Wed, 08 Apr 2026

Package hhdynamics updated to version 1.3.3 with previous version 1.3.2 dated 2026-03-26

Title: Fitting Household Transmission Model to Estimate Household Transmission Dynamics of Influenza
Description: A Bayesian household transmission model to estimate household transmission dynamics, with accounting for infection from community and tertiary cases.
Author: Tim Tsang [aut, cre]
Maintainer: Tim Tsang <timkltsang@gmail.com>

Diff between hhdynamics versions 1.3.2 dated 2026-03-26 and 1.3.3 dated 2026-04-08

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Package varPro updated to version 3.0.0 with previous version 2.1.0 dated 2026-02-12

Title: Model-Independent Variable Selection via the Rule-Based Variable Priority
Description: A new framework of variable selection, which instead of generating artificial covariates such as permutation importance and knockoffs, creates release rules to examine the affect on the response for each covariate where the conditional distribution of the response variable can be arbitrary and unknown.
Author: Min Lu [aut], Aster K. Shear [aut], Udaya B. Kogalur [aut, cre], Hemant Ishwaran [aut]
Maintainer: Udaya B. Kogalur <ubk@kogalur.com>

Diff between varPro versions 2.1.0 dated 2026-02-12 and 3.0.0 dated 2026-04-08

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Package agrmt updated to version 1.42.19 with previous version 1.42.12 dated 2023-11-22

Title: Calculate Concentration and Dispersion in Ordered Rating Scales
Description: Calculates concentration and dispersion in ordered rating scales. It implements various measures of concentration and dispersion to describe what researchers variably call agreement, concentration, consensus, dispersion, or polarization among respondents in ordered data. It also implements other related measures to classify distributions. In addition to a generic city-block based concentration measure and a generic dispersion measure, the package implements various measures, including van der Eijk's (2001) <DOI: 10.1023/A:1010374114305> measure of agreement A, measures of concentration by Leik, Tatsle and Wierman, Blair and Lacy, Kvalseth, Berry and Mielke, Reardon, and Garcia-Montalvo and Reynal-Querol. Furthermore, the package provides an implementation of Galtungs AJUS-system to classify distributions, as well as a function to identify the position of multiple modes.
Author: Didier Ruedin [aut, cre] , Clem Aeppli [ctb]
Maintainer: Didier Ruedin <didier.ruedin@unine.ch>

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Package adbcpostgresql updated to version 0.23.0 with previous version 0.22.0 dated 2026-01-21

Title: 'Arrow' Database Connectivity ('ADBC') 'PostgreSQL' Driver
Description: Provides a developer-facing interface to the 'Arrow' Database Connectivity ('ADBC') 'PostgreSQL' driver for the purposes of building high-level database interfaces for users. 'ADBC' <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses 'Arrow' for result sets and query parameters.
Author: Dewey Dunnington [aut, cre] , Apache Arrow [aut, cph], Apache Software Foundation [cph]
Maintainer: Dewey Dunnington <dewey@dunnington.ca>

Diff between adbcpostgresql versions 0.22.0 dated 2026-01-21 and 0.23.0 dated 2026-04-08

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Package LSDirf updated to version 0.1.4 with previous version 0.1.3 dated 2024-04-04

Title: Impulse-Response Function Analysis for Agent-Based Models
Description: Performing impulse-response function (IRF) analysis of relevant variables of agent-based simulation models, in particular for models described in 'LSD' format. Based on the data produced by the simulation model, it performs both linear and state-dependent IRF analysis, providing the tools required by the Counterfactual Monte Carlo (CMC) methodology (Amendola and Pereira (2024) <doi:10.1016/j.jebo.2024.106811>), including state identification and sensitivity. CMC proposes retrieving the causal effect of shocks by exploiting the opportunity to directly observe the counterfactual in a fully controlled experimental setup. 'LSD' (Laboratory for Simulation Development) is free software available at <https://www.labsimdev.org/>).
Author: Marcelo C. Pereira [aut, cre] , Marco Amendola [aut]
Maintainer: Marcelo C. Pereira <mcper@unicamp.br>

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Package heterocop readmission to version 1.0.1 with previous version 1.0.0 dated 2025-06-06

Title: Semi-Parametric Estimation with Gaussian Copula
Description: A method for estimating the correlation matrix of the Gaussian copula from the observed data. This package also contains a penalized estimation of the corresponding precision matrix, and enables to generate random vectors that are distributed according to a Gaussian copula.
Author: Julie Cartier [aut], Florence Jaffrezic [aut], Gildas Mazo [aut], Ekaterina Tomilina [aut, cre]
Maintainer: Ekaterina Tomilina <ekaterina.tomilina@inrae.fr>

This is a re-admission after prior archival of version 1.0.0 dated 2025-06-06

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Package DyadRatios updated to version 1.4 with previous version 1.3 dated 2025-10-10

Title: Dyad Ratios Algorithm
Description: Estimates the Dyad Ratios Algorithm for pooling and smoothing poll estimates. The Dyad Ratios Algorithm smooths both forward and backward in time over polling results allowing differences in both question type and polling house. The result is an estimate of a single latent variable that describes the systematic trend over time in the (noisy) polling results. See James A. Stimson (2018) <doi:10.1177/0759106318761614> and the package's vignette for more details.
Author: Dave Armstrong [cre], James Stimson [aut]
Maintainer: Dave Armstrong <davearmstrong.ps@gmail.com>

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Package climatehealth updated to version 1.0.1 with previous version 1.0.0 dated 2026-03-30

Title: Statistical Tools for Modelling Climate-Health Impacts
Description: Tools for producing climate-health indicators and supporting official statistics from health and climate data. Implements analytical workflows for temperature-related mortality, wildfire smoke exposure, air pollution, suicides related to extreme heat, malaria, and diarrhoeal disease outcomes, with utilities for descriptive statistics, model validation, attributable fraction and attributable number estimation, relative risk estimation, minimum mortality temperature estimation, and plotting for reporting. These six indicators are endorsed by the United Nations Statistical Commission for inclusion in the Global Set of Environment and Climate Change Statistics. Implemented methods include distributed lag non-linear models (DLNM), quasi-Poisson time-series regression, case-crossover analysis, Bayesian spatio-temporal models using the Integrated Nested Laplace Approximation ('INLA'), and multivariate meta-analysis for sub-national estimates. The package is based on methods developed in the S [...truncated...]
Author: Charlie Browning [aut], Kenechi Omeke [aut, cre], Etse Yawo Dzakpa [aut], Gladin Jose [aut], Matt Pearce [aut], Ellie Watkins [aut], Claire Hunt [aut], Beatrice Byukusenge [aut], Cassien Habyarimana [aut], Venuste Nyagahakwa [aut], Felix Scarbrough [ [...truncated...]
Maintainer: Kenechi Omeke <climate.health@ons.gov.uk>

Diff between climatehealth versions 1.0.0 dated 2026-03-30 and 1.0.1 dated 2026-04-08

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Package adbcsqlite updated to version 0.23.0 with previous version 0.22.0 dated 2026-01-20

Title: 'Arrow' Database Connectivity ('ADBC') 'SQLite' Driver
Description: Provides a developer-facing interface to the 'Arrow' Database Connectivity ('ADBC') 'SQLite' driver for the purposes of building high-level database interfaces for users. 'ADBC' <https://arrow.apache.org/adbc/> is an API standard for database access libraries that uses 'Arrow' for result sets and query parameters.
Author: Dewey Dunnington [aut, cre] , Apache Arrow [aut, cph], Apache Software Foundation [cph]
Maintainer: Dewey Dunnington <dewey@dunnington.ca>

Diff between adbcsqlite versions 0.22.0 dated 2026-01-20 and 0.23.0 dated 2026-04-08

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Package ukbflow updated to version 0.3.4 with previous version 0.3.3 dated 2026-04-07

Title: Streamlined Workflow for UK Biobank Data Extraction, Analysis, and Visualization
Description: Provides a streamlined workflow for UK Biobank cloud-based analysis on the Research Analysis Platform (RAP). Includes tools for phenotype extraction and decoding, variable derivation, survival and association analysis, genetic risk score computation, and publication-quality visualization. For details on the UK Biobank resource, see Bycroft et al. (2018) <doi:10.1038/s41586-018-0579-z>.
Author: Yibin Zhou [aut, cre]
Maintainer: Yibin Zhou <evanzhou.bio@gmail.com>

