Tue, 09 Dec 2025

New package SSLfmm with initial version 0.1.0
Package: SSLfmm
Title: Semi-Supervised Learning under a Mixed-Missingness Mechanism in Finite Mixture Models
Version: 0.1.0
Maintainer: Jinran Wu <jinran.wu@uq.edu.au>
Description: Implements a semi-supervised learning framework for finite mixture models under a mixed-missingness mechanism. The approach models both missing completely at random (MCAR) and entropy-based missing at random (MAR) processes using a logistic–entropy formulation. Estimation is carried out via an Expectation–-Conditional Maximisation (ECM) algorithm with robust initialisation routines for stable convergence. The methodology relates to the statistical perspective and informative missingness behaviour discussed in Ahfock and McLachlan (2020) <doi:10.1007/s11222-020-09971-5> and Ahfock and McLachlan (2023) <doi:10.1016/j.ecosta.2022.03.007>. The package provides functions for data simulation, model estimation, prediction, and theoretical Bayes error evaluation for analysing partially labelled data under a mixed-missingness mechanism.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.2.0)
Imports: stats, mvtnorm, matrixStats
NeedsCompilation: no
Packaged: 2025-12-04 00:22:06 UTC; uqjwu15
Author: Jinran Wu [aut, cre] , Geoffrey J. McLachlan [aut]
Repository: CRAN
Date/Publication: 2025-12-09 16:30:28 UTC

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Package opalr updated to version 3.5.2 with previous version 3.5.1 dated 2025-11-16

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 3.5.1 dated 2025-11-16 and 3.5.2 dated 2025-12-09

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Package metacor updated to version 1.2.1 with previous version 1.2.0 dated 2025-09-26

Title: Meta-Analytic Effect Size Calculation for Pre-Post Designs with Correlation Imputation
Description: Tools for the calculation of effect sizes (standardised mean difference) and mean difference in pre-post controlled studies, including robust imputation of missing variances (standard deviation of changes) and correlations (Pearson correlation coefficient). The main function 'metacor_dual()' implements several methods for imputing missing standard deviation of changes or Pearson correlation coefficient, and generates transparent imputation reports. Designed for meta-analyses with incomplete summary statistics. For details on the methods, see Higgins et al. (2023) and Fu et al. (2013).
Author: Iker J. Bautista [aut, cre], Saul M. Rodriguez [ctb]
Maintainer: Iker J. Bautista <ikerugr@gmail.com>

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Package maestro updated to version 0.7.1 with previous version 0.7.0 dated 2025-10-31

Title: Orchestration of Data Pipelines
Description: Framework for creating and orchestrating data pipelines. Organize, orchestrate, and monitor multiple pipelines in a single project. Use tags to decorate functions with scheduling parameters and configuration.
Author: Will Hipson [cre, aut, cph] , Ryan Garnett [aut, ctb, cph]
Maintainer: Will Hipson <will.e.hipson@gmail.com>

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Package ggstatsplot updated to version 0.13.4 with previous version 0.13.3 dated 2025-10-05

Title: 'ggplot2' Based Plots with Statistical Details
Description: Extension of 'ggplot2', 'ggstatsplot' creates graphics with details from statistical tests included in the plots themselves. It provides an easier syntax to generate information-rich plots for statistical analysis of continuous (violin plots, scatterplots, histograms, dot plots, dot-and-whisker plots) or categorical (pie and bar charts) data. Currently, it supports the most common types of statistical approaches and tests: parametric, nonparametric, robust, and Bayesian versions of t-test/ANOVA, correlation analyses, contingency table analysis, meta-analysis, and regression analyses. References: Patil (2021) <doi:10.21105/joss.03236>.
Author: Indrajeet Patil [cre, aut, cph]
Maintainer: Indrajeet Patil <patilindrajeet.science@gmail.com>

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New package AdaptiveBoxplot with initial version 0.1.1
Package: AdaptiveBoxplot
Title: FDR(BH) Boxplot and FWER(Holm) Boxplot
Version: 0.1.1
Description: Implements a framework for creating boxplots where the whisker lengths are determined by formal multiple testing procedures, making them adaptive to sample size and data characteristics. The function bh_boxplot() generates boxplots that control the False Discovery Rate (FDR) via the Benjamini-Hochberg procedure, and the function holm_boxplot() generates boxplots that control the Family-Wise Error Rate (FWER) via the Holm procedure. The methods are based on the framework in Gang, Lin, and Tong (2025) <doi:10.48550/arXiv.2510.20259>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2025-12-04 01:13:52 UTC; bowengang
Author: Bowen Gang [aut, cre], Hongmei Lin [aut], Tiejun Tong [aut]
Maintainer: Bowen Gang <gangbowen02@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-09 16:30:34 UTC

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New package VCBART with initial version 1.2.4
Package: VCBART
Title: Fit Varying Coefficient Models with Bayesian Additive Regression Trees
Version: 1.2.4
Date: 2025-12-03
Description: Fits linear varying coefficient (VC) models, which assert a linear relationship between an outcome and several covariates but allow that relationship (i.e., the coefficients or slopes in the linear regression) to change as functions of additional variables known as effect modifiers, by approximating the coefficient functions with Bayesian Additive Regression Trees. Implements a Metropolis-within-Gibbs sampler to simulate draws from the posterior over coefficient function evaluations. VC models with independent observations or repeated observations can be fit. For more details see Deshpande et al. (2024) <doi:10.1214/24-BA1470>.
License: GPL (>= 3)
LinkingTo: Rcpp, RcppArmadillo
Imports: Rcpp, MASS
URL: https://github.com/skdeshpande91/VCBART
NeedsCompilation: yes
Packaged: 2025-12-03 14:19:58 UTC; sameer
Author: Sameer K. Deshpande [aut, cre] , Ray Bai [aut] , Cecilia Balocchi [aut] , Jennifer Starling [aut], Jordan Weiss [aut]
Maintainer: Sameer K. Deshpande <sameer.deshpande@wisc.edu>
Repository: CRAN
Date/Publication: 2025-12-09 16:00:02 UTC

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Package pkgstats readmission to version 0.2.1 with previous version 0.1.1 dated 2022-06-21

Title: Metrics of R Packages
Description: Static code analyses for R packages using the external code-tagging libraries 'ctags' and 'gtags'. Static analyses enable packages to be analysed very quickly, generally a couple of seconds at most. The package also provides access to a database generating by applying the main function to the full 'CRAN' archive, enabling the statistical properties of any package to be compared with all other 'CRAN' packages.
Author: Mark Padgham [aut, cre] , Michael Sumner [ctb] , Jeffrey Hollister [ctb] , Egor Kotov [ctb]
Maintainer: Mark Padgham <mark.padgham@email.com>

This is a re-admission after prior archival of version 0.1.1 dated 2022-06-21

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Package mmrm updated to version 0.3.16 with previous version 0.3.15 dated 2025-06-10

