Thu, 21 May 2026

Package bonsai updated to version 0.4.1 with previous version 0.4.0 dated 2025-06-25

Title: Model Wrappers for Tree-Based Models
Description: Bindings for additional tree-based model engines for use with the 'parsnip' package. Models include gradient boosted decision trees with 'LightGBM' (Ke et al, 2017.), conditional inference trees and conditional random forests with 'partykit' (Hothorn and Zeileis, 2015. and Hothorn et al, 2006. <doi:10.1198/106186006X133933>), and accelerated oblique random forests with 'aorsf' (Jaeger et al, 2022 <doi:10.5281/zenodo.7116854>).
Author: Daniel Falbel [aut], Athos Damiani [aut], Roel M. Hogervorst [aut] , Max Kuhn [aut] , Simon Couch [aut] , Emil Hvitfeldt [aut, cre] , Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

Diff between bonsai versions 0.4.0 dated 2025-06-25 and 0.4.1 dated 2026-05-21

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More information about bonsai at CRAN
Permanent link

Package tidyclust updated to version 0.3.0 with previous version 0.2.4 dated 2025-01-27

Title: A Common API to Clustering
Description: A common interface to specifying clustering models, in the same style as 'parsnip'. Creates unified interface across different functions and computational engines.
Author: Emil Hvitfeldt [aut, cre] , Kelly Bodwin [aut], Posit Software, PBC [cph, fnd]
Maintainer: Emil Hvitfeldt <emil.hvitfeldt@posit.co>

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Package rlas updated to version 1.9.2 with previous version 1.9.1 dated 2026-05-14

Title: Read and Write 'las' and 'laz' Binary File Formats Used for Remote Sensing Data
Description: Read and write 'las' and 'laz' binary file formats. The LAS file format is a public file format for the interchange of 3-dimensional point cloud data between data users. The LAS specifications are approved by the American Society for Photogrammetry and Remote Sensing <https://community.asprs.org/leadership-restricted/leadership-content/public-documents/standards>. The LAZ file format is an open and lossless compression scheme for binary LAS format versions 1.0 to 1.4 <https://laszip.org/>.
Author: Jean-Romain Roussel [aut, cre, cph], Florian De Boissieu [aut, ctb] , Martin Isenburg [cph] , David Auty [ctb] , Pierrick Marie [ctb] , Tiago de Conto [ctb]
Maintainer: Jean-Romain Roussel <info@r-lidar.com>

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Package autotab updated to version 1.0.1 with previous version 1.0 dated 2026-03-25

Title: Variational Autoencoders for Heterogeneous Tabular Data
Description: Build and train a variational autoencoder (VAE) for mixed-type tabular data (continuous, binary, categorical). Models are implemented using 'TensorFlow' and 'Keras' via the 'reticulate' interface, enabling reproducible VAE training for heterogeneous tabular datasets.
Author: Sarah Milligan [aut, cre]
Maintainer: Sarah Milligan <slm1999@bu.edu>

Diff between autotab versions 1.0 dated 2026-03-25 and 1.0.1 dated 2026-05-21

 DESCRIPTION          |    7 ++++---
 MD5                  |   17 ++++++++++-------
 R/data.R             |only
 R/decoder.R          |   19 ++++++++++++++++---
 R/latent_sampling.R  |   10 ++++------
 R/loss.R             |    3 +--
 README.md            |   14 ++++++--------
 data                 |only
 man/Latent_sample.Rd |   10 ++++------
 man/data_example.Rd  |only
 man/decoder_model.Rd |    4 ++--
 11 files changed, 47 insertions(+), 37 deletions(-)

More information about autotab at CRAN
Permanent link

Package StepReg updated to version 1.6.5 with previous version 1.6.4 dated 2026-05-14

Title: Stepwise Regression Analysis
Description: Stepwise regression is a statistical technique used for model selection. This package streamlines stepwise regression analysis by supporting multiple regression types(linear, Cox, logistic, Poisson, Gamma, and negative binomial), incorporating popular selection strategies(forward, backward, bidirectional, and subset), and offering essential metrics. It enables users to apply multiple selection strategies and metrics in a single function call, visualize variable selection processes, and export results in various formats. StepReg offers a data-splitting option to address potential issues with invalid statistical inference and a randomized forward selection option to avoid overfitting. We validated StepReg's accuracy using public datasets within the SAS software environment. For an interactive web interface, users can install the companion 'StepRegShiny' package.
Author: Junhui Li [cre] , Junhui Li [aut], Kai Hu [aut], Xiaohuan Lu [aut], Wenxin Liu [aut], Lihua Julie Zhu [aut]
Maintainer: Junhui Li <junhui.li11@umassmed.edu>

Diff between StepReg versions 1.6.4 dated 2026-05-14 and 1.6.5 dated 2026-05-21

 DESCRIPTION           |    8 ++--
 MD5                   |   12 +++---
 R/performance.R       |    3 +
 R/stepwise.R          |    2 -
 R/stepwiseUtils.R     |   90 +++++++++++++++++++++++++++++---------------------
 inst/doc/StepReg.html |   60 ++++++++++++++++-----------------
 man/performance.Rd    |    3 +
 7 files changed, 98 insertions(+), 80 deletions(-)

More information about StepReg at CRAN
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Package rddensity updated to version 3.0 with previous version 2.6 dated 2024-10-06

Title: Manipulation Testing Based on Density Discontinuity
Description: Density discontinuity testing (a.k.a. manipulation testing) is commonly employed in regression discontinuity designs and other program evaluation settings to detect perfect self-selection (manipulation) around a cutoff where treatment/policy assignment changes. This package implements manipulation testing procedures using local polynomial density estimators: rddensity() constructs test statistics and p-values given a prespecified cutoff, rdbwdensity() performs data-driven bandwidth selection, and rdplotdensity() constructs density plots.
Author: Matias D. Cattaneo [aut, cre], Michael Jansson [aut], Xinwei Ma [aut]
Maintainer: Matias D. Cattaneo <matias.d.cattaneo@gmail.com>

Diff between rddensity versions 2.6 dated 2024-10-06 and 3.0 dated 2026-05-21

 DESCRIPTION              |   40 ++++++++++++++++++++--------------------
 MD5                      |   25 ++++++++++++++-----------
 R/rdbwdensity.R          |   44 +++++++++++++++++++++++---------------------
 R/rddensity-package.R    |    6 +++---
 R/rddensity.R            |   38 +++++++++++++++++++++-----------------
 R/rddensity_fun.R        |   34 +++++++++++++++++++++++++++++++---
 R/rdplotdensity.R        |    6 +++---
 build/partial.rdb        |binary
 man/rdbwdensity.Rd       |    6 +++---
 man/rddensity-package.Rd |    6 +++---
 man/rddensity.Rd         |    6 +++---
 man/rdplotdensity.Rd     |    6 +++---
 tests                    |only
 13 files changed, 127 insertions(+), 90 deletions(-)

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Package performance updated to version 0.17.0 with previous version 0.16.0 dated 2026-02-04

Title: Assessment of Regression Models Performance
Description: Utilities for computing measures to assess model quality, which are not directly provided by R's 'base' or 'stats' packages. These include e.g. measures like r-squared, intraclass correlation coefficient (Nakagawa, Johnson & Schielzeth (2017) <doi:10.1098/rsif.2017.0213>), root mean squared error or functions to check models for overdispersion, singularity or zero-inflation and more. Functions apply to a large variety of regression models, including generalized linear models, mixed effects models and Bayesian models. References: Lüdecke et al. (2021) <doi:10.21105/joss.03139>.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Remi Theriault [aut, ctb] , Vincent Arel-Bundock [ctb] , Martin J [...truncated...]
Maintainer: Daniel Luedecke <officialeasystats@gmail.com>

Diff between performance versions 0.16.0 dated 2026-02-04 and 0.17.0 dated 2026-05-21

 DESCRIPTION                                        |   12 
 MD5                                                |  103 +++----
 NAMESPACE                                          |    1 
 NEWS.md                                            |   28 ++
 R/check_collinearity.R                             |   53 +++
 R/check_homogeneity.R                              |    2 
 R/check_model.R                                    |   28 ++
 R/check_outliers.R                                 |    6 
 R/check_predictions.R                              |   80 ++---
 R/performance_cv.R                                 |  282 +++++++++++----------
 R/test_likelihoodratio.R                           |   15 -
 R/test_performance.R                               |   15 -
 build/partial.rdb                                  |binary
 man/check_autocorrelation.Rd                       |   22 -
 man/check_collinearity.Rd                          |   22 -
 man/check_convergence.Rd                           |   22 -
 man/check_heteroscedasticity.Rd                    |   22 -
 man/check_homogeneity.Rd                           |   22 -
 man/check_model.Rd                                 |   51 ++-
 man/check_outliers.Rd                              |   32 +-
 man/check_overdispersion.Rd                        |   22 -
 man/check_predictions.Rd                           |   29 +-
 man/check_singularity.Rd                           |   22 -
 man/check_zeroinflation.Rd                         |   22 -
 man/compare_performance.Rd                         |    2 
 man/figures/card.png                               |binary
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 man/performance-package.Rd                         |    1 
 man/performance_accuracy.Rd                        |    2 
 man/performance_cv.Rd                              |    6 
 man/r2_mlm.Rd                                      |    2 
 man/reexports.Rd                                   |    2 
 man/test_performance.Rd                            |   15 -
 tests/testthat/test-check_autocorrelation_simres.R |    4 
 tests/testthat/test-check_collinearity.R           |  110 ++++++++
 tests/testthat/test-check_homogeneity.R            |   12 
 tests/testthat/test-check_normality.R              |    2 
 tests/testthat/test-check_outliers.R               |    2 
 tests/testthat/test-check_overdispersion.R         |   18 -
 tests/testthat/test-check_predictions.R            |   52 +++
 tests/testthat/test-check_residuals.R              |    2 
 tests/testthat/test-check_zeroinflation.R          |   25 -
 tests/testthat/test-discovr_book.R                 |only
 tests/testthat/test-glmmPQL.R                      |    2 
 tests/testthat/test-performance_cv.R               |   27 +-
 tests/testthat/test-r2_mcfadden.R                  |    4 
 tests/testthat/test-test_likelihoodratio.R         |   71 +++++
 53 files changed, 827 insertions(+), 447 deletions(-)

