Mon, 01 Dec 2025

Package watcher updated to version 0.1.5 with previous version 0.1.4 dated 2025-07-16

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

Diff between watcher versions 0.1.4 dated 2025-07-16 and 0.1.5 dated 2025-12-01

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Package risk.assessr updated to version 3.0.1 with previous version 3.0.0 dated 2025-11-28

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>

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Package fastTS updated to version 1.0.3 with previous version 1.0.2 dated 2024-12-01

Title: Fast Time Series Modeling for Seasonal Series with Exogenous Variables
Description: An implementation of sparsity-ranked lasso and related methods for time series data. This methodology is especially useful for large time series with exogenous features and/or complex seasonality. Originally described in Peterson and Cavanaugh (2022) <doi:10.1007/s10182-021-00431-7> in the context of variable selection with interactions and/or polynomials, ranked sparsity is a philosophy with methods useful for variable selection in the presence of prior informational asymmetry. This situation exists for time series data with complex seasonality, as shown in Peterson and Cavanaugh (2024) <doi:10.1177/1471082X231225307>, which also describes this package in greater detail. The sparsity-ranked penalization methods for time series implemented in 'fastTS' can fit large/complex/high-frequency time series quickly, even with a high-dimensional exogenous feature set. The method is considerably faster than its competitors, while often producing more accurate predictions. Also includ [...truncated...]
Author: Ryan Andrew Peterson [aut, cre, cph]
Maintainer: Ryan Andrew Peterson <ryan-peterson@uiowa.edu>

Diff between fastTS versions 1.0.2 dated 2024-12-01 and 1.0.3 dated 2025-12-01

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Package algaeClassify updated to version 2.0.5 with previous version 2.0.4 dated 2025-05-14

Title: Tools to Query the 'Algaebase' Online Database, Standardize Phytoplankton Taxonomic Data, and Perform Functional Group Classifications
Description: Functions that facilitate the use of accepted taxonomic nomenclature, collection of functional trait data, and assignment of functional group classifications to phytoplankton species. Possible classifications include Morpho-functional group (MFG; Salmaso et al. 2015 <doi:10.1111/fwb.12520>) and CSR (Reynolds 1988; Functional morphology and the adaptive strategies of phytoplankton. In C.D. Sandgren (ed). Growth and reproductive strategies of freshwater phytoplankton, 388-433. Cambridge University Press, New York). Versions 2.0.0 and later includes new functions for querying the 'algaebase' online taxonomic database (www.algaebase.org), however these functions require a valid API key that must be acquired from the 'algaebase' administrators. Note that none of the 'algaeClassify' authors are affiliated with 'algaebase' in any way. Taxonomic names can also be checked against a variety of taxonomic databases using the 'Global Names Resolver' service via its API (<https://resolver.g [...truncated...]
Author: Vijay Patil [aut, cre], Torsten Seltmann [aut], Nico Salmaso [aut], Orlane Anneville [aut], Marc Lajeunesse [aut], Dietmar Straile [aut]
Maintainer: Vijay Patil <vij.patil@gmail.com>

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Package shinybrms updated to version 1.8.1 with previous version 1.8.0 dated 2022-08-05

Title: Graphical User Interface ('shiny' App) for 'brms'
Description: A graphical user interface (GUI) for fitting Bayesian regression models using the package 'brms' which in turn relies on 'Stan' (<https://mc-stan.org/>). The 'shinybrms' GUI is a 'shiny' app.
Author: Frank Weber [aut, cre] , Katja Ickstadt [ctb] , Änne Glass [ctb] , Thomas Park [ctb, cph] , Twitter, Inc. [ctb, cph] ), Google, LLC [ctb, cph]
Maintainer: Frank Weber <fweber144@protonmail.com>

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Package RWDataPlyr updated to version 0.6.5 with previous version 0.6.4 dated 2020-04-17

Title: Read and Manipulate Data from 'RiverWare'
Description: A tool to read and manipulate data generated from 'RiverWare'(TM) <https://www.riverware.org/> simulations. 'RiverWare' and 'RiverSMART' generate data in "rdf", "csv", and "nc" format. This package provides an interface to read, aggregate, and summarize data from one or more simulations in a 'dplyr' pipeline.
Author: Alan Butler [aut, cre], Cameron Bracken [aut]
Maintainer: Alan Butler <rabutler@usbr.gov>

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Package matrixprofiler updated to version 0.1.10 with previous version 0.1.9 dated 2023-01-26