Title: Mixed Models for Repeated Measures
Description: Mixed models for repeated measures (MMRM) are a popular choice for analyzing longitudinal continuous outcomes in randomized clinical trials and beyond; see Cnaan, Laird and Slasor (1997) <doi:10.1002/(SICI)1097-0258(19971030)16:20%3C2349::AID-SIM667%3E3.0.CO;2-E> for a tutorial and Mallinckrodt, Lane, Schnell, Peng and Mancuso (2008) <doi:10.1177/009286150804200402> for a review. This package implements MMRM based on the marginal linear model without random effects using Template Model Builder ('TMB') which enables fast and robust model fitting. Users can specify a variety of covariance matrices, weight observations, fit models with restricted or standard maximum likelihood inference, perform hypothesis testing with Satterthwaite or Kenward-Roger adjustment, and extract least square means estimates by using 'emmeans'.
Author: Daniel Sabanes Bove [aut, cre] , Liming Li [aut] , Julia Dedic [aut], Doug Kelkhoff [aut], Kevin Kunzmann [aut], Brian Matthew Lang [aut], Christian Stock [aut], Ya Wang [aut], Craig Gower-Page [ctb], Dan James [aut], Jonathan Sidi [aut], Daniel Leib [...truncated...]
Maintainer: Daniel Sabanes Bove <daniel.sabanes_bove@rconis.com>

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New package MethScope with initial version 1.0.0
Package: MethScope
Title: Ultra-Fast Analysis of Sparse DNA Methylome via Recurrent Pattern Encoding
Version: 1.0.0
Description: Methods for analyzing DNA methylation data via Most Recurrent Methylation Patterns (MRMPs). Supports cell-type annotation, spatial deconvolution, unsupervised clustering, and cancer cell-of-origin inference. Includes C-backed summaries for YAME “.cg/.cm” files (overlap counts, log2 odds ratios, beta/depth aggregation), an XGBoost classifier, NNLS deconvolution, and plotting utilities. Scales to large spatial and single-cell methylomes and is robust to extreme sparsity.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: xgboost, dplyr, utils, tidyr, stringr, caret, doParallel, parallel, ggplot2, uwot, magrittr, FNN, data.table, nnls
Suggests: knitr, rmarkdown, spelling
VignetteBuilder: knitr
Depends: R (>= 2.10)
NeedsCompilation: yes
Packaged: 2025-12-03 17:38:44 UTC; fuh1
Maintainer: Hongxiang Fu <fhx@seas.upenn.edu>
Language: en-US
Author: Hongxiang Fu [aut, cre] , Wanding Zhou [cph, fnd], The SAMtools/HTSlib authors [ctb, cph] , Attractive Chaos [ctb, cph] )
Repository: CRAN
Date/Publication: 2025-12-09 16:00:07 UTC

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Package robustHD updated to version 0.8.3 with previous version 0.8.2 dated 2025-10-02

Title: Robust Methods for High-Dimensional Data
Description: Robust methods for high-dimensional data, in particular linear model selection techniques based on least angle regression and sparse regression. Specifically, the package implements robust least angle regression (Khan, Van Aelst & Zamar, 2007; <doi:10.1198/016214507000000950>), (robust) groupwise least angle regression (Alfons, Croux & Gelper, 2016; <doi:10.1016/j.csda.2015.02.007>), and sparse least trimmed squares regression (Alfons, Croux & Gelper, 2013; <doi:10.1214/12-AOAS575>).
Author: Andreas Alfons [aut, cre] , Dirk Eddelbuettel [ctb]
Maintainer: Andreas Alfons <alfons@ese.eur.nl>

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Package sampcompR updated to version 0.3.2 with previous version 0.3.1.2 dated 2025-07-04

Title: Comparing and Visualizing Differences Between Surveys
Description: Easily analyze and visualize differences between samples (e.g., benchmark comparisons, nonresponse comparisons in surveys) on three levels. The comparisons can be univariate, bivariate or multivariate. On univariate level the variables of interest of a survey and a comparison survey (i.e. benchmark) are compared, by calculating one of several difference measures (e.g., relative difference in mean), and an average difference between the surveys. On bivariate level a function can calculate significant differences in correlations for the surveys. And on multivariate levels a function can calculate significant differences in model coefficients between the surveys of comparison. All of those differences can be easily plotted and outputted as a table. For more detailed information on the methods and example use see Rohr, B., Silber, H., & Felderer, B. (2024). Comparing the Accuracy of Univariate, Bivariate, and Multivariate Estimates across Probability and Nonprobability Surveys with Po [...truncated...]
Author: Bjoern Rohr [aut, cre, cph], Barbara Felderer [aut]
Maintainer: Bjoern Rohr <bjoern.rohr@gesis.org>

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Package ecotrends updated to version 1.2 with previous version 1.1 dated 2025-07-07

Title: Temporal Trends in Ecological Niche Models
Description: Computes temporal trends in environmental suitability obtained from ecological niche models, based on a set of species presence point coordinates and predictor variables.
Author: A. Marcia Barbosa [aut, cre], Joao Alirio [aut], Nuno Garcia [aut], Joao Campos [aut], Ana Claudia Teodoro [aut], Lia Barbara Duarte [aut], Isabel Pocas [aut], Salvador Arenas-Castro [aut], Neftali Sillero [aut]
Maintainer: A. Marcia Barbosa <ana.marcia.barbosa@gmail.com>

Diff between ecotrends versions 1.1 dated 2025-07-07 and 1.2 dated 2025-12-09

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Package StableEstim updated to version 2.4 with previous version 2.3 dated 2024-10-24

Title: Estimate the Four Parameters of Stable Laws using Different Methods
Description: Estimate the four parameters of stable laws using maximum likelihood method, generalised method of moments with finite and continuum number of points, iterative Koutrouvelis regression and Kogon-McCulloch method. The asymptotic properties of the estimators (covariance matrix, confidence intervals) are also provided.
Author: Tarak Kharrat [aut] , Georgi N. Boshnakov [aut, cre]
Maintainer: Georgi N. Boshnakov <georgi.boshnakov@manchester.ac.uk>

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Package rxode2 updated to version 5.0.1 with previous version 5.0.0 dated 2025-11-28

Title: Facilities for Simulating from ODE-Based Models
Description: Facilities for running simulations from ordinary differential equation ('ODE') models, such as pharmacometrics and other compartmental models. A compilation manager translates the ODE model into C, compiles it, and dynamically loads the object code into R for improved computational efficiency. An event table object facilitates the specification of complex dosing regimens (optional) and sampling schedules. NB: The use of this package requires both C and Fortran compilers, for details on their use with R please see Section 6.3, Appendix A, and Appendix D in the "R Administration and Installation" manual. Also the code is mostly released under GPL. The 'VODE' and 'LSODA' are in the public domain. The information is available in the inst/COPYRIGHTS.
Author: Matthew L. Fidler [aut, cre] , Wenping Wang [aut], Alan Hindmarsh [ctb], Arun Srinivasan [ctb], Awad H. Al-Mohy [ctb], Bill Denney [ctb] , Cleve Moler [ctb], David Cooley [ctb], Drew Schmidt [ctb], Ernst Hairer [ctb], Gabriel Staples [ctb], Gerhard W [...truncated...]
Maintainer: Matthew L. Fidler <matthew.fidler@gmail.com>

