Fri, 31 Jul 2026

Package multiModTest updated to version 1.1 with previous version 1.0 dated 2025-09-03

Title: Information Assessment for Individual Modalities in Multimodal Regression Models
Description: Provides methods for quantifying the information gain contributed by individual modalities in multimodal regression models. Information gain is measured using Expected Relative Entropy (ERE) or pseudo-R² metrics, with corresponding confidence intervals. Currently supports linear regression, logistic regression, and the Cox proportional hazards model. A robust Median-of-Means based estimator is also provided for heavy-tailed responses under the Gaussian and Negative-Binomial families, with basic bootstrap confidence intervals.
Author: Wanting Jin [aut, cre], Quefeng Li [aut]
Maintainer: Wanting Jin <jinwanting5@gmail.com>

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Package cata updated to version 0.1.2.0 with previous version 0.1.1.2 dated 2025-09-11

Title: Analysis of Check-All-that-Apply (CATA) Data
Description: Package contains functions for analyzing check-all-that-apply (CATA) data from consumer and sensory tests. Cochran's Q test, McNemar's test, and Penalty-Lift analysis are provided; for details, see Meyners, Castura & Carr (2013) <doi:10.1016/j.foodqual.2013.06.010>. Cluster analysis can be performed using b-cluster analysis, then evaluated using various measures; for details, see Castura, Meyners, Varela & Næs (2022) <doi:10.1016/j.foodqual.2022.104564>. Consumers can also be clustered on their product-related hedonic responses; see Castura, Meyners, Pohjanheimo, Varela & Næs (2023) <doi:10.1111/joss.12860>. Permutation tests based on the L1-norm methods are provided; for details, see Chaya, Castura & Greenacre (2025) <doi:10.1016/j.foodqual.2025.105639>.
Author: J.C. Castura [aut, cre, ctb]
Maintainer: J.C. Castura <jcastura@compusense.com>

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Package powergrid updated to version 0.6.2 with previous version 0.5.0 dated 2025-09-30

Title: Power Analysis Across a Grid of Assumptions
Description: Evaluate a function across a grid of parameters. The function may be evaluated once, or many times for simulation. Parallel computing is facilitated. Utilities aim at performing analyses of power and sample size, allowing for easy search of minimum n (or min/max of any other parameter) to achieve a desired minimal level of power (or maximum of any other objective). Plotting functions are included that present the dependency of n and power in relation to further assumptions.
Author: Gilles Dutilh [aut, cre] , Richard Charles Allen [aut]
Maintainer: Gilles Dutilh <info@gillesdutilh.com>

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Package livelink updated to version 0.1.1 with previous version 0.1.0 dated 2026-07-24

Title: Create Shareable Links for 'webR' and 'Shinylive' Environments
Description: Creates shareable links for 'R' code in 'WebAssembly' (WASM) Read-Eval-Print Loop (REPL) environments like 'webR' <https://webr.r-wasm.org/> and for 'Shiny' applications using 'Shinylive' <https://shinylive.io/>. Supports single scripts, multi-file projects, exercise and solution pairs, and batch processing. Includes encoding, decoding, and previewing of links for both 'R' and 'Python' environments.
Author: James Joseph Balamuta [aut, cre, cph], reprex authors [cph] and trim_common_leading_ws, adapted in R/process-input.R; see inst/COPYRIGHTS)
Maintainer: James Joseph Balamuta <james.balamuta@gmail.com>

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Package eyeris updated to version 3.3.0 with previous version 3.2.0 dated 2026-06-19

Title: Flexible, Extensible, & Reproducible Pupillometry Preprocessing
Description: Pupillometry offers a non-invasive window into the mind and has been used extensively as a psychophysiological readout of arousal signals linked with cognitive processes like attention, stress, and emotional states [Clewett et al. (2020) <doi:10.1038/s41467-020-17851-9>; Kret & Sjak-Shie (2018) <doi:10.3758/s13428-018-1075-y>; Strauch (2024) <doi:10.1016/j.tins.2024.06.002>]. Yet, despite decades of pupillometry research, many established packages and workflows to date lack design patterns based on Findability, Accessibility, Interoperability, and Reusability (FAIR) principles [see Wilkinson et al. (2016) <doi:10.1038/sdata.2016.18>]. 'eyeris' provides a modular, performant, and extensible preprocessing framework for pupillometry data with BIDS-like organization and interactive output reports [Esteban et al. (2019) <doi:10.1038/s41592-018-0235-4>; Gorgolewski et al. (2016) <doi:10.1038/sdata.2016.44>]. Development was supported, in part, by the S [...truncated...]
Author: Shawn Schwartz [aut, cre] , Mingjian He [ctb], Haopei Yang [ctb], Alice Xue [ctb], Gustavo Santiago-Reyes [ctb]
Maintainer: Shawn Schwartz <shawn.t.schwartz@gmail.com>

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Package munfold updated to version 0.3.7 with previous version 0.3.5 dated 2016-02-08

Title: Metric Unfolding
Description: Multidimensional unfolding using Schoenemann's algorithm for metric and Procrustes rotation of unfolding results.
Author: Martin Elff [aut, cre]
Maintainer: Martin Elff <martin@elff.eu>

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Package svySE updated to version 0.2.1 with previous version 0.2.0 dated 2026-07-14