More information about performance at CRAN
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Package modEvA updated to version 3.45 with previous version 3.41 dated 2026-01-09

Title: Model Evaluation and Analysis
Description: Analyses species distribution models and evaluates their performance. It includes functions for variation partitioning, extracting variable importance, computing several metrics of model discrimination and calibration performance, optimizing prediction thresholds based on a number of criteria, performing multivariate environmental similarity surface (MESS) analysis, and displaying various analytical plots. Initially described in Barbosa et al. (2013) <doi:10.1111/ddi.12100>.
Author: A. Marcia Barbosa [aut, cre], Jennifer A. Brown [aut], Alberto Jimenez-Valverde [aut], Raimundo Real [aut], Oswald van Ginkel [ctb], Jurica Levatic [ctb], Victoria Formoso-Freire [ctb], Andres Baselga [ctb], Carola Gomez-Rodriguez [ctb], Carlos C. Ra [...truncated...]
Maintainer: A. Marcia Barbosa <ana.marcia.barbosa@gmail.com>

Diff between modEvA versions 3.41 dated 2026-01-09 and 3.45 dated 2026-05-21

 DESCRIPTION            |   16 +--
 MD5                    |   98 ++++++++++---------
 NAMESPACE              |   10 +
 NEWS.md                |  113 +++++++++++++++++++++-
 R/AUC.R                |   33 +++++-
 R/Boyce.R              |   67 +++++++------
 R/HLfit.R              |  203 ++++++++++++++++++++++------------------
 R/Miller.R             |only
 R/MillerCalib.R        |   48 ---------
 R/evaluate.R           |    8 -
 R/getBins.R            |  246 ++++++++++++++++++++++++++++++-------------------
 R/lollipop.R           |    2 
 R/modEvAmethods.R      |   17 +--
 R/multModEv.R          |    2 
 R/optiPair.R           |    2 
 R/optiThresh.R         |    2 
 R/plotGLM.R            |  162 ++++++++++++++++----------------
 R/poMeasures.R         |only
 R/predDensity.R        |  236 ++++++++++++++++++++++++-----------------------
 R/predPlot.R           |   80 +++++++--------
 R/threshMeasures.R     |   33 ++++--
 data/rotif.mods.rda    |binary
 inst/CITATION          |   67 ++++++++++---
 man/AUC.Rd             |   31 ++++--
 man/Boyce.Rd           |   37 ++++---
 man/Dsquared.Rd        |    4 
 man/HLfit.Rd           |   40 +++----
 man/Miller.Rd          |only
 man/MillerCalib.Rd     |  102 ++++----------------
 man/RMSE.Rd            |    4 
 man/RsqGLM.Rd          |    4 
 man/applyThreshold.Rd  |    2 
 man/confusionLabel.Rd  |    2 
 man/confusionMatrix.Rd |    2 
 man/errorMeasures.Rd   |  118 +++++++++++------------
 man/getBins.Rd         |   49 ++++-----
 man/getModEqn.Rd       |    4 
 man/getThreshold.Rd    |    2 
 man/inputMunch.Rd      |    4 
 man/logLike.Rd         |  132 +++++++++++++-------------
 man/lollipop.Rd        |    6 -
 man/modEvA-package.Rd  |   33 +++---
 man/multModEv.Rd       |    6 -
 man/optiPair.Rd        |    4 
 man/optiThresh.Rd      |    4 
 man/plotGLM.Rd         |    4 
 man/poMeasures.Rd      |only
 man/predDensity.Rd     |   16 +--
 man/predPlot.Rd        |  162 ++++++++++++++++----------------
 man/pseudoRsq.Rd       |   14 +-
 man/similarity.Rd      |    2 
 man/threshMeasures.Rd  |   55 ++++++++--
 52 files changed, 1272 insertions(+), 1016 deletions(-)

More information about modEvA at CRAN
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Package mlr3fselect updated to version 1.6.0 with previous version 1.5.1 dated 2026-03-18

Title: Feature Selection for 'mlr3'
Description: Feature selection package of the 'mlr3' ecosystem. It selects the optimal feature set for any 'mlr3' learner. The package works with several optimization algorithms e.g. Random Search, Recursive Feature Elimination, and Genetic Search. Moreover, it can automatically optimize learners and estimate the performance of optimized feature sets with nested resampling.
Author: Marc Becker [aut, cre] , Patrick Schratz [aut] , Michel Lang [aut] , Bernd Bischl [aut] , John Zobolas [aut]
Maintainer: Marc Becker <marcbecker@posteo.de>

Diff between mlr3fselect versions 1.5.1 dated 2026-03-18 and 1.6.0 dated 2026-05-21

