Fri, 08 May 2026

Package watcher updated to version 0.1.6 with previous version 0.1.5 dated 2025-12-01

Title: Watch the File System for Changes
Description: R binding for 'libfswatch', a file system monitoring library. Watch files, or directories recursively, for changes in the background. Log activity, or call an R function, upon every change event.
Author: Charlie Gao [aut, cre] , Posit Software, PBC [cph, fnd] , Enrico M. Crisostomo [cph] , Alan Dipert [cph]
Maintainer: Charlie Gao <charlie.gao@posit.co>

Diff between watcher versions 0.1.5 dated 2025-12-01 and 0.1.6 dated 2026-05-08

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Package mori updated to version 0.2.0 with previous version 0.1.0 dated 2026-04-21

Title: Shared Memory for R Objects
Description: Share R objects across processes on the same machine via a single copy in 'POSIX' shared memory (Linux, macOS) or a 'Win32' file mapping (Windows). Every process reads from the same physical pages through the R Alternative Representation ('ALTREP') framework, giving lazy, zero-copy access. Shared objects serialize compactly as their shared memory name rather than their full contents.
Author: Charlie Gao [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Charlie Gao <charlie.gao@posit.co>

Diff between mori versions 0.1.0 dated 2026-04-21 and 0.2.0 dated 2026-05-08

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Package DyadRatios updated to version 2.0 with previous version 1.4 dated 2026-04-08

Title: Dyad Ratios Algorithm for Latent Variable Estimation
Description: Implements the Dyad Ratios algorithm for estimating latent variables from time-series survey data. The algorithm estimates a latent mood dimension (or two dimensions) from a set of issue opinion series. Supports annual, quarterly, monthly, and daily aggregation intervals, optional exponential smoothing, and up to two latent dimensions. Input data can be provided as a data frame or read from delimited text files. Based on Stimson's 'MCalc' C++ program. See Stimson (2018) <doi:10.1177/0759106318761614> for more details.
Author: James Stimson [aut] , Dave Armstrong [cre, aut]
Maintainer: Dave Armstrong <davearmstrong.ps@gmail.com>

Diff between DyadRatios versions 1.4 dated 2026-04-08 and 2.0 dated 2026-05-08

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Package subincomeR updated to version 0.5.0 with previous version 0.4.0 dated 2025-09-11

Title: Access to Global Sub-National Income Data
Description: Provides access to granular sub-national income data from the MCC-PIK Database Of Sub-national Economic Output (DOSE). The package downloads and processes the data from its open repository on 'Zenodo' (<https://zenodo.org/records/20035157>). Functions are provided to fetch data at multiple geographic levels, match coordinates to administrative regions, and access associated geometries.
Author: Pablo Garcia Guzman [aut, cre, cph]
Maintainer: Pablo Garcia Guzman <garciagp@ebrd.com>

Diff between subincomeR versions 0.4.0 dated 2025-09-11 and 0.5.0 dated 2026-05-08

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Package rapidcodeR updated to version 0.1.1 with previous version 0.1.0 dated 2026-03-10

Title: Optimized Data Analysis System for AI-Based Text Processing
Description: Extracts machine-readable variables from natural language text using AI APIs. Optimized for speed and cost efficiency through parallel processing and direct CSV-formatted responses from language models. Supports multiple AI providers with robust error handling and automatic retry mechanisms for failed extractions.
Author: Gabriel Loenn [aut, cre], Sebastian Schutte [ctb]
Maintainer: Gabriel Loenn <g.e.lonn@stv.uio.no>

Diff between rapidcodeR versions 0.1.0 dated 2026-03-10 and 0.1.1 dated 2026-05-08

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Package fastbioclim updated to version 0.4.2 with previous version 0.4.1 dated 2026-03-10

Title: Scalable and Flexible Derivation of Custom-Time Bioclimatic and Environmental Summary Variables
Description: Provides an efficient tool for creating custom-time bioclimatic and derived environmental summary variables from user-supplied raster data for user-defined timeframes. The package overcomes computational bottlenecks by automatically switching between an in-memory framework using the 'terra' package to maximize speed for smaller datasets, and an on-disk tiling framework for rasters that exceed available RAM, leveraging 'exactextractr' and 'Rfast' to process data in chunks. The core functions, derive_bioclim() and derive_statistics(), offer a unified interface with flexibility for custom time periods beyond standard quarters and the use of fixed temporal indices, facilitating the creation of temporally-matched environmental variables for ecological and biogeographical modeling. Visit the package website <https://gepinillab.github.io/fastbioclim/> to find tutorials in English and Spanish.
Author: Gonzalo E. Pinilla-Buitrago [aut, cre] , Luis Osorio-Olvera [aut]
Maintainer: Gonzalo E. Pinilla-Buitrago <gepinillab@gmail.com>

Diff between fastbioclim versions 0.4.1 dated 2026-03-10 and 0.4.2 dated 2026-05-08

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Package resultcheck updated to version 0.2.1 with previous version 0.2.0 dated 2026-05-03

Title: Result Stability Checks for Empirical R Projects
Description: Lightweight helpers for checking whether empirical results remain substantively unchanged across code revisions, platform differences, and package updates. The package supports regression-style testing of derived datasets, statistical model outputs, tables, and plots, helping researchers detect unintended result drift early and distinguish material from non-material changes in empirical workflows.
Author: Dianyi Yang [aut, cre, ctb]
Maintainer: Dianyi Yang <dianyi.yang@politics.ox.ac.uk>

Diff between resultcheck versions 0.2.0 dated 2026-05-03 and 0.2.1 dated 2026-05-08

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Package pharmaverseadamjnj updated to version 0.0.5 with previous version 0.0.4 dated 2026-05-07

Title: J&J Innovative Medicine ADaM Test Data
Description: A set of Analysis Data Model (ADaM) datasets constructed by modifying the ADaM datasets in the 'pharmaverseadam' package to meet J&J Innovative Medicine's standard data structure for Clinical and Statistical Programming.
Author: David Munoz Tord [aut, cre], Nicholas Masel [aut], Joe Kovach [aut], Mahesh Divakaran [ctb], J&J Innovative Medicine [cph, fnd]
Maintainer: David Munoz Tord <david.munoztord@mailbox.org>

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Package harbinger updated to version 2.0.707 with previous version 1.2.767 dated 2026-02-10

Title: A Unified Time Series Event Detection Framework
Description: By analyzing time series, it is possible to observe significant changes in the behavior of observations that frequently characterize events. Events present themselves as anomalies, change points, or motifs. In the literature, there are several methods for detecting events. However, searching for a suitable time series method is a complex task, especially considering that the nature of events is often unknown. This work presents Harbinger, a framework for integrating and analyzing event detection methods. Harbinger contains several state-of-the-art methods described in Salles et al. (2020) <doi:10.5753/sbbd.2020.13626>.
Author: Eduardo Ogasawara [aut, ths, cre] , Antonio Castro [aut], Antonio Mello [aut], Diego Carvalho [ctb], Eduardo Bezerra [ctb], Ellen Paixao [aut], Fernando Fraga [aut], Heraldo Borges [aut], Igor Andrade [aut], Isabele Rocha [aut], Janio Lima [aut], Jan [...truncated...]
Maintainer: Eduardo Ogasawara <eogasawara@ieee.org>