Title: Sampling Error Estimation for Complex Surveys
Description: Estimates sampling errors and produces indicator tables for complex survey data. Supports weighted totals, proportions, standard errors, confidence intervals, coefficients of variation, design effects, unweighted frequencies, grouped estimates, domain estimates, optional stratification and clustering variables, and customizable exports to '.xlsx' files. Survey estimation is based on design-based inference using Taylor series linearization implemented in the 'survey' package (Lumley, 2004, <doi:10.18637/jss.v009.i08>; Lumley, 2010, ISBN:9780470284308). The package provides a reproducible workflow for official statistics, household surveys, and applied survey research.
Author: Luis Burgos [aut, cre]
Maintainer: Luis Burgos <lburgoss1996@gmail.com>

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Package SlimR updated to version 1.1.8 with previous version 1.1.7 dated 2026-07-22

Title: Adaptive Machine Learning-Powered, Context-Matching Tool for Single-Cell and Spatial Transcriptomics Annotation
Description: Annotates single-cell and spatial-transcriptomic (ST) data using context-matching marker datasets. It creates a unified marker list (`Markers_list`) from multiple sources: built-in curated databases ('Cellmarker2', 'PanglaoDB', 'ScType', 'CellTypist', 'scIBD', 'TCellSI', 'PCTIT', 'PCTAM'), Seurat objects with cell labels, or user-provided Excel tables. SlimR first uses adaptive machine learning for parameter optimization, and then offers two automated annotation approaches: 'cluster-based' and 'per-cell'. Cluster-based annotation assigns one label per cluster, expression-based probability calculation, and AUC validation. Per-cell annotation assigns labels to individual cells using three scoring methods with adaptive thresholds and ratio-based confidence filtering, plus optional UMAP spatial smoothing, making it ideal for heterogeneous clusters and rare cell types. The package also supports semi-automated workflows with heatmaps, feature plots, and combined visualizations for manual ann [...truncated...]
Author: Zhaoqing Wang [aut, cre]
Maintainer: Zhaoqing Wang <zhaoqingwang@mail.sdu.edu.cn>

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Package ROOT updated to version 0.2.0 with previous version 0.1.1 dated 2026-03-10

Title: Rashomon Set of Optimal Trees
Description: Implements a general framework for globally optimizing user-specified objective functionals over interpretable binary weight functions represented as sparse decision trees, called ROOT (Rashomon Set of Optimal Trees). It searches over candidate trees to construct a Rashomon set of near-optimal solutions and derives a summary tree highlighting stable patterns in the optimized weights. ROOT includes a built-in generalizability mode for identifying subgroups in trial settings for transportability analyses (Parikh et al. (2025) <doi:10.1080/01621459.2025.2495319>).
Author: Yiren Hou [aut] , Peter Liu [aut, cre] , Sean McGrath [aut] , Harsh Parikh [aut]
Maintainer: Peter Liu <bliu68@jh.edu>

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Package projoint updated to version 1.1.3 with previous version 1.1.2 dated 2026-07-15

Title: Conjoint Analysis with Reliability Correction and Visualization
Description: Provides tools for analyzing data generated from conjoint survey experiments, a method widely used in the social sciences for studying multidimensional preferences. The package implements estimation of marginal means (MMs) and average marginal component effects (AMCEs), with corrections for measurement error. Methods include profile-level and choice-level estimators, bias correction using intra-respondent reliability (IRR), and visualization utilities. For details on the methodology, see Clayton, Horiuchi, Kaufman, King, and Komisarchik (2025) <https://gking.harvard.edu/conjointE>.
Author: Yusaku Horiuchi [aut, cre] , Aaron Kaufman [aut] , Gary King [aut]
Maintainer: Yusaku Horiuchi <yusaku.horiuchi@gmail.com>

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Package facomplex updated to version 1.0.0 with previous version 0.0.3 dated 2026-07-21

Title: Methods for Assessing Factor Complexity and Simplicity in Factor Analysis Solutions
Description: Provides methods for estimating factor complexity coefficients in exploratory and confirmatory factor analysis (EFA/CFA) results. Included indices are the Hofman coefficient, Fleming's approach for factor simplicity, and others. Additional outputs include descriptive statistics (minimum, maximum, and mean) for target and non-target loadings, and visualization of results. References: Fleming, J.S. (2003) <doi:10.3758/bf03195531>; Hofmann, R.J. (1978) <doi:10.1207/s15327906mbr1302_9>; Kaiser, H.F. (1974) <doi:10.1007/BF02291575>; Bentler, P.M. (1977) <doi:10.1007/BF02294054>; Lorenzo-Seva, U. (2003) <doi:10.1007/BF02296652>.
Author: Merino-Soto Cesar A. [aut, cre], Dominguez-Lara Sergio [ctb]
Maintainer: Merino-Soto Cesar A. <sikayax@yahoo.com.ar>

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Package OLSengine updated to version 1.1.1 with previous version 1.1.0 dated 2026-07-13

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 glasstabs updated to version 0.3.4 with previous version 0.3.3 dated 2026-06-24