 mlr3fselect-1.5.1/mlr3fselect/tests/testthat/helper_rush.R                         |only
 mlr3fselect-1.6.0/mlr3fselect/DESCRIPTION                                          |   13 
 mlr3fselect-1.6.0/mlr3fselect/MD5                                                  |  233 +++----
 mlr3fselect-1.6.0/mlr3fselect/NEWS.md                                              |    7 
 mlr3fselect-1.6.0/mlr3fselect/R/ArchiveAsyncFSelect.R                              |   44 -
 mlr3fselect-1.6.0/mlr3fselect/R/ArchiveAsyncFSelectFrozen.R                        |   34 -
 mlr3fselect-1.6.0/mlr3fselect/R/ArchiveBatchFSelect.R                              |   39 -
 mlr3fselect-1.6.0/mlr3fselect/R/AutoFSelector.R                                    |   83 +-
 mlr3fselect-1.6.0/mlr3fselect/R/CallbackAsyncFSelect.R                             |   95 +-
 mlr3fselect-1.6.0/mlr3fselect/R/CallbackBatchFSelect.R                             |   68 +-
 mlr3fselect-1.6.0/mlr3fselect/R/ContextAsyncFSelect.R                              |    9 
 mlr3fselect-1.6.0/mlr3fselect/R/ContextBatchFSelect.R                              |   11 
 mlr3fselect-1.6.0/mlr3fselect/R/EnsembleFSResult.R                                 |  229 ++++---
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectInstanceAsyncMultiCrit.R                    |   22 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectInstanceAsyncSingleCrit.R                   |   19 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectInstanceBatchMultiCrit.R                    |   16 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectInstanceBatchSingleCrit.R                   |   28 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelector.R                                        |   20 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorAsync.R                                   |   13 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorAsyncDesignPoints.R                       |    4 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorAsyncExhaustiveSearch.R                   |   19 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorAsyncFromOptimizerAsync.R                 |   14 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorAsyncRandomSearch.R                       |    4 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatch.R                                   |   37 -
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchDesignPoints.R                       |    4 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchExhaustiveSearch.R                   |   19 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchFromOptimizerBatch.R                 |    9 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchGeneticSearch.R                      |   20 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchRFE.R                                |   68 +-
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchRFECV.R                              |   46 -
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchRandomSearch.R                       |    7 
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchSequential.R                         |   53 -
 mlr3fselect-1.6.0/mlr3fselect/R/FSelectorBatchShadowVariableSearch.R               |   78 +-
 mlr3fselect-1.6.0/mlr3fselect/R/ObjectiveFSelect.R                                 |   16 
 mlr3fselect-1.6.0/mlr3fselect/R/ObjectiveFSelectAsync.R                            |   41 +
 mlr3fselect-1.6.0/mlr3fselect/R/ObjectiveFSelectBatch.R                            |   36 -
 mlr3fselect-1.6.0/mlr3fselect/R/assertions.R                                       |   38 -
 mlr3fselect-1.6.0/mlr3fselect/R/auto_fselector.R                                   |    5 
 mlr3fselect-1.6.0/mlr3fselect/R/bibentries.R                                       |   27 
 mlr3fselect-1.6.0/mlr3fselect/R/embedded_ensemble_fselect.R                        |   19 
 mlr3fselect-1.6.0/mlr3fselect/R/ensemble_fselect.R                                 |   30 
 mlr3fselect-1.6.0/mlr3fselect/R/extract_inner_fselect_archives.R                   |   32 
 mlr3fselect-1.6.0/mlr3fselect/R/extract_inner_fselect_results.R                    |   34 -
 mlr3fselect-1.6.0/mlr3fselect/R/faggregate.R                                       |   27 
 mlr3fselect-1.6.0/mlr3fselect/R/fselect.R                                          |   20 
 mlr3fselect-1.6.0/mlr3fselect/R/fselect_nested.R                                   |    5 
 mlr3fselect-1.6.0/mlr3fselect/R/helper.R                                           |    9 
 mlr3fselect-1.6.0/mlr3fselect/R/mlr_callbacks.R                                    |   53 +
 mlr3fselect-1.6.0/mlr3fselect/R/mlr_fselectors.R                                   |   27 
 mlr3fselect-1.6.0/mlr3fselect/R/sugar.R                                            |   19 
 mlr3fselect-1.6.0/mlr3fselect/README.md                                            |   26 
 mlr3fselect-1.6.0/mlr3fselect/build/partial.rdb                                    |binary
 mlr3fselect-1.6.0/mlr3fselect/inst/testthat/helper_expectations.R                  |    7 
 mlr3fselect-1.6.0/mlr3fselect/inst/testthat/helper_fselector.R                     |    6 
 mlr3fselect-1.6.0/mlr3fselect/inst/testthat/helper_misc.R                          |   42 -
 mlr3fselect-1.6.0/mlr3fselect/man/ArchiveAsyncFSelect.Rd                           |    3 
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 mlr3fselect-1.6.0/mlr3fselect/man/AutoFSelector.Rd                                 |   19 
 mlr3fselect-1.6.0/mlr3fselect/man/CallbackAsyncFSelect.Rd                          |    3 
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 mlr3fselect-1.6.0/mlr3fselect/man/FSelectInstanceAsyncMultiCrit.Rd                 |   13 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelectInstanceAsyncSingleCrit.Rd                |   10 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelectInstanceBatchMultiCrit.Rd                 |   10 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelectInstanceBatchSingleCrit.Rd                |   19 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelector.Rd                                     |    6 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelectorAsync.Rd                                |   15 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelectorAsyncFromOptimizerAsync.Rd              |    6 
 mlr3fselect-1.6.0/mlr3fselect/man/FSelectorBatch.Rd                                |   31 
 mlr3fselect-1.6.0/mlr3fselect/man/ObjectiveFSelect.Rd                              |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/ObjectiveFSelectAsync.Rd                         |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/ObjectiveFSelectBatch.Rd                         |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/auto_fselector.Rd                                |   15 
 mlr3fselect-1.6.0/mlr3fselect/man/callback_async_fselect.Rd                        |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/callback_batch_fselect.Rd                        |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/embedded_ensemble_fselect.Rd                     |   20 
 mlr3fselect-1.6.0/mlr3fselect/man/ensemble_fs_result.Rd                            |   93 +-
 mlr3fselect-1.6.0/mlr3fselect/man/ensemble_fselect.Rd                              |   27 
 mlr3fselect-1.6.0/mlr3fselect/man/extract_inner_fselect_archives.Rd                |    8 
 mlr3fselect-1.6.0/mlr3fselect/man/extract_inner_fselect_results.Rd                 |    6 
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 mlr3fselect-1.6.0/mlr3fselect/man/fsi_async.Rd                                     |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr3fselect.async_freeze_archive.Rd              |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr3fselect.svm_rfe.Rd                           |    2 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr_fselectors_genetic_search.Rd                 |    2 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr_fselectors_random_search.Rd                  |    3 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr_fselectors_rfe.Rd                            |   15 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr_fselectors_rfecv.Rd                          |   21 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr_fselectors_sequential.Rd                     |    6 
 mlr3fselect-1.6.0/mlr3fselect/man/mlr_fselectors_shadow_variable_search.Rd         |    3 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/helper.R                              |    5 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/setup.R                               |   14 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/teardown.R                            |    4 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_ArchiveAsyncFSelect.R            |   21 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_ArchiveBatchFSelect.R            |  322 ++++++++--
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_AutoFSelector.R                  |   94 ++
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_CallbackAsyncFSelect.R           |  254 ++++---
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectInstanceMultiCrit.R       |   21 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectInstanceSingleCrit.R      |   34 -
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectorAsyncDesignPoints.R     |    3 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectorBatchDesignPoints.R     |    6 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectorExhaustiveSearch.R      |    2 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectorRFE.R                   |   37 -
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectorRFECV.R                 |   28 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_FSelectorShadowVariableSearch.R  |   10 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_ObjectiveFSelect.R               |   90 +-
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_ObjectiveFSelectAsync.R          |   61 +
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_auto_fselector.R                 |   28 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_embedded_ensemble_fselect.R      |   16 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_ensemble_fselect.R               |  112 ++-
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_extract_inner_fselect_archives.R |  293 ++++++++-
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_extract_inner_fselect_result.R   |  306 ++++++++-
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_fselect.R                        |   30 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_fselect_nested.R                 |   12 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_fsi.R                            |  119 ++-
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_fsi_async.R                      |    6 
 mlr3fselect-1.6.0/mlr3fselect/tests/testthat/test_mlr_callbacks.R                  |    1 
 118 files changed, 2923 insertions(+), 1308 deletions(-)

More information about mlr3fselect at CRAN
Permanent link

Package logging updated to version 0.10-111 with previous version 0.10-108 dated 2019-07-14

Title: R Logging Package
Description: Pure R implementation of the ubiquitous log4j package. It offers hierarchic loggers, multiple handlers per logger, level based filtering, space handling in messages and custom formatting.
Author: Mario Frasca [aut, cre], Walerian Sokolowski [aut]
Maintainer: Mario Frasca <mariotomo@gmail.com>

Diff between logging versions 0.10-108 dated 2019-07-14 and 0.10-111 dated 2026-05-21

 DESCRIPTION                        |   16 ++++++++--------
 MD5                                |    9 +++++----
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Package amadeus updated to version 2.0.0 with previous version 1.3.2.1 dated 2026-01-26

Title: Accessing and Analyzing Large-Scale Environmental Data
Description: Functions are designed to facilitate access to and utility with large scale, publicly available environmental data in R. The package contains functions for downloading raw data files from web URLs (download_data()), processing the raw data files into clean spatial objects (process_covariates()), and extracting values from the spatial data objects at point and polygon locations (calculate_covariates()). These functions call a series of source-specific functions which are tailored to each data sources/datasets particular URL structure, data format, and spatial/temporal resolution. The functions are tested, versioned, and open source and open access. For sum_edc() method details, see Messier, Akita, and Serre (2012) <doi:10.1021/es203152a>.
Author: Mitchell Manware [aut, ctb] , Insang Song [aut, ctb] , Eva Marques [aut, ctb] , Mariana Alifa Kassien [aut, ctb] , Elizabeth Scholl [ctb] , Kyle Messier [aut, cre] , Spatiotemporal Exposures and Toxicology Group [cph]
Maintainer: Kyle Messier <kyle.messier@nih.gov>

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Package Spower updated to version 0.6.3 with previous version 0.6.2 dated 2026-05-05

Title: Power Analyses using Monte Carlo Simulations
Description: Provides a general purpose simulation-based power analysis API for routine and customized simulation experimental designs. The package focuses exclusively on Monte Carlo simulation experiment variants of (expected) prospective power analyses, criterion analyses, compromise analyses, sensitivity analyses, and a priori/post-hoc analyses. The default simulation experiment functions defined within the package provide stochastic variants of the power analysis subroutines in G*Power 3.1 (Faul, Erdfelder, Buchner, and Lang, 2009) <doi:10.3758/brm.41.4.1149>, along with various other parametric and non-parametric power analysis applications (e.g., mediation analyses) and support for Bayesian power analysis by way of Bayes factors or posterior probability evaluations. Additional functions for building empirical power curves, reanalyzing simulation information, and for increasing the precision of the resulting power estimates are also included, each of which utilize similar API structures. [...truncated...]
Author: Phil Chalmers [aut, cre]
Maintainer: Phil Chalmers <rphilip.chalmers@gmail.com>

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Package fiodata updated to version 0.2.0 with previous version 0.1.1 dated 2026-03-05

Title: Regional and Multi-Regional Input-Output Data
Description: Provides Regional (Brazil, 2020) and Multi-Regional (World, 2000) input-output matrices for R. This package serves as a data-only companion to the 'fio' package, facilitating input-output analysis by providing standardized R6 data objects.
Author: Alberson da Silva Miranda [aut, cre, cph] , Celso Bissoli Sessa [aut, dtc]
Maintainer: Alberson da Silva Miranda <albersonmiranda@hotmail.com>

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Package LLMR updated to version 0.6.4 with previous version 0.6.3 dated 2025-10-11

Title: Interface for Large Language Model APIs in R
Description: Provides a unified interface to large language models across multiple providers. Supports text generation, tidy data workflows, structured output with optional JSON Schema validation, XML-like tag extraction, and embeddings. Includes chat sessions, consistent error handling, and parallel batch tools.
Author: Ali Sanaei [aut, cre]
Maintainer: Ali Sanaei <sanaei@uchicago.edu>

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Package bioLeak updated to version 0.3.8 with previous version 0.3.7 dated 2026-04-29

Title: Leakage-Safe Modeling and Auditing for Genomic and Clinical Data
Description: Prevents and detects information leakage in biomedical machine learning. Provides leakage-resistant split policies (subject-grouped, batch-blocked, study leave-out, time-ordered), guarded preprocessing (train-only imputation, normalization, filtering, feature selection), cross-validated fitting with common learners, permutation-gap auditing, batch and fold association tests, and duplicate detection.
Author: Selcuk Korkmaz [aut, cre]
Maintainer: Selcuk Korkmaz <selcukorkmaz@gmail.com>