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Package groundhog updated to version 3.3.0 with previous version 3.2.3 dated 2025-05-12

Title: Version-Control for CRAN, GitHub, and GitLab Packages
Description: Make R scripts reproducible, by ensuring that every time a given script is run, the same version of the used packages are loaded (instead of whichever version the user running the script happens to have installed). This is achieved by using the command groundhog.library() instead of the base command library(), and including a date in the call. The date is used to call on the same version of the package every time (the most recent version available at that date). Load packages from CRAN, GitHub, or Gitlab.
Author: Uri Simonsohn [aut, cre] , Hugo Gruson [ctb, aut]
Maintainer: Uri Simonsohn <urisohn@gmail.com>

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Package geeLite updated to version 1.0.5 with previous version 1.0.4 dated 2025-12-01

Title: Building and Managing Local Databases from 'Google Earth Engine'
Description: Simplifies the creation, management, and updating of local databases using data extracted from 'Google Earth Engine' ('GEE'). It integrates with 'GEE' to store, aggregate, and process spatio-temporal data, leveraging 'SQLite' for efficient, serverless storage. The 'geeLite' package provides utilities for data transformation and supports real-time monitoring and analysis of geospatial features, making it suitable for researchers and practitioners in geospatial science. For details, see Kurbucz and Andrée (2025) "Building and Managing Local Databases from Google Earth Engine with the geeLite R Package" <https://hdl.handle.net/10986/43165>.
Author: Marcell T. Kurbucz [aut, cre], Bo Pieter Johannes Andree [aut]
Maintainer: Marcell T. Kurbucz <m.kurbucz@ucl.ac.uk>

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Package BAwiR updated to version 1.4.3 with previous version 1.4.2 dated 2025-11-20

Title: Analysis of Basketball Data
Description: Collection of tools to work with European basketball data. Functions available are related to friendly web scraping, data management and visualization. Data were obtained from <https://www.euroleaguebasketball.net/euroleague/>, <https://www.euroleaguebasketball.net/eurocup/> and <https://www.acb.com/>, following the instructions of their respectives robots.txt files, when available. Box score data are available for the three leagues. Play-by-play and spatial shooting data are also available for the Spanish league. Methods for analysis include a population pyramid, 2D plots, circular plots of players' percentiles, plots of players' monthly/yearly stats, team heatmaps, team shooting plots, team four factors plots, cross-tables with the results of regular season games, maps of nationalities, combinations of lineups, possessions-related variables, timeouts, performance by periods, personal fouls, offensive rebounds and different types of shooting charts. Please see Vinue [...truncated...]
Author: Guillermo Vinue [aut, cre]
Maintainer: Guillermo Vinue <guillermo.vinue@uv.es>

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Package PoweREST updated to version 0.1.2 with previous version 0.1.1 dated 2025-08-24

Title: A Bootstrap-Based Power Estimation Tool for Spatial Transcriptomics
Description: Power estimation and sample size calculation for 10X Visium Spatial Transcriptomics data to detect differential expressed genes between two conditions based on bootstrap resampling. See Shui et al. (2025) <doi:10.1371/journal.pcbi.1013293> for method details.
Author: Lan Shui [aut, cre]
Maintainer: Lan Shui <Lan.Shui@uth.tmc.edu>

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Package MSclassifR updated to version 0.5.0 with previous version 0.4.0 dated 2025-07-02

Title: Automated Classification of Mass Spectra
Description: Functions to classify mass spectra in known categories and to determine discriminant mass-to-charge values (m/z). Includes easy-to-use preprocessing pipelines for Matrix Assisted Laser Desorption Ionisation - Time Of Flight Mass Spectrometry (MALDI-TOF) mass spectra, methods to select discriminant m/z from labelled libraries, and tools to predict categories (species, phenotypes, etc.) from selected features. Also provides utilities to build design matrices from peak intensities and labels. While this package was developed with the aim of identifying very similar species or phenotypes of bacteria from MALDI-TOF MS, the functions of this package can also be used to classify other categories associated to mass spectra; or from mass spectra obtained with other mass spectrometry techniques. Parallelized processing and optional C++-accelerated functions are available (notably to deal with large datasets) from version 0.5.0. If you use this package in your research, please cite the associat [...truncated...]
Author: Alexandre Godmer [aut, cre], Quentin Giai Gianetto [aut], Karen Druart [aut]
Maintainer: Alexandre Godmer <alexandre.godmer@aphp.fr>

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Package gsynth updated to version 1.3.1 with previous version 1.2.1 dated 2021-08-06

Title: Generalized Synthetic Control Method
Description: Conducts causal inference with interactive fixed-effect models. It imputes counterfactuals for each treated unit using control group information based on a linear interactive fixed effects model that incorporates unit-specific intercepts interacted with time-varying coefficients. This method generalizes the synthetic control method to the case of multiple treated units and variable treatment periods, and improves efficiency and interpretability.
Author: Yiqing Xu [aut, cre] , Licheng Liu [aut], Ziyi Liu [aut], Shiyun Hu [aut]
Maintainer: Yiqing Xu <yiqingxu@stanford.edu>

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Package g6R updated to version 0.5.0 with previous version 0.1.0 dated 2025-07-10

Title: Graph Visualisation Engine Widget for R and 'shiny' Apps
Description: Create stunning network experiences powered by the 'G6' graph visualisation engine 'JavaScript' library <https://g6.antv.antgroup.com/en>. In 'shiny' mode, modify your graph directly from the server function to dynamically interact with nodes and edges. Select your favorite layout among 20 choices. 15 behaviors are available such as interactive edge creation, collapse-expand and brush select. 17 plugins designed to improve the user experience such as a mini-map, toolbars and grid lines. Customise the look and feel of your graph with comprehensive options for nodes, edges and more.
Author: David Granjon [aut, cre], David Schoch [aut], cynkra GmbH [fnd], Bristol Myers Squibb [fnd]
Maintainer: David Granjon <dgranjon@ymail.com>

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Package dittoViz updated to version 1.0.5 with previous version 1.0.4 dated 2025-07-22

Title: User Friendly Data Visualization
Description: A comprehensive visualization toolkit built with coders of all skill levels and color-vision impaired audiences in mind. It allows creation of finely-tuned, publication-quality figures from single function calls. Visualizations include scatter plots, compositional bar plots, violin, box, and ridge plots, and more. Customization ranges from size and title adjustments to discrete-group circling and labeling, hidden data overlay upon cursor hovering via ggplotly() conversion, and many more, all with simple, discrete inputs. Color blindness friendliness is powered by legend adjustments (enlarged keys), and by allowing the use of shapes or letter-overlay in addition to the carefully selected dittoColors().
Author: Daniel Bunis [aut, cre]
Maintainer: Daniel Bunis <daniel.bunis@ucsf.edu>

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Package CalibrationCurves updated to version 3.0.0 with previous version 2.0.7 dated 2025-07-07