Title: Animated Glass-Style Tabs and Select Inputs for 'Shiny'
Description: Tools for creating animated glassmorphism-style tab navigation and select filter widgets in 'Shiny' applications. Provides a tab navigation component with a sliding glass halo animation, a searchable multi-select dropdown, and a single-select dropdown - all with multiple colour themes and server-side update helpers. Tabs support icons, numeric badges, disable/enable toggling, runtime append/remove, reactive rendering via 'renderGlassTabs()', URL bookmarking, and compact mode for dashboard card layouts. 'glassTabCondition()' generates 'conditionalPanel()' condition strings without needing to recall the internal input key pattern. 'glasstabs_news()' displays the release notes from the R console. Built-in example apps can be launched with 'runGlassExample()'. All widgets are compatible with standard 'Shiny' layouts and 'bs4Dash' dashboards and 'bslib' themed applications. For full documentation and examples see Arthur (2026) <https://prigasg.github.io/glasstabs/>.
Author: George Arthur [aut, cre]
Maintainer: George Arthur <prigasgenthian48@gmail.com>

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Package ThSQCA updated to version 2.0.6 with previous version 2.0.5 dated 2026-07-23

Title: Threshold-Sweep QCA
Description: Provides threshold sweep methods for Qualitative Comparative Analysis (QCA). Implements Condition Threshold Sweep-Single (CTS-S), Condition Threshold Sweep-Multiple (CTS-M), Outcome Threshold Sweep (OTS), and Dual Threshold Sweep (DTS) for systematic exploration of threshold calibration effects on crisp-set QCA results. These methods extend traditional robustness approaches by treating threshold variation as an exploratory tool for discovering causal structures. Also provides Fiss (2011) <doi:10.5465/amj.2011.60263120> core/peripheral condition classification via compute_fiss_core() and generate_fiss_chart(), enabling four-symbol configuration charts that distinguish core conditions (present in both parsimonious and intermediate solutions) from peripheral conditions (intermediate only). Built on top of the 'QCA' package by Dusa (2019) <doi:10.1007/978-3-319-75668-4>, with function arguments following 'QCA' conventions. Based on set-theoretic methods by Ragin (2008) <doi: [...truncated...]
Author: Yuki Toyoda [aut, cre], Japan Society for the Promotion of Science [fnd]
Maintainer: Yuki Toyoda <yuki.toyoda.ds@hosei.ac.jp>

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Package rdecision updated to version 1.3.1 with previous version 1.3.0 dated 2025-02-10

Title: Decision Analytic Modelling in Health Economics
Description: Classes and functions for modelling health care interventions using decision trees and semi-Markov models. Mechanisms are provided for associating an uncertainty distribution with each source variable and for ensuring transparency of the mathematical relationships between variables. The package terminology follows Briggs "Decision Modelling for Health Economic Evaluation" (2006, ISBN:978-0-19-852662-9).
Author: Andrew Sims [aut, cre] , Kim Keltie [aut] , Paola Cognigni [aut]
Maintainer: Andrew Sims <andrew.sims@newcastle.ac.uk>

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Package stats19 updated to version 4.1.0 with previous version 4.0.0 dated 2026-03-18

Title: Work with Open Road Traffic Casualty Data from Great Britain
Description: Work with and download road traffic casualty data from Great Britain. Enables access to the UK's official road safety statistics, 'STATS19'. Enables users to specify a download directory for the data, which can be set permanently by adding `STATS19_DOWNLOAD_DIRECTORY=/path/to/a/dir` to your `.Renviron` file, which can be opened with `usethis::edit_r_environ()`. The data is provided as a series of `.csv` files. This package downloads, reads-in and formats the data, making it suitable for analysis. See the stats19 vignette for details. Data available from 1979 to 2025. See the official data series at <https://www.data.gov.uk/dataset/cb7ae6f0-4be6-4935-9277-47e5ce24a11f/road-accidents-safety-data>. The package is described in a paper in the Journal of Open Source Software (Lovelace et al. 2019) <doi:10.21105/joss.01181>. See Gilardi et al. (2022) <doi:10.1111/rssa.12823>, Vidal-Tortosa et al. (2021) <doi:10.1016/j.jth.2021.101291>, Tait et al. (2023) <doi:10.101 [...truncated...]
Author: Robin Lovelace [aut, cre] , Malcolm Morgan [aut] , Layik Hama [aut] , Mark Padgham [aut] , David Ranzolin [rev], Adam Sparks [rev, ctb] , Ivo Wengraf [ctb], RAC Foundation [fnd], Blaise Kelly [aut] , Roger Beecham [aut]
Maintainer: Robin Lovelace <rob00x@gmail.com>

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Package simtte updated to version 1.0.2 with previous version 1.0.1 dated 2026-07-11

Title: Simulate Bespoke Time-to-Event Models Using ODEs
Description: Simulates time-to-event (survival) datasets for clinical trial design and analysis using ordinary differential equation (ODE) models solved via the 'mrgsolve' backend. Built-in Weibull and flexible M-spline baseline hazard models are provided out of the box, and fully bespoke hazard models can be implemented as custom 'mrgsolve' ODE systems. Event times are generated by inverse transform sampling from the resulting cumulative hazard functions. See Bender et al. (2005) <doi:10.1002/sim.2059> for the inverse transform sampling methodology and Royston and Parmar (2002) <doi:10.1002/sim.1203> for flexible parametric survival models.
Author: Carlos Traynor [aut, cre]
Maintainer: Carlos Traynor <carlos.traynor.qcp@gmail.com>

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Package highdir updated to version 0.6.0 with previous version 0.5.0 dated 2026-05-27