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Package statgenHTP updated to version 1.0.9.2 with previous version 1.0.9.1 dated 2025-07-03

Title: High Throughput Phenotyping (HTP) Data Analysis
Description: Phenotypic analysis of data coming from high throughput phenotyping (HTP) platforms, including different types of outlier detection, spatial analysis, and parameter estimation. The package is being developed within the EPPN2020 project (<https://cordis.europa.eu/project/id/731013>). Some functions have been created to be used in conjunction with the R package 'asreml' for the 'ASReml' software, which can be obtained upon purchase from 'VSN' international (<https://vsni.co.uk/software/asreml-r/>).
Author: Emilie J Millet [aut] , Maria Xose Rodriguez Alvarez [aut] , Diana Marcela Perez Valencia [aut] , Isabelle Sanchez [aut], Nadine Hilgert [aut], Bart-Jan van Rossum [aut, cre] , Fred van Eeuwijk [aut] , Martin Boer [aut]
Maintainer: Bart-Jan van Rossum <bart-jan.vanrossum@wur.nl>

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Package ROpenCVLite updated to version 4.130.0 with previous version 4.110.0 dated 2025-05-05

Title: Helper Package for Installing 'OpenCV'
Description: Installs 'OpenCV' for use by other packages. 'OpenCV' <https://opencv.org/> is library of programming functions mainly aimed at real-time computer vision. This 'Lite' version installs the stable base version of 'OpenCV' and some of its experimental externally contributed modules. It does not provide R bindings directly.
Author: Simon Garnier [aut, cre, cph] , Muschelli John [ctb]
Maintainer: Simon Garnier <garnier@njit.edu>

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Package mpactr updated to version 0.3.3 with previous version 0.3.2 dated 2026-05-14

Title: Correction of Preprocessed MS Data
Description: An 'R' implementation of the 'python' program Metabolomics Peak Analysis Computational Tool ('MPACT') (Robert M. Samples, Sara P. Puckett, and Marcy J. Balunas (2023) <doi:10.1021/acs.analchem.2c04632>). Filters in the package serve to address common errors in tandem mass spectrometry preprocessing, including: (1) isotopic patterns that are incorrectly split during preprocessing, (2) features present in solvent blanks due to carryover between samples, (3) features whose abundance is greater than user-defined abundance threshold in a specific group of samples, for example media blanks, (4) ions that are inconsistent between technical replicates, and (5) in-source fragment ions created during ionization before fragmentation in the tandem mass spectrometry workflow.
Author: Allison Mason [aut] , Gregory Johnson [aut] , Patrick Schloss [aut, cre, cph]
Maintainer: Patrick Schloss <pschloss@umich.edu>

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Package ggpointless updated to version 0.3.0 with previous version 0.2.0 dated 2026-03-09

Title: Extra Geometries and Stats for 'ggplot2'
Description: A collection of layers for 'ggplot2'. Provides geoms built on linear and radial gradients from the 'grid' package, giving areas, bars, paths, rectangles, and ridgelines a fading or glowing visual effect. Also includes mathematically driven layers — catenary curves, Chaikin's corner-cutting smoothing (Chaikin, 1974, <doi:10.1016/0146-664X(74)90028-8>), and Fourier-series reconstruction — plus Lexis diagrams, isotype bar charts.
Author: Markus Doering [aut, cre, cph]
Maintainer: Markus Doering <m4rkus.doering@gmail.com>

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Package bayestestR updated to version 0.18.0 with previous version 0.17.0 dated 2025-08-29

Title: Understand and Describe Bayesian Models and Posterior Distributions
Description: Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.
Author: Dominique Makowski [aut, cre] , Daniel Luedecke [aut] , Mattan S. Ben-Shachar [aut] , Indrajeet Patil [aut] , Micah K. Wilson [aut] , Brenton M. Wiernik [aut] , Paul-Christian Buerkner [rev], Tristan Mahr [rev] , Henrik Singmann [ctb] , Quentin F. Gron [...truncated...]
Maintainer: Dominique Makowski <officialeasystats@gmail.com>

Diff between bayestestR versions 0.17.0 dated 2025-08-29 and 0.18.0 dated 2026-05-21

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Package tufte updated to version 0.15.0 with previous version 0.14.0 dated 2025-07-29

Title: Tufte's Styles for R Markdown Documents
Description: Provides R Markdown output formats to use Tufte styles for PDF and HTML output.
Author: Yihui Xie [aut] , Christophe Dervieux [ctb, cre] , JJ Allaire [aut], Andrzej Oles [ctb], Dave Liepmann [ctb] , Posit Software, PBC [cph, fnd]
Maintainer: Christophe Dervieux <cderv@posit.co>

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Package DSIR updated to version 0.7.0 with previous version 0.2.0 dated 2026-04-21

Title: Data Science Infrastructure for Global Health
Description: Supports global health data analysis, including a publication-ready 'ggplot2' theme, a 'flextable' defaults helper, a thin pie chart wrapper, built-in regional country-code datasets with a WHO region lookup helper, a geometric mean function for indicator aggregation, and convenience clients for the World Health Organization Global Health Observatory (GHO) OData API <https://ghoapi.azureedge.net/api/> and the United Nations Sustainable Development Goals (SDG) API <https://unstats.un.org/SDGAPI/swagger/>.
Author: Shanlong Ding [aut, cre]
Maintainer: Shanlong Ding <dings@who.int>

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More information about DSIR at CRAN
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Package comexr updated to version 0.3.0 with previous version 0.2.1 dated 2026-03-17

Title: Client for the Brazilian Foreign Trade Statistics API ('ComexStat')
Description: Interface to the 'ComexStat' API <https://comexstat.mdic.gov.br/> from the Brazilian Ministry of Development, Industry, Trade and Services (MDIC). Provides access to detailed export and import data, including general trade statistics (1997-present), city-level data, historical data (1989-1996), and auxiliary tables with product codes (NCM - Nomenclatura Comum do Mercosul, NBM - Nomenclatura Brasileira de Mercadorias, HS - Harmonized System), countries, economic classifications (CGCE - Classificacao por Grandes Categorias Economicas, SITC - Standard International Trade Classification, ISIC - International Standard Industrial Classification), and other categories. Uses only 'httr2' for HTTP requests and 'cli' for console messages.
Author: Andre Leite [aut, cre], Marcos Wasilew [aut], Hugo Vasconcelos [aut], Carlos Amorin [aut], Diogo Bezerra [aut]
Maintainer: Andre Leite <leite@castlab.org>

Diff between comexr versions 0.2.1 dated 2026-03-17 and 0.3.0 dated 2026-05-21

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Package fuzzySim updated to version 4.54 with previous version 4.50 dated 2026-03-28

Title: Fuzzy Similarity in Species Distributions
Description: Functions to compute fuzzy versions of species occurrence patterns based on presence-absence data (including inverse distance interpolation, trend surface analysis, and prevalence-independent favourability obtained from probability of presence), as well as pair-wise fuzzy similarity (based on fuzzy logic versions of commonly used similarity indices) among those occurrence patterns. Includes also functions for model consensus and comparison (overlap and fuzzy similarity, fuzzy loss, fuzzy gain), and for data preparation, such as obtaining unique abbreviations of species names, defining the background region, cleaning and gridding (thinning) point occurrence data onto raster maps, selecting among (pseudo)absences to address survey bias, converting species lists (long format) to presence-absence tables (wide format), transposing part of a data frame, selecting relevant variables for models, assessing the false discovery rate, or analysing and dealing with multicollinearity. Initially desc [...truncated...]
Author: A. Marcia Barbosa [aut], Alba Estrada [ctb], Paul Melloy [ctb], Jose Carlos Guerrero [fnd], A. Marcia Barbosa [cre]
Maintainer: A. Marcia Barbosa <ana.marcia.barbosa@gmail.com>

Diff between fuzzySim versions 4.50 dated 2026-03-28 and 4.54 dated 2026-05-21

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Package ecorest updated to version 2.0.3 with previous version 2.0.2 dated 2026-03-30

Title: Conducts Analyses Informing Ecosystem Restoration Decisions
Description: Three sets of data and functions for informing ecosystem restoration decisions, particularly in the context of the U.S. Army Corps of Engineers. First, model parameters are compiled as a data set and associated metadata for over 300 habitat suitability models developed by the U.S. Fish and Wildlife Service (USFWS 1980, <https://www.fws.gov/policy-library/870fw1>). Second, functions for conducting habitat suitability analyses both for the models described above as well as generic user-specified model parameterizations. Third, a suite of decision support tools for conducting cost-effectiveness and incremental cost analyses (Robinson et al. 1995, IWR Report 95-R-1, U.S. Army Corps of Engineers).
Author: S. Kyle McKay [aut, cre] , Darixa D. Hernandez-Abrams [aut], Kiara C. Cushway [aut]
Maintainer: S. Kyle McKay <skmckay@gmail.com>

Diff between ecorest versions 2.0.2 dated 2026-03-30 and 2.0.3 dated 2026-05-21

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Package spant updated to version 4.1.0 with previous version 4.0.0 dated 2026-05-08

