divided by the number of imputations M, the node-level p-values are recomputed from the chi-squared reference distribution 'ctree' uses (including its multiplicity adjustment across candidate splitting variables), and the tree is compressed bottom-up (the Stack/M correction). Degrees of freedom are derived for each node and each candidate variable, so univariate, bivariate and higher-dimensional outcomes are all handled, as are unordered factor predictors, whose degrees of freedom depend on how many levels remain in a node. The result is a single interpretable tree [...truncated...]
Author: Phillip Sherlock [aut, cre]
Maintainer: Phillip Sherlock <phillip.sherlock@ufl.edu>

Diff between ctreeMI versions 1.0.1 dated 2026-08-26 and 1.1.0 dated 2026-09-18

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Package opalr updated to version 3.7.0 with previous version 3.6.1 dated 2026-05-27

Title: 'Opal' Data Repository Client and 'DataSHIELD' Utils
Description: Data integration Web application for biobanks by 'OBiBa'. 'Opal' is the core database application for biobanks. Participant data, once collected from any data source, must be integrated and stored in a central data repository under a uniform model. 'Opal' is such a central repository. It can import, process, validate, query, analyze, report, and export data. 'Opal' is typically used in a research center to analyze the data acquired at assessment centres. Its ultimate purpose is to achieve seamless data-sharing among biobanks. This 'Opal' client allows to interact with 'Opal' web services and to perform operations on the R server side. 'DataSHIELD' administration tools are also provided.
Author: Yannick Marcon [aut, cre] , Amadou Gaye [ctb] , OBiBa group [cph]
Maintainer: Yannick Marcon <yannick.marcon@obiba.org>

Diff between opalr versions 3.6.1 dated 2026-05-27 and 3.7.0 dated 2026-09-18

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Package nflplotR updated to version 1.7.0 with previous version 1.6.0 dated 2025-11-14

Title: NFL Logo Plots in 'ggplot2' and 'gt'
Description: A set of functions to visualize National Football League analysis in 'ggplot2' plots and 'gt' tables.
Author: Sebastian Carl [aut, cre]
Maintainer: Sebastian Carl <mrcaseb@gmail.com>

Diff between nflplotR versions 1.6.0 dated 2025-11-14 and 1.7.0 dated 2026-09-18

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Permanent link

Package huggingfaceR updated to version 2.3.0 with previous version 2.2.0 dated 2026-08-29

Title: Access 'Hugging Face' Models and Datasets
Description: Access models and datasets hosted on the 'Hugging Face' Hub through its Inference Application Programming Interface (API). Run text classification, embeddings, chat, translation, image, audio, and other tasks from tidy 'R' workflows without installing 'Python' by default. Results are returned as data frames or simple 'R' objects so they can be composed with 'dplyr', 'tidyr', and related tooling. Helpers also support Hub search, file download, provider discovery, and guarded uploads for authenticated workflows. Optional local embeddings and text classification use 'Python' through 'reticulate'.
Author: Alex Farach [aut, cre, cph], Sam Terfa [aut, cph], Jack Penzer [aut, cph]
Maintainer: Alex Farach <alexfarach@gmail.com>

Diff between huggingfaceR versions 2.2.0 dated 2026-08-29 and 2.3.0 dated 2026-09-18

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More information about huggingfaceR at CRAN
Permanent link

Package RealVAMS updated to version 0.5.0 with previous version 0.4-6 dated 2024-04-05

Title: Multivariate VAM Fitting
Description: Fits a multivariate value-added model (VAM), see Broatch, Green, and Karl (2018) <doi:10.32614/RJ-2018-033> and Broatch and Lohr (2012) <doi:10.3102/1076998610396900>, with normally distributed test scores and a binary outcome indicator. A pseudo-likelihood approach, Wolfinger (1993) <doi:10.1080/00949659308811554>, is used for the estimation of this joint generalized linear mixed model. The inner loop of the pseudo-likelihood routine (estimation of a linear mixed model) occurs in the framework of the EM algorithm presented by Karl, Yang, and Lohr (2013) <DOI:10.1016/j.csda.2012.10.004>. This material is based upon work supported by the National Science Foundation under grants DRL-1336027 and DRL-1336265.
Author: Andrew Karl [cre, aut] , Jennifer Broatch [aut], Jennifer Green [aut]
Maintainer: Andrew Karl <akarl@asu.edu>

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Package mvglmmRank updated to version 1.2-6 with previous version 1.2-5 dated 2026-06-09

Title: Multivariate Generalized Linear Mixed Models for Ranking Sports Teams
Description: Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation as documented by Broatch and Karl (2018) <doi:10.48550/arXiv.1710.05284>, Karl, Yang, and Lohr (2014) <doi:10.1016/j.csda.2013.11.019>, and by Karl (2012) <doi:10.1515/1559-0410.1471>. Karl and Zimmerman <doi:10.1016/j.jspi.2020.06.004> use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling.
Author: Andrew T. Karl [cre, aut] , Jennifer Broatch [aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

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Package GPvam updated to version 3.3-0 with previous version 3.2-0 dated 2024-12-12

Title: Maximum Likelihood Estimation of Multiple Membership Mixed Models Used in Value-Added Modeling
Description: An EM algorithm, Karl et al. (2013) <doi:10.1016/j.csda.2012.10.004>, estimates generalized, reduced generalized, variable, complete, and zero persistence models by maximum likelihood or restricted maximum likelihood (the default). These are multiple-membership linear mixed models with teachers modeled as "G-side" effects and students modeled with either "G-side" or "R-side" effects; see Mariano et al. (2010) <doi:10.3102/1076998609346967>.
Author: Andrew Karl [cre, aut] , Yan Yang [aut], Sharon Lohr [aut]
Maintainer: Andrew Karl <akarl@asu.edu>

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Package glmmFEL updated to version 1.0.6 with previous version 1.0.5 dated 2026-01-09

Title: Generalized Linear Mixed Models via Fully Exponential Laplace in EM
Description: Fit generalized linear mixed models (GLMMs) with normal random effects using first-order Laplace, fully exponential Laplace (FEL) with mean-only corrections, and FEL with mean and variance-diagonal corrections in the E-step of an expectation-maximization (EM) algorithm. The current development version provides a matrix-based interface (y, X, Z) and supports binary logit and probit, and Poisson log-link models. An EM framework is used to update fixed effects, random effects, and a single variance component tau^2 for G = tau^2 I, with staged approximations (Laplace -> FEL mean-only -> FEL full) for efficiency and stability. A pseudo-likelihood engine glmmFEL_pl() implements the working-response / working-weights linearization approach of Wolfinger and O'Connell (1993) <doi:10.1080/00949659308811554>, and is adapted from the implementation used in the 'RealVAMS' package (Broatch, Green, and Karl (2018)) <doi:10.32614/RJ-2018-033>. The FEL implementation follows Karl, Yan [...truncated...]
Author: Andrew T. Karl [cre, aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

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Package morseDR updated to version 0.1.3 with previous version 0.1.2 dated 2025-05-29

Title: Bayesian Inference of Binary, Count and Continuous Data in Toxicology
Description: Advanced methods for a valuable quantitative environmental risk assessment using Bayesian inference of several type of toxicological data. 'binary' (e.g., survival, mobility), 'count' (e.g., reproduction) and 'continuous' (e.g., growth as length, weight). Estimation procedures can be used without a deep knowledge of their underlying probabilistic model or inference methods. Rather, they were designed to behave as well as possible without requiring a user to provide values for some obscure parameters. That said, models can also be used as a first step to tailor new models for more specific situations.
Author: Virgile Baudrot [aut, cre], Sandrine Charles [aut], Marie Laure Delignette-Muller [aut], Nils Kehrein [ctb], Guillaume Kon-Kam-King [ctb], Christelle Lopes [ctb], Philippe Veber [aut]
Maintainer: Virgile Baudrot <virgile.baudrot@qonfluens.com>

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Package mixedbiastest updated to version 1.0.3 with previous version 1.0.2 dated 2025-11-30

Title: Bias Diagnostic for Linear Mixed Models
Description: Provides a function to perform bias diagnostics on linear mixed models fitted with lmer() from the 'lme4' package. Implements permutation tests for assessing the bias of fixed effects, as described in Karl and Zimmerman (2021) <doi:10.1016/j.jspi.2020.06.004>. Karl and Zimmerman (2020) <doi:10.17632/tmynggddfm.1> provide R code for implementing the test using 'mvglmmRank' output. Development of this package was assisted by 'GPT o1-preview' for code structure and documentation.
Author: Andrew T. Karl [cre, aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

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Package zipcodeR updated to version 0.4.1 with previous version 0.4.0 dated 2026-09-07