Title: Calibration Performance
Description: Plots calibration curves and computes statistics for assessing calibration performance. See Lasai et al. (2025) <doi:10.48550/arXiv.2503.08389>, De Cock Campo (2023) <doi:10.48550/arXiv.2309.08559> and Van Calster et al. (2016) <doi:10.1016/j.jclinepi.2015.12.005>.
Author: De Cock Bavo [aut, cre], Barrenada Lasai [aut], Nieboer Daan [aut], Van Calster Ben [aut], Steyerberg Ewout [aut], Vergouwe Yvonne [aut]
Maintainer: De Cock Bavo <bavo.decock@kuleuven.be>

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Package svDialogs updated to version 1.1.2 with previous version 1.1.1 dated 2025-08-26

Title: 'SciViews::R' - Standard Dialog Boxes for Windows, MacOS and Linuxes
Description: Quickly construct standard dialog boxes for your GUI, including message boxes, input boxes, list, file or directory selection, ... In case R cannot display GUI dialog boxes, a simpler command line version of these interactive elements is also provided as fallback solution.
Author: Philippe Grosjean [aut, cre] , Paul Hibbins [ctb]
Maintainer: Philippe Grosjean <phgrosjean@sciviews.org>

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Package geneExpressionFromGEO updated to version 1.3 with previous version 1.2 dated 2025-04-11

Title: Easily Downloads a Gene Expression Dataset from a GEO Code and Retrieves the Gene Symbols of Its Probesets
Description: A function that reads in the GEO code of a gene expression dataset, retrieves its data from GEO, (optionally) retrieves the gene symbols of the dataset, and returns a simple dataframe table containing all the data. Platforms available: GPL11532, GPL23126, GPL6244, GPL8300, GPL80, GPL96, GPL570, GPL571, GPL20115, GPL1293, GPL6102, GPL6104, GPL6883, GPL6884, GPL13497, GPL14550, GPL17077, GPL6480. GEO: Gene Expression Omnibus. ID: identifier code. The GEO datasets are downloaded from the URL <https://ftp.ncbi.nlm.nih.gov/geo/series/>. More information can be found in the following manuscript: Davide Chicco, "geneExpressionFromGEO: an R package to facilitate data reading from Gene Expression Omnibus (GEO)". Microarray Data Analysis, Methods in Molecular Biology, volume 2401, chapter 12, pages 187-194, Springer Protocols, 2021, <doi:10.1007/978-1-0716-1839-4_12>.
Author: Davide Chicco [aut, cre]
Maintainer: Davide Chicco <davidechicco@davidechicco.it>

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Package diceplot updated to version 0.2.2 with previous version 0.2.1 dated 2025-08-18

Title: High Dimensional Categorical Data Visualization
Description: Easy visualization for datasets with more than two categorical variables and additional continuous variables. The package is particularly useful for exploring complex categorical data in the context of pathway analysis across multiple conditions. This package is now in maintenance-only mode and kept for legacy compatibility; for new projects and active development, please use the successor package 'ggdiceplot' (see <https://github.com/maflot/ggdiceplot> and <https://dice-and-domino-plot.readthedocs.io/en/latest/>).
Author: Matthias Flotho [aut, cre]
Maintainer: Matthias Flotho <matthias.flotho@ccb.uni-saarland.de>

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Package box.linters updated to version 0.10.7 with previous version 0.10.6 dated 2025-06-26

Title: Linters for 'box' Modules
Description: Static code analysis of 'box' modules. The package enhances code quality by providing linters that check for common issues, enforce best practices, and ensure consistent coding standards.
Author: Ricardo Rodrigo Basa [aut, cre], Jakub Nowicki [aut], Mateusz Kolomanski [ctb], Guilherme Vituri [ctb], Appsilon Sp. z o.o. [cph]
Maintainer: Ricardo Rodrigo Basa <opensource+rodrigo@appsilon.com>

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

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

2021-07-19 0.1.2
2021-05-12 0.1.0
2021-05-12 0.1.1

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Package drugprepr (with last version 0.0.4) was removed from CRAN

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

2021-11-09 0.0.4

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Package conflr (with last version 0.1.1) was removed from CRAN

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

2020-04-08 0.1.1
2020-03-16 0.1.0

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Package rosetteApi (with last version 1.14.4) was removed from CRAN

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

2020-06-17 1.14.4
2019-10-28 1.14.3
2019-03-15 1.12.1
2018-01-19 1.9.0
2017-10-24 1.8.0
2017-06-14 1.7.0
2016-12-20 1.5.0
2016-07-23 1.2.0
2016-05-22 1.0

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Package wordvector updated to version 0.6.0 with previous version 0.5.1 dated 2025-06-20

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

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Package VLMC updated to version 1.4-5 with previous version 1.4-4 dated 2024-08-19

Title: Variable Length Markov Chains ('VLMC') Models
Description: Functions, Classes & Methods for estimation, prediction, and simulation (bootstrap) of Variable Length Markov Chain ('VLMC') Models.
Author: Martin Maechler [aut, cre]
Maintainer: Martin Maechler <maechler@stat.math.ethz.ch>

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Package shiny updated to version 1.12.1 with previous version 1.12.0 dated 2025-12-03

Title: Web Application Framework for R
Description: Makes it incredibly easy to build interactive web applications with R. Automatic "reactive" binding between inputs and outputs and extensive prebuilt widgets make it possible to build beautiful, responsive, and powerful applications with minimal effort.
Author: Winston Chang [aut] , Joe Cheng [aut], JJ Allaire [aut], Carson Sievert [aut, cre] , Barret Schloerke [aut] , Garrick Aden-Buie [aut] , Yihui Xie [aut], Jeff Allen [aut], Jonathan McPherson [aut], Alan Dipert [aut], Barbara Borges [aut], Posit Softwa [...truncated...]
Maintainer: Carson Sievert <carson@posit.co>

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Package ReliaGrowR readmission to version 0.3.2 with previous version 0.3.1 dated 2025-11-21

Title: Reliability Growth Analysis
Description: Modeling and plotting functions for Reliability Growth Analysis (RGA). Models include the Duane (1962) <doi:10.1109/TA.1964.4319640>, Non-Homogeneous Poisson Process (NHPP) by Crow (1975) (No. AMSAATR138), Piecewise Weibull NHPP by Guo et al. (2010) <doi:10.1109/RAMS.2010.5448029>, and Piecewise Weibull NHPP with Change Point Detection based on the 'segmented' package by Muggeo (2024) <https://cran.r-project.org/package=segmented>.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

This is a re-admission after prior archival of version 0.3.1 dated 2025-11-21

Diff between ReliaGrowR versions 0.3.1 dated 2025-11-21 and 0.3.2 dated 2025-12-09

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Package redcapAPI updated to version 2.11.5 with previous version 2.11.4 dated 2025-10-29