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>

Diff between spant versions 4.0.0 dated 2026-05-08 and 4.1.0 dated 2026-05-21

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New package scindex with initial version 0.1.0
Package: scindex
Title: Strategic Convergence Index for Inter-Rater Reliability
Version: 0.1.0
Description: Inter-rater reliability analysis for binary classification tasks involving two or more raters within a signal detection-theoretic framework. User-supplied rating data are standardised into a common long-format structure. The package automatically computes Cohen's kappa for two raters and Fleiss' kappa for multiple raters. When ground-truth labels are available, rater-specific hit rates, false-alarm rates, sensitivity, specificity, and decision thresholds are estimated from observed classification responses using standard signal detection-theoretic transformations (DeCarlo, 1998) <doi:10.1037/1082-989X.3.2.186>. The package implements the Strategic Convergence Index (SCI; Gianeselli, 2026) <doi:10.1177/00131644261417643>, defined as SCI = 1 - [Var(t_i) / Var_max], where Var(t_i) denotes the variance of rater-specific decision thresholds and Var_max denotes the reference variance under maximal threshold dispersion. SCI quantifies convergence in rater decision criteria beyond [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
LazyData: true
NeedsCompilation: no
Packaged: 2026-05-18 13:05:50 UTC; irene
Author: Irene Gianeselli [aut, cre]
Maintainer: Irene Gianeselli <irene.gianeselli@unibz.it>
Repository: CRAN
Date/Publication: 2026-05-21 13:40:02 UTC

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New package hespdiv with initial version 1.2.10
Package: hespdiv
Title: Hierarchical Spatial Data Subdivision into Topologically Contiguous Units
Version: 1.2.10
Maintainer: Liudas Daumantas <liudas.daumantas@chgf.vu.lt>
Description: Implementation of the HespDiv framework for hierarchical spatial subdivision of geographical occurrence data. The main function hespdiv() performs iterative spatially constrained subdivision of a study area to identify topologically contiguous clusters in geographic space using user-defined or preset subdivision methods. Additional functions provide tools for analysing subdivision results, visualizing hierarchical spatial structures, and evaluating robustness through sensitivity analyses and statistical testing. Some examples use the optional HDData data package, which is available from GitHub at Liudas-Dau/hespdiv_data. The methodology is described in Daumantas and Spiridonov (2024) <doi:10.1111/pala.12702>.
License: GPL-3
Encoding: UTF-8
OS_type: windows
LazyData: true
URL: https://doi.org/10.1111/pala.12702, https://github.com/Liudas-Dau/hespdiv, https://github.com/Liudas-Dau/hespdiv_data
Imports: pracma, DescTools, ggplot2, viridis, ggrepel, grDevices, RColorBrewer, rgl, scales, graphics, igraph, gridExtra, grid, gridGraphics, stats, magick, future.apply, future, rlang
Suggests: HDData
Depends: R (>= 4.0)
NeedsCompilation: yes
Packaged: 2026-05-18 07:22:53 UTC; liuda
Author: Liudas Daumantas [aut, cre], Andrej Spiridonov [aut], Joseph O'Rourke [ctb, cph] , Min Xu [ctb]
Repository: CRAN
Date/Publication: 2026-05-21 13:10:02 UTC

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Package hanyupinyin updated to version 0.1.3 with previous version 0.1.1 dated 2026-04-22

Title: Convert Chinese Characters into Hanyu Pinyin
Description: Convert Chinese characters into Hanyu Pinyin (the official romanization system for Standard Chinese) with support for tones, toneless output, initials, URL slugs, and valid R variable names. The package was inspired by the now-orphaned CRAN package 'pinyin' (archived in April 2026 after the maintainer became unreachable). 'hanyupinyin' is a ground-up rewrite using the authoritative Unicode Unihan database, a vectorized engine, and modern R practices. Dictionary data are derived from the Unicode Unihan Database (Unicode Consortium, 2025) <https://www.unicode.org/reports/tr38/>.
Author: Haoran Cui [aut, cre]
Maintainer: Haoran Cui <hao.ran.cui@ktstat.com>

Diff between hanyupinyin versions 0.1.1 dated 2026-04-22 and 0.1.3 dated 2026-05-21

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New package venny with initial version 0.0.2
Package: venny
Title: Venn Diagram
Version: 0.0.2
Description: Generate Venn plots, summary tables, and ellipse paths for polygon clipping. Provides direct access to subsets of interest and offers flexible customization of Venn diagrams. Summary tables are also available when Venn diagram visualization is not suitable.
License: MIT + file LICENSE
Encoding: UTF-8
Imports: ggplot2, polyclip
Depends: R (>= 4.1)
LazyData: true
Suggests: tidyr, dplyr, BiocManager, org.At.tair.db, DESeq2, clusterProfiler, testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2026-05-18 02:17:01 UTC; ABRC
Author: Joon-Keat Lai [aut, cre, cph]
Maintainer: Joon-Keat Lai <p10911004@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-21 12:30:02 UTC

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Package tidyBdE updated to version 0.6.1 with previous version 0.6.0 dated 2026-03-23

Title: Retrieve Data from 'Banco de España'
Description: Tools for retrieving time series data from 'Banco de España' ('BdE') as 'tibble' objects. 'Banco de España' is the national central bank and, within the framework of the Single Supervisory Mechanism ('SSM'), the supervisor of the Spanish banking system alongside the European Central Bank. This package is not sponsored, endorsed or administered by 'Banco de España'.
Author: Diego H. Herrero [aut, cre, cph]
Maintainer: Diego H. Herrero <dev.dieghernan@gmail.com>

Diff between tidyBdE versions 0.6.0 dated 2026-03-23 and 0.6.1 dated 2026-05-21

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New package smriti with initial version 0.1.0
Package: smriti
Title: Automated Routing Engine for Longitudinal Missing Data
Version: 0.1.0
Description: An automated routing engine for longitudinal missing data. It utilizes a Lagrange-constrained Random Forest based on sample size, missingness rate, and skew to preserve structural variance.
License: MIT + file LICENSE
SystemRequirements: C++17
Encoding: UTF-8
VignetteBuilder: knitr
Imports: Rcpp (>= 1.0.0), missForest, MASS
Suggests: lavaan, ggplot2, tidyr, dplyr, knitr, rmarkdown
LinkingTo: Rcpp, RcppArmadillo
NeedsCompilation: yes
Packaged: 2026-05-17 22:06:44 UTC; xguo
Author: Xiyuan Guo [aut, cre]
Maintainer: Xiyuan Guo <tommyguo039@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-21 12:30:08 UTC

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New package REDCapSync with initial version 0.1.0
Package: REDCapSync
Title: Encapsulated 'REDCap' Projects for Synchronized Data Pipelines
Version: 0.1.0
Description: Wraps dozens of 'REDCap' API endpoints into a standardized R6 object. Research Electronic Data Capture ('REDCap') is a survey and database web application software maintained by Vanderbilt University. It has a robust application programming interface (API) utilized by several R packages. 'REDCapSync' uses 'redcapAPI' and 'REDCapR' behind-the-scenes to retrieve all metadata, data, and log details for a project. To minimize unnecessary server calls, the interim 'REDCap' log is analyzed and used to only update necessary records. Furthermore, the user can define custom datasets that save to a directory. Those datasets continue to refresh when projects are synced. Having a secure, standardized, API-efficient, project-agnostic R object for 'REDCap' projects, streamlines downstream use in scripts, functions, and shiny applications.
License: GPL (>= 3)
URL: https://github.com/thecodingdocs/REDCapSync, https://thecodingdocs.github.io/REDCapSync/
BugReports: https://github.com/thecodingdocs/REDCapSync/issues
Depends: R (>= 4.1)
Imports: checkmate, cli, dplyr, hoardr, lubridate, openxlsx, R6, readxl, redcapAPI, REDCapR, skimr, stats, stringr, utils
Suggests: keyring, knitr, listviewer, rmarkdown, spelling, testthat (>= 3.3.0), withr
VignetteBuilder: knitr
Encoding: UTF-8
Language: en-US
NeedsCompilation: no
Packaged: 2026-05-18 03:19:43 UTC; brandonrose
Author: Brandon Rose [cre, aut, cph] , Natalie Goulett [ctb]
Maintainer: Brandon Rose <thecodingdocs@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-21 12:40:02 UTC

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Package nanotime updated to version 0.3.15 with previous version 0.3.14 dated 2026-04-22

Title: Nanosecond-Resolution Time Support for R
Description: Full 64-bit resolution date and time functionality with nanosecond granularity is provided, with easy transition to and from the standard 'POSIXct' type. Three additional classes offer interval, period and duration functionality for nanosecond-resolution timestamps.
Author: Dirk Eddelbuettel [aut, cre] , Leonardo Silvestri [aut]
Maintainer: Dirk Eddelbuettel <edd@debian.org>

Diff between nanotime versions 0.3.14 dated 2026-04-22 and 0.3.15 dated 2026-05-21

 ChangeLog          |   24 ++++++++++++++++++++----
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Package lpcde updated to version 1.0.0 with previous version 0.1.6 dated 2025-02-25

Title: Boundary Adaptive Local Polynomial Conditional Density Estimator
Description: Tools for estimation and inference of conditional densities, derivatives and functions. This is the companion software for Cattaneo, Chandak, Jansson and Ma (2024) <doi:10.3150/23-BEJ1711>.
Author: Matias D. Cattaneo [aut, cre], Rajita Chandak [aut], Michael Jansson [aut], Xinwei Ma [aut]
Maintainer: Matias D. Cattaneo <matias.d.cattaneo@gmail.com>