Title: Unified Data Visualization Framework for Dynamic and Static Graphics
Description: Provides a unified API for creating data visualizations across dynamic and static rendering modes. Visualizations are defined once using a specification object and can be rendered with 'highcharter', 'ggplot2', or other supported packages without modifying user code. The package supports declarative and layered workflows, reusable themes and colour palettes, optional 'JavaScript' enhancements, export tools, and interactive exploration through 'shiny' applications.
Author: Yusman Kamaleri [aut, cre]
Maintainer: Yusman Kamaleri <ybkamaleri@gmail.com>

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Package exams2learnr updated to version 0.1-1 with previous version 0.1-0 dated 2022-10-21

Title: Interface for 'exams' Exercises in 'learnr' Tutorials
Description: Automatic generation of quizzes or individual questions for 'learnr' tutorials based on 'R/exams' exercises.
Author: Achim Zeileis [aut, cre]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package exams2forms updated to version 0.2-2 with previous version 0.2-1 dated 2026-05-05

Title: Embedding 'exams' Exercises as Forms in 'rmarkdown' or 'quarto' Documents
Description: Automatic generation of quizzes or individual questions as (interactive) forms within 'rmarkdown' or 'quarto' documents based on 'R/exams' exercises.
Author: Achim Zeileis [aut, cre] , Reto Stauffer [aut] , Dale Barr [ctb] , Lisa DeBruine [ctb] , Florian Stampfer [ctb] , Jonas Tscholl [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package DRomics updated to version 2.6.3 with previous version 2.6-2 dated 2024-10-16

Title: Dose Response for Omics
Description: Several functions are provided for dose-response (or concentration-response) characterization from omics data. 'DRomics' is especially dedicated to omics data obtained using a typical dose-response design, favoring a great number of tested doses (or concentrations) rather than a great number of replicates (no need of replicates). 'DRomics' provides functions 1) to check, normalize and or transform data, 2) to select monotonic or biphasic significantly responding items (e.g. probes, metabolites), 3) to choose the best-fit model among a predefined family of monotonic and biphasic models to describe each selected item, 4) to derive a benchmark dose or concentration and a typology of response from each fitted curve. In the available version data are supposed to be single-channel microarray data in log2, RNAseq data in raw counts, or already pretreated continuous omics data (such as metabolomic data) in log scale. In order to link responses across biological levels based on a common method, [...truncated...]
Author: Marie-Laure Delignette-Muller [aut] , Elise Billoir [aut] , Floriane Larras [ctb], Aurelie Siberchicot [aut, cre]
Maintainer: Aurelie Siberchicot <aurelie.siberchicot@univ-lyon1.fr>

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New package coxmnar with initial version 0.1.0
Package: coxmnar
Title: Cox Regression with Missing not at Random Failure Indicators
Version: 0.1.0
Description: Implements estimation for the Cox (1972, 1975) <doi:10.1111/j.2517-6161.1972.tb00899.x> <doi:10.1093/biomet/62.2.269> proportional hazards model when the failure indicator (cause of failure) is missing not at random (MNAR), following the two adjusted imputation-based estimating equations of Liu and Liu (2026) <doi:10.1007/s11222-026-10857-1>. Also provided for comparison are the full-data partial-likelihood estimator of Andersen and Gill (1982) <doi:10.1214/aos/1176345976>, the complete-case estimator, and the missing-at-random imputation estimator of Liu and Wang (2010, Statistica Sinica, 20, 1125-1142). The probability models for the failure indicator and for the missingness mechanism are estimated jointly by maximum likelihood following Sun, Xie, and Liang (2013) <doi:10.1007/s11425-012-4492-x>, and a Nadaraya-Watson kernel-smoothed estimator of the missingness propensity is constructed following Qiu, Chen, and Zhou (2015) <doi:10.1016/j.spl.2014.12. [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: survival (>= 3.5-0), stats, Rdpack
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, covr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-07-22 23:23:20 UTC; shikhar tyagi
Author: Shikhar Tyagi [aut, cre] , Arvind Pandey [aut], Bhupendra Singh [aut], Vrijesh Tripathi [aut]
Maintainer: Shikhar Tyagi <shikhar1093tyagi@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-31 15:10:02 UTC

More information about coxmnar at CRAN
Permanent link

Package BetaDanish updated to version 0.3.0 with previous version 0.2.0 dated 2026-06-03

Title: The Beta-Danish Distribution for Lifetime Data Analysis
Description: Implements the four-parameter Beta-Danish distribution and its three-parameter Exponentiated Danish submodel for survival, reliability and lifetime data analysis, following Ahmad and Danish (2025) <doi:10.2478/jamsi-2025-0010>. Density, distribution, quantile, survival, hazard and random generation functions are evaluated so as to retain accuracy in the heavy upper tail, where the survival function is regularly varying. Estimation covers maximum likelihood for complete and right-censored samples, ridge-penalized fitting for weakly identified regimes, a grouped likelihood for times recorded on a coarse grid, and Bayesian sampling. Inference provides log-scale Wald and profile likelihood intervals, together with a reparameterization in terms of the identified composite of the two shape parameters. Structural properties include raw, incomplete and conditional moments with their existence conditions, Shannon, Renyi and Tsallis entropies, mean residual life, mean deviations, Lorenz an [...truncated...]
Author: Bilal Ahmad [aut, cre], Muhammad Yameen Danish [aut]
Maintainer: Bilal Ahmad <bilalahmad.imcbh9@gmail.com>