Diff between harbinger versions 1.2.767 dated 2026-02-10 and 2.0.707 dated 2026-05-08

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New package XGeoRTR with initial version 0.7.0
Package: XGeoRTR
Title: Backend-Neutral Explainable Geometry State and Operators
Date: 2026-04-25
Version: 0.7.0
Author: Frederic Bertrand [cre, aut]
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Provides the platform layer for explanation geometry in R. The package standardizes generic explanation tables into a normalized backend state object, computes embeddings, diagnostics, and multiscale level-of-detail summaries, and serializes backend-neutral state for reproducible workflows. It also exposes selected long-table and regular-grid views for downstream use-case packages. Rendering and viewport orchestration are delegated to downstream frontends such as 'ggWebGL'.
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cli, jsonlite
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), uwot
VignetteBuilder: knitr
URL: https://fbertran.github.io/XGeoRTR/, https://github.com/fbertran/XGeoRTR
BugReports: https://github.com/fbertran/XGeoRTR/issues
NeedsCompilation: no
Packaged: 2026-05-05 14:54:49 UTC; bertran7
Repository: CRAN
Date/Publication: 2026-05-08 15:40:09 UTC

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New package mlmodels with initial version 0.1.2
Package: mlmodels
Title: Maximum Likelihood Models and Tools for Estimation, Prediction, and Testing
Version: 0.1.2
Description: Provides a collection of maximum likelihood estimators with a consistent S3 interface. Supported models include Gaussian (linear and log-normal), logit, probit, Poisson, negative binomial (NB1 and NB2), gamma, and beta regression. A distinctive feature is flexible modeling of the scale parameter (variance, dispersion, precision, or shape) alongside the location/mean parameters. The package offers unified predict() methods, multiple variance-covariance estimators (observed information, outer product of gradients, robust/Huber-White, cluster-robust, bootstrap, jackknife), and a full suite of hypothesis tests (Wald, likelihood ratio, information matrix, Vuong, overdispersion, and goodness-of-fit). It is fully compatible with 'marginaleffects' for post-estimation analysis. Methods implemented include Cameron and Trivedi (1990) <doi:10.1016/0304-4076(90)90014-K>, for Poisson overdispersion testing, Manjon and Martinez (2014) <doi:10.1177/1536867X1401400406>, for goodness-of-fit [...truncated...]
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: cli, hardhat, insight, marginaleffects, MASS, matrixcalc, maxLik, rlang, tibble
Suggests: boot, dplyr, e1071, ggplot2, knitr, patchwork, pkgdown, rmarkdown, testthat (>= 3.0.0), wooldridge
VignetteBuilder: knitr
URL: https://alfisankipan.github.io/mlmodels/
BugReports: https://github.com/alfisankipan/mlmodels/issues
Depends: R (>= 4.1.0)
NeedsCompilation: no
Packaged: 2026-05-05 16:18:02 UTC; alfonso
Author: Alfonso Sanchez-Penalver [aut, cre]
Maintainer: Alfonso Sanchez-Penalver <oneiros_spain@yahoo.com>
Repository: CRAN
Date/Publication: 2026-05-08 15:40:02 UTC

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New package gridmicrotex with initial version 0.0.1
Package: gridmicrotex
Title: Native 'LaTeX' Math Rendering for Grid Graphics
Version: 0.0.1
Description: Renders 'LaTeX' math equations as native R grid graphics objects (grobs) using the 'MicroTeX' 'C++' library as the layout engine. Produces resolution-independent vector output that works on any R graphics device, with no external 'LaTeX' installation required.
License: MIT + file LICENSE
Encoding: UTF-8
SystemRequirements: C++17, FreeType (>= 2.9), pkg-config
Depends: R (>= 4.2.0)
LinkingTo: Rcpp, systemfonts
Imports: grDevices, grid, Rcpp, systemfonts, tools
Suggests: ggplot2 (>= 4.0.0), knitr, ragg, rmarkdown, S7, testthat (>= 3.0.0), vdiffr
VignetteBuilder: knitr
URL: https://github.com/adayim/gridmicrotex, https://adayim.github.io/gridmicrotex/
BugReports: https://github.com/adayim/gridmicrotex/issues
NeedsCompilation: yes
Packaged: 2026-05-05 13:49:14 UTC; alim
Author: Alim Dayim [aut, cre] , Nano Michael [cph] , Bundled math font authors [cph]
Maintainer: Alim Dayim <ad938@cam.ac.uk>
Repository: CRAN
Date/Publication: 2026-05-08 15:00:02 UTC

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Package funHDDC readmission to version 2.3.1.1 with previous version 2.3.1 dated 2021-03-17

Title: Univariate and Multivariate Model-Based Clustering in Group-Specific Functional Subspaces
Description: The funHDDC algorithm allows to cluster functional univariate (Bouveyron and Jacques, 2011, <doi:10.1007/s11634-011-0095-6>) or multivariate data (Schmutz et al., 2018) by modeling each group within a specific functional subspace.
Author: A Schmutz [aut], J. Jacques & C. Bouveyron [aut], Julien Jacques [cre]
Maintainer: Julien Jacques <julien.jacques@univ-lyon2.fr>

This is a re-admission after prior archival of version 2.3.1 dated 2021-03-17

Diff between funHDDC versions 2.3.1 dated 2021-03-17 and 2.3.1.1 dated 2026-05-08

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Package fastei updated to version 0.0.16 with previous version 0.0.0.12 dated 2026-01-09

Title: Methods for ''A Fast Alternative for the R x C Ecological Inference Case''
Description: Estimates the probability matrix for the R×C Ecological Inference problem using the Expectation-Maximization Algorithm with four approximation methods for the E-Step, and an exact method as well. It also provides a bootstrap function to estimate the standard deviation of the estimated probabilities. In addition, it has functions that aggregate rows optimally to have more reliable estimates in cases of having few data points. For comparing the probability estimates of two groups, a Wald test routine is implemented. The library has data from the first round of the Chilean Presidential Election 2021 and can also generate synthetic election data. Methods described in Thraves, Charles; Ubilla, Pablo; Hermosilla, Daniel (2024) ''A Fast Ecological Inference Algorithm for the R×C case'' <doi:10.2139/ssrn.4832834>.
Author: Charles Thraves [aut] , Pablo Ubilla [aut] , Daniel Hermosilla [aut, cre]
Maintainer: Daniel Hermosilla <daniel.hermosilla.r@ug.uchile.cl>