Title: Data & Functions for Working with US ZIP Codes
Description: Make working with ZIP codes in R painless with an integrated dataset of U.S. ZIP codes and functions for working with them. Search ZIP codes by multiple geographies, including state, county, city & across time zones. Also included are functions for relating ZIP codes to Census data, geocoding & distance calculations. New analyses can select an immutable modern data bundle through the next-generation API, while the historical interface remains compatible with version 0.3.5 for reproducible research.
Author: Gavin Rozzi [aut, cre]
Maintainer: Gavin Rozzi <gr@gavinrozzi.com>

Diff between zipcodeR versions 0.4.0 dated 2026-09-07 and 0.4.1 dated 2026-09-18

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Package vostokR readmission to version 0.2.2 with previous version 0.2.1 dated 2026-03-25

Title: Solar Potential Calculation for Point Clouds using 'VOSTOK'
Description: Calculate solar potential for LiDAR point clouds using the 'VOSTOK' (Voxel Octree Solar Toolkit) algorithm. This R program provides an interface to the original 'VOSTOK' C++ implementation by Bechtold and Hofle (2020), enabling efficient ray casting and solar position algorithms to compute solar irradiance for each point while accounting for shadowing effects. Integrates seamlessly with the 'lidR' package for LiDAR data processing workflows. The original 'VOSTOK' toolkit is available at <doi:10.11588/data/QNA02B>.
Author: Andrew J. Sanchez Meador [aut, cre], Sebastian Bechtold [aut] , Bernhard Hofle [aut]
Maintainer: Andrew J. Sanchez Meador <andrew.sanchezmeador@nau.edu>

This is a re-admission after prior archival of version 0.2.1 dated 2026-03-25

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Package spanner readmission to version 1.0.5 with previous version 1.0.4 dated 2026-04-01

Title: Utilities to Support Lidar Applications at the Landscape, Forest, and Tree Scale
Description: Implements algorithms for terrestrial, mobile, and airborne lidar processing, tree detection, segmentation, and attribute estimation (Donager et al., 2021) <doi:10.3390/rs13122297>, and a hierarchical patch delineation algorithm 'PatchMorph' (Girvetz & Greco, 2007) <doi:10.1007/s10980-007-9104-8>. Tree detection uses rasterized point cloud metrics (relative neighborhood density and verticality) combined with RANSAC cylinder fitting to locate tree boles and estimate diameter at breast height. Tree segmentation applies graph-theory approaches inspired by Tao et al. (2015) <doi:10.1016/j.isprsjprs.2015.08.007> with cylinder fitting methods from de Conto et al. (2017) <doi:10.1016/j.compag.2017.07.019>. PatchMorph delineates habitat patches across spatial scales using organism-specific thresholds. Built on 'lidR' (Roussel et al., 2020) <doi:10.1016/j.rse.2020.112061>.
Author: Andrew Sanchez Meador [aut, cre, ctb] , Jonathon Donager [aut, ctb] , Blackburn Ryan [aut, ctb] , Cannon Jeffery [ctb] , Tiago de Conto [ctb, cph] , Keith O'Hara [ctb, cph]
Maintainer: Andrew Sanchez Meador <Andrew.SanchezMeador@nau.edu>

This is a re-admission after prior archival of version 1.0.4 dated 2026-04-01

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Package simFastBOIN updated to version 2.0.0 with previous version 1.3.2 dated 2025-12-17

Title: Fast Simulation of Bayesian Optimal Interval Designs for Phase I Trials
Description: Design and evaluate phase I dose-finding trials that use the Bayesian optimal interval (BOIN) design of Liu and Yuan (2015) <doi:10.1111/rssc.12089>. Functions are provided to tabulate the decision boundaries, to simulate trials, to estimate the dose-toxicity curve under a monotonicity constraint and to select the maximum tolerated dose. The simulation engine is written in C++ and draws one random variate per patient in enrollment order, which reproduces the reference implementation in the 'BOIN' package trial by trial for a given seed. The traditional 3+3 design is provided as a comparator, with operating characteristics obtained in closed form rather than by simulation.
Author: Gosuke Homma [aut, cre]
Maintainer: Gosuke Homma <my.name.is.gosuke@gmail.com>

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Package sidra readmission to version 0.2.0 with previous version 0.1.9 dated 2025-09-06

Title: Acesso aos Dados do 'SIDRA' do IBGE
Description: Functions for accessing and manipulating data from Brazilian Institute of Geography and Statistics (IBGE)'s API 'SIDRA' (acronym for IBGE System of Automatic Retrieval) from the new endpoints at <https://servicodados.ibge.gov.br/api/docs/agregados?versao=3>. Ferramentas para acessar e manipular dados via API do Sistema IBGE De Recuperação Automática 'SIDRA' do Instituto Brasileiro de Geografia e Estatística (IBGE).
Author: Rodrigo Emmanuel Santana Borges [cre, aut, cph]
Maintainer: Rodrigo Emmanuel Santana Borges <rodrigo@borges.net.br>

This is a re-admission after prior archival of version 0.1.9 dated 2025-09-06

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Package prepR4pcm updated to version 1.0.3 with previous version 1.0.2 dated 2026-08-25

Title: Prepare Data and Trees for Phylogenetic Comparative Methods
Description: Reconcile species names across datasets and phylogenetic trees for comparative biology workflows. Identifies mismatches due to formatting differences, taxonomic synonymy, and spelling errors. Produces detailed reports documenting how each name was resolved, which taxonomic authority was used, and what remains unresolved. Supports exact matching, name normalisation, synonym resolution via local taxonomic databases, and fuzzy matching for likely typos. Detects taxonomic splits and lumps. For methodological context, see Nakagawa et al. (2026) <doi:10.32942/X2468Z>.
Author: Shinichi Nakagawa [aut, cre, cph] , Santiago Ortega [aut], Ayumi Mizuno [aut], Eduardo S.A. Santos [aut], Malgorzata Lagisz [aut] , Bhavya Jain [aut], Jimuel Jr Celeste [aut], Sergio Poo Hernandez [aut]
Maintainer: Shinichi Nakagawa <itchyshin@gmail.com>

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Package OLSengine updated to version 1.2.0 with previous version 1.1.1 dated 2026-07-31

Title: Transparent and Assisted Linear Modeling Engine
Description: Unified estimation, diagnostics, and reporting for ordinary least squares (OLS) regression, ANOVA/t-tests, logistic regression, panel data (fixed/random effects with Hausman test), instrumental variables (2SLS with weak instrument diagnostics), and difference-in-differences. Designed for applied researchers in social sciences with integrated "Methodological Customs" that audit assumptions and provide literature references. All methods implemented in pure base R without external dependencies beyond stats and graphics packages.
Author: Manuel Soto-Perez [aut, cre]
Maintainer: Manuel Soto-Perez <msoto@up.edu.mx>

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Package mvnma updated to version 0.3-0 with previous version 0.2-0 dated 2026-07-09

Title: Multivariate Network Meta-Analysis using Bayesian Methods
Description: Tools to conduct Bayesian multivariate network meta-analysis providing - the single correlation coefficient model by Efthimiou et al. (2015) <doi:10.1093/biostatistics/kxu030>; - per-outcome consistency checks using the node-splitting method (Dias et al., 2010) <doi:10.1002/sim.3767>; - per-outcome treatment hierarchies using the surface under the cumulative ranking curve (SUCRA), the probability of best value, or median (or mean) ranks (Salanti et al., 2011) <doi:10.1016/j.jclinepi.2010.03.016>; - across-outcomes benefit-risk assessment using the VišeKriterijumska Optimizacija I Kompromisno Rešenje (VIKOR) method (Opricovic & Tzeng, 2004) <doi:10.1016/S0377-2217(03)00020-1>; - convergence checks using trace plots, density plots, or the R-hat statistic; - forest plots of treatment estimates and consistency checks, scatter plots of per-outcome rankings, Hasse diagrams (Carlsen & Bruggemann, 2014) <doi:10.1002/cem.2569> to visualize the partial order [...truncated...]
Author: Theodoros Evrenoglou [aut, cre] , Guido Schwarzer [aut]
Maintainer: Theodoros Evrenoglou <theodoros.evrenoglou@uniklinik-freiburg.de>

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Package dyads updated to version 1.2.22.3 with previous version 1.2.1 dated 2022-08-17