Diff between lpcde versions 0.1.6 dated 2025-02-25 and 1.0.0 dated 2026-05-21

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Package rasterpic updated to version 0.5.0 with previous version 0.4.0 dated 2026-03-21

Title: Convert Digital Images into 'SpatRaster' Objects
Description: Create 'SpatRaster' objects, as defined by the 'terra' package, from digital images using a spatial object as a geographic reference. Supported inputs include objects from the 'sf', 'terra' and 'stars' packages. The main function is an S3 generic, so other packages can provide methods for additional spatial classes.
Author: Diego Hernangomez [aut, cre, cph]
Maintainer: Diego Hernangomez <diego.hernangomezherrero@gmail.com>

Diff between rasterpic versions 0.4.0 dated 2026-03-21 and 0.5.0 dated 2026-05-21

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Package CalibrateSSB updated to version 1.4.0 with previous version 1.3.0 dated 2020-08-04

Title: Weighting and Estimation for Panel Data with Non-Response
Description: Functions to calculate weights, estimates of changes and corresponding variance estimates for panel data with non-response. Partially overlapping samples are handled. Initially, weights are calculated by linear calibration. By default, the 'survey' package is used for this purpose. It is also possible to use 'ReGenesees', which can be installed from <https://github.com/DiegoZardetto/ReGenesees>. Variances of linear combinations (changes and averages) and ratios are calculated from a covariance matrix based on residuals according to the calibration model. The methodology was presented at the conference, The Use of R in Official Statistics, and is described in Langsrud (2016) <http://www.revistadestatistica.ro/wp-content/uploads/2016/06/RRS2_2016_A021.pdf>.
Author: Oeyvind Langsrud [aut, cre]
Maintainer: Oeyvind Langsrud <oyl@ssb.no>

Diff between CalibrateSSB versions 1.3.0 dated 2020-08-04 and 1.4.0 dated 2026-05-21

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Package seminrExtras updated to version 1.0.1 with previous version 1.0.0 dated 2026-04-29

Title: Conduct Additional Modeling and Analysis for 'seminr'
Description: Supplementary tools for evaluating and validating partial least squares structural equation models estimated with 'seminr'. Provides methods for predictive model assessment, importance-performance analysis with necessary condition testing, overfitting diagnostics, measurement model verification, mediator contribution analysis, unobserved heterogeneity detection via latent class and prediction-oriented segmentation, and congruence coefficient testing. All functions accept estimated 'seminr' model objects and return results with print, summary, and plot methods.
Author: Soumya Ray [aut, ths], Nicholas Patrick Danks [aut, cre]
Maintainer: Nicholas Patrick Danks <nicholasdanks@hotmail.com>

Diff between seminrExtras versions 1.0.0 dated 2026-04-29 and 1.0.1 dated 2026-05-21

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Package rtpcr updated to version 2.1.8 with previous version 2.1.7 dated 2026-04-13

Title: qPCR Data Analysis
Description: Tools for qPCR data analysis using Delta Ct and Delta Delta Ct methods, including t-test, Wilcoxon-test, ANOVA models, and publication-ready visualizations. The package supports multiple target, and multiple reference genes, and uses a calculation framework adopted from Ganger et al. (2017) <doi:10.1186/s12859-017-1949-5> and Taylor et al. (2019) <doi:10.1016/j.tibtech.2018.12.002>, covering both the Livak and Pfaffl methods.
Author: Ghader Mirzaghaderi [aut, cre, cph]
Maintainer: Ghader Mirzaghaderi <mirzaghaderi@gmail.com>

Diff between rtpcr versions 2.1.7 dated 2026-04-13 and 2.1.8 dated 2026-05-21

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New package rollshap with initial version 1.0.1
Package: rollshap
Title: Rolling Shapley Values
Version: 1.0.1
Description: Analytical computation of rolling and expanding Shapley values for time-series data. The 'rollshap' package decomposes the coefficient of determination (R-squared) of a linear regression into nonnegative contributions from each explanatory variable using the Shapley value from cooperative game theory (Shapley, 1953, <doi:10.1515/9781400881970-018>). For each window, the exact Shapley value is computed by fitting all subsets of the explanatory variables and averaging the marginal contribution to R-squared across all orderings, which returns an order-invariant attribution that sums to the full-model R-squared. Use cases include variable importance, factor attribution, and feature selection in time-series regression. The package supports rolling and expanding windows, weights, and handling of missing values via 'min_obs', 'complete_obs', and 'na_restore' arguments. The implementation uses the online and offline algorithms from the 'roll' package to compute rolling and expanding cros [...truncated...]
License: GPL (>= 2)
URL: https://github.com/jasonjfoster/rollshap
BugReports: https://github.com/jasonjfoster/rollshap/issues
Depends: R (>= 3.0.2)
Imports: Rcpp, RcppParallel
LinkingTo: Rcpp, RcppArmadillo, RcppParallel, roll (>= 1.1.7)
SystemRequirements: GNU make
Encoding: UTF-8
Suggests: covr, testthat, zoo, relaimpo, roll
NeedsCompilation: yes
Packaged: 2026-05-17 12:13:20 UTC; jason
Author: Jason Foster [aut, cre]
Maintainer: Jason Foster <jason.j.foster@gmail.com>
Repository: CRAN
Date/Publication: 2026-05-21 09:10:02 UTC

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New package rextor with initial version 1.1.0
Package: rextor
Title: Prepare 'WEXTOR' Data
Version: 1.1.0
Depends: R (>= 4.1.0)
Description: Facilitate data preparation for data collected on 'WEXTOR' <https://wextor.eu>, created by Reips and Neuhaus (2002) <doi:10.3758/bf03195449>. Perform plausibility and other checks and make use of cool color palettes and themes for data visualization.
License: GPL (>= 3)
Date: 2026-05-06
Encoding: UTF-8
Imports: dplyr, readr, ggplot2
Suggests: knitr, rmarkdown, rlang, scales, tibble
VignetteBuilder: knitr
URL: https://iscience-kn.github.io/rextor/
NeedsCompilation: no
Packaged: 2026-05-17 15:51:44 UTC; PCUser
Author: Annika Tave Overlander [aut, cre] , Ulf-Dietrich Reips [ths, cph]
Maintainer: Annika Tave Overlander <annika-tave.overlander@uni.kn>
Repository: CRAN
Date/Publication: 2026-05-21 09:20:07 UTC

More information about rextor at CRAN
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Package morpheus readmission to version 1.0-5 with previous version 1.0-4 dated 2023-02-09

Title: Estimate Parameters of Mixtures of Logistic Regressions
Description: Mixture of logistic regressions parameters (H)estimation with (U)spectral methods. The main methods take d-dimensional inputs and a vector of binary outputs, and return parameters according to the GLMs mixture model (General Linear Model). For more details see chapter 3 in the PhD thesis of Mor-Absa Loum: <https://theses.fr/s156435>, available here <https://theses.hal.science/tel-01877796/document>.
Author: Benjamin Auder [aut, cre], Mor-Absa Loum [aut]
Maintainer: Benjamin Auder <benjamin.auder@universite-paris-saclay.fr>

This is a re-admission after prior archival of version 1.0-4 dated 2023-02-09

Diff between morpheus versions 1.0-4 dated 2023-02-09 and 1.0-5 dated 2026-05-21

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Package MMRcaseselection readmission to version 0.2.0 with previous version 0.1.0 dated 2020-06-03

Title: Case Classification and Selection Based on Regression Results
Description: Researchers doing a mixed-methods analysis (nested analysis as developed by Lieberman (2005) <doi:10.1017/S0003055405051762>) can use the package for the classification of cases and case selection using results of a linear regression. One can designate cases as typical, deviant, extreme and pathway case and use different case selection strategies for the choice of a case belonging to one of these types.
Author: Ingo Rohlfing [aut, cre]
Maintainer: Ingo Rohlfing <ingo.rohlfing@uni-passau.de>

This is a re-admission after prior archival of version 0.1.0 dated 2020-06-03

Diff between MMRcaseselection versions 0.1.0 dated 2020-06-03 and 0.2.0 dated 2026-05-21

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Package insight updated to version 1.5.1 with previous version 1.5.0 dated 2026-04-14

Title: Easy Access to Model Information for Various Model Objects
Description: A tool to provide an easy, intuitive and consistent access to information contained in various R models, like model formulas, model terms, information about random effects, data that was used to fit the model or data from response variables. 'insight' mainly revolves around two types of functions: Functions that find (the names of) information, starting with 'find_', and functions that get the underlying data, starting with 'get_'. The package has a consistent syntax and works with many different model objects, where otherwise functions to access these information are missing.
Author: Daniel Luedecke [aut, cre] , Dominique Makowski [aut, ctb] , Indrajeet Patil [aut, ctb] , Philip Waggoner [aut, ctb] , Mattan S. Ben-Shachar [aut, ctb] , Brenton M. Wiernik [aut, ctb] , Vincent Arel-Bundock [aut, ctb] , Etienne Bacher [aut, ctb] , Ale [...truncated...]
Maintainer: Daniel Luedecke <officialeasystats@gmail.com>

Diff between insight versions 1.5.0 dated 2026-04-14 and 1.5.1 dated 2026-05-21

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More information about insight at CRAN
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Package cvcqv readmission to version 1.0.3 with previous version 1.0.0 dated 2019-08-06