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New package SVARtca with initial version 1.0.2
Package: SVARtca
Title: Transmission Channel Analysis in Structural VAR Models
Version: 1.0.2
Date: 2026-03-15
Description: Implements Transmission Channel Analysis (TCA) for structural vector autoregressive (SVAR) models following the methodology of Wegner, Lieb, and Smeekes (2025) <doi:10.48550/arXiv.2405.18987>. TCA decomposes impulse response functions (IRFs) into contributions from distinct transmission channels using a systems form representation and directed acyclic graph (DAG) path analysis. Supports overlapping channels, exhaustive 3-way and 4-way decompositions via inclusion-exclusion principle. This is a parallel R implementation of the 'tca-matlab-toolbox' (<https://github.com/enweg/tca-matlab-toolbox>).
License: MIT + file LICENSE
URL: https://github.com/muhammedalkhalaf/SVARtca
BugReports: https://github.com/muhammedalkhalaf/SVARtca/issues
Encoding: UTF-8
Depends: R (>= 3.5.0)
Imports: Matrix, ggplot2, rlang
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, vars
NeedsCompilation: no
Packaged: 2026-04-02 15:26:36 UTC; SYSTEM
Author: Muhammad Alkhalaf [aut, cre] , Emanuel Wegner [ctb] , Lenard Lieb [ctb] , Stephan Smeekes [ctb]
Maintainer: Muhammad Alkhalaf <muhammedalkhalaf@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-08 19:10:27 UTC

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New package standrecon with initial version 0.1.0
Package: standrecon
Title: Reconstruct Historical Forest Stand Conditions
Version: 0.1.0
Description: Reconstructs forest stand basal area and stem density at user-specified reference years using tree-level inventory data. The method estimates missing tree ages, back-calculates diameters using species-specific growth rates, and incorporates decay-class-based decomposition to infer mortality timing for dead trees. Results are returned in a tidy long format suitable for analysis and visualization.
License: MIT + file LICENSE
Encoding: UTF-8
URL: https://github.com/kriggithub/standrecon
BugReports: https://github.com/kriggithub/standrecon/issues
Suggests: testthat (>= 3.0.0)
Imports: stats, utils
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: no
Packaged: 2026-04-01 22:43:12 UTC; Kurt
Author: Kurt Riggin [aut, cre, cph]
Maintainer: Kurt Riggin <krigscholar@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-08 19:10:12 UTC

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Package rocrateR updated to version 0.1.0 with previous version 0.0.1 dated 2025-11-07

Title: Tools for Creating and Manipulating RO-Crates
Description: Provides tools for creating, manipulating and reading Research Object Crates (RO-Crates), a lightweight approach to packaging research data with structured metadata. Includes utilities for metadata generation, entity management, validation and reading existing RO-Crates following the specification <https://w3id.org/ro/crate/1.2/>.
Author: Roberto Villegas-Diaz [aut, cre] , Rebecca Wilson [aut] , Olly Butters [aut] , Stuart Wheater [aut] , Research Object community [cph]
Maintainer: Roberto Villegas-Diaz <r.villegas-diaz@outlook.com>

Diff between rocrateR versions 0.0.1 dated 2025-11-07 and 0.1.0 dated 2026-04-08

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Package risk.assessr updated to version 3.1.1 with previous version 3.1.0 dated 2026-03-25

Title: Assessing Package Risk Metrics
Description: A reliable and validated tool that captures detailed risk metrics such as R 'CMD' check, test coverage, traceability matrix, documentation, dependencies, reverse dependencies, suggested dependency analysis, repository data, and enhanced reporting for R packages that are local or stored on remote repositories such as GitHub, CRAN, and Bioconductor.
Author: Edward Gillian [cre, aut] , Hugo Bottois [aut] , Paulin Charliquart [aut], Andre Couturier [aut], Sanofi [cph, fnd]
Maintainer: Edward Gillian <edward.gillian-ext@sanofi.com>

Diff between risk.assessr versions 3.1.0 dated 2026-03-25 and 3.1.1 dated 2026-04-08

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Package PRA updated to version 0.4.0 with previous version 0.3.0 dated 2024-08-20

Title: Project Risk Analysis
Description: Data analysis for Project Risk Management via the Second Moment Method, Monte Carlo Simulation, Contingency Analysis, Sensitivity Analysis, Earned Value Management, Learning Curves, Bayesian Methods, and more.
Author: Paul Govan [aut, cre, cph]
Maintainer: Paul Govan <paul.govan2@gmail.com>

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Package HYPEtools updated to version 1.6.7 with previous version 1.6.6 dated 2025-08-19

Title: Tools for Processing and Analyzing Files from the Hydrological Catchment Model HYPE
Description: Work with model files (setup, input, output) from the hydrological catchment model HYPE: Streamlined file import and export, standard evaluation plot routines, diverse post-processing and aggregation routines for hydrological model analysis. The HYPEtools package is also archived at <doi:10.5281/zenodo.7627955> and can be cited in publications with Brendel et al. (2024) <doi:10.1016/j.envsoft.2024.106094>.
Author: Rene Capell [aut, cre] , Conrad Brendel [aut] , Jafet Andersson [ctb], David Gustafsson [ctb], Jude Musuuza [ctb], Jude Lubega [ctb]
Maintainer: Rene Capell <hypetools.rene@smhi.se>

Diff between HYPEtools versions 1.6.6 dated 2025-08-19 and 1.6.7 dated 2026-04-08

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New package gpss with initial version 1.0.3
Package: gpss
Title: Gaussian Processes for Social Science
Version: 1.0.3
Date: 2026-04-01
Description: Provides Gaussian process (GP) regression tools for social science inference problems. GPs combine flexible nonparametric regression with principled uncertainty quantification: rather than committing to a single model fit, the posterior reflects lesser knowledge at the edge of or beyond the observed data, where other approaches become highly model-dependent. The package reduces user-chosen hyperparameters from three to zero and supplies convenience functions for regression discontinuity (gp_rdd()), interrupted time-series (gp_its()), and general GP fitting (gpss(), gp_train(), gp_predict()). Methods are described in Cho, Kim, and Hazlett (2026) <doi:10.1017/pan.2026.10032>.
License: GPL (>= 3)
Encoding: UTF-8
URL: https://doeunkim.org/gpss/, https://github.com/doeun-kim/gpss
BugReports: https://github.com/doeun-kim/gpss/issues
Imports: Rcpp (>= 1.0.14), Matrix, ggplot2, rlang
LinkingTo: Rcpp, RcppArmadillo
Depends: R (>= 3.5.0)
LazyData: true
Suggests: MASS, posterior, testthat (>= 3.0.0)
NeedsCompilation: yes
Packaged: 2026-04-01 20:02:06 UTC; chadhazlett
Author: Soonhong Cho [aut], Doeun Kim [aut] , Chad Hazlett [aut, cre]
Maintainer: Chad Hazlett <chazlett@ucla.edu>
Repository: CRAN
Date/Publication: 2026-04-08 19:10:17 UTC

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Package git2rdata updated to version 0.5.2 with previous version 0.5.1 dated 2025-12-10

Title: Store and Retrieve Data.frames in a Git Repository
Description: The git2rdata package is an R package for writing and reading dataframes as plain text files. A metadata file stores important information. 1) Storing metadata allows to maintain the classes of variables. By default, git2rdata optimizes the data for file storage. The optimization is most effective on data containing factors. The optimization makes the data less human readable. The user can turn this off when they prefer a human readable format over smaller files. Details on the implementation are available in vignette("plain_text", package = "git2rdata"). 2) Storing metadata also allows smaller row based diffs between two consecutive commits. This is a useful feature when storing data as plain text files under version control. Details on this part of the implementation are available in vignette("version_control", package = "git2rdata"). Although we envisioned git2rdata with a git workflow in mind, you can use it in combination with other version control systems like subversion [...truncated...]
Author: Thierry Onkelinx [aut, cre] ), Floris Vanderhaeghe [ctb] ), Peter Desmet [ctb] ), Els Lommelen [ctb] ), Research Institute for Nature and Forest [cph, fnd]
Maintainer: Thierry Onkelinx <thierry.onkelinx@inbo.be>

Diff between git2rdata versions 0.5.1 dated 2025-12-10 and 0.5.2 dated 2026-04-08