Title: Dyadic Network Analysis
Description: Contains functions for the MCMC simulation of (multilevel) dyadic network models j2 (Zijlstra, 2017, <doi:10.1080/0022250X.2017.1387858>) and p2 (Van Duijn, Snijders & Zijlstra, 2004, <doi: 10.1046/j.0039-0402.2003.00258.x>), the multilevel p2 model (Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>), and the bidirectional (multilevel) counterpart of the the multilevel p2 model as described in Zijlstra, Van Duijn & Snijders (2009) <doi: 10.1348/000711007X255336>, the (multilevel) b2 model.
Author: Bonne J.H. Zijlstra [aut, cre]
Maintainer: Bonne J.H. Zijlstra <B.J.H.Zijlstra@uva.nl>

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Package archeoViz updated to version 1.4.3 with previous version 1.4.2 dated 2026-07-30

Title: Visualisation, Exploration, and Web Communication of Archaeological Spatial Data
Description: An R 'Shiny' application for visual and statistical exploration and web communication of archaeological spatial data, either remains or sites. It offers interactive 3D and 2D visualisations (cross sections and maps of remains, timeline of the work made in a site) which can be exported in SVG and HTML formats. It performs simple spatial statistics (convex hull, regression surfaces, 2D kernel density estimation) and allows exporting data to other online applications for more complex methods. 'archeoViz' can be used offline locally or deployed on a server, either with interactive input of data or with a static data set. Example is provided at <https://analytics.huma-num.fr/archeoviz/en>.
Author: Sebastien Plutniak [aut, cre] , Renata Araujo [ctb] , Laura Coltofean [ctb] , Nicolas Delsol [ctb] , Sara Giardino [ctb] , Julian Laabs [ctb]
Maintainer: Sebastien Plutniak <sebastien.plutniak@posteo.net>

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Package nflfastR updated to version 6.0.0 with previous version 5.2.0 dated 2026-02-07

Title: Functions to Efficiently Access NFL Play by Play Data
Description: A set of functions to access National Football League play-by-play data from <https://www.nfl.com/>.
Author: Sebastian Carl [aut], Ben Baldwin [cre, aut], Lee Sharpe [ctb], Maksim Horowitz [ctb], Ron Yurko [ctb], Samuel Ventura [ctb], Tan Ho [ctb], John Edwards [ctb]
Maintainer: Ben Baldwin <bbaldwin206@gmail.com>

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Package multilevLCA updated to version 2.1.6 with previous version 2.1.5 dated 2026-08-26

Title: Estimates and Plots Single-Level and Multilevel Latent Class Models
Description: Efficiently estimates single- and multilevel latent class models with covariates, allowing for output visualization in all specifications. For more technical details, see Lyrvall et al. (2025) <doi:10.1080/00273171.2025.2473935>.
Author: Roberto Di Mari [aut, cre], Johan Lyrvall [aut], Zsuzsa Bakk [ctb], Jennifer Oser [ctb], Jouni Kuha [ctb]
Maintainer: Roberto Di Mari <roberto.dimari@unict.it>

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Package funbootband updated to version 0.3.0 with previous version 0.2.0 dated 2025-10-20

Title: Simultaneous Prediction and Confidence Bands for Functional Data
Description: Computes simultaneous prediction and confidence bands for densely sampled functional data on a common grid. The calibration builds on the functional bootstrap approach of Lenhoff et al. (1999) <doi:10.1016/S0966-6362(98)00043-5>; hierarchical measurement designs are motivated by Koska et al. (2023) <doi:10.1016/j.jbiomech.2023.111506>. Independent curves are resampled individually. Clustered data use an intact-subject bootstrap with equal subject weighting, and the clustered prediction target is one future curve from a new subject. Curves are represented by finite Fourier series, and an 'Rcpp' backend performs the bootstrap calibration.
Author: Daniel Koska [aut, cre, cph]
Maintainer: Daniel Koska <dkoska@proton.me>

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Package tall updated to version 1.0.1 with previous version 1.0.0 dated 2026-04-15

Title: Text Analysis for All
Description: An R 'shiny' app designed for diverse text analysis tasks, offering a wide range of methodologies tailored to Natural Language Processing (NLP) needs. It is a versatile, general-purpose tool for analyzing textual data. 'tall' features a comprehensive workflow, including data cleaning, preprocessing, statistical analysis, and visualization, all integrated for effective text analysis.
Author: Massimo Aria [aut, cre, cph] , Maria Spano [aut] , Luca D'Aniello [aut] , Corrado Cuccurullo [ctb] , Michelangelo Misuraca [ctb]
Maintainer: Massimo Aria <aria@unina.it>

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Package SqlRender updated to version 1.19.7 with previous version 1.19.6 dated 2026-07-31

Title: Rendering Parameterized SQL and Translation to Dialects
Description: A rendering tool for parameterized SQL that also translates into different SQL dialects. These dialects include 'Microsoft SQL Server', 'Oracle', 'PostgreSql', 'Amazon RedShift', 'Apache Impala', 'IBM Netezza', 'Google BigQuery', 'Microsoft PDW', 'Snowflake', 'Azure Synapse Analytics Dedicated', 'Apache Spark', 'SQLite', and 'InterSystems IRIS'.
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package poldis updated to version 0.2.0 with previous version 0.1.2 dated 2024-09-04

Title: Analyse Political Texts
Description: Wrangle and annotate different types of political texts. It also introduces Urgency Analysis, a new method for the analysis of urgency in political texts.
Author: Henrique Sposito [cre, aut, ctb], James Hollway [ctb], Jael Tan [ctb]
Maintainer: Henrique Sposito <henrique.sposito@graduateinstitute.ch>

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Package layeranalyzer updated to version 0.4.2 with previous version 0.4.1 dated 2026-08-28

Title: Time Series Analysis Tool using Linear Layered SDEs
Description: Time series analysis tool using linear layered stochastic differential equations. The package allows for multiple time series with correlative and/or causal links between them. Unmeasured causal processes are allowed to affect the measured processes in a layered structure, hence the name of the package. In case of causal feedback loops, the matrix operations (including eigenvalue decompositions) allows for complex numbers. In this case, cyclic behavior can be expected. Details can be found in Reitan and Liow (2019)<doi:10.1111/2041-210X.13299>.
Author: Trond Reitan [aut, cre] , Lee Hsiang Liow [ctb] , Adam T. Kocsis [ctb]
Maintainer: Trond Reitan <trond.reitan@geo.uio.no>

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Package baseline updated to version 1.3-8 with previous version 1.3-7 dated 2025-06-18

Title: Baseline Correction of Spectra
Description: Collection of baseline correction algorithms, along with a framework and a Tcl/Tk enabled GUI for optimising baseline algorithm parameters. Typical use of the package is for removing background effects from spectra originating from various types of spectroscopy and spectrometry, possibly optimizing this with regard to regression or classification results. Correction methods include polynomial fitting, weighted local smoothers and many more.
Author: Kristian Hovde Liland [aut, cre] , Bjoern-Helge Mevik [aut], Roberto Canteri [ctb]
Maintainer: Kristian Hovde Liland <kristian.liland@nmbu.no>

Diff between baseline versions 1.3-7 dated 2025-06-18 and 1.3-8 dated 2026-09-18

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Package SVEMnet updated to version 3.6.2 with previous version 3.6.0 dated 2026-09-06

Title: Self-Validated Ensemble Models with Lasso and Relaxed Elastic Net Regression
Description: Implements the self-validated elastic-net and relaxed elastic-net ensemble modeling and multi-response optimization workflow described in Karl (2026) <doi:10.1016/j.chemolab.2026.105660>. Self-validated ensemble models (SVEM; Lemkus et al. (2021) <doi:10.1016/j.chemolab.2021.104439>) are fitted for small-sample design-of-experiments and related workflows using 'glmnet' (Friedman et al. (2010) <doi:10.18637/jss.v033.i01>). Fractional random-weight bootstraps with anti-correlated validation copies are used to tune penalty paths by validation-weighted AIC/BIC. Supports Gaussian and binomial responses, deterministic expansion helpers for shared factor spaces, prediction with bootstrap uncertainty, and a random-search optimizer that respects mixture constraints and combines multiple responses via desirability functions. Also includes a permutation-based whole-model test for Gaussian SVEM fits (Karl (2024) <doi:10.1016/j.chemolab.2024.105122>). Package code was drafte [...truncated...]
Author: Andrew T. Karl [cre, aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>

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Package OlinkAnalyze updated to version 5.1.0 with previous version 5.0.2 dated 2026-06-23

Title: Facilitate Analysis of Proteomic Data from Olink
Description: A collection of functions to facilitate analysis of proteomic data from Olink, primarily NPX data that has been exported from Olink Software. The functions also work on QUANT data from Olink by log- transforming the QUANT data. The functions are focused on reading data, facilitating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to help users extract biological insights from proteomic data run on the Olink platform.
Author: Kathleen Nevola [aut, cre] , Marianne Sandin [aut] , Jamey Guess [aut] , Simon Forsberg [aut] , Christoffer Cambronero [aut] , Pascal Pucholt [aut] , Boxi Zhang [aut] , Masoumeh Sheikhi [aut] , Klev Diamanti [aut] , Amrita Kar [aut] , Lei Conze [aut] [...truncated...]
Maintainer: Kathleen Nevola <biostattools@olink.com>