Diff between fastei versions 0.0.0.12 dated 2026-01-09 and 0.0.16 dated 2026-05-08

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New package contagionchannels with initial version 0.1.3
Package: contagionchannels
Title: Two-Stage Detection and Attribution of Cross-Border Financial Contagion Channels
Version: 0.1.3
Date: 2026-04-30
Description: Implementation of a two-stage framework for the joint detection-and-attribution of cross-border financial contagion. Stage one detects directional information flows between equity markets via Wavelet-Quantile Transfer Entropy, combining maximal-overlap discrete wavelet decomposition (Percival and Walden, 2000, ISBN:9780521685085) with the transfer-entropy estimator of Schreiber (2000) <doi:10.1103/PhysRevLett.85.461> and quantile conditioning following Han, Linton, Oka and Whang (2016) <doi:10.1016/j.jeconom.2016.03.001>. Stage two attributes each significant directional link to one of five mutually exclusive transmission channels (Trade, Financial, Geopolitical, Behavioural, Monetary Policy) through a multi-method structural identification architecture combining instrumental-variables two-stage least squares with channel-specific external instruments (Stock and Watson, 2018) <doi:10.1111/ecoj.12593>, LASSO-based instrument selection (Belloni, Chernozhukov and Hansen, [...truncated...]
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 4.1.0)
Imports: xts, zoo, waveslim, quantreg, igraph, parallel, MASS, stats, utils
Suggests: hdm, glmnet, ggplot2, dplyr, tidyr, patchwork, RColorBrewer, viridis, scales, readxl, knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/avishekb9/contagionchannels
BugReports: https://github.com/avishekb9/contagionchannels/issues
NeedsCompilation: no
Packaged: 2026-05-05 14:13:57 UTC; ecolex
Author: Avishek Bhandari [aut, cre] , Ipsita Parida [aut] , Hitesh Kumar Sahu [aut]
Maintainer: Avishek Bhandari <avishekb@iitbbs.ac.in>
Repository: CRAN
Date/Publication: 2026-05-08 15:10:09 UTC

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Package coalitions readmission to version 0.6.27 with previous version 0.6.24 dated 2022-08-17

Title: Bayesian "Now-Cast" Estimation of Event Probabilities in Multi-Party Democracies
Description: An implementation of a Bayesian framework for the opinion poll based estimation of event probabilities in multi-party electoral systems (Bender and Bauer (2018) <doi:10.21105/joss.00606>).
Author: Andreas Bender [aut, cre] , Alexander Bauer [aut] , Rebekka Schade [ctb]
Maintainer: Andreas Bender <bender.at.R@gmail.com>

This is a re-admission after prior archival of version 0.6.24 dated 2022-08-17

Diff between coalitions versions 0.6.24 dated 2022-08-17 and 0.6.27 dated 2026-05-08

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Package BiplotML readmission to version 1.1.1 with previous version 1.1.0 dated 2022-04-22

Title: Logistic Biplot Estimation Using Machine Learning Algorithms
Description: Implements methods for fitting logistic biplot models to multivariate binary data. The logistic biplot represents individuals as points and binary variables as directed vectors in a low-dimensional subspace; the orthogonal projection of each individual onto a variable vector approximates the expected probability that the corresponding characteristic is present. Available fitting methods include conjugate gradient algorithms, a coordinate descent Majorization-Minimization (MM) algorithm, and a block coordinate descent algorithm based on data projection that supports matrices with missing values and allows new individuals to be projected as supplementary rows without refitting the model. A cross-validation procedure is provided to select the number of latent dimensions k. References: Babativa-Marquez and Vicente-Villardon (2021) <doi:10.3390/math9162015>; Vicente-Villardon and Galindo (2006, ISBN:9780470973196).
Author: Jose Giovany Babativa-Marquez [cre, aut]
Maintainer: Jose Giovany Babativa-Marquez <jgbabativam@unal.edu.co>

This is a re-admission after prior archival of version 1.1.0 dated 2022-04-22

Diff between BiplotML versions 1.1.0 dated 2022-04-22 and 1.1.1 dated 2026-05-08

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New package topcc with initial version 1.2
Package: topcc
Title: Topological Correlation Coefficient
Version: 1.2
Description: Topological correlation coefficient is used to identify dependencies between Time-Dependent Objects and is applicable to objects such as time series, chaotic systems, and dynamic networks.
License: GPL-3
Encoding: UTF-8
LazyData: true
Depends: R (>= 2.10)
Imports: parallel
NeedsCompilation: no
Packaged: 2026-05-05 12:23:22 UTC; niech
Author: Chun-Xiao Nie [aut, cre]
Maintainer: Chun-Xiao Nie <niechunxiao2009@163.com>
Repository: CRAN
Date/Publication: 2026-05-08 14:40:02 UTC

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New package mGSFPCA with initial version 0.2.2
Package: mGSFPCA
Title: Estimate Functional Principal Components from Sparse Data
Version: 0.2.2
Description: Implements functional principal component analysis (FPCA) for univariate and multivariate sparse functional data. The package estimates eigenfunctions, eigenvalues, and error variance simultaneously via maximum likelihood estimation (MLE), using a spline basis representation of the eigenfunctions. Orthonormality of the estimated eigenfunctions is enforced through a modified Gram-Schmidt (MGS) orthogonalization procedure applied iteratively during estimation, avoiding direct optimization over the Stiefel manifold and improving numerical stability. The optimal number of basis functions and principal components is selected via an Akaike Information Criterion (AIC)-type criterion, supporting both a full grid-search strategy and a computationally efficient sequential selection approach. Principal component scores are estimated by conditional expectation, enabling reconstruction of individual trajectories over the entire domain from sparse observations. Pointwise confidence intervals for rec [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 2.10)
LazyData: true
Imports: fda, pracma, Rcpp, Metrics
LinkingTo: Rcpp, RcppEigen
NeedsCompilation: yes
Packaged: 2026-05-05 11:16:36 UTC; fdagroup
Author: Uche Mbaka [aut, cre] , Michelle Carey [ctb]
Maintainer: Uche Mbaka <uche.mbaka@ucd.ie>
Repository: CRAN
Date/Publication: 2026-05-08 14:30:02 UTC

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Package meteoland updated to version 2.2.7 with previous version 2.2.6 dated 2026-02-18

Title: Landscape Meteorology Tools
Description: Functions to estimate weather variables at any position of a landscape [De Caceres et al. (2018) <doi:10.1016/j.envsoft.2018.08.003>].
Author: Miquel De Caceres [aut, cre] , Victor Granda [aut] , Nicolas Martin [aut] , Antoine Cabon [aut]
Maintainer: Miquel De Caceres <miquelcaceres@gmail.com>

Diff between meteoland versions 2.2.6 dated 2026-02-18 and 2.2.7 dated 2026-05-08