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New package fastFGEE with initial version 0.1.0
Package: fastFGEE
Title: Fast Functional Generalized Estimating Equations via a One-Step Estimator
Version: 0.1.0
Description: Fits functional generalized estimating equations for longitudinal functional outcomes and covariates using a one-step estimator that is fast even for large cluster sizes or large numbers of clusters. The package supports quasi-likelihoods derived from a range of families, common link functions, and several working correlation structures. Uncertainty quantification is based on sandwich variance estimators and bootstrap procedures that remain valid even when the working correlation is incorrectly specified. The package provides an implementation of the method described in Loewinger et al. (2025) <https://pmc.ncbi.nlm.nih.gov/articles/PMC12306803/>. For irregularly spaced AR(1) precision matrices, the package can optionally use the archived package 'irregulAR1'; if needed, it can be obtained from the CRAN Archive at <https://cran.r-project.org/src/contrib/Archive/irregulAR1/>.
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.2)
Imports: data.table, ggplot2, gridExtra, MASS, Matrix, mgcv, refund, Rfast, SuperGauss
Suggests: irregulAR1, knitr, rmarkdown, sanic, Rcpp, RcppArmadillo
VignetteBuilder: knitr
URL: https://github.com/gloewing/fastFGEE
BugReports: https://github.com/gloewing/fastFGEE/issues
NeedsCompilation: no
Packaged: 2026-04-01 18:37:49 UTC; loewingergc
Author: Gabriel Loewinger [aut, cre]
Maintainer: Gabriel Loewinger <gloewinger@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-08 19:10:22 UTC

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Package enrichit updated to version 0.1.4 with previous version 0.1.3 dated 2026-03-10

Title: 'C++' Implementations of Functional Enrichment Analysis
Description: Fast implementations of functional enrichment analysis methods using 'C++' via 'Rcpp'. Currently provides Over-Representation Analysis (ORA) and Gene Set Enrichment Analysis (GSEA). The multilevel GSEA algorithm is derived from the 'fgsea' package. Methods are described in Subramanian et al. (2005) <doi:10.1073/pnas.0506580102> and Korotkevich et al. (2021) <doi:10.1101/060012>.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between enrichit versions 0.1.3 dated 2026-03-10 and 0.1.4 dated 2026-04-08

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New package VizModules with initial version 0.1.1
Package: VizModules
Title: Flexible, Interactive 'shiny' Modules for Almost Any Plot
Version: 0.1.1
Description: Offers a core selection of interactivity-first 'shiny' modules for many plot types meant to serve as flexible building blocks for applications and as the base for more complex modules. These modules allow for the rapid and convenient construction of 'shiny' apps with very few lines of code and decouple plotting from the underlying data. These modules allow for full plot aesthetic customization by the end user through UI inputs. Utility functions for simple UI organization, automated UI tooltips, and additional plot enhancements are also provided.
License: MIT + file LICENSE
Depends: shiny, dittoViz, plotly, R (>= 4.5), shinyBS, plotthis (>= 0.11.0)
Imports: roclang, colourpicker, dplyr, DT, readxl, shinyjs, scales, shinyjqui, ggplot2, htmltools, jsonlite, methods, shinyWidgets, htmlwidgets
Encoding: UTF-8
LazyData: true
Suggests: knitr, rmarkdown, shinytest2, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://j-andrews7.github.io/VizModules/, https://github.com/j-andrews7/VizModules
NeedsCompilation: no
Packaged: 2026-04-01 15:57:59 UTC; jandrews
Author: Jared Andrews [aut, cre] , Jacob Martin [aut]
Maintainer: Jared Andrews <jared.andrews07@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-08 19:00:02 UTC

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New package drmeta with initial version 0.1.0
Package: drmeta
Title: Design-Robust Meta-Analysis via Variance-Function Models
Version: 0.1.0
Description: Implements Design-Robust Meta-Analysis (DR-Meta), a variance-function random-effects framework in which between-study heterogeneity is modelled as a function of a study-level design robustness index, allowing heterogeneity to depend systematically on study quality or design strength rather than being treated as a single nuisance parameter. The package provides profiled restricted maximum likelihood (REML) estimation of the overall effect and variance-function parameters, study-specific weights, heterogeneity diagnostics (tau-squared, I-squared), influence and leave-one-out analysis, and graphical tools including forest plots and influence plots. The DR-Meta framework nests classical fixed-effects and standard random-effects meta-analysis as special cases, making it a strict generalisation of existing approaches.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: grDevices, graphics, stats, utils
Suggests: ggplot2 (>= 3.4.0), knitr, metafor (>= 4.0.0), rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
URL: https://github.com/causalfragility-lab/drmeta
BugReports: https://github.com/causalfragility-lab/drmeta/issues
NeedsCompilation: no
Packaged: 2026-04-01 22:48:08 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-08 18:40:03 UTC

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New package weightedVoronoi with initial version 1.1.1
Package: weightedVoronoi
Title: Weighted Spatial Tessellations in Constrained Polygon Domains
Version: 1.1.1
Depends: R (>= 4.1.0)
Description: Provides tools for weighted spatial tessellation using Euclidean and geodesic distances within constrained polygonal domains. The package can generate complete and connected spatial partitions that respect complex boundaries, heterogeneous point weights, and optional resistance or terrain effects. The methods extend weighted Voronoi tessellations to constrained domains and graph-based cost-distance surfaces. For background see Aurenhammer (1991) <doi:10.1145/116873.116880> and van Etten (2017) <doi:10.18637/jss.v076.i13>.
URL: https://HarriRaven.github.io/weightedVoronoi/, https://github.com/HarriRaven/weightedVoronoi
BugReports: https://github.com/HarriRaven/weightedVoronoi/issues
License: MIT + file LICENSE
Encoding: UTF-8
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Imports: methods, sf, stats, terra, dplyr, gdistance, raster, Matrix
NeedsCompilation: no
Packaged: 2026-04-02 11:20:26 UTC; exet4339
Author: Harri Ravenscroft [aut, cre]
Maintainer: Harri Ravenscroft <harri.ravenscroft@hotmail.co.uk>
Repository: CRAN
Date/Publication: 2026-04-08 14:20:03 UTC

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New package sparsecommunity with initial version 0.1.1
Package: sparsecommunity
Title: Spectral Community Detection for Sparse Networks
Version: 0.1.1
Description: Implements spectral clustering algorithms for community detection in sparse networks under the stochastic block model ('SBM') and degree-corrected stochastic block model ('DCSBM'), following the methods of Lei and Rinaldo (2015) <doi:10.1214/14-AOS1274>. Provides a regularized normalized Laplacian embedding, spherical k-median clustering for 'DCSBM', standard k-means for 'SBM', simulation utilities for both models, and a misclustering rate evaluation metric. Also includes the 'NCAA' college football network of Girvan and Newman (2002) <doi:10.1073/pnas.122653799> as a benchmark dataset, and the Bethe-Hessian community number estimator of Hwang (2023) <doi:10.1080/01621459.2023.2223793>.
License: GPL-3
Encoding: UTF-8
Language: en-US
LazyData: true
Depends: R (>= 4.0.0)
Imports: graphics, Matrix, methods, RSpectra, stats
Suggests: irlba, clue, igraph, igraphdata, testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-02 10:58:16 UTC; neilh
Author: Neil Hwang [aut, cre]
Maintainer: Neil Hwang <neil.hwang@bcc.cuny.edu>
Repository: CRAN
Date/Publication: 2026-04-08 14:10:02 UTC

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New package sparqlr with initial version 0.1.0
Package: sparqlr
Title: A SPARQL Client for R
Version: 0.1.0
Description: Provides a client for running SPARQL queries directly from R. SPARQL (short for SPARQL Protocol and RDF Query Language) is a query language used to retrieve and manipulate data stored in RDF (Resource Description Framework) format.
License: GPL-3
URL: https://github.com/sib-swiss/sparqlr
BugReports: https://github.com/sib-swiss/sparqlr/issues
Depends: R (>= 4.1.0)
Imports: dplyr, httr2, purrr, rlang, stringr, tibble, tidyr
Suggests: knitr, lintr, rcmdcheck, rmarkdown, styler, testthat (>= 3.0.0)
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2026-04-02 09:12:39 UTC; rengler
Author: Marco Pagni [aut] , Robin Engler [aut, cre] , SIB Swiss Institute of Bioinformatics [cph]
Maintainer: Robin Engler <robin.engler@sib.swiss>
Repository: CRAN
Date/Publication: 2026-04-08 14:10:08 UTC