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Package MDgof updated to version 1.2.0 with previous version 1.1.0 dated 2026-08-03

Title: Various Methods for the Goodness-of-Fit Problem in D>1 Dimensions
Description: Provides multivariate goodness-of-fit testing with a common interface for several test statistics. Null models may be simple or include parameter estimation, with p-values obtained by parametric bootstrap simulation. The function gof_test_adjusted_pvalue() combines several tests and computes a p-value adjusted for simultaneous inference. The function gof_power() estimates test power. The functions hybrid_test() and hybrid_power() use Monte Carlo samples under the null together with two-sample procedures. The function run.studies() supports systematic power comparisons of user-supplied and included methods across case studies. See the included vignettes for method details and references.
Author: Wolfgang Rolke [aut, cre]
Maintainer: Wolfgang Rolke <wolfgang.rolke@upr.edu>

Diff between MDgof versions 1.1.0 dated 2026-08-03 and 1.2.0 dated 2026-09-18

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Package climate updated to version 1.4.1 with previous version 1.4.0 dated 2026-07-10

Title: Interface to Download Meteorological (and Hydrological) Datasets
Description: Automatize downloading of meteorological and hydrological data from publicly available repositories: OGIMET (<http://ogimet.com/index.phtml.en>), University of Wyoming - atmospheric vertical profiling data (<http://weather.uwyo.edu/upperair/>), Polish Institute of Meteorology and Water Management - National Research Institute (<https://danepubliczne.imgw.pl>), and National Oceanic & Atmospheric Administration (NOAA). This package also allows for searching geographical coordinates for each observation and calculate distances to the nearest stations.
Author: Bartosz Czernecki [aut, cre] , Arkadiusz Glogowski [aut] , Jakub Nowosad [aut] , IMGW-PIB [ctb]
Maintainer: Bartosz Czernecki <nwp@amu.edu.pl>

Diff between climate versions 1.4.0 dated 2026-07-10 and 1.4.1 dated 2026-09-18

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More information about climate at CRAN
Permanent link

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

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

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

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

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

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

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

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

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

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

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

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Package HMDA updated to version 0.4.1 with previous version 0.3.0 dated 2026-03-04

Title: Holistic Multimodel Domain Analysis for Exploratory Machine Learning
Description: Holistic Multimodel Domain Analysis (HMDA) is a robust and transparent framework designed for exploratory machine learning research, aiming to enhance the process of feature assessment and selection. HMDA addresses key limitations of traditional machine learning methods by evaluating the consistency across multiple high-performing models within a fine-tuned modeling grid, thereby improving the interpretability and reliability of feature importance assessments. Specifically, it computes Weighted Mean SHapley Additive exPlanations (WMSHAP), which aggregate feature contributions from multiple models based on weighted performance metrics. HMDA also provides confidence intervals to demonstrate the stability of these feature importance estimates. This framework is particularly beneficial for analyzing complex, multidimensional datasets common in health research, supporting reliable exploration of mental health outcomes such as suicidal ideation, suicide attempts, and other psychological cond [...truncated...]
Author: E. F. Haghish [aut, cre, cph]
Maintainer: E. F. Haghish <haghish@hotmail.com>

Diff between HMDA versions 0.3.0 dated 2026-03-04 and 0.4.1 dated 2026-09-18

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Package spatstat.geom updated to version 3.8-3 with previous version 3.8-2 dated 2026-07-24

Title: Geometrical Functionality of the 'spatstat' Family
Description: Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph] , Warick Brown [ctb], Tilman Davies [ctb], Ute Hahn [ctb], Martin Hazelton [ctb], Abdollah Jalilian [ctb], Greg McSwiggan [ctb, cph], Sebastian Meyer [ctb, cph], Jens Oeh [...truncated...]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

Diff between spatstat.geom versions 3.8-2 dated 2026-07-24 and 3.8-3 dated 2026-09-18

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Package rjd3jars updated to version 0.0.6 with previous version 0.0.5 dated 2026-07-07

Title: External jars for 'rjdverse' R Packages
Description: It provides external jars required for the 'rjdverse' (as 'rjd3toolkit', 'rjd3x13' and 'rjd3tramoseats').
Author: Tanguy Barthelemy [aut, cre, cph]
Maintainer: Tanguy Barthelemy <timeserieswithjdemetraandr@gmail.com>

Diff between rjd3jars versions 0.0.5 dated 2026-07-07 and 0.0.6 dated 2026-09-18

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Package RcppArray updated to version 0.3.1 with previous version 0.3.0 dated 2023-11-08

Title: 'Rcpp' Meets 'C++' Arrays
Description: Interoperability between 'Rcpp' and the 'C++11' array and tuple types. Linking to this package allows fixed-length 'std::array' objects to be converted to and from equivalent R vectors, and 'std::tuple' objects converted to lists, via the as() and wrap() functions. There is also experimental support for 'std::span' from 'C++20'.
Author: Jon Clayden [cre, aut] , Dirk Eddelbuettel [aut], Andrew Johnson [ctb]
Maintainer: Jon Clayden <code@clayden.org>

Diff between RcppArray versions 0.3.0 dated 2023-11-08 and 0.3.1 dated 2026-09-18

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Package RBesT updated to version 1.12-0 with previous version 1.11-0 dated 2026-08-04

Title: R Bayesian Evidence Synthesis Tools
Description: Tool-set to support Bayesian evidence synthesis. This includes meta-analysis, (robust) prior derivation from historical data, operating characteristics and analysis (1 and 2 sample cases). Please refer to Weber et al. (2021) <doi:10.18637/jss.v100.i19> for details on applying this package while Neuenschwander et al. (2010) <doi:10.1177/1740774509356002> and Schmidli et al. (2014) <doi:10.1111/biom.12242> explain details on the methodology.
Author: Novartis Pharma AG [cph], Sebastian Weber [aut, cre], Beat Neuenschwander [ctb], Heinz Schmidli [ctb], Baldur Magnusson [ctb], Yue Li [ctb], Satrajit Roychoudhury [ctb], Lukas A. Widmer [ctb] , Daniel Sabanes Bove [ctb] , Trustees of Columbia Univers [...truncated...]
Maintainer: Sebastian Weber <sebastian.weber@novartis.com>

Diff between RBesT versions 1.11-0 dated 2026-08-04 and 1.12-0 dated 2026-09-18

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 R/asthma.R                                                                         |    2 
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 R/gMAP.R                                                                           |  248 
 R/gMAP_draws.R                                                                     |    4 
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Package clampSeg (with last version 1.2-0) was removed from CRAN

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

2025-06-27 1.2-0

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Package subselect updated to version 0.16.2 with previous version 0.16.1 dated 2026-05-04

Title: Selecting Variable Subsets
Description: A collection of functions which (i) assess the quality of variable subsets as surrogates for a full data set, in either an exploratory data analysis or in the context of a multivariate linear model, and (ii) search for subsets which are optimal under various criteria. Theoretical support for the heuristic search methods and exploratory data analysis criteria is in Cadima, Cerdeira, Minhoto (2003, <doi:10.1016/j.csda.2003.11.001>). Theoretical support for the leap and bounds algorithm and the criteria for the general multivariate linear model is in Duarte Silva (2001, <doi:10.1006/jmva.2000.1920>). There is a package vignette "subselect", which includes additional references.
Author: Jorge Orestes Cerdeira [aut], Pedro Duarte Silva [aut, cre], Jorge Cadima [aut], Manuel Minhoto [aut]
Maintainer: Pedro Duarte Silva <psilva@ucp.pt>

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Package sidrar updated to version 0.5.1 with previous version 0.5.0 dated 2026-08-25

Title: An Interface to IBGE's SIDRA API
Description: Provides a flexible interface to discover, inspect, plan, and retrieve aggregate data from the Brazilian Institute of Geography and Statistics (IBGE) through its SIDRA application programming interfaces. SIDRA is IBGE's system for retrieving aggregate statistical data.
Author: Renato Prado Siqueira [aut, cre]
Maintainer: Renato Prado Siqueira <rpradosiqueira@gmail.com>

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Package Rsearch updated to version 1.2.0 with previous version 1.1.0 dated 2026-07-20