Title: Interface to 'REDCap'
Description: Access data stored in 'REDCap' databases using the Application Programming Interface (API). 'REDCap' (Research Electronic Data CAPture; <https://projectredcap.org>, Harris, et al. (2009) <doi:10.1016/j.jbi.2008.08.010>, Harris, et al. (2019) <doi:10.1016/j.jbi.2019.103208>) is a web application for building and managing online surveys and databases developed at Vanderbilt University. The API allows users to access data and project meta data (such as the data dictionary) from the web programmatically. The 'redcapAPI' package facilitates the process of accessing data with options to prepare an analysis-ready data set consistent with the definitions in a database's data dictionary.
Author: Benjamin Nutter [ctb, aut], Shawn Garbett [cre, ctb] , Savannah Obregon [ctb], Thomas Obadia [ctb], Marcus Lehr [ctb], Brian High [ctb], Stephen Lane [ctb], Will Beasley [ctb], Will Gray [ctb], Nick Kennedy [ctb], Tan Hsi-Nien [ctb], Jeffrey Horner [ [...truncated...]
Maintainer: Shawn Garbett <shawn.garbett@vumc.org>

Diff between redcapAPI versions 2.11.4 dated 2025-10-29 and 2.11.5 dated 2025-12-09

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Package netdiffuseR readmission to version 1.24.0 with previous version 1.23.0 dated 2025-06-12

Title: Analysis of Diffusion and Contagion Processes on Networks
Description: Empirical statistical analysis, visualization and simulation of diffusion and contagion processes on networks. The package implements algorithms for calculating network diffusion statistics such as transmission rate, hazard rates, exposure models, network threshold levels, infectiousness (contagion), and susceptibility. The package is inspired by work published in Valente, et al., (2015) <DOI:10.1016/j.socscimed.2015.10.001>; Valente (1995) <ISBN: 9781881303213>, Myers (2000) <DOI:10.1086/303110>, Iyengar and others (2011) <DOI:10.1287/mksc.1100.0566>, Burt (1987) <DOI:10.1086/228667>; among others.
Author: George Vega Yon [aut, cre] , Thomas Valente [aut, cph] , Anibal Olivera Morales [aut, ctb] , Stephanie Dyal [ctb] , Timothy Hayes [ctb]
Maintainer: George Vega Yon <g.vegayon@gmail.com>

This is a re-admission after prior archival of version 1.23.0 dated 2025-06-12

Diff between netdiffuseR versions 1.23.0 dated 2025-06-12 and 1.24.0 dated 2025-12-09

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Package doFuture updated to version 1.1.3 with previous version 1.1.2 dated 2025-07-14

Title: Use Foreach to Parallelize via the Future Framework
Description: The 'future' package provides a unifying parallelization framework for R that supports many parallel and distributed backends <doi:10.32614/RJ-2021-048>. The 'foreach' package provides a powerful API for iterating over an R expression in parallel. The 'doFuture' package brings the best of the two together. There are two alternative ways to use this package. The recommended approach is to use 'y <- foreach(...) %dofuture% { ... }', which does not require using 'registerDoFuture()' and has many advantages over '%dopar%'. The alternative is the traditional 'foreach' approach by registering the 'foreach' adapter 'registerDoFuture()' and so that 'y <- foreach(...) %dopar% { ... }' runs in parallelizes with the 'future' framework.
Author: Henrik Bengtsson [aut, cre, cph]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between doFuture versions 1.1.2 dated 2025-07-14 and 1.1.3 dated 2025-12-09

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New package valueprhr with initial version 0.1.0
Package: valueprhr
Title: Value-Price Analysis with Bayesian and Panel Data Methods
Version: 0.1.0
Description: Provides tools for analyzing the relationship between direct prices (based on labor values) and prices of production using Bayesian generalized linear models, panel data methods, partial least squares regression, canonical correlation analysis, and panel vector autoregression. Includes functions for model comparison, out-of-sample validation, and structural break detection. Here, methods use raw accounting data with explicit temporal structure, following Gomez Julian (2023) <doi:10.17605/OSF.IO/7J8KF> and standard econometric techniques for panel data analysis.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, utils, Metrics
Suggests: rstanarm, loo, plm, lme4, pls, vars, panelvar, strucchange, lmtest, sandwich, dplyr, tidyr, tibble, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://github.com/isadorenabi/valueprhr
BugReports: https://github.com/isadorenabi/valueprhr/issues
NeedsCompilation: no
Packaged: 2025-12-02 21:29:21 UTC; ROG
Author: Jose Mauricio Gomez Julian [aut, cre]
Maintainer: Jose Mauricio Gomez Julian <isadore.nabi@pm.me>
Repository: CRAN
Date/Publication: 2025-12-09 08:10:02 UTC

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New package SHARK4R with initial version 1.0.1
Package: SHARK4R
Title: Accessing and Validating Marine Environmental Data from 'SHARK' and Related Databases
Version: 1.0.1
Description: Provides functions to retrieve, process, analyze, and quality-control marine physical, chemical, and biological data. The main focus is on Swedish monitoring data available through the 'SHARK' database <https://shark.smhi.se/en/>, with additional API support for 'Nordic Microalgae' <https://nordicmicroalgae.org/>, 'Dyntaxa' <https://artfakta.se/>, World Register of Marine Species ('WoRMS') <https://www.marinespecies.org>, 'AlgaeBase' <https://www.algaebase.org>, OBIS 'xylookup' web service <https://iobis.github.io/xylookup/> and Intergovernmental Oceanographic Commission (IOC) - UNESCO databases on harmful algae <https://www.marinespecies.org/hab/> and toxins <https://toxins.hais.ioc-unesco.org/>.
License: MIT + file LICENSE
URL: https://sharksmhi.github.io/SHARK4R/, https://github.com/sharksmhi/SHARK4R
BugReports: https://github.com/sharksmhi/SHARK4R/issues
Depends: R (>= 4.1.0)
Imports: dplyr, DT, ggplot2, httr, jsonlite, leaflet, lifecycle, purrr, readr, readxl, rlang, sf, sp, stringi, terra, tidyr, vroom, worrms
Suggests: htmltools, iRfcb, knitr, plotly, RColorBrewer, rmarkdown, skimr, spelling, shiny, shinythemes, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2025-12-02 22:56:45 UTC; anders
Author: Markus Lindh [aut] , Anders Torstensson [aut, cre] , Mikael Hedblom [ctb] , Bengt Karlson [ctb] , SHARK [cph], SBDI [fnd]
Maintainer: Anders Torstensson <anders.torstensson@smhi.se>
Repository: CRAN
Date/Publication: 2025-12-09 08:50:07 UTC

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New package msPCA with initial version 0.1.0
Package: msPCA
Title: Sparse Principal Component Analysis with Multiple Principal Components
Version: 0.1.0
Date: 2025-12-02
Description: Implements an algorithm for computing multiple sparse principal components of a dataset. The method is based on Cory-Wright and Pauphilet "Sparse PCA with Multiple Principal Components" (2022) <doi:10.48550/arXiv.2209.14790>. The algorithm uses an iterative deflation heuristic with a truncated power method applied at each iteration to compute sparse principal components with controlled sparsity.
License: MIT + file LICENSE
Imports: Rcpp (>= 1.0.11)
LinkingTo: Rcpp, RcppEigen
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2025-12-02 21:29:55 UTC; jeanpauphilet
Author: Ryan Cory-Wright [aut, cph] , Jean Pauphilet [aut, cre, cph]
Maintainer: Jean Pauphilet <jpauphilet@london.edu>
Repository: CRAN
Date/Publication: 2025-12-09 08:50:02 UTC