Title: Coefficient of Variation (CV) with Confidence Intervals (CI)
Description: Provides some easy-to-use functions and classes to calculate variability measures such as coefficient of variation with confidence intervals provided with all available methods. References are 'Panichkitkosolkul' (2013) <doi:10.1155/2013/324940>, 'Altunkaynak' & 'Gamgam' (2018) <doi:10.1080/03610918.2018.1435800>, 'Albatineh', 'Kibria', Wilcox & 'Zogheib' (2014) <doi:10.1080/02664763.2013.847405>.
Author: Maani Beigy [aut, cre]
Maintainer: Maani Beigy <manibeygi@gmail.com>

This is a re-admission after prior archival of version 1.0.0 dated 2019-08-06

Diff between cvcqv versions 1.0.0 dated 2019-08-06 and 1.0.3 dated 2026-05-21

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New package CopernicusDataspace with initial version 0.0.1
Package: CopernicusDataspace
Title: Search Download and Handle Data from the Copernicus Data Space Ecosystem
Version: 0.0.1
Description: The Copernicus Data Space Ecosystem, is an open ecosystem that provides free instant access to a wide range of data and services from the Copernicus Sentinel missions and more on our planet’s land, oceans and atmosphere. This package provides entry points to several APIs allowing users to access the data directly in R.
Depends: R (>= 4.1.0)
Imports: aws.s3, cli, dplyr, httr2, jsonlite, lubridate, memoise, methods, rlang, sf, stringr, tibble, tidyr, xml2
Suggests: clipr, jose, knitr, lwgeom, rmarkdown, rstudioapi, stars, testthat (>= 3.0.0)
License: GPL (>= 3)
Encoding: UTF-8
Language: en-GB
URL: https://github.com/pepijn-devries/CopernicusDataspace, https://pepijn-devries.github.io/CopernicusDataspace/
BugReports: https://github.com/pepijn-devries/CopernicusDataspace/issues
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2026-05-17 13:50:43 UTC; vries171
Author: Pepijn de Vries [aut, cre] , Alicia Hamer [rtm] , LVVN [fnd] , WMR [ctr]
Maintainer: Pepijn de Vries <pepijn.devries@outlook.com>
Repository: CRAN
Date/Publication: 2026-05-21 09:10:15 UTC

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Package admiralonco updated to version 1.4.1 with previous version 1.4.0 dated 2026-01-29

Title: Oncology Extension Package for ADaM in 'R' Asset Library
Description: Programming oncology specific Clinical Data Interchange Standards Consortium (CDISC) compliant Analysis Data Model (ADaM) datasets in 'R'. ADaM datasets are a mandatory part of any New Drug or Biologics License Application submitted to the United States Food and Drug Administration (FDA). Analysis derivations are implemented in accordance with the "Analysis Data Model Implementation Guide" (CDISC Analysis Data Model Team (2021), <https://www.cdisc.org/standards/foundational/adam>). The package is an extension package of the 'admiral' package.
Author: Stefan Bundfuss [aut, cre], Amit Jain [aut], Vinh Nguyen [aut], Olga Starostecka [aut], Kiran Peddamudium [aut], Tomoyuki Namai [aut], Ross Farrugia [aut], Yirong Cao [ctb], Ashwini Weber [ctb], F. Hoffmann-La Roche AG [cph, fnd], GlaxoSmithKline LLC [...truncated...]
Maintainer: Stefan Bundfuss <stefan.bundfuss@external.roche.com>

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Package yahoofinancer updated to version 0.5.0 with previous version 0.4.0 dated 2024-11-14

Title: Fetch Data from Yahoo Finance API
Description: Obtain historical and near real time data related to stocks, index and currencies from the Yahoo Finance API. This package is community maintained and is not officially supported by 'Yahoo'. The accuracy of data is only as correct as provided on <https://finance.yahoo.com/>.
Author: Aravind Hebbali [aut, cre]
Maintainer: Aravind Hebbali <hebbali.aravind@gmail.com>

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Package ksformat updated to version 0.7.1 with previous version 0.4.2 dated 2026-03-28

Title: 'SAS'-Style 'PROC FORMAT' for R
Description: Provides 'SAS' 'PROC FORMAT'-like functionality for creating and applying value formats in R. Supports discrete and range-based mapping of values to labels, reverse formatting (invalue), date/time/datetime formatting with built-in 'SAS' format names, multi-label formats, expression labels evaluated at apply-time, case-insensitive matching, import/export of format definitions, and proper handling of missing values (NA, NULL, NaN).
Author: Vladimir Larchenko [aut, cre], Igor Aleschenkov [aut]
Maintainer: Vladimir Larchenko <vladimir.larchenko@keystatsolutions.com>

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Package EDOtrans updated to version 0.3.5 with previous version 0.2.5 dated 2024-04-14

Title: Euclidean Distance-Optimized Data Transformation
Description: A data transformation method which takes into account the special property of scale non-invariance with a breakpoint at 1 of the Euclidean distance.
Author: Jorn Lotsch [aut, cre] , Alfred Ultsch [aut]
Maintainer: Jorn Lotsch <j.lotsch@em.uni-frankfurt.de>

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Package SEQTaRget updated to version 1.4.2 with previous version 1.4.1 dated 2026-03-31

Title: Sequential Trial Emulation
Description: Implementation of sequential trial emulation for the analysis of observational databases. The 'SEQTaRget' software accommodates time-varying treatments and confounders, as well as binary and failure time outcomes. 'SEQTaRget' allows to compare both static and dynamic strategies, can be used to estimate observational analogs of intention-to-treat and per-protocol effects, and can adjust for potential selection bias induced by losses-to-follow-up. (Paper to come).
Author: Ryan O'Dea [aut, cre] , Alejandro Szmulewicz [aut] , Tom Palmer [aut] , Paul Madley-Dowd [aut] , Miguel Hernan [aut] , The President and Fellows of Harvard College [cph]
Maintainer: Ryan O'Dea <ryan.odea@psi.ch>

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Package scf updated to version 1.0.10 with previous version 1.0.8 dated 2026-05-14

Title: Analyzing the Survey of Consumer Finances
Description: Analyze public-use micro data from the Survey of Consumer Finances. Provides tools to download prepared data files, construct replicate-weighted multiply imputed survey designs, compute descriptive statistics and model estimates, and produce plots and tables. Methods follow design-based inference for complex surveys and pooling across multiple imputations. See the package website and the code book for background.
Author: Joseph Cohen [aut, cre]
Maintainer: Joseph Cohen <joseph.cohen@qc.cuny.edu>

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Package retroharmonize readmission to version 0.2.8 with previous version 0.2.7 dated 2026-01-14

Title: Ex Post Survey Data Harmonization
Description: Assist in reproducible retrospective (ex-post) harmonization of data, particularly individual level survey data, by providing tools for organizing metadata, standardizing the coding of variables, and variable names and value labels, including missing values, and documenting the data transformations, with the help of comprehensive s3 classes.
Author: Daniel Antal [aut, cre] , Marta Kolczynska [ctb]
Maintainer: Daniel Antal <daniel.antal@dataobservatory.eu>

This is a re-admission after prior archival of version 0.2.7 dated 2026-01-14

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Package rerddapUtils updated to version 1.0.1 with previous version 1.0.0 dated 2026-05-19

Title: Miscellaneous Utilities for 'rerddap'
Description: The 'rerddapUtils' package is an 'R' package that is a set of four main functions designed to work with and extend the 'rerddap' package. These functions includes one for restricting by season, one for splitting large requests, and two for working with projected datasets. There are also two utility functions that provide estimates of the size of a proposed 'rerddap::griddap()' request.
Author: Roy Mendelssohn [aut, cre]
Maintainer: Roy Mendelssohn <roy.mendelssohn@noaa.gov>

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Package multimediate updated to version 0.1.6 with previous version 0.1.4 dated 2025-07-14

Title: Causal Mediation Analysis in Presence of Multiple Mediators Uncausally Related
Description: Estimates key quantities in causal mediation analysis - including average causal mediation effects (indirect effects), average direct effects, total effects, and proportions mediated - in the presence of multiple uncausally related mediators. Methods are described by Jerolon et al., (2021) <doi:10.1515/ijb-2019-0088> and extended to accommodate survival outcomes as described by Domingo-Relloso et al., (2024) <doi:10.1101/2024.02.16.24302923>.
Author: Allan Jerolon [aut], Arce Domingo-Relloso [aut], Samara Kiihl [cre, aut], Maria Tellez-Plaza [aut]
Maintainer: Samara Kiihl <samarak@unicamp.br>

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Package lpdensity updated to version 3.0 with previous version 2.5 dated 2024-10-06

Title: Local Polynomial Density Estimation and Inference
Description: Implements local polynomial distribution and density methods for point estimation, inference and bandwidth selection, documented in Cattaneo, Jansson and Ma (2020) <doi:10.1080/01621459.2019.1635480>, Cattaneo, Jansson and Ma (2022) <doi:10.18637/jss.v101.i02>, and Cattaneo, Jansson and Ma (2024) <doi:10.1016/j.jeconom.2021.01.006>. lpdensity() constructs local polynomial distribution and density estimators with robust bias-corrected inference, and lpbwdensity() implements data-driven bandwidth selection.
Author: Matias D. Cattaneo [aut, cre], Michael Jansson [aut], Xinwei Ma [aut]
Maintainer: Matias D. Cattaneo <matias.d.cattaneo@gmail.com>

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Package htrSPRanalysis readmission to version 0.1.3 with previous version 0.1.2 dated 2026-05-05