Title: Processing and Analyzing Amplicon Sequence Data
Description: Processing and analysis of targeted sequencing data. The package provides a user-friendly interface for core 'VSEARCH' (Rognes et al. (2016), <doi:10.7717/peerj.2584>) functions, in addition to tools for visualization and parameter tuning.
Author: Cassandra Stamsaas [cre, aut], Lars Snipen [aut], Torbjoern Rognes [aut], Hilde Vinje [aut]
Maintainer: Cassandra Stamsaas <cassandra.stamsaas@nmbu.no>

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Package mcptools updated to version 1.0.3 with previous version 1.0.2 dated 2026-08-22

Title: Model Context Protocol Servers and Clients
Description: Implements the Model Context Protocol (MCP). Users can start 'R'-based servers, serving functions as tools for large language models to call before responding to the user in MCP-compatible apps like 'Claude Desktop' and 'Claude Code', with options to run those tools inside of interactive 'R' sessions. On the other end, when 'R' is the client via the 'ellmer' package, users can register tools from third-party MCP servers to integrate additional context into chats.
Author: Simon Couch [aut, cre] , Winston Chang [aut] , Charlie Gao [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Simon Couch <simon.couch@posit.co>

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Package clinpubr updated to version 1.4.2 with previous version 1.4.1 dated 2026-07-13

Title: Clinical Publication
Description: Accelerate the process from clinical data to medical publication, including clinical data cleaning, significant result screening, and the generation of publish-ready tables and figures.
Author: Yue Niu [aut, cre, cph] , Keyun Wang [aut]
Maintainer: Yue Niu <niuyuesam@163.com>

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Package alcyon updated to version 0.10.0 with previous version 0.9.0 dated 2026-08-29

Title: Spatial Network Analysis
Description: Interface package for 'sala', the spatial network analysis library from the 'depthmapX' software application. The R parts of the code are based on the 'rdepthmap' package. Allows for the analysis of urban and building-scale networks and provides metrics and methods usually found within the Space Syntax domain. Methods in this package are described by K. Al-Sayed, A. Turner, B. Hillier, S. Iida and A. Penn (2014) "Space Syntax methodology", and also by A. Turner (2004) <https://discovery.ucl.ac.uk/id/eprint/2651> "Depthmap 4: a researcher's handbook".
Author: Petros Koutsolampros [cre, aut] , Fani Kostourou [ctb] , Kimon Krenz [ctb] , Alasdair Turner [ctb] , Tasos Varoudis [ctb] , Christian Sailer [ctb] , Eva Friedrich [ctb] , University College London [fnd, cph] , Spacelab UK [fnd]
Maintainer: Petros Koutsolampros <r-devel@pklampros.net>

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Package tabxplor updated to version 2.0.1 with previous version 2.0.0 dated 2026-08-29

Title: User-Friendly Tables with Color Helpers for Data Exploration
Description: Make it easy to deal with multiple cross-tables in data exploration, by creating them, manipulating them, and adding color helpers to highlight deviations (differences from totals, comparisons between lines or columns, contributions to variance, odds ratios, etc.) and significance (confidence intervals, stars, etc.). Create the same kind of tables for regression models, with a framework to compare model effects with their crude/observed counterpart systematically. All functions render data frames which can be easily manipulated. All tables can be exported with formats and colors to 'Excel', html and markdown.
Author: Brice Nocenti [aut, cre]
Maintainer: Brice Nocenti <brice.nocenti@protonmail.com>

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Package rupturesRcpp updated to version 1.0.3 with previous version 1.0.2 dated 2025-11-23

Title: Object-Oriented Interface for Offline Change-Point Detection
Description: A collection of efficient implementations of popular offline change-point detection algorithms, featuring a consistent, object-oriented interface for practical use.
Author: Minh Long Nguyen [aut, cre], Toby Hocking [aut], Charles Truong [aut]
Maintainer: Minh Long Nguyen <edelweiss611428@gmail.com>

Diff between rupturesRcpp versions 1.0.2 dated 2025-11-23 and 1.0.3 dated 2026-09-18

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Package POT updated to version 1.1-12 with previous version 1.1-11 dated 2024-10-17

Title: Generalized Pareto Distribution and Peaks Over Threshold
Description: Some functions useful to perform a Peak Over Threshold analysis in univariate and bivariate cases, see Beirlant et al. (2004) <doi:10.1002/0470012382>. A user guide is available in the vignette.
Author: Christophe Dutang [aut, cre] , Mathieu Ribatet [aut]
Maintainer: Christophe Dutang <dutangc@gmail.com>

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Package ksamplesLTRC updated to version 0.1.1 with previous version 0.1.0 dated 2026-07-30

Title: K-Sample Tests for Truncated and/or Censored Data
Description: Nonparametric analysis and comparison of distributions under left truncation and right censoring. The package includes simulation routines for truncated and/or censored survival data, nonparametric distribution comparison methods based on Kolmogorov-Smirnov-type and Cramér-von Mises-type statistics, and bootstrap routines for p-value approximation. For methodological details, see Lago, de Uña-Álvarez and Pardo-Fernández (2025) <doi:10.1007/s11749-024-00948-4> and Lago, Pardo-Fernández and de Uña-Álvarez (2026) <doi:10.1007/s10985-026-09713-1>.
Author: Adrian Lago [aut, cre], Jacobo de Una-Alvarez [aut], Juan Carlos Pardo-Fernandez [aut]
Maintainer: Adrian Lago <adrian.lago@uvigo.gal>

Diff between ksamplesLTRC versions 0.1.0 dated 2026-07-30 and 0.1.1 dated 2026-09-18

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Package HeatStressR updated to version 2.4.0 with previous version 2.2.1 dated 2026-08-07

Title: Calculate Heat Stress Indices
Description: Calculates heat-stress indices from meteorological observations, including the physically based wet-bulb globe temperature model described by Liljegren et al. (2008) <doi:10.1080/15459620802310770>. The package provides an independently maintained R implementation with row-level diagnostics, configurable physical controls, and batch processing for the Liljegren method; it is not a bitwise-compatible port of the original program, and cross-implementation differences are expected.
Author: Yifei Zheng [aut, cre] , Ana Casanueva [aut]
Maintainer: Yifei Zheng <zyf0717@gmail.com>

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Package GGIRread updated to version 1.0.11 with previous version 1.0.10 dated 2026-08-26

Title: Wearable Accelerometer Data File Readers
Description: Reads data collected from wearable acceleratometers as used in sleep and physical activity research. Currently supports file formats: binary data from 'GENEActiv' <https://activinsights.com/>, .bin-format from GENEA devices (not for sale), and .cwa-format from 'Axivity' <https://axivity.com>. Further, it has functions for reading text files with epoch level aggregates from 'Actical', 'Fitbit', 'Actiwatch', 'ActiGraph', and 'PhilipsHealthBand'. Primarily designed to complement R package GGIR <https://CRAN.R-project.org/package=GGIR>.
Author: Vincent T van Hees [aut, cre], Patrick Bos [aut] , Lena Kushleyeva [ctb], Jing Hua Zhao [ctb], Evgeny Mirkes [ctb], Dan Jackson [ctb], Jairo H Migueles [ctb], John Muschelli [ctb], Jia Ying Chua [ctb], Medical Research Council UK [cph, fnd], Acceltin [...truncated...]
Maintainer: Vincent T van Hees <v.vanhees@accelting.com>

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Package taxify updated to version 0.5.5 with previous version 0.5.0 dated 2026-09-02

Title: Offline Taxonomic Name Matching Against Darwin Core Backbones
Description: Match taxonomic names against locally stored Darwin Core backbone databases ('WFO', 'COL', 'GBIF', 'ITIS', 'NCBI Taxonomy', 'Open Tree of Life', 'WoRMS', 'Euro+Med', 'Species Fungorum', 'AlgaeBase', 'FishBase', 'SeaLifeBase', 'Reptile Database', 'LCVP', 'WCVP', 'Mammal Diversity Database', 'AviList', 'LPSN'). Provides offline fuzzy and exact matching with synonym resolution, hybrid name detection, and a unified output schema across all sources. All heavy computation runs in the 'vectra' C11 columnar engine.
Author: Gilles Colling [aut, cre, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>

Diff between taxify versions 0.5.0 dated 2026-09-02 and 0.5.5 dated 2026-09-18

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 155 files changed, 20995 insertions(+), 13722 deletions(-)

More information about taxify at CRAN
Permanent link

Package shinyOAuth updated to version 0.6.1 with previous version 0.6.0 dated 2026-09-17