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New package forecastADAPT with initial version 0.1.0
Package: forecastADAPT
Title: Computation of Adaptive Forecast
Version: 0.1.0
Description: The function forAD() implements the adaptive forecasting procedure of Giraitis, Kapetanios and Price (2013) <doi:10.1016/j.jeconom.2013.04.003>. The method can be iterated (e.g., adapt²) and combined with autoregressive (AR) forecasting. These approaches are computationally simple and adapt automatically to structural changes without requiring prior specification of the underlying data-generating process. They are applicable to both stationary and non-stationary time series. The numerical and graphical outputs assist in selecting an appropriate forecasting method, particularly one that minimises mean squared forecast error (MSFE) and yields uncorrelated forecast errors.
License: GPL-3
Encoding: UTF-8
Imports: stats, graphics, lubridate, grDevices, knitr, testcorr, xts, zoo
Suggests: testthat
NeedsCompilation: no
Packaged: 2026-05-05 10:34:53 UTC; drvio
Author: Violetta Dalla [aut, cre], Liudas Giraitis [aut], George Kapetanios [aut]
Maintainer: Violetta Dalla <vidalla@econ.uoa.gr>
Repository: CRAN
Date/Publication: 2026-05-08 14:40:08 UTC

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Package coda.base updated to version 1.0.6 with previous version 1.0.5 dated 2026-03-04

Title: A Basic Set of Functions for Compositional Data Analysis
Description: A minimum set of functions to perform compositional data analysis using the log-ratio approach introduced by John Aitchison (1982). Main functions have been implemented in c++ for better performance.
Author: Marc Comas-Cufi [aut, cre]
Maintainer: Marc Comas-Cufi <mcomas@imae.udg.edu>

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Package cicalc updated to version 0.2.1 with previous version 0.2.0 dated 2026-01-07

Title: Calculate Confidence Intervals
Description: This calculates a variety of different CIs for proportions and difference of proportions that are commonly used in the pharmaceutical industry including Wald, Wilson, Clopper-Pearson, Agresti-Coull and Jeffreys for proportions. And Miettinen-Nurminen (1985) <doi:10.1002/sim.4780040211>, Wald, Haldane, and Mee <https://www.lexjansen.com/wuss/2016/127_Final_Paper_PDF.pdf> for difference in proportions.
Author: Christina Fillmore [aut, cre] , GlaxoSmithKline Research & Development Limited [cph, fnd], Mike Sprys [aut], Dan Lythgoe [aut]
Maintainer: Christina Fillmore <christina.e.fillmore@gsk.com>

Diff between cicalc versions 0.2.0 dated 2026-01-07 and 0.2.1 dated 2026-05-08

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Package scCustomize updated to version 3.3.0 with previous version 3.2.4 dated 2025-12-11

Title: Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing
Description: Collection of functions created and/or curated to aid in the visualization and analysis of single-cell data using 'R'. 'scCustomize' aims to provide 1) Customized visualizations for aid in ease of use and to create more aesthetic and functional visuals. 2) Improve speed/reproducibility of common tasks/pieces of code in scRNA-seq analysis with a single or group of functions. For citation please use: Marsh SE (2021) "Custom Visualizations & Functions for Streamlined Analyses of Single Cell Sequencing" <doi:10.5281/zenodo.5706430> RRID:SCR_024675.
Author: Samuel Marsh [aut, cre] , Ming Tang [ctb], Velina Kozareva [ctb], Lucas Graybuck [ctb], Zoe Clarke [ctb]
Maintainer: Samuel Marsh <sccustomize@gmail.com>

Diff between scCustomize versions 3.2.4 dated 2025-12-11 and 3.3.0 dated 2026-05-08

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Package lgspline updated to version 1.1.0 with previous version 1.0.2 dated 2026-04-13

Title: Lagrangian Multiplier Smoothing Splines for Smooth Function Estimation
Description: Implements Lagrangian multiplier smoothing splines for flexible nonparametric regression and function estimation. Provides tools for fitting, prediction, and inference using a constrained optimization approach to enforce smoothness. Supports generalized linear models, Weibull accelerated failure time (AFT) models, Cox proportional hazards models, quadratic programming constraints, and customizable working-correlation structures, with options for parallel fitting. The core spline construction builds on Ezhov et al. (2018) <doi:10.1515/jag-2017-0029>. Quadratic-programming and SQP details follow Goldfarb & Idnani (1983) <doi:10.1007/BF02591962> and Nocedal & Wright (2006) <doi:10.1007/978-0-387-40065-5>. For smoothing spline and penalized spline background, see Wahba (1990) <doi:10.1137/1.9781611970128> and Wood (2017) <doi:10.1201/9781315370279>. For variance-component and correlation-parameter estimation, see Searle et al. (2006) <ISBN:978-04700 [...truncated...]
Author: Matthew Davis [aut, cre]
Maintainer: Matthew Davis <matthewlouisdavis@gmail.com>

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Package kollaR updated to version 1.1.4 with previous version 1.1.3 dated 2026-02-25

Title: Event Classification, Visualization and Analysis of Eye Tracking Data
Description: Functions for analysing eye tracking data, including event detection, visualizations and area of interest (AOI) based analyses. The package includes implementations of the IV-T, I-DT, adaptive velocity threshold, and Identification by two means clustering (I2MC) algorithms. See separate documentation for each function. The principles underlying I-VT and I-DT algorithms are described in Salvucci & Goldberg (2000) <doi:10.1145/355017.355028>. Two-means clustering is described in Hessels et al. (2017), <doi: 10.3758/s13428-016-0822-1>. The adaptive velocity threshold algorithm is described in Nyström & Holmqvist (2010),<doi:10.3758/BRM.42.1.188>. A documentation of the 'kollaR' can be found in Kleberg et al (2026) <doi:10.3758/s13428-025-02903-z>. Cite this paper when using 'kollaR' See a demonstration in the URL.
Author: Johan Lundin Kleberg [aut, cre]
Maintainer: Johan Lundin Kleberg <johan.lundin.kleberg@su.se>

Diff between kollaR versions 1.1.3 dated 2026-02-25 and 1.1.4 dated 2026-05-08

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Package iTensor updated to version 1.0.4 with previous version 1.0.2 dated 2023-04-28

Title: ICA-Based Matrix/Tensor Decomposition
Description: Some functions for performing ICA, MICA, Group ICA, and Multilinear ICA are implemented. ICA, MICA/Group ICA, and Multilinear ICA extract statistically independent components from single matrix, multiple matrices, and single tensor, respectively. For the details of these methods, see the reference section of GitHub README.md <https://github.com/rikenbit/iTensor>.
Author: Koki Tsuyuzaki [aut, cre]
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

Diff between iTensor versions 1.0.2 dated 2023-04-28 and 1.0.4 dated 2026-05-08

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Package tidyaudit updated to version 0.2.1 with previous version 0.2.0 dated 2026-03-24