Title: Analysis of Surface Plasmon Resonance Data
Description: Analysis of Surface Plasmon Resonance (SPR) and Biolayer Interferometry data, with automations for high-throughput SPR. This version of the package fits the 1: 1 binding model, with and without bulkshift. It offers optional local or global Rmax fitting. The user must provide a sample sheet and a Carterra output file in Carterra's current format. There is a utility function to convert from Carterra's old output format. The user may run a custom pipeline or use the provided 'Runscript', which will produce a pdf file containing fitted Rmax, ka, kd and standard errors, a plot of the sensorgram and fits, and a plot of residuals. The script will also produce a .csv file with all of the relevant parameters for each spot on the SPR chip.
Author: Janice McCarthy Developer [aut, cre, cph], Kan Li Dev [aut], S. Moses Dennison [aut], Georgia D. Tomaras [aut]
Maintainer: Janice McCarthy Developer <janice.mccarthy@duke.edu>

This is a re-admission after prior archival of version 0.1.2 dated 2026-05-05

Diff between htrSPRanalysis versions 0.1.2 dated 2026-05-05 and 0.1.3 dated 2026-05-21

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Package ETDQualitizer updated to version 1.0.0 with previous version 0.9.0 dated 2025-09-09

Title: Automated Eye Tracking Data Quality Determination for Screen-Based Eye Trackers
Description: Compute common data quality metrics for accuracy, precision and data loss for screen-based eye trackers. The package supports gaze input in screen pixels or degrees and reports angular measures in degrees where appropriate. If you use this package, please cite Niehorster, D.C., Nyström, M., Hessels, R.S., Benjamins, J.S., Andersson, R., and Hooge, I.T.C. (2026). The fundamentals of eye tracking part 7: Determining data quality. Behavior Research Methods. <doi:10.3758/s13428-026-03039-4>.
Author: Diederick Niehorster [aut, cre, cph]
Maintainer: Diederick Niehorster <diederick_c.niehorster@humlab.lu.se>

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Package bayesianETAS readmission to version 2.0.0 with previous version 1.0.3 dated 2017-01-17

Title: Bayesian Estimation of the Temporal and Spatio-Temporal ETAS Models for Earthquake Occurrences
Description: The Epidemic Type Aftershock Sequence (ETAS) model is widely used for modelling and forecasting earthquake occurrences. This package implements Bayesian estimation routines for both the temporal and spatial ETAS model, allowing samples to be drawn from the full posterior distribution of the model parameters given an earthquake catalogue. The methods are described in Ross (2021) "Bayesian Estimation of the ETAS Model for Earthquake Occurrences" <doi:10.1785/0120200198>.
Author: Gordon J. Ross [aut, cre]
Maintainer: Gordon J. Ross <gordon@gordonjross.co.uk>

This is a re-admission after prior archival of version 1.0.3 dated 2017-01-17

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Package automatedRecLin updated to version 1.1.1 with previous version 1.1.0 dated 2026-05-08

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>

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Package bmgarch updated to version 2.1.0 with previous version 2.0.0 dated 2023-09-11

Title: Bayesian Multivariate GARCH Models
Description: Fit Bayesian multivariate GARCH models using 'Stan' for full Bayesian inference. Generate (weighted) forecasts for means, variances (volatility) and correlations. Currently DCC(P,Q), CCC(P,Q), pdBEKK(P,Q), and BEKK(P,Q) parameterizations are implemented, alongside a constant covariance baseline (that can be used for testing whether GARCH is warranted), based either on a multivariate gaussian normal or student-t distribution. DCC and CCC models are based on Engle (2002) <doi:10.1198/073500102288618487> and Bollerslev (1990). The BEKK parameterization follows Engle and Kroner (1995) <doi:10.1017/S0266466600009063> while the pdBEKK as well as the estimation approach for this package is described in Rast et al. (2020) <doi:10.31234/osf.io/j57pk>. The fitted models contain 'rstan' objects and can be examined with 'rstan' functions.
Author: Philippe Rast [aut, cre] , Stephen Martin [aut]
Maintainer: Philippe Rast <rast.ph@gmail.com>

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Package spatstat.sparse updated to version 3.2-0 with previous version 3.1-0 dated 2024-06-21

Title: Sparse Three-Dimensional Arrays and Linear Algebra Utilities
Description: Defines sparse three-dimensional arrays and supports standard operations on them. The package also includes utility functions for matrix calculations that are common in statistics, such as quadratic forms.
Author: Adrian Baddeley [aut, cre, cph] , Rolf Turner [aut, cph] , Ege Rubak [aut, cph]
Maintainer: Adrian Baddeley <Adrian.Baddeley@curtin.edu.au>

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Package ISwR updated to version 2.0-12 with previous version 2.0-11 dated 2025-10-23

Title: Introductory Statistics with R
Description: Data sets and scripts for text examples and exercises in P. Dalgaard (2008), `Introductory Statistics with R', 2nd ed., Springer Verlag, ISBN 978-0387790534.
Author: Peter Dalgaard [aut, cre]
Maintainer: Peter Dalgaard <pd.mes@cbs.dk>

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Package gkwdist updated to version 1.1.3 with previous version 1.1.2 dated 2026-01-08

Title: Generalized Kumaraswamy Distribution Family
Description: Implements the five-parameter Generalized Kumaraswamy ('gkw') distribution proposed by 'Carrasco, Ferrari and Cordeiro (2010)' <doi:10.48550/arXiv.1004.0911> and its seven nested sub-families for modeling bounded continuous data on the unit interval (0,1). The 'gkw' distribution extends the Kumaraswamy distribution described by Jones (2009) <doi:10.1016/j.stamet.2008.04.001>. Provides density, distribution, quantile, and random generation functions, along with analytical log-likelihood, gradient, and Hessian functions implemented in 'C++' via 'RcppArmadillo' for maximum computational efficiency. Suitable for modeling proportions, rates, percentages, and indices exhibiting complex features such as asymmetry, or heavy tails and other shapes not adequately captured by standard distributions like simple Beta or Kumaraswamy.
Author: Jose Evandeilton Lopes [aut, cre]
Maintainer: Jose Evandeilton Lopes <evandeilton@gmail.com>

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Package dplR updated to version 1.7.9 with previous version 1.7.8 dated 2025-01-30

Title: Dendrochronology Program Library in R
Description: Perform tree-ring analyses such as detrending, chronology building, and cross dating. Read and write standard file formats used in dendrochronology.
Author: Andy Bunn [aut, cph, cre, trl], Mikko Korpela [aut, cph, trl], Franco Biondi [aut, cph], Filipe Campelo [aut, cph], Stefan Klesse [aut, cph], Pierre Merian [aut, cph], Fares Qeadan [aut, cph], Christian Zang [aut, cph], Allan Buras [ctb], Alice Cecil [...truncated...]
Maintainer: Andy Bunn <bunna@wwu.edu>

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Package plotbb updated to version 0.1.2 with previous version 0.1.1 dated 2026-01-30

Title: Grammar of Graphics for 'base' Plot
Description: A grammar of graphics framework built on 'base' graphics. It provides a 'bbplot' object and a '+' operator to incrementally compose plots from data, aesthetic mappings and layers, then render them using the base plotting system. The package includes common geometric layers (points, lines, segments, bars, histograms, boxplots and tiles), scales for color and other aesthetics, legends, faceting, themes, and significance annotations.
Author: Guangchuang Yu [aut, cre, cph]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

Diff between plotbb versions 0.1.1 dated 2026-01-30 and 0.1.2 dated 2026-05-21

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More information about plotbb at CRAN
Permanent link

Package pandemonium updated to version 1.0.0 with previous version 0.2.4 dated 2025-11-03

Title: High Dimensional Analysis in Linked Spaces
Description: A 'shiny' GUI that performs high dimensional cluster analysis. This tool performs data preparation, clustering and visualisation within a dynamic GUI. With interactive methods allowing the user to change settings all without having to to leave the GUI. An earlier version of this package was described in Laa and Valencia (2022) <doi:10.1140/epjp/s13360-021-02310-1>.
Author: Gabriel McCoy [aut, cre] , Ursula Laa [aut] , German Valencia [aut]
Maintainer: Gabriel McCoy <gabe.mccoy02@gmail.com>

Diff between pandemonium versions 0.2.4 dated 2025-11-03 and 1.0.0 dated 2026-05-21

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More information about pandemonium at CRAN
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Package LikertMakeR updated to version 2.3.0 with previous version 2.0.0 dated 2026-03-23

Title: Synthesise and Correlate Likert Scale and Rating-Scale Data Based on Summary Statistics
Description: Generate and correlate synthetic Likert and rating-scale questionnaire responses with predefined means, standard deviations, Cronbach's Alpha, Factor Loading table, coefficients, and other summary statistics. It can be used to simulate Likert data, construct multi-item scales, generate correlation matrices, and create example survey datasets for teaching statistics, psychometrics, and methodological research. Worked examples and documentation are available in the package articles, accessible via the package website, <https://winzarh.github.io/LikertMakeR/>.
Author: Hume Winzar [cre, aut]
Maintainer: Hume Winzar <winzar@gmail.com>

Diff between LikertMakeR versions 2.0.0 dated 2026-03-23 and 2.3.0 dated 2026-05-21

 DESCRIPTION                          |   21 
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More information about LikertMakeR at CRAN
Permanent link


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