Title: OIDC Authentication and OAuth Authorization for 'shiny' Applications
Description: Provides a simple, configurable framework for 'OpenID Connect' (OIDC) authentication and 'OAuth 2.0' authorization in 'shiny' applications using 'S7' classes. Defines providers, clients, and tokens, as well as various supporting functions and a 'shiny' module. Features include cross-site request forgery (CSRF) protection, state encryption, 'Proof Key for Code Exchange' (PKCE) handling, validation of OIDC identity tokens (nonces, signatures, claims), automatic user info retrieval for OIDC and supported 'OAuth' providers, asynchronous flows, and hooks for audit logging.
Author: Luka Koning [aut, cre, cph]
Maintainer: Luka Koning <koningluka@gmail.com>

Diff between shinyOAuth versions 0.6.0 dated 2026-09-17 and 0.6.1 dated 2026-09-18

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 R/providers__apple.R                                          |  344 
 R/shinyOAuth-package.R                                        |   48 
 R/telemetry.R                                                 | 4034 ++---
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 R/utils__audit_digest.R                                       |  250 
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 R/utils__key_dependencies.R                                   |  110 
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 tests/testthat/fixtures/mtls/generate-san-fixtures.py         |   50 
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 tests/testthat/teardown-chromote.R                            |   44 
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 tests/testthat/test-audit-async-options.R                     | 2804 ++--
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More information about shinyOAuth at CRAN
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Package Luminescence updated to version 1.3.1 with previous version 1.3.0 dated 2026-07-22

Title: Comprehensive Luminescence Dating Data Analysis
Description: A collection of various R functions for the purpose of Luminescence dating data analysis. This includes, amongst others, data import, export, application of age models, curve deconvolution, sequence analysis and plotting of equivalent dose distributions.
Author: Sebastian Kreutzer [aut, trl, cre, dtc] , Christoph Burow [aut, trl, dtc] , Michael Dietze [aut] , Margret C. Fuchs [aut] , Christoph Schmidt [aut] , Manfred Fischer [aut, trl], Johannes Friedrich [aut] , Norbert Mercier [aut] , Rachel K. Smedley [ct [...truncated...]
Maintainer: Sebastian Kreutzer <maintainer_luminescence@r-luminescence.org>

Diff between Luminescence versions 1.3.0 dated 2026-07-22 and 1.3.1 dated 2026-09-18