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New package smimodel with initial version 0.1.3
Package: smimodel
Title: Sparse Multiple Index Models for Nonparametric Forecasting
Version: 0.1.3
Description: Implements a general algorithm for estimating Sparse Multiple Index (SMI) models for nonparametric forecasting and prediction. Estimation of SMI models requires the Gurobi mixed integer programming (MIP) solver via the gurobi R package. To use this functionality, the Gurobi Optimizer must be installed, and a valid license obtained and activated from <https://www.gurobi.com>. The gurobi R package must then be installed and configured following the instructions at <https://support.gurobi.com/hc/en-us/articles/14462206790033-How-do-I-install-Gurobi-for-R>. The package also includes functions for fitting nonparametric additive models with backward elimination, group-wise additive index models, and projection pursuit regression models as benchmark comparison methods. In addition, it provides tools for generating prediction intervals to quantify uncertainty in point forecasts produced by the SMI model and benchmark models, using the classical block bootstrap and a new method call [...truncated...]
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: cgaim, conformalForecast, dplyr, furrr, future, generics, ggplot2, gratia, gtools, Matrix, methods, mgcv, purrr, ROI, tibble, tidyselect, tidyr, tsibble, utils
Suggests: gurobi, knitr, lubridate, rmarkdown, testthat (>= 3.0.0)
URL: https://github.com/nuwani-palihawadana/smimodel, https://nuwani-palihawadana.github.io/smimodel/
BugReports: https://github.com/nuwani-palihawadana/smimodel/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-02 05:48:54 UTC; nkod0004
Author: Nuwani Palihawadana [aut, cre, cph] , Xiaoqian Wang [ctb]
Maintainer: Nuwani Palihawadana <nuwanipalihawadana@gmail.com>
Repository: CRAN
Date/Publication: 2026-04-08 14:10:13 UTC

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New package Nestimate with initial version 0.3.0
Package: Nestimate
Title: Network Estimation, Bootstrap, and Higher-Order Analysis
Version: 0.3.0
Description: Estimate, compare, and analyze dynamic and psychological networks using a unified interface. Provides transition network analysis estimation (transition, frequency, co-occurrence, attention-weighted) Saqr et al. (2025) <doi:10.1145/3706468.3706513>, psychological network methods (correlation, partial correlation, 'graphical lasso', 'Ising') Saqr, Beck, and Lopez-Pernas (2024) <doi:10.1007/978-3-031-54464-4_19>, and higher-order network methods including higher-order networks, higher-order network embedding, hyper-path anomaly, and multi-order generative model. Supports bootstrap inference, permutation testing, split-half reliability, centrality stability analysis, mixed Markov models, multi-cluster multi-layer networks and clustering.
License: MIT + file LICENSE
URL: https://github.com/mohsaqr/Nestimate
BugReports: https://github.com/mohsaqr/Nestimate/issues
Language: en-US
Encoding: UTF-8
Imports: ggplot2, glasso, data.table, cluster
Suggests: testthat (>= 3.0.0), tna, cograph, igraph, glmnet, lavaan, stringdist, nnet, IsingFit, bootnet, gimme, qgraph, reticulate, gridExtra, knitr, rmarkdown, pkgdown
Depends: R (>= 3.5)
LazyData: true
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-04-02 11:13:24 UTC; mohammedsaqr
Author: Mohammed Saqr [aut, cre, cph], Sonsoles Lopez-Pernas [aut]
Maintainer: Mohammed Saqr <saqr@saqr.me>
Repository: CRAN
Date/Publication: 2026-04-08 14:20:09 UTC

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New package CEDMr with initial version 0.1.0
Package: CEDMr
Title: Capability-Ecological Developmental Model (CEDM) Analysis
Version: 0.1.0
Description: Implements the Capability-Ecological Developmental Model (CEDM) for longitudinal and multilevel data. The package supports estimation and interpretation of models examining how socioeconomic status (SES), health indicators, and contextual factors jointly relate to academic outcomes. Functionality includes: (1) classification of ecological capability regimes (amplifying, neutral, compensatory); (2) estimation of moderated multilevel models with higher-order interaction terms; (3) causal mediation analysis using doubly robust estimation; (4) random-effects within-between (REWB) decomposition; (5) nonlinear moderation using restricted cubic splines; (6) clustering of longitudinal health trajectories; and (7) sensitivity analysis using the impact threshold for a confounding variable (ITCV) and robustness-to-replacement (RIR) measures. The package is designed for use with general longitudinal multilevel datasets.
License: MIT + file LICENSE
URL: https://github.com/causalfragility-lab/CEDMr
BugReports: https://github.com/causalfragility-lab/CEDMr/issues
Encoding: UTF-8
Language: en-US
Depends: R (>= 4.1.0)
Imports: dplyr (>= 1.1.0), ggplot2 (>= 3.4.0), lme4 (>= 1.1-31), magrittr (>= 2.0.0), mediation (>= 4.5.0), rlang (>= 1.1.0), rms (>= 6.7-0), stats, tidyr (>= 1.3.0)
Suggests: cluster (>= 2.1.4), konfound (>= 0.4.0), mice (>= 3.16.0), testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-04-02 04:12:12 UTC; Subir
Author: Subir Hait [aut, cre]
Maintainer: Subir Hait <haitsubi@msu.edu>
Repository: CRAN
Date/Publication: 2026-04-08 14:30:02 UTC

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New package integrity with initial version 1.0
Package: integrity
Title: Tests Checking for Implausible Values in Clinical Trials Data
Version: 1.0
Date: 2026-03-10
VignetteBuilder: knitr
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: ggplot2, dplyr, janitor, gtsummary, ggpubr, lubridate, car, rlang
Suggests: knitr, readxl, yaml
Description: Sixteen individual participant data-specific checks in a report-style result. Items are automated where possible, and are grouped into eight domains, including unusual data patterns, baseline characteristics, correlations, date violations, patterns of allocation, internal and external inconsistencies, and plausibility of data. The package may be applied by evidence synthesists, editors, and others to determine whether a randomised controlled trial may be considered trustworthy to contribute to the evidence base that informs policy and practice. For more details, see Hunter et al. (2024) <doi:10.1002/jrsm.1738> and <doi:10.32614/RJ-2017-008> in the same issue of Research Synthesis Methods.
License: GPL-3
URL: https://github.sydney.edu.au/Charles-Perkins-Centre-Data-Science-Hub/CPCDASH0010
NeedsCompilation: no
Packaged: 2026-04-02 08:31:36 UTC; dstr7320
Author: Sol Libesman [aut], Kylie Hunter [aut], David Nguyen [aut], Dario Strbenac [aut, cre], Jie Kang [aut]
Maintainer: Dario Strbenac <dario.strbenac@sydney.edu.au>
Repository: CRAN
Date/Publication: 2026-04-08 14:00:03 UTC

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Package epiR updated to version 2.0.92 with previous version 2.0.91 dated 2026-02-23

Title: Tools for the Analysis of Epidemiological Data
Description: Tools for the analysis of epidemiological and surveillance data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, computation of confidence intervals around incidence risk and incidence rate estimates and sample size calculations for cross-sectional, case-control and cohort studies. Surveillance tools include functions to calculate an appropriate sample size for 1- and 2-stage representative freedom surveys, functions to estimate surveillance system sensitivity and functions to support scenario tree modelling analyses.
Author: Mark Stevenson [aut, cre] , Evan Sergeant [aut], Cord Heuer [ctb], Telmo Nunes [ctb], Cord Heuer [ctb], Jonathon Marshall [ctb], Javier Sanchez [ctb], Ron Thornton [ctb], Jeno Reiczigel [ctb], Jim Robison-Cox [ctb], Paola Sebastiani [ctb], Peter Soly [...truncated...]
Maintainer: Mark Stevenson <mark.stevenson1@unimelb.edu.au>

Diff between epiR versions 2.0.91 dated 2026-02-23 and 2.0.92 dated 2026-04-08

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 13 files changed, 680 insertions(+), 268 deletions(-)

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Package rJava updated to version 1.0-18 with previous version 1.0-16 dated 2026-03-15

Title: Low-Level R to Java Interface
Description: Low-level interface to Java VM very much like .C/.Call and friends. Allows creation of objects, calling methods and accessing fields.
Author: Simon Urbanek [aut, cre, cph]
Maintainer: Simon Urbanek <Simon.Urbanek@r-project.org>

Diff between rJava versions 1.0-16 dated 2026-03-15 and 1.0-18 dated 2026-04-08

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More information about rJava at CRAN
Permanent link

Package ThurMod updated to version 1.1.15 with previous version 1.1.11 dated 2023-09-19

Title: Thurstonian CFA and Thurstonian IRT Modeling
Description: Fit Thurstonian forced-choice models (CFA (simple and factor) and IRT) in R. This package allows for the analysis of item response modeling (IRT) as well as confirmatory factor analysis (CFA) in the Thurstonian framework. Currently, estimation can be performed by 'Mplus' and 'lavaan'. References: Brown & Maydeu-Olivares (2011) <doi:10.1177/0013164410375112>; Jansen, M. T., & Schulze, R. (in review). The Thurstonian linked block design: Improving Thurstonian modeling for paired comparison and ranking data.; Maydeu-Olivares & Böckenholt (2005) <doi:10.1037/1082-989X.10.3.285>.
Author: Markus Thomas Jansen [aut, cre]
Maintainer: Markus Thomas Jansen <mjansen@uni-wuppertal.de>