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Package BEND updated to version 2.1.1 with previous version 2.1.0 dated 2026-07-10

Title: Bayesian Estimation of Nonlinear Data (BEND)
Description: Provides a set of models to estimate nonlinear longitudinal data using Bayesian estimation methods. These models include the: 1) Bayesian Piecewise Random Effects Model (Bayes_PREM()) which estimates a piecewise random effects (mixture) model for a given number of latent classes and a latent number of possible changepoints in each class, and can incorporate class and outcome predictive covariates (see Lamm (2022) <https://hdl.handle.net/11299/252533> and Lock et al., (2018) <doi:10.1007/s11336-017-9594-5>), 2) Bayesian Crossed Random Effects Model (Bayes_CREM()) which estimates a linear, quadratic, exponential, or piecewise crossed random effects models where individuals are changing groups over time (e.g., students and schools; see Rohloff et al., (2024) <doi:10.1111/bmsp.12334>), and 3) Bayesian Bivariate Piecewise Random Effects Model (Bayes_BPREM()) which estimates a bivariate piecewise random effects model to jointly model two related outcomes (e.g., reading and [...truncated...]
Author: Corissa T. Rohloff [aut, cre] , Rik Lamm [aut] , Yadira Peralta [aut] , Nidhi Kohli [aut] , Eric F. Lock [aut]
Maintainer: Corissa T. Rohloff <corissa.wurth@gmail.com>

Diff between BEND versions 2.1.0 dated 2026-07-10 and 2.1.1 dated 2026-07-31

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New package regMR with initial version 1.0.0
Package: regMR
Title: Regularized Finite Mixture Regression Models Using MM Algorithm
Version: 1.0.0
Description: Provides a comprehensive framework for fitting regularized finite mixture regression models via an MM algorithm. The sparse group lasso (sgl) penalty is applied to parameter updates within the MM algorithm for variable selection with respect to groups and covariates. The package provides multiple functions for estimation and allows users to fit models over different lambda-alpha sgl penalties and group counts.
License: MIT + file LICENSE
Encoding: UTF-8
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 4.1.0)
Imports: furrr, future, ggplot2, graphics, mclust, purrr, Rcpp, reshape2, plotly, stats
Suggests: mvtnorm, rlang, testthat (>= 3.0.0)
URL: https://github.com/vjoshy/regMR
BugReports: https://github.com/vjoshy/regMR/issues
NeedsCompilation: yes
Packaged: 2026-07-22 18:41:35 UTC; cambechthold
Author: Cameron Bechthold [aut, cre, cph], Vinay Joshy [aut, ctb, cph], Zeny Feng [aut, ths, cph], Grace Stelter [ctb]
Maintainer: Cameron Bechthold <cbechtho@uoguelph.ca>
Repository: CRAN
Date/Publication: 2026-07-31 14:10:02 UTC

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New package envar with initial version 0.1.0
Package: envar
Title: Download and Process Environmental Variables
Version: 0.1.0
Description: Provides a unified interface to download, harmonise and extract a wide range of environmental and socio-economic variables from established open data web services (such as 'WorldClim' <https://www.worldclim.org/>, 'CHELSA' <https://chelsa-climate.org/> and 'Bio-ORACLE' <https://www.bio-oracle.org/>, among others) for use in macroecology and biogeography. The package handles spatial subsetting to a study area, reprojection to a common coordinate reference system, and extraction of values at sampling points, so that predictors from heterogeneous sources can be assembled within a single reproducible workflow. Helper functions for collinearity checking and variable exploration are also included.
License: GPL-3
Language: en-US
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Imports: terra, dplyr, httr, sf, rnaturalearth, usdm, corrplot, cli, fs, utils, digest, rangeBuilder
Suggests: knitr, rmarkdown, rnaturalearthdata
VignetteBuilder: knitr
URL: https://animalbiodiversitylab.github.io/envar/, https://github.com/animalbiodiversitylab/envar
BugReports: https://github.com/animalbiodiversitylab/envar/issues
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2026-07-22 21:50:06 UTC; andre
Author: Andrea Simoncini [aut, cre] , Michele Bertoncini [aut] , Andrea Cerofolini [aut] , Andrea Dalpasso [aut] , Mattia Falaschi [aut] , Gentile Francesco Ficetola [aut] , Elia Lo Parrino [aut]
Maintainer: Andrea Simoncini <simonciniandre@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-31 14:30:02 UTC

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New package olympicAthletes with initial version 0.5.10
Package: olympicAthletes
Title: Olympic Athlete Event Data, Athens 1896 to Milano-Cortina 2026
Version: 0.5.10
Description: A tidy, long-format dataset of every athlete-event participation in the modern Olympic Games, spanning Athens 1896 through Milano-Cortina 2026 (about 315,000 rows). Extends the rgriff23 'Olympic_history' dataset (1896-2016) with five additional editions scraped from Olympedia (<https://www.olympedia.org>): PyeongChang 2018, Tokyo 2020, Beijing 2022, Paris 2024, and Milano-Cortina 2026. Companion datasets cover edition-level metadata and verified medal tables for every edition from 1896 to 2026.
License: CC BY 4.0
Language: en-US
Encoding: UTF-8
LazyData: true
LazyDataCompression: xz
Depends: R (>= 4.1)
Suggests: dplyr, knitr, pkgdown, rmarkdown, testthat (>= 3.0.0), tidyr
VignetteBuilder: knitr
URL: https://github.com/moderndive/olympicAthletes, https://moderndive.github.io/olympicAthletes/
BugReports: https://github.com/moderndive/olympicAthletes/issues
NeedsCompilation: no
Packaged: 2026-07-22 17:31:28 UTC; chesterismay
Author: Chester Ismay [aut, cre]
Maintainer: Chester Ismay <chester.ismay@gmail.com>
Repository: CRAN
Date/Publication: 2026-07-31 14:00:02 UTC