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Package gdim updated to version 0.1.1 with previous version 0.1.0 dated 2023-09-05

Title: Estimate Graph Dimension using Cross-Validated Eigenvalues
Description: Cross-validated eigenvalues are estimated by splitting a graph into two parts, the training and the test graph. The training graph is used to estimate eigenvectors, and the test graph is used to evaluate the correlation between the training eigenvectors and the eigenvectors of the test graph. The correlations follow a simple central limit theorem that can be used to estimate graph dimension via hypothesis testing, see Chen et al. (2021) <doi:10.48550/arXiv.2108.03336> for details.
Author: Fan Chen [aut] , Alex Hayes [cre, aut, cph] , Karl Rohe [aut]
Maintainer: Alex Hayes <alexpghayes@gmail.com>

Diff between gdim versions 0.1.0 dated 2023-09-05 and 0.1.1 dated 2025-12-09

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Package ClusteredMutations readmission to version 1.0.2 with previous version 1.0.1 dated 2016-04-29

Title: Location and Visualization of Clustered Somatic Mutations
Description: Identification and visualization of groups of closely spaced mutations in the DNA sequence of cancer genome. The extremely mutated zones are searched in the symmetric dissimilarity matrix using the anti-Robinson matrix properties. Different data sets are obtained to describe and plot the clustered mutations information.
Author: David Lora [aut, cre]
Maintainer: David Lora <dalora@ucm.es>

This is a re-admission after prior archival of version 1.0.1 dated 2016-04-29

Diff between ClusteredMutations versions 1.0.1 dated 2016-04-29 and 1.0.2 dated 2025-12-09

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Package bruceR updated to version 2025.11 with previous version 2025.8 dated 2025-08-20

Title: Broadly Useful Convenient and Efficient R Functions
Description: Broadly useful convenient and efficient R functions that bring users concise and elegant R data analyses. This package includes easy-to-use functions for (1) basic R programming (e.g., set working directory to the path of currently opened file; import/export data from/to files in any format; print tables to Microsoft Word); (2) multivariate computation (e.g., compute scale sums/means/... with reverse scoring); (3) reliability analyses and factor analyses; (4) descriptive statistics and correlation analyses; (5) t-test, multi-factor analysis of variance (ANOVA), simple-effect analysis, and post-hoc multiple comparison; (6) tidy report of statistical models (to R Console and Microsoft Word); (7) mediation and moderation analyses (PROCESS); and (8) additional toolbox for statistics and graphics.
Author: Han Wu Shuang Bao [aut, cre]
Maintainer: Han Wu Shuang Bao <baohws@foxmail.com>

Diff between bruceR versions 2025.8 dated 2025-08-20 and 2025.11 dated 2025-12-09

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New package SIP with initial version 0.1.0
Package: SIP
Title: Single-Iteration Permutation for Large-Scale Biobank Data
Version: 0.1.0
Description: A single, phenome-wide permutation of large-scale biobank data. When a large number of phenotypes are analyzed in parallel, a single permutation across all phenotypes followed by genetic association analyses of the permuted data enables estimation of false discovery rates (FDRs) across the phenome. These FDR estimates provide a significance criterion for interpreting genetic associations in a biobank context. For the basic permutation of unrelated samples, this package takes a sample-by-variable file with ID, genotypic covariates, phenotypic covariates, and phenotypes as input. For data with related samples, it also takes a file with sample pair-wise identity-by-descent information. The function outputs a permuted sample-by-variable file ready for genome-wide association analysis. See Annis et al. (2021) <doi:10.21203/rs.3.rs-873449/v1> for details.
URL: https://github.com/acannis/SIP
BugReports: https://github.com/acannis/SIP/issues
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 3.5)
Imports: stats, data.table, ggplot2
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-12-02 14:26:37 UTC; mk
Author: Aubrey Annis [aut, cre]
Maintainer: Aubrey Annis <acannis@umich.edu>
Repository: CRAN
Date/Publication: 2025-12-09 08:00:02 UTC

More information about SIP at CRAN
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New package resizableSplitLayout with initial version 0.1.1
Package: resizableSplitLayout
Title: Resizable Split Layout Module for 'shiny'
Version: 0.1.1
Description: A 'shiny' module to facilitate page layouts with resizable panes for page content based on 'split.js' 'JavaScript' library (<https://split.js.org>).
License: GPL (>= 3)
Imports: shiny, shinyjs
Suggests: testthat (>= 3.0.0)
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-12-02 12:01:27 UTC; mschaff
Author: Michael Schaffer [aut, cre]
Maintainer: Michael Schaffer <mschaff@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-09 07:50:02 UTC

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New package RealSurvSim with initial version 1.0.0
Package: RealSurvSim
Title: Simulate Survival Data
Version: 1.0.0
Date: 2025-11-05
Description: Provides tools for simulating synthetic survival data using a variety of methods, including kernel density estimation, parametric distribution fitting, and bootstrap resampling techniques for a desired sample size.
Encoding: UTF-8
Suggests: testthat (>= 3.0.0)
Imports: fitdistrplus, kdensity, survival, univariateML, actuar, flexsurv, stats, FAdist
Depends: R (>= 3.5)
LazyData: true
License: MIT + file LICENSE
NeedsCompilation: no
Packaged: 2025-12-02 10:42:34 UTC; thurow
Author: Maria Thurow [aut, cre] , Manasi Butee [aut], Ina Dormuth [ctb], Christina Sauer [ctb], Marc Ditzhaus [ctb], Markus Pauly [ctb]
Maintainer: Maria Thurow <maria.thurow@tu-dortmund.de>
Repository: CRAN
Date/Publication: 2025-12-09 07:50:18 UTC

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New package PSsurvival with initial version 0.1.0
Package: PSsurvival
Title: Propensity Score Methods for Survival Analysis
Version: 0.1.0
Description: Implements propensity score weighting methods for estimating counterfactual survival functions and marginal hazard ratios in observational studies with time-to-event outcomes. Supports binary and multiple treatment groups with average treatment effect on the combined full population (ATE), average treatment effect on the treated or target group (ATT), and overlap weighting estimands. Includes symmetric (Crump) and asymmetric (Sturmer) trimming options for extreme propensity scores. Variance estimation via analytical M-estimation or bootstrap. Methods based on Cheng et al. (2022) <doi:10.1093/aje/kwac043> and Li & Li (2019) <doi:10.1214/19-AOAS1282>.
License: GPL (>= 2)
URL: https://github.com/cxinyang/PSsurvival
BugReports: https://github.com/cxinyang/PSsurvival/issues
Depends: R (>= 3.5.0)
Imports: survival, stats, utils
Suggests: nnet, ggplot2, parallel, testthat (>= 3.0.0), knitr, rmarkdown
Encoding: UTF-8
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-12-02 10:59:23 UTC; chengxinyang
Author: Chengxin Yang [aut, cre], Chao Cheng [aut], Fan Li [aut], Fan Li [aut]
Maintainer: Chengxin Yang <chengxin.yang@duke.edu>
Repository: CRAN
Date/Publication: 2025-12-09 07:40:18 UTC