Diff between ThurMod versions 1.1.11 dated 2023-09-19 and 1.1.15 dated 2026-04-08

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Package INLAtools updated to version 0.1.2 with previous version 0.1.1 dated 2026-04-03

Title: Functionalities for the 'INLA' Package
Description: Contain code to work with a C struct, in short cgeneric, to define a Gaussian Markov random (GMRF) model. The cgeneric contain code to specify GMRF elements such as the graph and the precision matrix, and also the initial and prior for its parameters, useful for model inference. It can be accessed from a C program and is the recommended way to implement new GMRF models in the 'INLA' package (<https://www.r-inla.org>). The 'INLAtools' implement functions to evaluate each one of the model specifications from R. The implemented functionalities leverage the use of 'cgeneric' models and provide a way to debug the code as well to work with the prior for the model parameters and to sample from it. The `generic0` can be used to implement intrinsic models with the scaling as proposed in Sørbye & Rue (2014) <doi:10.1016/j.spasta.2013.06.004>, and the required contraints. A very useful functionality is the Kronecker product method that creates a new model from multiple cgeneric mo [...truncated...]
Author: Elias Teixeira Krainski [cre, aut, cph] , Finn Lindgren [aut] , Haavard Rue’ [aut]
Maintainer: Elias Teixeira Krainski <eliaskrainski@gmail.com>

Diff between INLAtools versions 0.1.1 dated 2026-04-03 and 0.1.2 dated 2026-04-08

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Package FactoMineR updated to version 2.14 with previous version 2.13 dated 2026-01-12

Title: Multivariate Exploratory Data Analysis and Data Mining
Description: Exploratory data analysis methods to summarize, visualize and describe datasets. The main principal component methods are available, those with the largest potential in terms of applications: principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, Multiple Factor Analysis when variables are structured in groups, etc. and hierarchical cluster analysis. F. Husson, S. Le and J. Pages (2017).
Author: Francois Husson [aut, cre] , Julie Josse [aut], Sebastien Le [aut], Jeremy Mazet [aut]
Maintainer: Francois Husson <francois.husson@institut-agro.fr>

Diff between FactoMineR versions 2.13 dated 2026-01-12 and 2.14 dated 2026-04-08

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Package webfakes updated to version 1.4.1 with previous version 1.4.0 dated 2025-06-24

Title: Fake Web Apps for HTTP Testing
Description: Create a web app that makes it easier to test web clients without using the internet. It includes a web app framework with path matching, parameters and templates. Can parse various 'HTTP' request bodies. Can send 'JSON' data or files from the disk. Includes a web app that implements the 'httpbin.org' web service.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd] , Civetweb contributors [ctb] , Redoc contributors [ctb] , L. Peter Deutsch [ctb] , Martin Purschke [ctb] , Aladdin Enterprises [cph] , Maelle Salmon [ctb]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between webfakes versions 1.4.0 dated 2025-06-24 and 1.4.1 dated 2026-04-08

 DESCRIPTION                          |    6 ++--
 MD5                                  |   10 +++----
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Package VertexWiseR updated to version 1.5.1 with previous version 1.5.0 dated 2026-03-12

Title: Simplified Vertex-Wise Analyses of Whole-Brain and Subcortical Surface
Description: Provides functions to run statistical analyses on surface-based neuroimaging data, computing measures including cortical thickness and surface area of the whole-brain and of the hippocampi. It can make use of 'FreeSurfer', 'fMRIprep', 'XCP-D', 'HCP' and 'CAT12' preprocessed datasets, 'HippUnfold' hippocampal outputs and 'SubCortexMesh' subcortical outputs for a given sample by restructuring the data values into a single file. The single file can then be used by the package for analyses independently from its base dataset and without need for its access.
Author: Junhong Yu [aut] , Charly Billaud [aut, cre]
Maintainer: Charly Billaud <charly.billaud@ntu.edu.sg>

Diff between VertexWiseR versions 1.5.0 dated 2026-03-12 and 1.5.1 dated 2026-04-08

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Package splinemixmeta updated to version 1.0.1 with previous version 1.0.0 dated 2026-03-30

Title: Additive Mixed Meta-Analysis with Spline Meta-Regression
Description: Fit additive mixed meta-analysis (AMMA) models, extending the 'mixmeta' package <https://cran.r-project.org/package=mixmeta> to allow for spline-based meta-regression. Functions combine features of 'mgcv' <https://cran.r-project.org/package=mgcv> for building spline components and 'mixmeta' for estimating general mixed-effects meta-analysis models.
Author: Perry de Valpine [aut] , Marcus Beck [aut, cre]
Maintainer: Marcus Beck <mbeck@tbep.org>

Diff between splinemixmeta versions 1.0.0 dated 2026-03-30 and 1.0.1 dated 2026-04-08

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Package pkgndep updated to version 2.0.0 with previous version 1.99.3 dated 2023-10-13

Title: Analyze Dependency Heaviness of R Packages
Description: A new metric named 'dependency heaviness' is proposed that measures the number of additional dependency packages that a parent package brings to its child package and are unique to the dependency packages imported by all other parents. The dependency heaviness analysis is visualized by a customized heatmap. The package is described in <doi:10.1093/bioinformatics/btac449>. We have also performed the dependency heaviness analysis on the CRAN/Bioconductor package ecosystem, described in <doi:10.1016/j.jss.2023.111610>.
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <guzuguang@suat-sz.edu.cn>

Diff between pkgndep versions 1.99.3 dated 2023-10-13 and 2.0.0 dated 2026-04-08

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Package GlobalOptions updated to version 0.1.4 with previous version 0.1.3 dated 2025-11-28

Title: Generate Functions to Get or Set Global Options
Description: It provides more configurations on the option values such as validation and filtering on the values, making options invisible or private.
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <guzuguang@suat-sz.edu.cn>

Diff between GlobalOptions versions 0.1.3 dated 2025-11-28 and 0.1.4 dated 2026-04-08

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Package GetoptLong updated to version 1.1.1 with previous version 1.1.0 dated 2025-11-28

Title: Parsing Command-Line Arguments
Description: This is a command-line argument parser which wraps the powerful Perl module Getopt::Long and with some adaptations for easier use in R.
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <guzuguang@suat-sz.edu.cn>

Diff between GetoptLong versions 1.1.0 dated 2025-11-28 and 1.1.1 dated 2026-04-08

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Package bsub updated to version 2.0.7 with previous version 2.0.6 dated 2025-11-28

Title: Submitter and Monitor of the 'LSF Cluster'
Description: It submits R code/R scripts/shell commands to 'LSF cluster' (<https://en.wikipedia.org/wiki/Platform_LSF>, the 'bsub' system) without leaving R. There is also an interactive 'shiny' application for monitoring job status.
Author: Zuguang Gu [aut, cre]
Maintainer: Zuguang Gu <guzuguang@suat-sz.edu.cn>

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Package vecvec updated to version 0.2.1 with previous version 0.2.0 dated 2025-09-18

Title: Construct Mixed Type Data Structures with Vectors of Vectors
Description: Mixed type vectors are useful for combining semantically similar classes. Some examples of semantically related classes include time across different granularities (e.g. daily, monthly, annual) and probability distributions (e.g. Normal, Uniform, Poisson). These groups of vector types typically share common statistical operations which vary in results with the attributes of each vector. The 'vecvec' data structure facilitates efficient storage and computation across multiple vectors within the same object.
Author: Mitchell O'Hara-Wild [aut, cre]
Maintainer: Mitchell O'Hara-Wild <mail@mitchelloharawild.com>

Diff between vecvec versions 0.2.0 dated 2025-09-18 and 0.2.1 dated 2026-04-08

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Package UComp updated to version 5.1.9 with previous version 5.1.7 dated 2026-02-03

Title: Automatic Univariate Time Series Modelling of many Kinds
Description: Comprehensive analysis and forecasting of univariate time series using automatic time series models of many kinds. Harvey AC (1989) <doi:10.1017/CBO9781107049994>. Pedregal DJ and Young PC (2002) <doi:10.1002/9780470996430>. Durbin J and Koopman SJ (2012) <doi:10.1093/acprof:oso/9780199641178.001.0001>. Hyndman RJ, Koehler AB, Ord JK, and Snyder RD (2008) <doi:10.1007/978-3-540-71918-2>. Gómez V, Maravall A (2000) <doi:10.1002/9781118032978>. Pedregal DJ, Trapero JR and Holgado E (2024) <doi:10.1016/j.ijforecast.2023.09.004>.
Author: Diego J. Pedregal [aut, cre]
Maintainer: Diego J. Pedregal <diego.pedregal@uclm.es>