 Luminescence-1.3.0/Luminescence/man/calc_MaxDose.Rd                                  |only
 Luminescence-1.3.0/Luminescence/man/merge_RLum.Data.Spectrum.Rd                      |only
 Luminescence-1.3.1/Luminescence/DESCRIPTION                                          |   26 
 Luminescence-1.3.1/Luminescence/MD5                                                  |  563 +--
 Luminescence-1.3.1/Luminescence/NAMESPACE                                            |   60 
 Luminescence-1.3.1/Luminescence/NEWS.md                                              | 1656 ++--------
 Luminescence-1.3.1/Luminescence/R/Luminescence-generics.R                            |   60 
 Luminescence-1.3.1/Luminescence/R/Luminescence-package.R                             |    4 
 Luminescence-1.3.1/Luminescence/R/RLum.Analysis-class.R                              |   31 
 Luminescence-1.3.1/Luminescence/R/RLum.Data.Curve-class.R                            |   27 
 Luminescence-1.3.1/Luminescence/R/RLum.Data.Image-class.R                            |   14 
 Luminescence-1.3.1/Luminescence/R/RLum.Data.Spectrum-class.R                         |   15 
 Luminescence-1.3.1/Luminescence/R/RLum.Results-class.R                               |   15 
 Luminescence-1.3.1/Luminescence/R/Risoe.BINfileData-class.R                          |    5 
 Luminescence-1.3.1/Luminescence/R/Risoe.BINfileData2RLum.Analysis.R                  |   52 
 Luminescence-1.3.1/Luminescence/R/analyse_Al2O3C_CrossTalk.R                         |   19 
 Luminescence-1.3.1/Luminescence/R/analyse_Al2O3C_ITC.R                               |   10 
 Luminescence-1.3.1/Luminescence/R/analyse_Al2O3C_Measurement.R                       |    6 
 Luminescence-1.3.1/Luminescence/R/analyse_FadingMeasurement.R                        |   15 
 Luminescence-1.3.1/Luminescence/R/analyse_IRSAR.RF.R                                 |  168 -
 Luminescence-1.3.1/Luminescence/R/analyse_SAR.CWOSL.R                                |   54 
 Luminescence-1.3.1/Luminescence/R/analyse_SAR.NCF.R                                  |    4 
 Luminescence-1.3.1/Luminescence/R/analyse_SAR.TL.R                                   |   11 
 Luminescence-1.3.1/Luminescence/R/analyse_baSAR.R                                    |    2 
 Luminescence-1.3.1/Luminescence/R/analyse_pIRIRSequence.R                            |   14 
 Luminescence-1.3.1/Luminescence/R/calc_AverageDose.R                                 |    2 
 Luminescence-1.3.1/Luminescence/R/calc_CentralDose.R                                 |   60 
 Luminescence-1.3.1/Luminescence/R/calc_FadingCorr.R                                  |    4 
 Luminescence-1.3.1/Luminescence/R/calc_FastRatio.R                                   |   57 
 Luminescence-1.3.1/Luminescence/R/calc_FiniteMixture.R                               |    2 
 Luminescence-1.3.1/Luminescence/R/calc_FuchsLang2001.R                               |   87 
 Luminescence-1.3.1/Luminescence/R/calc_Huntley2006.R                                 |  103 
 Luminescence-1.3.1/Luminescence/R/calc_IEU.R                                         |    4 
 Luminescence-1.3.1/Luminescence/R/calc_MaxDose.R                                     |  103 
 Luminescence-1.3.1/Luminescence/R/calc_MinDose.R                                     |  177 -
 Luminescence-1.3.1/Luminescence/R/calc_MoransI.R                                     |    2 
 Luminescence-1.3.1/Luminescence/R/calc_OSLLxTxRatio.R                                |   20 
 Luminescence-1.3.1/Luminescence/R/calc_SourceDoseRate.R                              |   48 
 Luminescence-1.3.1/Luminescence/R/calc_Statistics.R                                  |   45 
 Luminescence-1.3.1/Luminescence/R/calc_WodaFuchs2008.R                               |    2 
 Luminescence-1.3.1/Luminescence/R/calc_gSGC.R                                        |    7 
 Luminescence-1.3.1/Luminescence/R/calc_gSGC_feldspar.R                               |    4 
 Luminescence-1.3.1/Luminescence/R/convert_CW2pLMi.R                                  |    2 
 Luminescence-1.3.1/Luminescence/R/fit_CWCurve.R                                      |    8 
 Luminescence-1.3.1/Luminescence/R/fit_DoseResponseCurve.R                            |  134 
 Luminescence-1.3.1/Luminescence/R/fit_EmissionSpectra.R                              |    9 
 Luminescence-1.3.1/Luminescence/R/fit_IsothermalHolding.R                            |    5 
 Luminescence-1.3.1/Luminescence/R/fit_LMCurve.R                                      |    5 
 Luminescence-1.3.1/Luminescence/R/fit_OSLLifeTimes.R                                 |   10 
 Luminescence-1.3.1/Luminescence/R/fit_SurfaceExposure.R                              |   20 
 Luminescence-1.3.1/Luminescence/R/get_Layout.R                                       |    8 
 Luminescence-1.3.1/Luminescence/R/internals_RLum.R                                   |   98 
 Luminescence-1.3.1/Luminescence/R/merge_RLum.Analysis.R                              |   23 
 Luminescence-1.3.1/Luminescence/R/merge_RLum.Data.Curve.R                            |   83 
 Luminescence-1.3.1/Luminescence/R/merge_RLum.Data.Spectrum.R                         |  124 
 Luminescence-1.3.1/Luminescence/R/merge_RLum.R                                       |   36 
 Luminescence-1.3.1/Luminescence/R/merge_RLum.Results.R                               |  145 
 Luminescence-1.3.1/Luminescence/R/merge_Risoe.BINfileData.R                          |   40 
 Luminescence-1.3.1/Luminescence/R/plot_AbanicoPlot.R                                 |  703 ++--
 Luminescence-1.3.1/Luminescence/R/plot_DRCSummary.R                                  |   11 
 Luminescence-1.3.1/Luminescence/R/plot_DRTResults.R                                  |   55 
 Luminescence-1.3.1/Luminescence/R/plot_DetPlot.R                                     |   28 
 Luminescence-1.3.1/Luminescence/R/plot_DoseResponseCurve.R                           |   28 
 Luminescence-1.3.1/Luminescence/R/plot_Histogram.R                                   |   53 
 Luminescence-1.3.1/Luminescence/R/plot_KDE.R                                         |   81 
 Luminescence-1.3.1/Luminescence/R/plot_NRt.R                                         |    2 
 Luminescence-1.3.1/Luminescence/R/plot_RLum.Data.Curve.R                             |   15 
 Luminescence-1.3.1/Luminescence/R/plot_RLum.Data.Spectrum.R                          |   21 
 Luminescence-1.3.1/Luminescence/R/plot_RLum.R                                        |   13 
 Luminescence-1.3.1/Luminescence/R/plot_RLum.Results.R                                |   43 
 Luminescence-1.3.1/Luminescence/R/plot_RadialPlot.R                                  |   67 
 Luminescence-1.3.1/Luminescence/R/plot_ViolinPlot.R                                  |   32 
 Luminescence-1.3.1/Luminescence/R/read_RF2R.R                                        |   75 
 Luminescence-1.3.1/Luminescence/R/read_XSYG2R.R                                      |   11 
 Luminescence-1.3.1/Luminescence/R/scale_GammaDose.R                                  |   77 
 Luminescence-1.3.1/Luminescence/R/verify_SingleGrainData.R                           |   12 
 Luminescence-1.3.1/Luminescence/R/write_R2BIN.R                                      |   12 
 Luminescence-1.3.1/Luminescence/README.md                                            |   11 
 Luminescence-1.3.1/Luminescence/inst/doc/crosstalk.html                              |   62 
 Luminescence-1.3.1/Luminescence/man/Risoe.BINfileData-class.Rd                       |    2 
 Luminescence-1.3.1/Luminescence/man/Risoe.BINfileData2RLum.Analysis.Rd               |   32 
 Luminescence-1.3.1/Luminescence/man/analyse_Al2O3C_CrossTalk.Rd                      |    7 
 Luminescence-1.3.1/Luminescence/man/analyse_Al2O3C_ITC.Rd                            |    8 
 Luminescence-1.3.1/Luminescence/man/analyse_Al2O3C_Measurement.Rd                    |    2 
 Luminescence-1.3.1/Luminescence/man/analyse_FadingMeasurement.Rd                     |   15 
 Luminescence-1.3.1/Luminescence/man/analyse_IRSAR.RF.Rd                              |   29 
 Luminescence-1.3.1/Luminescence/man/analyse_SAR.CWOSL.Rd                             |   10 
 Luminescence-1.3.1/Luminescence/man/analyse_SAR.NCF.Rd                               |    4 
 Luminescence-1.3.1/Luminescence/man/analyse_SAR.TL.Rd                                |    4 
 Luminescence-1.3.1/Luminescence/man/analyse_baSAR.Rd                                 |    2 
 Luminescence-1.3.1/Luminescence/man/analyse_pIRIRSequence.Rd                         |    2 
 Luminescence-1.3.1/Luminescence/man/analyse_portableOSL.Rd                           |    2 
 Luminescence-1.3.1/Luminescence/man/apply_CosmicRayRemoval.Rd                        |    2 
 Luminescence-1.3.1/Luminescence/man/apply_Crosstalk.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/apply_EfficiencyCorrection.Rd                    |    2 
 Luminescence-1.3.1/Luminescence/man/as.Rd                                            |only
 Luminescence-1.3.1/Luminescence/man/bin_RLum.Data.Rd                                 |    4 
 Luminescence-1.3.1/Luminescence/man/calc_AliquotSize.Rd                              |    2 
 Luminescence-1.3.1/Luminescence/man/calc_AverageDose.Rd                              |    4 
 Luminescence-1.3.1/Luminescence/man/calc_CentralDose.Rd                              |    4 
 Luminescence-1.3.1/Luminescence/man/calc_CobbleDoseRate.Rd                           |    2 
 Luminescence-1.3.1/Luminescence/man/calc_CommonDose.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/calc_CosmicDoseRate.Rd                           |    2 
 Luminescence-1.3.1/Luminescence/man/calc_EED_Model.Rd                                |    2 
 Luminescence-1.3.1/Luminescence/man/calc_FadingCorr.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/calc_FastRatio.Rd                                |    7 
 Luminescence-1.3.1/Luminescence/man/calc_FiniteMixture.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/calc_FuchsLang2001.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/calc_HomogeneityTest.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/calc_Huntley2006.Rd                              |   12 
 Luminescence-1.3.1/Luminescence/man/calc_IEU.Rd                                      |    2 
 Luminescence-1.3.1/Luminescence/man/calc_Lamothe2003.Rd                              |    2 
 Luminescence-1.3.1/Luminescence/man/calc_MinDose.Rd                                  |  106 
 Luminescence-1.3.1/Luminescence/man/calc_MoransI.Rd                                  |    2 
 Luminescence-1.3.1/Luminescence/man/calc_OSLLxTxDecomposed.Rd                        |    2 
 Luminescence-1.3.1/Luminescence/man/calc_OSLLxTxRatio.Rd                             |    2 
 Luminescence-1.3.1/Luminescence/man/calc_SourceDoseRate.Rd                           |    8 
 Luminescence-1.3.1/Luminescence/man/calc_Statistics.Rd                               |   25 
 Luminescence-1.3.1/Luminescence/man/calc_TLLxTxRatio.Rd                              |    2 
 Luminescence-1.3.1/Luminescence/man/calc_ThermalLifetime.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/calc_WodaFuchs2008.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/calc_gSGC.Rd                                     |    2 
 Luminescence-1.3.1/Luminescence/man/calc_gSGC_feldspar.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/combine_De_Dr.Rd                                 |    2 
 Luminescence-1.3.1/Luminescence/man/convert_Activity2Concentration.Rd                |    2 
 Luminescence-1.3.1/Luminescence/man/convert_BIN2CSV.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/convert_CW2pHMi.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/convert_CW2pLM.Rd                                |    2 
 Luminescence-1.3.1/Luminescence/man/convert_CW2pLMi.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/convert_CW2pPMi.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/convert_Concentration2DoseRate.Rd                |    2 
 Luminescence-1.3.1/Luminescence/man/convert_Daybreak2CSV.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/convert_PSL2CSV.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/convert_PSL2Risoe.BINfileData.Rd                 |    2 
 Luminescence-1.3.1/Luminescence/man/convert_RLum2Risoe.BINfileData.Rd                |    2 
 Luminescence-1.3.1/Luminescence/man/convert_SG2MG.Rd                                 |    2 
 Luminescence-1.3.1/Luminescence/man/convert_Second2Gray.Rd                           |    2 
 Luminescence-1.3.1/Luminescence/man/convert_Wavelength2Energy.Rd                     |    2 
 Luminescence-1.3.1/Luminescence/man/convert_XSYG2CSV.Rd                              |    2 
 Luminescence-1.3.1/Luminescence/man/correct_PMTLinearity.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/dot-as.latex.table.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/extract_IrradiationTimes.Rd                      |    2 
 Luminescence-1.3.1/Luminescence/man/extract_ROI.Rd                                   |    2 
 Luminescence-1.3.1/Luminescence/man/fit_CWCurve.Rd                                   |    2 
 Luminescence-1.3.1/Luminescence/man/fit_DoseResponseCurve.Rd                         |   11 
 Luminescence-1.3.1/Luminescence/man/fit_EmissionSpectra.Rd                           |    2 
 Luminescence-1.3.1/Luminescence/man/fit_LMCurve.Rd                                   |    2 
 Luminescence-1.3.1/Luminescence/man/fit_OSLLifeTimes.Rd                              |    4 
 Luminescence-1.3.1/Luminescence/man/fit_SurfaceExposure.Rd                           |    2 
 Luminescence-1.3.1/Luminescence/man/fit_ThermalQuenching.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/get_Layout.Rd                                    |    2 
 Luminescence-1.3.1/Luminescence/man/get_RLum.Rd                                      |    4 
 Luminescence-1.3.1/Luminescence/man/get_rightAnswer.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/import_Data.Rd                                   |    2 
 Luminescence-1.3.1/Luminescence/man/length_RLum.Rd                                   |    4 
 Luminescence-1.3.1/Luminescence/man/melt_RLum.Rd                                     |    4 
 Luminescence-1.3.1/Luminescence/man/merge_RLum.Analysis.Rd                           |   10 
 Luminescence-1.3.1/Luminescence/man/merge_RLum.Data.Curve.Rd                         |   94 
 Luminescence-1.3.1/Luminescence/man/merge_RLum.Rd                                    |   10 
 Luminescence-1.3.1/Luminescence/man/merge_RLum.Results.Rd                            |   11 
 Luminescence-1.3.1/Luminescence/man/merge_Risoe.BINfileData.Rd                       |   10 
 Luminescence-1.3.1/Luminescence/man/metadata.Rd                                      |    2 
 Luminescence-1.3.1/Luminescence/man/names_RLum.Rd                                    |    4 
 Luminescence-1.3.1/Luminescence/man/normalise_RLum.Rd                                |    2 
 Luminescence-1.3.1/Luminescence/man/plot_AbanicoPlot.Rd                              |  122 
 Luminescence-1.3.1/Luminescence/man/plot_DRCSummary.Rd                               |   10 
 Luminescence-1.3.1/Luminescence/man/plot_DRTResults.Rd                               |   10 
 Luminescence-1.3.1/Luminescence/man/plot_DetPlot.Rd                                  |   14 
 Luminescence-1.3.1/Luminescence/man/plot_DoseResponseCurve.Rd                        |   17 
 Luminescence-1.3.1/Luminescence/man/plot_FilterCombinations.Rd                       |    2 
 Luminescence-1.3.1/Luminescence/man/plot_GrowthCurve.Rd                              |   11 
 Luminescence-1.3.1/Luminescence/man/plot_Histogram.Rd                                |   31 
 Luminescence-1.3.1/Luminescence/man/plot_KDE.Rd                                      |   16 
 Luminescence-1.3.1/Luminescence/man/plot_MoranScatterplot.Rd                         |    2 
 Luminescence-1.3.1/Luminescence/man/plot_NRt.Rd                                      |    2 
 Luminescence-1.3.1/Luminescence/man/plot_OSLAgeSummary.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/plot_RLum.Analysis.Rd                            |    2 
 Luminescence-1.3.1/Luminescence/man/plot_RLum.Data.Curve.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/plot_RLum.Data.Image.Rd                          |    2 
 Luminescence-1.3.1/Luminescence/man/plot_RLum.Data.Spectrum.Rd                       |   11 
 Luminescence-1.3.1/Luminescence/man/plot_RLum.Rd                                     |   10 
 Luminescence-1.3.1/Luminescence/man/plot_RLum.Results.Rd                             |    2 
 Luminescence-1.3.1/Luminescence/man/plot_ROI.Rd                                      |    2 
 Luminescence-1.3.1/Luminescence/man/plot_RadialPlot.Rd                               |   19 
 Luminescence-1.3.1/Luminescence/man/plot_Risoe.BINfileData.Rd                        |    2 
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 Luminescence-1.3.1/Luminescence/man/read_BIN2R.Rd                                    |    2 
 Luminescence-1.3.1/Luminescence/man/read_BINXLOG2R.Rd                                |    2 
 Luminescence-1.3.1/Luminescence/man/read_Daybreak2R.Rd                               |    2 
 Luminescence-1.3.1/Luminescence/man/read_HeliosOSL2R.Rd                              |    2 
 Luminescence-1.3.1/Luminescence/man/read_PSL2R.Rd                                    |    2 
 Luminescence-1.3.1/Luminescence/man/read_RF2R.Rd                                     |   16 
 Luminescence-1.3.1/Luminescence/man/read_SPE2R.Rd                                    |    2 
 Luminescence-1.3.1/Luminescence/man/read_TIFF2R.Rd                                   |    2 
 Luminescence-1.3.1/Luminescence/man/read_XSYG2R.Rd                                   |    4 
 Luminescence-1.3.1/Luminescence/man/remove_RLum.Rd                                   |    4 
 Luminescence-1.3.1/Luminescence/man/remove_SignalBackground.Rd                       |    2 
 Luminescence-1.3.1/Luminescence/man/replicate_RLum.Rd                                |    4 
 Luminescence-1.3.1/Luminescence/man/report_RLum.Rd                                   |    2 
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 Luminescence-1.3.1/Luminescence/man/write_R2BIN.Rd                                   |    4 
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Package ICESat2VegR updated to version 0.0.2 with previous version 0.0.1 dated 2026-09-11