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New package gvcAnalyzer with initial version 0.1.1
Package: gvcAnalyzer
Title: Global Value Chain Decomposition for Value-Added Trade
Version: 0.1.1
Description: Provides tools for decomposing Global Value Chain (GVC) participation and value-added trade. It implements the frameworks proposed by Borin and Mancini (2023) 10.1080/09535314.2022.2153221> for source-based and sink-based decompositions, and by Borin, Mancini, and Taglioni (2025) 10.1093/wber/lhaf017> for tripartite and output-based GVC measures.
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.0.0)
Imports: Matrix, methods, stats
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-12-02 09:36:15 UTC; ballavbabu
Author: Lila Ballav Bhusal [aut, cre] , Alessandro Borin [ctb] ; Borin, Mancini and Taglioni ), Michele Mancini [ctb] ; Borin, Mancini and Taglioni ), Daria Taglioni [ctb] )
Maintainer: Lila Ballav Bhusal <krish.bhula@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-09 07:40:01 UTC

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Package future.apply updated to version 1.20.1 with previous version 1.20.0 dated 2025-06-06

Title: Apply Function to Elements in Parallel using Futures
Description: Implementations of apply(), by(), eapply(), lapply(), Map(), .mapply(), mapply(), replicate(), sapply(), tapply(), and vapply() that can be resolved using any future-supported backend, e.g. parallel on the local machine or distributed on a compute cluster. These future_*apply() functions come with the same pros and cons as the corresponding base-R *apply() functions but with the additional feature of being able to be processed via the future framework <doi:10.32614/RJ-2021-048>.
Author: Henrik Bengtsson [aut, cre, cph] , R Core Team [cph, ctb]
Maintainer: Henrik Bengtsson <henrikb@braju.com>

Diff between future.apply versions 1.20.0 dated 2025-06-06 and 1.20.1 dated 2025-12-09

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New package decompositionLE with initial version 1.0.0
Package: decompositionLE
Title: Provides Easy Methods to Perform Life Expectancy Decomposition
Version: 1.0.0
Description: Provides an easy to use implementation of life expectancy decomposition formulas for age bands, derived from Ponnapalli, K. (2005). A comparison of different methods for decomposition of changes in expectation of life at birth and differentials in life expectancy at birth. Demographic Research, 12, pp.141–172. <doi:10.4054/demres.2005.12.7> In addition, there is a decomposition function for disease cause breakdown and a couple helpful plot functions.
License: GPL (>= 3)
Depends: R (>= 4.1.0)
Imports: dplyr, magrittr, stringr, tidyr, purrr, ggplot2, rlang
Encoding: UTF-8
LazyData: true
Suggests: testthat (>= 3.0.0), tibble, forcats
URL: https://github.com/herts-phei/decompositionLE
BugReports: https://github.com/herts-phei/decompositionLE/issues
NeedsCompilation: no
Packaged: 2025-12-02 11:07:31 UTC; vyu
Author: Victor Yu [aut, cre, cph], Will Yuill [ctb] , Emily Dickson [ctb]
Maintainer: Victor Yu <victor.yu@hertfordshire.gov.uk>
Repository: CRAN
Date/Publication: 2025-12-09 07:40:06 UTC

More information about decompositionLE at CRAN
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New package crownsegmentr with initial version 1.0.1
Package: crownsegmentr
Title: Tree Crown Segmentation in Airborne LiDAR Point Clouds
Version: 1.0.1
Maintainer: Timon Miesner <timon.miesner@thuenen.de>
Description: Provides a function that performs the adaptive mean shift algorithm for individual tree crown delineation in 3D point clouds as proposed by Ferraz et al. (2016) <doi:10.1016/j.rse.2016.05.028>, as well as supporting functions.
License: GPL-3
URL: https://github.com/Lenostatos/crownsegmentr
Depends: R (>= 4.0.0)
Imports: assertthat, data.table, dbscan, lidR (>= 4.0.0), methods, Rcpp (>= 1.0.0), sf, terra
Suggests: EBImage, future, testthat (>= 3.0.0), raster
LinkingTo: BH (>= 1.75.0-0), progress, Rcpp (>= 1.0.0)
Contact: timon.miesner@thuenen.de, Leon.Steinmeier@posteo.net, nikolai.knapp@thuenen.de
Encoding: UTF-8
SystemRequirements: C++17, GNU make
NeedsCompilation: yes
Packaged: 2025-12-02 11:58:22 UTC; miesner
Author: Leon Steinmeier [aut] , Timon Miesner [cre, aut] , Nikolai Knapp [aut]
Repository: CRAN
Date/Publication: 2025-12-09 07:50:13 UTC

More information about crownsegmentr at CRAN
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New package aNCA with initial version 0.1.0
Package: aNCA
Title: (Pre-)Clinical NCA in a Dynamic Shiny App
Version: 0.1.0
Description: An interactive 'shiny' application for performing non-compartmental analysis (NCA) on pre-clinical and clinical pharmacokinetic data. The package builds on 'PKNCA' for core estimators and provides interactive visualizations, CDISC outputs ('ADNCA', 'PP', 'ADPP') and configurable TLGs (tables, listings, and graphs). Typical use cases include exploratory analysis, validation, reporting or teaching/demonstration of NCA methods. Methods and core estimators are described in Denney, Duvvuri, and Buckeridge (2015) "Simple, Automatic Noncompartmental Analysis: The PKNCA R Package" <doi:10.1007/s10928-015-9432-2>.
License: Apache License (>= 2)
Imports: dplyr, formatters, flextable, ggplot2, magrittr, methods, officer, PKNCA (>= 0.12.1), plotly, purrr, rlang, rlistings, scales, stats, stringr, tern, tidyr, units, utils
Encoding: UTF-8
Suggests: arrow, covr, DT, ggh4x, glue, haven, htmltools, htmlwidgets, jsonlite, knitr, lintr (>= 3.1.2), logger, markdown, mockery, nestcolor, openxlsx2, pak, reactable, reactable.extras, rmarkdown, sass, shiny, shinycssloaders, shinyjs, shinyjqui, shinytest2, shinyWidgets, stringi, testthat (>= 3.0.0), tools, quarto, vdiffr, withr, yaml
VignetteBuilder: knitr
Language: en-US
URL: https://pharmaverse.github.io/aNCA/, https://github.com/pharmaverse/aNCA
BugReports: https://github.com/pharmaverse/aNCA/issues
Depends: R (>= 4.1)
LazyData: true
NeedsCompilation: no
Packaged: 2025-12-02 08:59:24 UTC; gerardo
Author: Ercan Suekuer [aut] , Gerardo Jose Rodriguez [aut] , Pascal Baertschi [aut] , Jana Spinner [aut] , Mateusz Kolomanski [aut] , Lucy Aspridis [aut] , Valentin Legras [aut, cre], F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Valentin Legras <anca.pharmaverse@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-09 07:40:12 UTC