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Package otelsdk updated to version 0.2.4 with previous version 0.2.3 dated 2026-03-10

Title: R SDK and Exporters for OpenTelemetry
Description: OpenTelemetry is a collection of tools, APIs, and SDKs used to instrument, generate, collect, and export telemetry data (metrics, logs, and traces) for analysis in order to understand your software's performance and behavior. This package contains the OpenTelemetry SDK, and exporters. Use this package to export traces, metrics, logs from instrumented R code. Use the otel package to instrument your R code for OpenTelemetry.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd] , opentelemetry-cpp authors [ctb]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package oskeyring updated to version 0.1.7 with previous version 0.1.6 dated 2023-04-11

Title: Raw System Credential Store Access from R
Description: Aims to support all features of the system credential store, including non-portable ones. Supports 'Keychain' on 'macOS', and 'Credential Manager' on 'Windows'. See the 'keyring' package if you need a portable 'API'.
Author: Gabor Csardi [aut, cre], Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package cleancall updated to version 0.1.4 with previous version 0.1.3 dated 2022-10-26

Title: C Resource Cleanup via Exit Handlers
Description: Wrapper of .Call() that runs exit handlers to clean up C resources. Helps managing C (non-R) resources while using the R API.
Author: Lionel Henry [aut], Gabor Csardi [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

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Package weatherOz updated to version 3.0.0 with previous version 2.0.2 dated 2025-09-19

Title: An API Client for Australian Weather and Climate Data Resources
Description: Provides automated downloading, parsing and formatting of weather data for Australia through API endpoints provided by the Department of Primary Industries and Regional Development (DPIRD) of Western Australia and by the Science and Technology Division of the Queensland Government's Department of Environment and Science (DES). As well as the Bureau of Meteorology (BOM) of the Australian government precis and coastal forecasts, and downloading and importing radar and satellite imagery files. DPIRD weather data are accessed through public APIs provided by DPIRD, <https://www.dpird.wa.gov.au/online-tools/apis/>, providing access to weather station data from the DPIRD weather station network. Australia-wide weather data are based on data from the Australian Bureau of Meteorology (BOM) data and accessed through SILO (Scientific Information for Land Owners) Jeffrey et al. (2001) <doi:10.1016/S1364-8152(01)00008-1>. DPIRD data are made available under a Creative Commons Attribut [...truncated...]
Author: Rodrigo Pires [aut, cre] , Anna Hepworth [aut] , Rebecca O'Leary [aut], Jonathan Carroll [aut] , James Goldie [aut] , Dean Marchiori [aut] , Paul Melloy [aut] , Mark Padgham [aut] , Hugh Parsonage [aut] , Keith Pembleton [ctb] , Maelle Salmon [ctb] . [...truncated...]
Maintainer: Rodrigo Pires <rodrigo.pires@dpird.wa.gov.au>

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Package starnet updated to version 1.0.1 with previous version 1.0.0 dated 2025-06-10

Title: Stacked Elastic Net
Description: Implements stacked elastic net regression (Rauschenberger 2021 <doi:10.1093/bioinformatics/btaa535>). The elastic net generalises ridge and lasso regularisation (Zou 2005 <doi:10.1111/j.1467-9868.2005.00503.x>). Instead of fixing or tuning the mixing parameter alpha, we combine multiple alpha by stacked generalisation (Wolpert 1992 <doi:10.1016/S0893-6080(05)80023-1>).
Author: Armin Rauschenberger [aut, cre]
Maintainer: Armin Rauschenberger <armin.rauschenberger@uni.lu>

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Package lrstat updated to version 0.3.1 with previous version 0.3.0 dated 2026-03-07

Title: Power and Sample Size Calculation for Non-Proportional Hazards and Beyond
Description: Performs power and sample size calculation for non-proportional hazards model using the Fleming-Harrington family of weighted log-rank tests. The sequentially calculated log-rank test score statistics are assumed to have independent increments as characterized in Anastasios A. Tsiatis (1982) <doi:10.1080/01621459.1982.10477898>. The mean and variance of log-rank test score statistics are calculated based on Kaifeng Lu (2021) <doi:10.1002/pst.2069>. The boundary crossing probabilities are calculated using the recursive integration algorithm described in Christopher Jennison and Bruce W. Turnbull (2000, ISBN:0849303168). The package can also be used for continuous, binary, and count data. For continuous data, it can handle missing data through mixed-model for repeated measures (MMRM). In crossover designs, it can estimate direct treatment effects while accounting for carryover effects. For binary data, it can design Simon's 2-stage, modified toxicity probability-2 (mTPI-2), a [...truncated...]
Author: Kaifeng Lu [aut, cre]
Maintainer: Kaifeng Lu <kaifenglu@gmail.com>

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 man/getDesignSlopeDiff.Rd                        |   40 +-
 man/getDesignSlopeDiffMMRM.Rd                    |   46 +--
 man/getDesignWilcoxon.Rd                         |   40 +-
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 man/getNeventsFromHazardRatio.Rd                 |   40 +-
 man/hazard_pd.Rd                                 |    2 
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 man/kmpower.Rd                                   |   34 +-
 man/kmpower1s.Rd                                 |   34 +-
 man/kmpowerequiv.Rd                              |   25 -
 man/kmsamplesize.Rd                              |   46 +--
 man/kmsamplesize1s.Rd                            |   46 +--
 man/kmsamplesizeequiv.Rd                         |   25 -
 man/kmstat.Rd                                    |    6 
 man/kmsurv.Rd                                    |    2 
 man/lrpower.Rd                                   |   38 +-
 man/lrpowerequiv.Rd                              |   29 +
 man/lrsamplesize.Rd                              |   50 +--
 man/lrsamplesizeequiv.Rd                         |   29 +
 man/lrschoenfeld.Rd                              |   46 +--
 man/lrsim.Rd                                     |    9 
 man/lrsim2e.Rd                                   |    6 
 man/lrsim2e3a.Rd                                 |    6 
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 man/lrsimsub.Rd                                  |    6 
 man/lrstat.Rd                                    |    6 
 man/mtpwexp.Rd                                   |    2 
 man/natrisk.Rd                                   |    4 
 man/nbpower.Rd                                   |   34 +-
 man/nbpower1s.Rd                                 |   34 +-
 man/nbpowerequiv.Rd                              |   25 -
 man/nbsamplesize.Rd                              |   46 +--
 man/nbsamplesize1s.Rd                            |   46 +--
 man/nbsamplesizeequiv.Rd                         |   25 -
 man/nbstat.Rd                                    |    6 
 man/nevent.Rd                                    |    4 
 man/param_accrualTime.Rd                         |    2 
 man/param_efficacyStopping.Rd                    |    2 
 man/param_fixedFollowup.Rd                       |    2 
 man/param_futilityBounds.Rd                      |    2 
 man/param_futilityStopping.Rd                    |    2 
 man/param_parameterAlphaSpending.Rd              |    3 
 man/param_parameterBetaSpending.Rd               |    3 
 man/param_piecewiseSurvivalTime.Rd               |    2 
 man/param_typeAlphaSpending.Rd                   |   16 -
 man/param_typeBetaSpending.Rd                    |   12 
 man/param_typeOfComputation.Rd                   |    4 
 man/patrisk.Rd                                   |    2 
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 man/pmvnormr.Rd                                  |only
 man/print.lrsim_tsssd.Rd                         |only
 man/print.tsssd.Rd                               |only
 man/ptpwexp.Rd                                   |    2 
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 man/qtpwexp.Rd                                   |    2 
 man/repeatedPValue.Rd                            |   19 -
 man/rmpower.Rd                                   |   34 +-
 man/rmpower1s.Rd                                 |   34 +-
 man/rmpowerequiv.Rd                              |   25 -
 man/rmsamplesize.Rd                              |   46 +--
 man/rmsamplesize1s.Rd                            |   46 +--
 man/rmsamplesizeequiv.Rd                         |   25 -
 man/rmst.Rd                                      |    2 
 man/rmstat.Rd                                    |    6 
 man/rtpwexp.Rd                                   |    2 
 man/simonBayesSim.Rd                             |    2 
 src/Makevars                                     |only
 src/Makevars.win                                 |only
 src/RcppExports.cpp                              |  168 +++++++++++
 src/dataframe_list.cpp                           |  159 ++++++++++
 src/dataframe_list.h                             |  323 +++++++++++++++------
 src/enrollment_event.h                           |   32 --
 src/generic_design.cpp                           |    5 
 src/generic_design.h                             |   16 -
 src/logistic_regression.cpp                      |    3 
 src/logistic_regression.h                        |   13 
 src/lrsim.cpp                                    |   25 +
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 src/miettinen_nurminen.h                         |    8 
 src/mvnormr.cpp                                  |only
 src/mvnormr.h                                    |only
 src/survival_analysis.cpp                        |   15 
 src/survival_analysis.h                          |   19 -
 src/thread_utils.h                               |    5 
 src/tsssd_design.cpp                             |only
 src/utilities.cpp                                |  347 +++++++++++++++++------
 src/utilities.h                                  |  239 ++++++++-------
 144 files changed, 2955 insertions(+), 1417 deletions(-)