Title: Pipeline Audit Trails and Data Diagnostics for 'tidyverse' Workflows
Description: Provides pipeline audit trails and data diagnostics for 'tidyverse' workflows. The audit trail system captures lightweight metadata snapshots at each step of a pipeline, building a structured record without storing the data itself. Operation-aware taps enrich snapshots with join match rates and filter drop statistics. Trails can be serialized to 'JSON' or 'RDS' and exported as self-contained 'HTML' visualizations. Also includes diagnostic functions for interactive data analysis including frequency tables, string quality auditing, and data comparison.
Author: Fernando Cordeiro [aut, cre, cph]
Maintainer: Fernando Cordeiro <fernandolpcordeiro@gmail.com>

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Package nnTensor updated to version 1.4.0 with previous version 1.3.0 dated 2024-05-13

Title: Non-Negative Tensor Decomposition
Description: Some functions for performing non-negative matrix factorization, non-negative CANDECOMP/PARAFAC (CP) decomposition, non-negative Tucker decomposition, and generating toy model data. See Andrzej Cichock et al (2009) and the reference section of GitHub README.md <https://github.com/rikenbit/nnTensor>, for details of the methods.
Author: Koki Tsuyuzaki [aut, cre], Itoshi Nikaido [aut]
Maintainer: Koki Tsuyuzaki <k.t.the-answer@hotmail.co.jp>

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Package EFAtools updated to version 0.7.1 with previous version 0.7.0 dated 2026-04-30

Title: Fast and Flexible Implementations of Exploratory Factor Analysis Tools
Description: Provides functions to perform exploratory factor analysis (EFA) procedures and compare their solutions. The goal is to provide state-of-the-art factor retention methods and a high degree of flexibility in the EFA procedures. This way, for example, implementations from R 'psych' and 'SPSS' can be compared. Moreover, functions for Schmid-Leiman transformation and the computation of omegas are provided. To speed up the analyses, some of the iterative procedures, like principal axis factoring (PAF), are implemented in C++.
Author: Markus Steiner [aut, cre], Silvia Grieder [aut], William Revelle [ctb], Max Auerswald [ctb], Morten Moshagen [ctb], John Ruscio [ctb], Brendan Roche [ctb], Urbano Lorenzo-Seva [ctb], David Navarro-Gonzalez [ctb], Johan Braeken [ctb], Andreas Soteriad [...truncated...]
Maintainer: Markus Steiner <markus.d.steiner@gmail.com>

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Package spant updated to version 4.0.0 with previous version 3.9.0 dated 2026-02-23

Title: MR Spectroscopy Analysis Tools
Description: Tools for reading, visualising and processing Magnetic Resonance Spectroscopy data. The package includes methods for spectral fitting: Wilson (2021) <DOI:10.1002/mrm.28385>, Wilson (2025) <DOI:10.1002/mrm.30462> and spectral alignment: Wilson (2018) <DOI:10.1002/mrm.27605>.
Author: Martin Wilson [cre, aut] , Yong Wang [ctb], John Muschelli [ctb]
Maintainer: Martin Wilson <martin.wilson111@gmail.com>

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Package SelfControlledCaseSeries updated to version 6.1.5 with previous version 6.1.4 dated 2026-03-26

Title: Self-Controlled Case Series
Description: Execute the self-controlled case series (SCCS) design using observational data in the OMOP Common Data Model. Extracts all necessary data from the database and transforms it to the format required for SCCS. Age and season can be modeled using splines assuming constant hazard within calendar months. Event-dependent censoring of the observation period can be corrected for. Many exposures can be included at once (MSCCS), with regularization on all coefficients except for the exposure of interest. Includes diagnostics for all major assumptions of the SCCS.
Author: Martijn Schuemie [aut, cre], Patrick Ryan [aut], Trevor Shaddox [aut], Marc Suchard [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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More information about SelfControlledCaseSeries at CRAN
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Package okxr updated to version 0.4.5 with previous version 0.2.4 dated 2026-04-28

Title: R Interface to the 'OKX' REST API
Description: Provides lightweight R wrappers for the 'OKX' REST API, covering endpoints for market data, trading, account management, asset balances, and copy trading. The upstream API reference is available at <https://www.okx.com/docs-v5/en/>.
Author: Oliver Zhou [aut, cre], Lily Li [aut]
Maintainer: Oliver Zhou <oliver.yxzhou@gmail.com>

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More information about okxr at CRAN
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Package mirai updated to version 2.7.0 with previous version 2.6.1 dated 2026-03-02

Title: Minimalist Async Evaluation Framework for R
Description: Evaluates R expressions asynchronously and in parallel, locally or distributed across networks. An official parallel cluster type for R. Built on 'nanonext' and 'NNG', its non-polling, event-driven architecture scales from a laptop to thousands of processes across high-performance computing clusters and cloud platforms. Features FIFO scheduling with task cancellation and bounded queues, promises for reactive programming, 'OpenTelemetry' distributed tracing, and custom serialization for cross-language data types.
Author: Charlie Gao [aut, cre] , Joe Cheng [ctb], Posit Software, PBC [cph, fnd] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@posit.co>

Diff between mirai versions 2.6.1 dated 2026-03-02 and 2.7.0 dated 2026-05-08

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Package ggplate updated to version 0.3.0 with previous version 0.2.0 dated 2026-01-09

Title: Create Layout Plots of Biological Culture Plates and Microplates
Description: Enables users to create simple plots of biological culture plates as well as microplates. Both continuous and discrete values can be plotted onto the plate layout.
Author: Jan-Philipp Quast [aut, cre]
Maintainer: Jan-Philipp Quast <jpquast.software@gmail.com>

Diff between ggplate versions 0.2.0 dated 2026-01-09 and 0.3.0 dated 2026-05-08

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Package CohortMethod updated to version 6.0.2 with previous version 6.0.1 dated 2026-03-21

Title: Comparative Cohort Method with Large Scale Propensity and Outcome Models
Description: Functions for performing comparative cohort studies in an observational database in the Observational Medical Outcomes Partnership (OMOP) Common Data Model. Can extract all necessary data from a database. This implements large-scale propensity scores (LSPS) as described in Tian et al. (2018) <doi:10.1093/ije/dyy120>, using a large set of covariates, including for example all drugs, diagnoses, procedures, as well as age, comorbidity indexes, etc. Large scale regularized regression is used to fit the propensity and outcome models as described in Suchard et al. (2013) <doi:10.1145/2414416.2414791>. Functions are included for trimming, stratifying, (variable and fixed ratio) matching and weighting by propensity scores, as well as diagnostic functions, such as propensity score distribution plots and plots showing covariate balance before and after matching and/or trimming. Supported outcome models are (conditional) logistic regression, (conditional) Poisson regression, and (stra [...truncated...]
Author: Martijn Schuemie [aut, cre], Marc Suchard [aut], Patrick Ryan [aut]
Maintainer: Martijn Schuemie <schuemie@ohdsi.org>