More information about aNCA at CRAN
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Package kDGLM (with last version 1.2.7) was removed from CRAN

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

2025-03-19 1.2.7
2024-05-25 1.2.0

Permanent link
Package beanz (with last version 3.1) was removed from CRAN

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

2023-08-09 3.1

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Package isotracer (with last version 1.1.8) was removed from CRAN

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

2025-03-07 1.1.8
2024-11-04 1.1.7
2024-05-15 1.1.6
2023-09-21 1.1.5
2023-03-21 1.1.4
2022-03-27 1.1.3
2022-02-18 1.1.2
2021-12-19 1.1.0
2021-09-27 1.0.4

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Package metricminer (with last version 1.0.0) was removed from CRAN

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

2025-02-19 1.0.0
2024-02-02 0.5.1

Permanent link
Package streamy updated to version 0.2.1 with previous version 0.2.0 dated 2025-05-21

Title: Inline Asynchronous Generator Results into Documents
Description: Given a 'coro' asynchronous generator instance that produces text, write that text into a document selection in 'RStudio' and 'Positron'. This is particularly helpful for streaming large language model responses into the user's editor.
Author: Simon Couch [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Simon Couch <simon.couch@posit.co>

Diff between streamy versions 0.2.0 dated 2025-05-21 and 0.2.1 dated 2025-12-09

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Package sparsevctrs updated to version 0.3.5 with previous version 0.3.4 dated 2025-05-25

Title: Sparse Vectors for Use in Data Frames
Description: Provides sparse vectors powered by ALTREP (Alternative Representations for R Objects) that behave like regular vectors, and can thus be used in data frames. Also provides tools to convert between sparse matrices and data frames with sparse columns and functions to interact with sparse vectors.
Author: Emil Hvitfeldt [aut, cre] , Davis Vaughan [ctb], Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

Diff between sparsevctrs versions 0.3.4 dated 2025-05-25 and 0.3.5 dated 2025-12-09

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Package robmed updated to version 1.3.0 with previous version 1.2.2 dated 2025-09-08

Title: (Robust) Mediation Analysis
Description: Perform mediation analysis via the fast-and-robust bootstrap test ROBMED (Alfons, Ates & Groenen, 2022a; <doi:10.1177/1094428121999096>), as well as various other methods. Details on the implementation and code examples can be found in Alfons, Ates, and Groenen (2022b) <doi:10.18637/jss.v103.i13>. Further discussion on robust mediation analysis can be found in Alfons & Schley (2025) <doi:10.1002/wics.70051>.
Author: Andreas Alfons [aut, cre] , Nufer Y. Ates [dtc]
Maintainer: Andreas Alfons <alfons@ese.eur.nl>

Diff between robmed versions 1.2.2 dated 2025-09-08 and 1.3.0 dated 2025-12-09

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Package mmap updated to version 0.6-23 with previous version 0.6-22 dated 2023-12-08

Title: Map Pages of Memory
Description: R interface to POSIX mmap and Window's MapViewOfFile.
Author: Jeffrey A. Ryan [aut, cre]
Maintainer: Jeffrey A. Ryan <jeff.a.ryan@gmail.com>

Diff between mmap versions 0.6-22 dated 2023-12-08 and 0.6-23 dated 2025-12-09

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Package MIAmaxent updated to version 1.4.1 with previous version 1.4.0 dated 2025-10-18

Title: A Modular, Integrated Approach to Maximum Entropy Distribution Modeling
Description: Tools for training, selecting, and evaluating maximum entropy (and standard logistic regression) distribution models. This package provides tools for user-controlled transformation of explanatory variables, selection of variables by nested model comparison, and flexible model evaluation and projection. It follows principles based on the maximum- likelihood interpretation of maximum entropy modeling, and uses infinitely- weighted logistic regression for model fitting. The package is described in Vollering et al. (2019; <doi:10.1002/ece3.5654>).
Author: Julien Vollering [aut, cre], Sabrina Mazzoni [aut], Rune Halvorsen [aut], Steven Phillips [cph], Michael Bedward [ctb]
Maintainer: Julien Vollering <julienvollering@gmail.com>

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Package metR updated to version 0.18.3 with previous version 0.18.2 dated 2025-09-05

Title: Tools for Easier Analysis of Meteorological Fields
Description: Many useful functions and extensions for dealing with meteorological data in the tidy data framework. Extends 'ggplot2' for better plotting of scalar and vector fields and provides commonly used analysis methods in the atmospheric sciences.
Author: Elio Campitelli [cre, aut]
Maintainer: Elio Campitelli <eliocampitelli@gmail.com>

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Package httk updated to version 2.7.4 with previous version 2.7.3 dated 2025-09-12

Title: High-Throughput Toxicokinetics
Description: Pre-made models that can be rapidly tailored to various chemicals and species using chemical-specific in vitro data and physiological information. These tools allow incorporation of chemical toxicokinetics ("TK") and in vitro-in vivo extrapolation ("IVIVE") into bioinformatics, as described by Pearce et al. (2017) (<doi:10.18637/jss.v079.i04>). Chemical-specific in vitro data characterizing toxicokinetics have been obtained from relatively high-throughput experiments. The chemical-independent ("generic") physiologically-based ("PBTK") and empirical (for example, one compartment) "TK" models included here can be parameterized with in vitro data or in silico predictions which are provided for thousands of chemicals, multiple exposure routes, and various species. High throughput toxicokinetics ("HTTK") is the combination of in vitro data and generic models. We establish the expected accuracy of HTTK for chemicals without in vivo data through statistical evaluation of HTTK predicti [...truncated...]
Author: John Wambaugh [aut, cre] , Sarah Davidson-Fritz [aut] , Robert Pearce [aut] , Caroline Ring [aut] , Greg Honda [aut] , Mark Sfeir [aut], Matt Linakis [aut] , Dustin Kapraun [aut] , Kimberly Truong [aut] , Colin Thomson [aut] , Meredith Scherer [aut] [...truncated...]
Maintainer: John Wambaugh <wambaugh.research@gmail.com>

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Package hamlet updated to version 0.9.8 with previous version 0.9.6 dated 2018-05-26

Title: Hierarchical Optimal Matching and Machine Learning Toolbox
Description: Various functions and algorithms are provided here for solving optimal matching tasks in the context of preclinical cancer studies. Further, various helper and plotting functions are provided for unsupervised and supervised machine learning as well as longitudinal mixed-effects modeling of tumor growth response patterns.
Author: Teemu Daniel Laajala [aut, cre]
Maintainer: Teemu Daniel Laajala <teelaa@utu.fi>

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Package butcher updated to version 0.4.0 with previous version 0.3.6 dated 2025-08-18

Title: Model Butcher
Description: Provides a set of S3 generics to axe components of fitted model objects and help reduce the size of model objects saved to disk.
Author: Joyce Cahoon [aut] , Davis Vaughan [aut], Max Kuhn [cre, aut] , Alex Hayes [aut], Julia Silge [aut] , Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

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