More information about lrstat at CRAN
Permanent link

Package bbotk updated to version 1.10.0 with previous version 1.9.0 dated 2026-02-28

Title: Black-Box Optimization Toolkit
Description: Features highly configurable search spaces via the 'paradox' package and optimizes every user-defined objective function. The package includes several optimization algorithms e.g. Random Search, Iterated Racing, Bayesian Optimization (in 'mlr3mbo') and Hyperband (in 'mlr3hyperband'). bbotk is the base package of 'mlr3tuning', 'mlr3fselect' and 'miesmuschel'.
Author: Marc Becker [cre, aut] , Jakob Richter [aut] , Michel Lang [aut] , Bernd Bischl [aut] , Martin Binder [aut], Olaf Mersmann [ctb]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between bbotk versions 1.9.0 dated 2026-02-28 and 1.10.0 dated 2026-04-08

 bbotk-1.10.0/bbotk/DESCRIPTION                                           |   12 
 bbotk-1.10.0/bbotk/MD5                                                   |  228 +++++-----
 bbotk-1.10.0/bbotk/NAMESPACE                                             |    5 
 bbotk-1.10.0/bbotk/NEWS.md                                               |    7 
 bbotk-1.10.0/bbotk/R/Archive.R                                           |   10 
 bbotk-1.10.0/bbotk/R/ArchiveAsync.R                                      |   37 +
 bbotk-1.10.0/bbotk/R/ArchiveAsyncFrozen.R                                |   13 
 bbotk-1.10.0/bbotk/R/ArchiveBatch.R                                      |   45 +
 bbotk-1.10.0/bbotk/R/CallbackAsync.R                                     |   63 +-
 bbotk-1.10.0/bbotk/R/CallbackBatch.R                                     |   48 +-
 bbotk-1.10.0/bbotk/R/Codomain.R                                          |   24 -
 bbotk-1.10.0/bbotk/R/ContextAsync.R                                      |   11 
 bbotk-1.10.0/bbotk/R/ContextBatch.R                                      |   11 
 bbotk-1.10.0/bbotk/R/EvalInstance.R                                      |   16 
 bbotk-1.10.0/bbotk/R/Objective.R                                         |   45 +
 bbotk-1.10.0/bbotk/R/ObjectiveRFun.R                                     |   28 -
 bbotk-1.10.0/bbotk/R/ObjectiveRFunDt.R                                   |   38 +
 bbotk-1.10.0/bbotk/R/ObjectiveRFunMany.R                                 |   43 +
 bbotk-1.10.0/bbotk/R/OptimInstance.R                                     |   20 
 bbotk-1.10.0/bbotk/R/OptimInstanceAsync.R                                |   14 
 bbotk-1.10.0/bbotk/R/OptimInstanceAsyncMultiCrit.R                       |   21 
 bbotk-1.10.0/bbotk/R/OptimInstanceAsyncSingleCrit.R                      |   23 -
 bbotk-1.10.0/bbotk/R/OptimInstanceBatch.R                                |   40 +
 bbotk-1.10.0/bbotk/R/OptimInstanceBatchMultiCrit.R                       |   13 
 bbotk-1.10.0/bbotk/R/OptimInstanceBatchSingleCrit.R                      |   21 
 bbotk-1.10.0/bbotk/R/OptimInstanceMultiCrit.R                            |   10 
 bbotk-1.10.0/bbotk/R/OptimInstanceSingleCrit.R                           |   10 
 bbotk-1.10.0/bbotk/R/Optimizer.R                                         |   40 +
 bbotk-1.10.0/bbotk/R/OptimizerAsync.R                                    |   76 ++-
 bbotk-1.10.0/bbotk/R/OptimizerAsyncDesignPoints.R                        |   11 
 bbotk-1.10.0/bbotk/R/OptimizerAsyncGridSearch.R                          |   16 
 bbotk-1.10.0/bbotk/R/OptimizerAsyncRandomSearch.R                        |   10 
 bbotk-1.10.0/bbotk/R/OptimizerBatch.R                                    |   36 +
 bbotk-1.10.0/bbotk/R/OptimizerBatchChain.R                               |   18 
 bbotk-1.10.0/bbotk/R/OptimizerBatchCmaes.R                               |   15 
 bbotk-1.10.0/bbotk/R/OptimizerBatchDesignPoints.R                        |    8 
 bbotk-1.10.0/bbotk/R/OptimizerBatchFocusSearch.R                         |  163 ++++---
 bbotk-1.10.0/bbotk/R/OptimizerBatchGenSA.R                               |   21 
 bbotk-1.10.0/bbotk/R/OptimizerBatchGridSearch.R                          |   11 
 bbotk-1.10.0/bbotk/R/OptimizerBatchIrace.R                               |   35 +
 bbotk-1.10.0/bbotk/R/OptimizerBatchLocalSearch.R                         |    4 
 bbotk-1.10.0/bbotk/R/OptimizerBatchNLoptr.R                              |   40 +
 bbotk-1.10.0/bbotk/R/OptimizerBatchRandomSearch.R                        |    7 
 bbotk-1.10.0/bbotk/R/Progressor.R                                        |   12 
 bbotk-1.10.0/bbotk/R/Terminator.R                                        |   30 -
 bbotk-1.10.0/bbotk/R/TerminatorClockTime.R                               |    6 
 bbotk-1.10.0/bbotk/R/TerminatorCombo.R                                   |   16 
 bbotk-1.10.0/bbotk/R/TerminatorEvals.R                                   |    7 
 bbotk-1.10.0/bbotk/R/TerminatorNone.R                                    |   11 
 bbotk-1.10.0/bbotk/R/TerminatorPerfReached.R                             |    7 
 bbotk-1.10.0/bbotk/R/TerminatorRunTime.R                                 |   13 
 bbotk-1.10.0/bbotk/R/TerminatorStagnation.R                              |    8 
 bbotk-1.10.0/bbotk/R/TerminatorStagnationBatch.R                         |   24 -
 bbotk-1.10.0/bbotk/R/TerminatorStagnationHypervolume.R                   |   10 
 bbotk-1.10.0/bbotk/R/as_terminator.R                                     |   15 
 bbotk-1.10.0/bbotk/R/assertions.R                                        |   65 ++
 bbotk-1.10.0/bbotk/R/bb_optimize.R                                       |   32 +
 bbotk-1.10.0/bbotk/R/bbotk_reflections.R                                 |   13 
 bbotk-1.10.0/bbotk/R/bibentries.R                                        |    3 
 bbotk-1.10.0/bbotk/R/conditions.R                                        |    8 
 bbotk-1.10.0/bbotk/R/helper.R                                            |    8 
 bbotk-1.10.0/bbotk/R/local_search.R                                      |   21 
 bbotk-1.10.0/bbotk/R/mlr_callbacks.R                                     |   12 
 bbotk-1.10.0/bbotk/R/mlr_optimizers.R                                    |   63 +-
 bbotk-1.10.0/bbotk/R/mlr_terminators.R                                   |   25 -
 bbotk-1.10.0/bbotk/R/mlr_test_functions.R                                |only
 bbotk-1.10.0/bbotk/R/nds_selection.R                                     |    7 
 bbotk-1.10.0/bbotk/R/sugar.R                                             |   46 +-
 bbotk-1.10.0/bbotk/R/worker_loops.R                                      |   16 
 bbotk-1.10.0/bbotk/build/partial.rdb                                     |binary
 bbotk-1.10.0/bbotk/man/ArchiveAsync.Rd                                   |    2 
 bbotk-1.10.0/bbotk/man/ArchiveAsyncFrozen.Rd                             |    2 
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 bbotk-1.10.0/bbotk/man/OptimInstanceAsyncMultiCrit.Rd                    |    2 
 bbotk-1.10.0/bbotk/man/OptimInstanceAsyncSingleCrit.Rd                   |    2 
 bbotk-1.10.0/bbotk/man/OptimizerAsync.Rd                                 |    8 
 bbotk-1.10.0/bbotk/man/mlr_optimizers_async_design_points.Rd             |    2 
 bbotk-1.10.0/bbotk/man/mlr_optimizers_async_grid_search.Rd               |    2 
 bbotk-1.10.0/bbotk/man/mlr_optimizers_async_random_search.Rd             |    2 
 bbotk-1.10.0/bbotk/man/mlr_test_functions.Rd                             |only
 bbotk-1.10.0/bbotk/man/oi_async.Rd                                       |    2 
 bbotk-1.10.0/bbotk/man/otfun.Rd                                          |only
 bbotk-1.10.0/bbotk/src/rc_helpers.c                                      |    7 
 bbotk-1.10.0/bbotk/tests/testthat/helper.R                               |   32 -
 bbotk-1.10.0/bbotk/tests/testthat/setup.R                                |   12 
 bbotk-1.10.0/bbotk/tests/testthat/teardown.R                             |    4 
 bbotk-1.10.0/bbotk/tests/testthat/test_ArchiveAsync.R                    |    7 
 bbotk-1.10.0/bbotk/tests/testthat/test_ArchiveBatch.R                    |   92 ++--
 bbotk-1.10.0/bbotk/tests/testthat/test_CallbackAsync.R                   |  106 ++--
 bbotk-1.10.0/bbotk/tests/testthat/test_CallbackBatch.R                   |   99 +---
 bbotk-1.10.0/bbotk/tests/testthat/test_Objective.R                       |  147 ++++--
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimInstanceAsyncSingleCrit.R    |    2 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimInstanceBatchMultiCrit.R     |    1 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimInstanceBatchSingleCrit.R    |   22 
 bbotk-1.10.0/bbotk/tests/testthat/test_Optimizer.R                       |   12 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerAsynDesignPoints.R       |    1 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerAsync.R                  |   12 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchChain.R             |   32 -
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchCmaes.R             |    6 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchDesignPoints.R      |   10 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchFocusSearch.R       |  105 ++--
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchGenSA.R             |    6 
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchIrace.R             |  126 +++--
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchLocalSearch.R       |   60 +-
 bbotk-1.10.0/bbotk/tests/testthat/test_OptimizerBatchNLoptr.R            |   30 +
 bbotk-1.10.0/bbotk/tests/testthat/test_TerminatorClockTime.R             |    6 
 bbotk-1.10.0/bbotk/tests/testthat/test_TerminatorEvals.R                 |    2 
 bbotk-1.10.0/bbotk/tests/testthat/test_TerminatorRunTime.R               |    2 
 bbotk-1.10.0/bbotk/tests/testthat/test_TerminatorStagnationHypervolume.R |    1 
 bbotk-1.10.0/bbotk/tests/testthat/test_bb_optimize.R                     |    9 
 bbotk-1.10.0/bbotk/tests/testthat/test_c_functions.R                     |   24 -
 bbotk-1.10.0/bbotk/tests/testthat/test_deprecated.R                      |   32 -
 bbotk-1.10.0/bbotk/tests/testthat/test_local_search.R                    |   17 
 bbotk-1.10.0/bbotk/tests/testthat/test_mlr_callbacks.R                   |    8 
 bbotk-1.10.0/bbotk/tests/testthat/test_mlr_test_functions.R              |only
 bbotk-1.10.0/bbotk/tests/testthat/test_nds_selection.R                   |   47 +-
 bbotk-1.10.0/bbotk/tests/testthat/test_search_start.R                    |   12 
 bbotk-1.9.0/bbotk/tests/testthat/helper_rush.R                           |only
 118 files changed, 1824 insertions(+), 1136 deletions(-)