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Package episomer updated to version 3.0.35 with previous version 3.0.34 dated 2026-04-20

Title: Early Detection of Public Health Threats from Social Media Data
Description: It allows you to automatically monitor trends of social media messages by time, place and topic aiming at detecting public health threats early through the detection of signals (i.e., an unusual increase in the number of messages per time, topic and location). It was designed to focus on infectious diseases, and it can be extended to all hazards or other fields of study by modifying the topics and keywords. More information on the original package 'epitweetr' is available in the peer-review publication Espinosa et al. (2022) <doi:10.2807/1560-7917.ES.2022.27.39.2200177>.
Author: Laura Espinosa [aut, fnd, cre] , Francisco Orchard [aut, ctr] , Gianfranco Spiteri [ctb, fnd], Ariana Wijermans [ctb] , Thomas Mollet [ctb] , Adrian Prodan [ctb], Martin Norling [ctb], Enrique Delgado [ctb], Thomas Czernichow [ctb], Maria Prieto Gonz [...truncated...]
Maintainer: Laura Espinosa <laura.espinosa@ecdc.europa.eu>

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Package rbiom updated to version 3.1.0 with previous version 2.2.1 dated 2025-06-27

Title: Integrated Analysis and Visualization of Microbiome Data
Description: A toolkit for working with Biological Observation Matrix ('BIOM') files. Read/write all 'BIOM' formats. Compute rarefaction, alpha diversity, and beta diversity (including 'UniFrac'). Summarize counts by taxonomic level. Subset based on metadata. Generate visualizations and statistical analyses.
Author: Daniel P. Smith [aut, cre] , Alkek Center for Metagenomics and Microbiome Research [cph, fnd]
Maintainer: Daniel P. Smith <dansmith01@gmail.com>

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Package PGaovR updated to version 0.1.1 with previous version 0.1.0 dated 2026-04-28

Title: Analysis of Experimental Data using ANOVA and Mean Comparison
Description: Provides tools for designing and analyzing agricultural experiments. It includes functions for generating randomized treatment layouts for standard experimental designs such as Completely Randomized Design (CRD), Randomized Block Design (RBD), Latin Square Design (LSD), Factorial Randomized Block Design (FRBD), split-plot design, and strip-plot design. The package implements one-factor and two-factor analysis of variance (ANOVA) and offers multiple comparison procedures, including Least Significant Difference (lsd), Tukey, and Duncan tests, to compare treatment means in single-factor and factorial experiments. The methods follow classical experimental design principles described in Gomez and Gomez (1984, Statistical Procedures for Agricultural Research, John Wiley & Sons, New York).
Author: Santosh Patil [aut, cre] , Yogesh Garde [aut]
Maintainer: Santosh Patil <patil.sgstat@gmail.com>

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Package geoAr updated to version 1.2.2 with previous version 1.0.0 dated 2024-03-03

Title: Argentina's Spatial Data Toolbox
Description: Collection of tools that facilitates data access and workflow for spatial analysis of Argentina. Includes historical information from censuses, administrative limits at different levels of aggregation, location of human settlements, among others. Since it is expected that the majority of users will be Spanish-speaking, the documentation of the package prioritizes this language, although an effort is made to also offer annotations in English.
Author: Juan Pablo Ruiz Nicolini [aut, cre, cph] , Patricio Del Boca [aut], Juan Gabriel Juara [aut]
Maintainer: Juan Pablo Ruiz Nicolini <juanpabloruiznicolini@gmail.com>

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Package distfreereg updated to version 1.2 with previous version 1.1 dated 2025-07-02

Title: Distribution-Free Goodness-of-Fit Testing for Regression
Description: Implements the distribution-free goodness-of-fit regression testing procedure, introduced by Estate Khmaladze (2021, <doi:10.1007/s10463-021-00786-3>) to test whether or not the mean structure of a parametric model belongs to a specified model family. The test is implemented for general mean functions with minimal distributional assumptions as well as common models (e.g., lm, glm) with the usual model assumptions.
Author: Jesse Miller [aut, cre]
Maintainer: Jesse Miller <smallepsilon@proton.me>

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Package vectra readmission to version 0.6.2 with previous version 0.5.1 dated 2026-04-21

Title: Columnar Query Engine for Larger-than-RAM Data
Description: A minimal columnar query engine with lazy execution on datasets larger than RAM. Provides 'dplyr'-like verbs (filter(), select(), mutate(), group_by(), summarise(), joins, window functions) and common aggregations (n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a pure C11 pull-based execution engine and a custom on-disk format ('.vtr'). Reads and writes 'GeoTIFF' (including tiled and 'BigTIFF' layouts) and a tiled raster format ('.vec') with overview pyramids and time cubes for larger-than-RAM raster data.
Author: Gilles Colling [aut, cre, cph]
Maintainer: Gilles Colling <gilles.colling051@gmail.com>

This is a re-admission after prior archival of version 0.5.1 dated 2026-04-21

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Package savvyGLM updated to version 0.1.4 with previous version 0.1.2 dated 2026-05-03

Title: Generalized Linear Models with Slab and Shrinkage Estimators
Description: Provides a flexible framework for fitting generalized linear models (GLMs) with slab and shrinkage estimators. Methods include the Stein estimator (St), Diagonal Shrinkage (DSh), Simple Slab Regression (SR), Generalized Slab Regression (GSR), Ledoit-Wolf Linear Shrinkage (LW), Quadratic-Inverse Shrinkage (QIS), and Shrinkage (Sh), all integrated into the iteratively reweighted least squares (IRLS) algorithm. This approach enhances estimation accuracy, convergence, and robustness in the presence of multicollinearity. The best-fitting model is selected based on the Akaike Information Criterion (AIC). Methods are related to methods described in Marschner (2011) <doi:10.32614/RJ-2011-012>, Asimit et al. (2025) <https://openaccess.city.ac.uk/id/eprint/35005/>, Ledoit and Wolf (2004) <doi:10.1016/S0047-259X(03)00096-4>, and Ledoit and Wolf (2022) <doi:10.3150/20-BEJ1315>.
Author: Ziwei Chen [aut, cre] , Vali Asimit [aut] , Claudio Senatore [aut]
Maintainer: Ziwei Chen <Ziwei.Chen.3@citystgeorges.ac.uk>

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Package RFmerge readmission to version 0.3-3 with previous version 0.1-10 dated 2020-05-22