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Package camtrapdp updated to version 0.6.0 with previous version 0.5.0 dated 2026-01-14

Title: Read and Manipulate Camera Trap Data Packages
Description: Read and manipulate Camera Trap Data Packages ('Camtrap DP'). 'Camtrap DP' (<https://camtrap-dp.tdwg.org>) is a data exchange format for camera trap data. With 'camtrapdp' you can read, filter and transform data (including to Darwin Core) before further analysis in e.g. 'camtraptor' or 'camtrapR'.
Author: Peter Desmet [aut, cre] ), Sanne Govaert [aut] ), Pieter Huybrechts [aut] ), Damiano Oldoni [aut] ), Research Institute for Nature and Forest [cph] , Research Foundation - Flanders [fnd]
Maintainer: Peter Desmet <peter.desmet@inbo.be>

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Package tidync updated to version 0.5.0 with previous version 0.4.0 dated 2024-08-17

Title: Tidy Approach to 'NetCDF' Data Exploration and Extraction
Description: Tidy tools for 'NetCDF' data sources. Explore the contents of a 'NetCDF' source (file or URL) presented as variables organized by grid with a database-like interface. The hyper_filter() interactive function translates the filter value or index expressions to array-slicing form. No data is read until explicitly requested, as a data frame or list of arrays via hyper_tibble() or hyper_array().
Author: Michael Sumner [aut, cre, cph], Simon Wotherspoon [ctb], Tomas Remenyi [ctb], Ben Raymond [ctb], Jakub Nowosad [ctb], Tim Lucas [ctb], Hadley Wickham [ctb], Adrian Odenweller [ctb], Patrick Van Laake [ctb], Fabian Bernhard [ctb]
Maintainer: Michael Sumner <mdsumner@gmail.com>

Diff between tidync versions 0.4.0 dated 2024-08-17 and 0.5.0 dated 2026-07-31

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Package SqlRender updated to version 1.19.6 with previous version 1.19.5 dated 2026-03-25

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 wmwAUC updated to version 1.0.0 with previous version 0.2.0 dated 2025-12-19

Title: Test of No Group Discrimination Using the WMW Statistic
Description: Implements a wmwAUC test of H0: AUC = 1/2 for continuous, discrete, or mixed random variables, based on the Wilcoxon-Mann-Whitney (WMW) statistic. The classic WMW test is calibrated under H0: {(F, G): F = G} which does not match the set {(F, G): AUC = 1/2}, implied by the test statistic, and consequently leads to erroneous inferences. wmwAUC is calibrated under the correct null and implements two finite-sample corrected p-value methods: an Exact Unbiased (EU) method and a Bias-Corrected (BC) method, both valid for any tie pattern. Methods are described in M. Grendar (2025) "Wilcoxon-Mann-Whitney Test of No Group Discrimination" <doi:10.48550/arXiv.2511.20308>.
Author: Marian Grendar [aut, cre]
Maintainer: Marian Grendar <marian.grendar@gmail.com>

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Package reaborn updated to version 1.0.2 with previous version 1.0.1 dated 2026-07-03

Title: Statistical Data Visualization, the 'seaborn' Way
Description: An 'R' port of the 'Python' 'seaborn' library. 'reaborn' mirrors the 'seaborn' public function API (identical function names, argument names, and defaults) and renders visually indistinguishable plots using 'ggplot2'. Because every 'reaborn' plot is a 'ggplot' object, it can be extended with the full 'ggplot2' grammar of graphics.
Author: Shawn Schwartz [aut, cre]
Maintainer: Shawn Schwartz <shawn.t.schwartz@gmail.com>

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Package IssueTrackeR updated to version 1.4.1 with previous version 1.4.0 dated 2026-06-20

Title: List Things to Do
Description: Manage a 'GitHub' problem using R: wrangle issues, labels and milestones. It includes functions for storing, prioritizing (sorting), displaying, adding, deleting, and selecting (filtering) issues based on qualitative and quantitative information. Issues (labels and milestones) are written in lists and categorized into the S3 class to be easily manipulated as datasets in R.
Author: Tanguy Barthelemy [aut, cre, art, cph]
Maintainer: Tanguy Barthelemy <tanguy.barthelemy@insee.fr>

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Package fscontext updated to version 0.2.1 with previous version 0.2.0 dated 2026-07-06

Title: File System Contextualisation and Record Set Reconstruction
Description: Provides a provenance-aware framework for contextual reconstruction from file systems and related digital resource collections. The package creates reproducible snapshots of file-level metadata, paths, repository context, and optional content signatures. It supports contextual grouping, structural abstraction, temporal analysis, semantic stabilization, duplicate and reuse detection, and lightweight workflow reconstruction from file system observations. The framework deliberately separates observational evidence, contextual abstraction, semantic interpretation, and analytical reconstruction, enabling reproducible workflows that can be inspected by reviewers. It is designed to support future alignment with archival and contextual knowledge representation models, including the World Wide Web Consortium Provenance Ontology (PROV-O): Lebo et al. (2013) <https://www.w3.org/TR/prov-o/> and Records in Contexts developed by the International Council on Archives Expert Group on Archival De [...truncated...]
Author: Daniel Antal [aut, cre]
Maintainer: Daniel Antal <daniel.antal@dataobservatory.eu>