More information about bbotk at CRAN
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Package armadillo4r updated to version 0.8.0 with previous version 0.7.0 dated 2025-12-04

Title: An 'Armadillo' Interface
Description: Provides function declarations and inline function definitions that facilitate communication between R and the 'Armadillo' 'C++' library for linear algebra and scientific computing. This implementation is derived from Vargas Sepulveda and Schneider Malamud (2024) <doi:10.1016/j.softx.2025.102087>.
Author: Mauricio Vargas Sepulveda [aut, cre] , Jonathan Schneider Malamud [ctb], Conrad Sanderson [aut] )
Maintainer: Mauricio Vargas Sepulveda <m.vargas.sepulveda@gmail.com>

Diff between armadillo4r versions 0.7.0 dated 2025-12-04 and 0.8.0 dated 2026-04-08

 armadillo4r-0.7.0/armadillo4r/inst/extdata/src/02_your_functions.h                  |only
 armadillo4r-0.8.0/armadillo4r/DESCRIPTION                                           |    6 
 armadillo4r-0.8.0/armadillo4r/MD5                                                   |   31 -
 armadillo4r-0.8.0/armadillo4r/NEWS.md                                               |    9 
 armadillo4r-0.8.0/armadillo4r/README.md                                             |    2 
 armadillo4r-0.8.0/armadillo4r/build/partial.rdb                                     |binary
 armadillo4r-0.8.0/armadillo4r/configure                                             |  155 +++---
 armadillo4r-0.8.0/armadillo4r/inst/extdata/configure                                |  254 ++++++++--
 armadillo4r-0.8.0/armadillo4r/inst/extdata/configure.win                            |only
 armadillo4r-0.8.0/armadillo4r/inst/extdata/dev/01_load_or_install.R                 |    2 
 armadillo4r-0.8.0/armadillo4r/inst/extdata/src/02_ols_qr.h                          |only
 armadillo4r-0.8.0/armadillo4r/inst/extdata/src/Makevars.win                         |    3 
 armadillo4r-0.8.0/armadillo4r/inst/extdata/src/main.cpp                             |    4 
 armadillo4r-0.8.0/armadillo4r/inst/include/armadillo4r.hpp                          |   42 +
 armadillo4r-0.8.0/armadillo4r/inst/include/armadillo4r/wrappers/cubes.hpp           |only
 armadillo4r-0.8.0/armadillo4r/inst/include/armadillo4r/wrappers/fields.hpp          |only
 armadillo4r-0.8.0/armadillo4r/inst/include/armadillo4r/wrappers/matrices.hpp        |   16 
 armadillo4r-0.8.0/armadillo4r/inst/include/armadillo4r/wrappers/sparse_matrices.hpp |  199 ++++---
 armadillo4r-0.8.0/armadillo4r/inst/include/armadillo4r/wrappers/vectors.hpp         |    7 
 19 files changed, 536 insertions(+), 194 deletions(-)

More information about armadillo4r at CRAN
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Package misl updated to version 2.0.0 with previous version 1.0.0 dated 2026-03-30

Title: Multiple Imputation by Super Learning
Description: Performs multiple imputation of missing data using an ensemble super learner built with the tidymodels framework. For each incomplete column, a stacked ensemble of candidate learners is trained on a bootstrap sample of the observed data and used to generate imputations via predictive mean matching (continuous), probability draws (binary), or cumulative probability draws (categorical). Supports parallelism across imputed datasets via the future framework.
Author: Justin Manjourides [aut, cre] , Thomas Carpenito [aut]
Maintainer: Justin Manjourides <j.manjourides@northeastern.edu>

Diff between misl versions 1.0.0 dated 2026-03-30 and 2.0.0 dated 2026-04-08

 DESCRIPTION                     |   25 +
 MD5                             |   26 +
 NAMESPACE                       |    1 
 NEWS.md                         |   53 +++
 R/misl.R                        |  533 +++++++++++++++++++++++++++++---------
 inst/doc/misl-introduction.R    |  215 ++++++++++-----
 inst/doc/misl-introduction.Rmd  |  235 ++++++++++++----
 inst/doc/misl-introduction.html |  560 ++++++++++++++++++++++++----------------
 man/check_datatype.Rd           |    3 
 man/list_learners.Rd            |    9 
 man/misl.Rd                     |   65 +++-
 man/plot_misl_trace.Rd          |only
 man/predict.misl_polr_fit.Rd    |only
 tests/testthat/test-misl.R      |  275 +++++++++++++++++++
 vignettes/misl-introduction.Rmd |  235 ++++++++++++----
 15 files changed, 1660 insertions(+), 575 deletions(-)

More information about misl at CRAN
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