Title: Merging of Satellite Datasets with Ground Observations using Random Forests
Description: S3 implementation of the Random Forest MErging Procedure (RF-MEP), which combines two or more satellite-based datasets (e.g., precipitation products, topography) with ground observations to produce a new dataset with improved spatio-temporal distribution of the target field. In particular, this package was developed to merge different Satellite-based Rainfall Estimates (SREs) with measurements from rain gauges, in order to obtain a new precipitation dataset where the time series in the rain gauges are used to correct different types of errors present in the SREs. However, this package might be used to merge other hydrological/environmental gridded datasets with point observations. For details, see Baez-Villanueva et al. (2020) <doi:10.1016/j.rse.2019.111606>. Bugs / comments / questions / collaboration of any kind are very welcomed.
Author: Mauricio Zambrano-Bigiarini [aut, cre, cph] , Oscar M. Baez-Villanueva [aut, cph] , Juan Giraldo-Osorio [ctb]
Maintainer: Mauricio Zambrano-Bigiarini <mzb.devel@gmail.com>

This is a re-admission after prior archival of version 0.1-10 dated 2020-05-22

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Package iheiddown updated to version 0.9.9 with previous version 0.9.7 dated 2022-11-09

Title: For Writing Geneva Graduate Institute Documents
Description: A set of tools for writing documents according to Geneva Graduate Institute conventions and regulations. The most common use is for writing and compiling theses or thesis chapters, as drafts or for examination with correct preamble formatting. However, the package also offers users to create HTML presentation slides with 'xaringan', complete problem sets, format posters, and, for course instructors, prepare a syllabus. The package includes additional functions for institutional color palettes, an institutional 'ggplot' theme, a function for counting manuscript words, and a bibliographical analysis toolkit.
Author: James Hollway [aut, cre, cph] , Bernhard Bieri [ctb] , Henrique Sposito [ctb]
Maintainer: James Hollway <james.hollway@graduateinstitute.ch>

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Package espadon updated to version 1.11.5 with previous version 1.11.3 dated 2025-11-17

Title: Easy Study of Patient DICOM Data in Oncology
Description: Read, process, and export DICOM and DICOM-RT files (structures, dosimetry, imagery) for medical physics and clinical research, with patient-oriented 2D-3D visualization.
Author: Cathy Fontbonne [aut, cre] , Jean-Marc Fontbonne [aut] , Nathan Azemar [ctb]
Maintainer: Cathy Fontbonne <contact.espadon@lpccaen.in2p3.fr>

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More information about espadon at CRAN
Permanent link

Package CatPredi readmission to version 2.0 with previous version 1.4 dated 2025-10-30

Title: Optimal Categorisation of Continuous Variables in Prediction Models
Description: Allows the user to categorise a continuous predictor variable in a logistic or a Cox proportional hazards regression setting, by maximising the discriminative ability of the model. I Barrio, I Arostegui, MX Rodriguez-Alvarez, JM Quintana (2015) <doi:10.1177/0962280215601873>. I Barrio, MX Rodriguez-Alvarez, L Meira-Machado, C Esteban, I Arostegui (2017) <https://www.idescat.cat/sort/sort411/41.1.3.barrio-etal.pdf>.
Author: Irantzu Barrio [aut, cre], Maria Xose Rodriguez-Alvarez [aut], Inmaculada Arostegui [ctb], Diana Marcela Perez [ctb]
Maintainer: Irantzu Barrio <irantzu.barrio@ehu.eus>

This is a re-admission after prior archival of version 1.4 dated 2025-10-30

Diff between CatPredi versions 1.4 dated 2025-10-30 and 2.0 dated 2026-05-08

 CatPredi-1.4/CatPredi/man/CatPredi-package.Rd             |only
 CatPredi-2.0/CatPredi/DESCRIPTION                         |   17 
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More information about CatPredi at CRAN
Permanent link

Package BayesPIM readmission to version 1.0.1 with previous version 1.0.0 dated 2025-03-22

Title: Bayesian Prevalence-Incidence Mixture Model
Description: Models time-to-event data from interval-censored screening studies. It accounts for latent prevalence at baseline and incorporates misclassification due to imperfect test sensitivity. For usage details, see the package vignette "BayesPIM_intro". Further details can be found in Klausch, Lissenberg-Witte and Coupé (2026) <doi:10.1002/sim.70433>.
Author: Thomas Klausch [aut, cre]
Maintainer: Thomas Klausch <t.klausch@amsterdamumc.nl>

This is a re-admission after prior archival of version 1.0.0 dated 2025-03-22

Diff between BayesPIM versions 1.0.0 dated 2025-03-22 and 1.0.1 dated 2026-05-08

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More information about BayesPIM at CRAN
Permanent link

Package automatedRecLin updated to version 1.1.0 with previous version 1.0.1 dated 2025-12-13

Title: Record Linkage Based on an Entropy-Maximizing Classifier
Description: The goal of 'automatedRecLin' is to perform record linkage (also known as entity resolution) in unsupervised or supervised settings. It compares pairs of records from two datasets using selected comparison functions to estimate the probability or density ratio between matched and non-matched records. Based on these estimates, it predicts a set of matches that maximizes entropy. For details see: Lee et al. (2022) <https://www150.statcan.gc.ca/n1/pub/12-001-x/2022001/article/00007-eng.htm>, Vo et al. (2023) <https://ideas.repec.org/a/eee/csdana/v179y2023ics0167947322002365.html>, Sugiyama et al. (2008) <doi:10.1007/s10463-008-0197-x>.
Author: Adam Struzik [aut, cre] , Maciej Beresewicz [aut, ctb]
Maintainer: Adam Struzik <adastr5@st.amu.edu.pl>

Diff between automatedRecLin versions 1.0.1 dated 2025-12-13 and 1.1.0 dated 2026-05-08

 DESCRIPTION                              |   21 
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 NAMESPACE                                |    4 
 NEWS.md                                  |   24 
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More information about automatedRecLin at CRAN
Permanent link

Package SCE updated to version 1.1.3 with previous version 1.1.2 dated 2025-10-04

Title: Stepwise Clustered Ensemble
Description: Implementation of Stepwise Clustered Ensemble (SCE) and Stepwise Cluster Analysis (SCA) for multivariate data analysis. The package provides comprehensive tools for feature selection, model training, prediction, and evaluation in hydrological and environmental modeling applications. Key functionalities include recursive feature elimination (RFE), Wilks feature importance analysis, model validation through out-of-bag (OOB) validation, and ensemble prediction capabilities. The package supports both single and multivariate response variables, making it suitable for complex environmental modeling scenarios. For more details see Li et al. (2021) <doi:10.5194/hess-25-4947-2021>.
Author: Kailong Li [aut, cre]
Maintainer: Kailong Li <lkl98509509@gmail.com>

Diff between SCE versions 1.1.2 dated 2025-10-04 and 1.1.3 dated 2026-05-08

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Package geessbin updated to version 1.0.2 with previous version 1.0.1 dated 2025-12-02