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Package exams updated to version 2.4-4 with previous version 2.4-3 dated 2025-12-23

Title: Automatic Generation of Exams in R
Description: Automatic generation of exams based on exercises in Markdown or LaTeX format, possibly including R code for dynamic generation of exercise elements. Exercise types include single-choice and multiple-choice questions, arithmetic problems, string questions, and combinations thereof (cloze). Output formats include standalone files (PDF, HTML, Docx, ODT, ...), Moodle XML, QTI 1.2, QTI 2.1, Blackboard, Canvas, OpenOlat, ILIAS, TestVision, Particify, ARSnova, Kahoot!, Grasple, and TCExam. In addition to fully customizable PDF exams, a standardized PDF format (NOPS) is provided that can be printed, scanned, and automatically evaluated.
Author: Achim Zeileis [aut, cre] , Bettina Gruen [aut] , Friedrich Leisch [aut] , Nikolaus Umlauf [aut] , Niels Smits [aut] , Mirko Birbaumer [ctb], Dominik Ernst [ctb] , Patrik Keller [ctb], Reto Stauffer [ctb] , Kenji Sato [ctb] , Florian Wickelmaier [ctb] [...truncated...]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package simDAG updated to version 1.0.1 with previous version 1.0.0 dated 2026-05-14

Title: Simulate Data from a (Time-Dependent) Causal DAG
Description: Simulate complex data from a given directed acyclic graph and information about each individual node. Root nodes are simply sampled from the specified distribution. Child Nodes are simulated according to one of many implemented regressions, such as logistic regression, linear regression, poisson regression or any other function. Also includes a comprehensive framework for discrete-time simulation, discrete-event simulation, and networks-based simulation which can generate even more complex longitudinal and dependent data. For more details, see Robin Denz, Nina Timmesfeld (2026) <doi:10.18637/jss.v116.i02>.
Author: Robin Denz [aut, cre], Katharina Meiszl [aut]
Maintainer: Robin Denz <robin.denz@rub.de>

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Package phsmethods updated to version 1.2.0 with previous version 1.1.0 dated 2026-03-30

Title: Standard Methods for Use in Public Health Scotland
Description: A collection of methods for commonly undertaken analytical tasks, primarily developed for Public Health Scotland (PHS) analysts, but the package is also generally useful to others working in the healthcare space, particularly since it has functions for working with Community Health Index (CHI) numbers. The package can help to make data manipulation and analysis more efficient and reproducible.
Author: Public Health Scotland [cph], David Caldwell [aut], Lucinda Lawrie [rev], Jack Hannah [aut], Tina Fu [aut, cre], Ciara Gribben [aut], Chris Deans [aut], Jaime Villacampa [aut], Graeme Gowans [aut], Alice Byers [ctb], Alan Yeung [ctb], James Hayes [au [...truncated...]
Maintainer: Tina Fu <Yuyan.Fu2@phs.scot>

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Package mermboost updated to version 0.1.2 with previous version 0.1.1 dated 2025-05-16

Title: Gradient Boosting for Generalized Additive Mixed Models
Description: Provides a novel framework to estimate mixed models via gradient boosting. The implemented functions are based on the 'mboost' and 'lme4' packages, and the family range is therefore determined by 'lme4'. A correction mechanism for cluster-constant covariates is implemented, as well as estimation of the covariance of random effects. These methods are described in the accompanying publication; see <doi:10.1007/s11222-025-10612-y> for details.
Author: Lars Knieper [aut, cre], Torsten Hothorn [aut], Elisabeth Bergherr [aut], Colin Griesbach [aut]
Maintainer: Lars Knieper <lars.knieper@uni-goettingen.de>

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Package migraph updated to version 1.6.8 with previous version 1.6.6 dated 2026-06-24

Title: Inferential Methods for Multimodal and Other Networks
Description: A set of tools for testing networks. It includes functions for univariate and multivariate conditional uniform graph and quadratic assignment procedure testing, and network regression. The package is a complement to 'Multimodal Political Networks' (2021, ISBN:9781108985000), and includes various datasets used in the book. Built on the 'manynet' package, all functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects, and on one-mode and two-mode (bipartite) networks.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb] , Jael Tan [ctb] , Bernhard Bieri [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package spatstat updated to version 3.6-2 with previous version 3.6-1 dated 2026-06-02

Title: Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests
Description: Comprehensive open-source toolbox for analysing Spatial Point Patterns. Focused mainly on two-dimensional point patterns, including multitype/marked points, in any spatial region. Also supports three-dimensional point patterns, space-time point patterns in any number of dimensions, point patterns on a linear network, and patterns of other geometrical objects. Supports spatial covariate data such as pixel images. Contains over 3000 functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, pixel images, tessellations, and linear networks. Exploratory methods include quadrat counts, K-functions and their simulation envelopes, nearest neighbour distance and empty space statistics, Fry plots, pair correlation function, kernel smoothed intensity, relative risk estimation with cross-validated bandwidth selection, mark correlatio [...truncated...]
Author: Adrian Baddeley [aut, cre] , Rolf Turner [aut] , Ege Rubak [aut]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package ip2proxy updated to version 1.2.2 with previous version 1.2.0 dated 2023-02-10