Title: ICESat-2 Data Analysis for Land and Vegetation
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.
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>

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Package galah updated to version 2.3.0 with previous version 2.2.0 dated 2026-02-11

Title: Biodiversity Data from the GBIF Node Network
Description: The Global Biodiversity Information Facility ('GBIF', <https://www.gbif.org>) sources data from an international network of data providers, known as 'nodes'. Several of these nodes - the "living atlases" (<https://living-atlases.gbif.org>) - maintain their own web services using software originally developed by the Atlas of Living Australia ('ALA', <https://www.ala.org.au>). 'galah' enables the R community to directly access data and resources hosted by 'GBIF' and its partner nodes.
Author: Martin Westgate [aut, cre], Dax Kellie [aut], Shandiya Balasubramaniam [ctb], Matilda Stevenson [ctb]
Maintainer: Martin Westgate <martin.westgate@csiro.au>

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Package evbsreg updated to version 1.2.0 with previous version 1.0.0 dated 2026-06-30

Title: Local Influence Diagnostics for the Extreme-Value Birnbaum-Saunders Regression Model
Description: Implements local influence diagnostics for the Extreme-Value Birnbaum-Saunders (EVBS) regression model: joint maximum likelihood estimation, conformal normal curvature diagnostics under three perturbation schemes (case-weight, response variable, and explanatory variable), randomized quantile residuals with simulation envelope, Monte Carlo simulation utilities, and publication-quality density and diagnostic plots. Version 1.1.0 adds the density, distribution and quantile functions, the finite upper endpoint, return levels and expected shortfall, block bootstrap standard errors for serially dependent series, local influence diagnostics for the generalized extreme-value regression model, and a GAMLSS family allowing the tail-shape parameter to depend on covariates. Version 1.2.0 adds a prospective control chart for endpoint identifiability. The methods are described in Ospina, Lima, Barros, and Macedo (2026, submitted) and are applied to monthly maximum wind gust data from Itajai, Brazil.
Author: Raydonal Ospina [aut, cre]
Maintainer: Raydonal Ospina <raydonal@de.ufpe.br>

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Package clogitL1 updated to version 1.6 with previous version 1.5 dated 2019-02-02

Title: Fitting Exact Conditional Logistic Regression with Lasso and Elastic Net Penalties
Description: Tools for the fitting and cross validation of exact conditional logistic regression models with lasso and elastic net penalties. Uses cyclic coordinate descent and warm starts to compute the entire path efficiently.
Author: Stephen Reid [aut, cre], Robert Tibshirani [aut]
Maintainer: Stephen Reid <sreid1652@gmail.com>

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Package basetable updated to version 1.4.2 with previous version 1.4.1 dated 2026-09-13

Title: Fast and Memory-Efficient Base R Table Manipulation
Description: A tabular data manipulation, exploration and validation toolkit with a base R-style interface (subset, transform, aggregate, merge, split) and no external computation dependency. Grouping, joins, ordering, filtering, reshaping and delimited-file reading run in a bundled 'C++' engine that uses multiple threads for the heavier operations. Grouped reducers accumulate in compiled code without materialising intermediate columns, so grouped aggregation and counting allocate close to nothing. Results are returned as an ordinary data frame with a light 'basetable' class.
Author: Imad El Badisy [aut, cre]
Maintainer: Imad El Badisy <elbadisyimad@gmail.com>

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Package prototest updated to version 1.3 with previous version 1.2 dated 2019-02-03

Title: Inference on Prototypes from Clusters of Features
Description: Procedures for testing for group-wide signal in clusters of variables. Tests can be performed for single groups in isolation (univariate) or multiple groups together (multivariate). Specific tests include the exact and approximate (un)selective likelihood ratio tests described in Reid et al (2015), the selective F test and marginal screening prototype test of Reid and Tibshirani (2015). User may pre-specify columns to be included in prototype formation, or allow the function to select them itself. A mixture of these two is also possible. Any variable selection is accounted for using the selective inference framework. Options for non-sampling and hit-and-run null reference distributions.
Author: Stephen Reid [aut, cre]
Maintainer: Stephen Reid <sreid1652@gmail.com>

Diff between prototest versions 1.2 dated 2019-02-03 and 1.3 dated 2026-09-18

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Package wsMed updated to version 1.1.0 with previous version 1.0.2 dated 2025-12-11

Title: Within-Subject Mediation Analysis Using Structural Equation Modeling
Description: Within-subject mediation analysis using structural equation modeling. Examine how changes in an outcome variable between two conditions are mediated through one or more variables. Supports within-subject mediation analysis using the 'lavaan' package by Rosseel (2012) <doi:10.18637/jss.v048.i02>, and extends Monte Carlo confidence interval estimation to missing data scenarios using the 'semmcci' package by Pesigan and Cheung (2023) <doi:10.3758/s13428-023-02114-4>.
Author: Wendie Yang [aut, cre] , Shu Fai Cheung [aut]
Maintainer: Wendie Yang <1581075494q@gmail.com>

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More information about wsMed at CRAN
Permanent link


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