Title: Modified Generalized Estimating Equations for Binary Outcome
Description: Analyze small-sample clustered or longitudinal data with binary outcome using modified generalized estimating equations (GEE) with bias-adjusted covariance estimator. The package provides any combination of three GEE methods and 12 covariance estimators.
Author: Ryota Ishii [aut, cre], Tomohiro Ohigashi [ctb], Kazushi Maruo [ctb], Masahiko Gosho [ctb]
Maintainer: Ryota Ishii <r.ishii0808@gmail.com>

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Package REndo updated to version 2.5.0 with previous version 2.4.11 dated 2026-03-23

Title: Fitting Linear Models with Endogenous Regressors using Latent Instrumental Variables
Description: Fits linear models with endogenous regressor using latent instrumental variable approaches. The methods included in the package are Lewbel's (1997) <doi:10.2307/2171884> higher moments approach as well as Lewbel's (2012) <doi:10.1080/07350015.2012.643126> heteroscedasticity approach, Park and Gupta's (2012) <doi:10.1287/mksc.1120.0718> joint estimation method that uses Gaussian copula and Kim and Frees's (2007) <doi:10.1007/s11336-007-9008-1> multilevel generalized method of moment approach that deals with endogeneity in a multilevel setting. These are statistical techniques to address the endogeneity problem where no external instrumental variables are needed. See the publication related to this package in the Journal of Statistical Software for more details: <doi:10.18637/jss.v107.i03>. Note that with version 2.0.0 sweeping changes were introduced which greatly improve functionality and usability but break backwards compatibility.
Author: Raluca Gui [cre, aut], Markus Meierer [aut], Rene Algesheimer [aut], Patrik Schilter [aut], Kimberly-Anne Lew Chuk Wai [aut]
Maintainer: Raluca Gui <raluca.gui@gmail.com>

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Package refundBayes updated to version 0.6.0 with previous version 0.5.1 dated 2026-04-07

Title: Bayesian Regression with Functional Data
Description: Bayesian regression with functional data, including regression with scalar, survival, or functional outcomes. The package allows regression with scalar and functional predictors. Methods are described in Jiang et al. (2025) "Tutorial on Bayesian Functional Regression Using Stan" <doi:10.1002/sim.70265>.
Author: Ziren Jiang [aut, cre], Erjia Cui [aut], Ciprian Crainiceanu [ctb]
Maintainer: Ziren Jiang <jian0746@umn.edu>

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Package MCPAN updated to version 1.1-22 with previous version 1.1-21 dated 2018-03-22

Title: Multiple Comparisons Using Normal Approximation
Description: Multiple contrast tests and simultaneous confidence intervals based on normal approximation. With implementations for binomial proportions in a 2xk setting (risk difference and odds ratio), poly-3-adjusted tumour rates, biodiversity indices (multinomial data) and expected values under lognormal assumption. Approximative power calculation for multiple contrast tests of binomial and Gaussian data.
Author: Frank Schaarschmidt [aut, cre], Daniel Gerhard [aut], Martin Sill [aut]
Maintainer: Frank Schaarschmidt <schaarschmidt@biostat.uni-hannover.de>

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Package icecdr updated to version 1.2.0 with previous version 1.1.0 dated 2026-03-24

Title: Download Sea Ice Concentration Data from the NSIDC Climate Data Record
Description: Programmatic access to NSIDC's sea ice concentration CDR <https://nsidc.org/data/g02202> via ERDAPP server and Sea Ice index <https://nsidc.org/data/g02135>. Supports caching results and optional fixes for some inconsistencies of the raw files.
Author: Elio Campitelli [cre, aut, cph]
Maintainer: Elio Campitelli <eliocampitelli@gmail.com>

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Package BayesMallowsSMC2 updated to version 0.3.0 with previous version 0.2.1 dated 2026-02-04

Title: Nested Sequential Monte Carlo for the Bayesian Mallows Model
Description: Provides nested sequential Monte Carlo algorithms for performing sequential inference in the Bayesian Mallows model, which is a widely used probability model for rank and preference data. The package implements the SMC2 (Sequential Monte Carlo Squared) algorithm for handling sequentially arriving rankings and pairwise preferences, including support for complete rankings, partial rankings, and pairwise comparisons. The methods are based on Sorensen (2025) <doi:10.1214/25-BA1564>.
Author: Oystein Sorensen [aut, cre]
Maintainer: Oystein Sorensen <oystein.sorensen.1985@gmail.com>

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Package geospatialsuite updated to version 0.2.0 with previous version 0.1.1 dated 2025-11-05

Title: Comprehensive Geospatiotemporal Analysis and Multimodal Integration Toolkit
Description: A comprehensive toolkit for geospatiotemporal analysis featuring 60+ vegetation indices, advanced raster visualization, universal spatial mapping, water quality analysis, CDL crop analysis, spatial interpolation, temporal analysis, and terrain analysis. Designed for agricultural research, environmental monitoring, remote sensing applications, and publication-quality mapping with support for any geographic region and robust error handling. Methods include vegetation indices calculations (Rouse et al. 1974), NDVI and enhanced vegetation indices (Huete et al. 1997) <doi:10.1016/S0034-4257(97)00104-1>, (Akanbi et al. 2024) <doi:10.1007/s41651-023-00164-y>, spatial interpolation techniques (Cressie 1993, ISBN:9780471002556), water quality indices (McFeeters 1996) <doi:10.1080/01431169608948714>, and crop data layer analysis (USDA NASS 2024) <https://www.nass.usda.gov/Research_and_Science/Cropland/>. Funding: This material is based upon financial support by the Natio [...truncated...]
Author: Olatunde D. Akanbi [aut, cre, cph] , Vibha Mandayam [aut] , Yinghui Wu [aut] , Jeffrey Yarus [aut] , Erika I. Barcelos [aut, cph] , Roger H. French [aut, cph]
Maintainer: Olatunde D. Akanbi <olatunde.akanbi@case.edu>

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2019-04-24 0.1.6
2018-07-26 0.1.5
2018-04-03 0.1.4
2017-06-30 0.1.2
2016-12-20 0.1.1

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Package bcrm (with last version 0.5.4) was removed from CRAN

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

2019-08-23 0.5.4
2019-06-04 0.5.3
2019-05-24 0.5.2
2019-05-22 0.5.1
2018-01-28 0.4.7
2015-11-20 0.4.6
2015-09-23 0.4.5
2014-04-08 0.4.4
2013-09-10 0.4.3
2013-03-26 0.4.2
2012-10-24 0.4.1
2012-09-18 0.4
2012-05-01 0.3
2012-02-09 0.2
2012-01-11 0.1

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

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

2019-05-17 0.1.0

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Package AF (with last version 0.1.5) was removed from CRAN

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

2019-05-20 0.1.5
2017-02-10 0.1.4
2016-02-19 0.1.2
2015-12-14 0.1.1
2015-08-26 0.1

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Package Rpoet (with last version 1.1.0) was removed from CRAN

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

2019-08-19 1.1.0

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