Title: Lookup for IP Address Proxy Information
Description: A R package to find the IP addresses which are used as VPN anonymizer, open proxies, web proxies and Tor exits. The package lookup the proxy IP address from IP2Proxy BIN Data file. You may visit <https://lite.ip2location.com> for free database download.
Author: IP2Location [aut, cre]
Maintainer: IP2Location <support@ip2location.com>

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Package easyalluvial updated to version 0.4.1 with previous version 0.4.0 dated 2025-09-03

Title: Generate Alluvial Plots with a Single Line of Code
Description: Alluvial plots are similar to sankey diagrams and visualise categorical data over multiple dimensions as flows. (Rosvall M, Bergstrom CT (2010) Mapping Change in Large Networks. PLoS ONE 5(1): e8694. <doi:10.1371/journal.pone.0008694> Their graphical grammar however is a bit more complex then that of a regular x/y plots. The 'ggalluvial' package made a great job of translating that grammar into 'ggplot2' syntax and gives you many options to tweak the appearance of an alluvial plot, however there still remains a multi-layered complexity that makes it difficult to use 'ggalluvial' for explorative data analysis. 'easyalluvial' provides a simple interface to this package that allows you to produce a decent alluvial plot from any dataframe in either long or wide format from a single line of code while also handling continuous data. It is meant to allow a quick visualisation of entire dataframes with a focus on different colouring options that can make alluvial plots a great tool for d [...truncated...]
Author: Bjoern Koneswarakantha [aut, cre]
Maintainer: Bjoern Koneswarakantha <datistics@gmail.com>

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Package autograph updated to version 1.1.2 with previous version 1.1.1 dated 2026-07-21

Title: Automatic Plotting and Theming of Many Graphs
Description: Visual exploration and presentation of networks should not be difficult. This package includes functions for plotting networks and network-related metrics with sensible and pretty defaults. It includes 'ggplot2'-based plot methods for many popular network package classes. It also includes some novel layout algorithms, and options for straightforward, consistent themes.
Author: James Hollway [cre, aut, ctb] , Henrique Sposito [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package tth updated to version 4.16-1 with previous version 4.16-0 dated 2024-04-26

Title: TeX-to-HTML/MathML Translators TtH/TtM
Description: C source code and R wrappers for the tth/ttm TeX-to-HTML/MathML translators.
Author: Ian H. Hutchinson [aut] , Friedrich Leisch [aut] , Achim Zeileis [aut, cre]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package frictionless updated to version 1.3.0 with previous version 1.2.1 dated 2025-05-23

Title: Read and Write Frictionless Data Packages
Description: Read and write Frictionless Data Packages. A 'Data Package' (<https://specs.frictionlessdata.io/data-package/>) is a simple container format and standard to describe and package a collection of (tabular) data. It is typically used to publish FAIR (<https://www.go-fair.org/fair-principles/>) and open datasets.
Author: Peter Desmet [aut, cre] ), Damiano Oldoni [aut] ), Pieter Huybrechts [aut] ), Sanne Govaert [aut] ), Kyle Husmann [ctb] , Research Institute for Nature and Forest [cph] , Research Foundation - Flanders [fnd] , Beatriz Milz [rev] , Joao Martins [rev] [...truncated...]
Maintainer: Peter Desmet <peter.desmet@inbo.be>

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Package zoo updated to version 1.9-0 with previous version 1.8-15 dated 2025-12-15

Title: S3 Infrastructure for Regular and Irregular Time Series (Z's Ordered Observations)
Description: An S3 class with methods for working with regular and irregular time series. The class stores data as numeric vectors/matrices (or factors) along with a time index of arbitrary class (including numeric, Date, POSIXct, chron, yearmon, yearqtr, etc.). Functions and methods are consistent with the ts class and base R and also extend standard generics. Tools include: Data import/export, coercion, visualization (with base R, 'ggplot2', 'lattice', 'tinyplot'), alignment and merging, aggregation, lags and subsets, rolling analytics, and time-based interpolation/filling. The design is introduced in Zeileis and Grothendieck (2005) <doi:10.18637/jss.v014.i06>.
Author: Achim Zeileis [aut, cre] , Gabor Grothendieck [aut], Jeffrey A. Ryan [aut], Joshua M. Ulrich [ctb], Felix Andrews [ctb]
Maintainer: Achim Zeileis <Achim.Zeileis@R-project.org>

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Package fitODBOD (with last version 1.5.5) was removed from CRAN

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

2025-11-19 1.5.5
2024-11-20 1.5.4
2024-10-10 1.5.3
2024-06-28 1.5.2
2024-02-09 1.5.1
2023-01-15 1.5.0
2020-01-16 1.4.1-1
2019-07-02 1.4.1
2019-06-12 1.4.0
2019-05-07 1.3.0
2018-09-15 1.2.0
2018-02-27 1.1.0

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Package modelDown (with last version 1.1) was removed from CRAN

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

2020-04-14 1.1

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Package glmbayes (with last version 0.9.72) was removed from CRAN

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

2026-07-26 0.9.72
2026-07-19 0.9.7
2026-06-21 0.9.6
2026-05-18 0.9.5
2026-05-04 0.9.3

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