Title: Matrix Profile for R
Description: This is the core functions needed by the 'tsmp' package. The low level and carefully checked mathematical functions are here. These are implementations of the Matrix Profile concept that was created by CS-UCR <http://www.cs.ucr.edu/~eamonn/MatrixProfile.html>.
Author: Francisco Bischoff [aut, cre] , Michael Yeh [res, ccp, ctb] , Diego Silva [res, ccp, ctb] , Yan Zhu [res, ccp, ctb] , Hoang Dau [res, ccp, ctb] , Michele Linardi [res, ccp, ctb]
Maintainer: Francisco Bischoff <fbischoff@med.up.pt>

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Package genie updated to version 1.0.6 with previous version 1.0.5 dated 2020-08-02

Title: Fast, Robust, and Outlier Resistant Hierarchical Clustering
Description: Includes the basic implementation of Genie - a hierarchical clustering algorithm that links two point groups in such a way that an inequity measure (namely, the Gini index) of the cluster sizes does not significantly increase above a given threshold. This method most often outperforms many other data segmentation approaches in terms of clustering quality as tested on a wide range of benchmark datasets. At the same time, Genie retains the high speed of the single linkage approach, therefore it is also suitable for analysing larger data sets. For more details see (Gagolewski et al. 2016 <DOI:10.1016/j.ins.2016.05.003>). For an even faster and more feature-rich implementation, including, amongst others, see the 'genieclust' package (Gagolewski, 2021 <DOI:10.1016/j.softx.2021.100722>).
Author: Marek Gagolewski [aut, cre, cph] , Maciej Bartoszuk [aut] , Anna Cena [aut]
Maintainer: Marek Gagolewski <marek@gagolewski.com>

Diff between genie versions 1.0.5 dated 2020-08-02 and 1.0.6 dated 2025-12-01

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Package mathjaxr updated to version 2.0-0 with previous version 1.8-0 dated 2025-04-30

Title: Using 'Mathjax' in Rd Files
Description: Provides 'MathJax' and macros to enable its use within Rd files for rendering equations in the HTML help files.
Author: Wolfgang Viechtbauer [aut, cre]
Maintainer: Wolfgang Viechtbauer <wvb@wvbauer.com>

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Package HAC updated to version 1.1-2 with previous version 1.1-1 dated 2024-09-16

Title: Estimation, Simulation and Visualization of Hierarchical Archimedean Copulae (HAC)
Description: Package provides the estimation of the structure and the parameters, sampling methods and structural plots of Hierarchical Archimedean Copulae (HAC).
Author: Ostap Okhrin [aut], Alexander Ristig [aut], Ankit Anil Chaudhari [cre]
Maintainer: Ankit Anil Chaudhari <ankit_anil.chaudhari@tu-dresden.de>

Diff between HAC versions 1.1-1 dated 2024-09-16 and 1.1-2 dated 2025-12-01

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Package xpose.xtras updated to version 0.1.2 with previous version 0.1.1 dated 2025-11-30

Title: Extra Functionality for the 'xpose' Package
Description: Adding some at-present missing functionality, or functions unlikely to be added to the base 'xpose' package. This includes some diagnostic plots that have been missing in translation from 'xpose4', but also some useful features that truly extend the capabilities of what can be done with 'xpose'. These extensions include the concept of a set of 'xpose' objects, and diagnostics for likelihood-based models.
Author: John Prybylski [aut, cre, cph]
Maintainer: John Prybylski <jprybylski@gmail.com>

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Package vegdata updated to version 1.9.15 with previous version 0.9.12 dated 2024-01-29

Title: Access Vegetation Databases and Treat Taxonomy
Description: Handling of vegetation data from different sources ( Turboveg 2.0 <https://www.synbiosys.alterra.nl/turboveg/>; the German national repository <https://www.vegetweb.de> and others. Taxonomic harmonization (given appropriate taxonomic lists, e.g. the Euro+Med list <https://eurosl.infinitenature.org>).
Author: Florian Jansen [aut, cre]
Maintainer: Florian Jansen <florian.jansen@uni-rostock.de>

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Package siera updated to version 0.5.5 with previous version 0.5.4 dated 2025-09-25

Title: Generate Analysis Results Programmes Using ARS Metadata
Description: Analysis Results Standard (ARS), a foundational standard by CDISC (Clinical Data Interchange Standards Consortium), provides a logical data model for metadata describing all components to calculate Analysis Results. <https://www.cdisc.org/standards/foundational/analysis-results-standard> Using 'siera' package, ARS metadata is ingested (JSON or Excel format), producing programmes to generate Analysis Results Datasets (ARDs).
Author: Malan Bosman [aut, cre], Clymb Clinical [cph, fnd]
Maintainer: Malan Bosman <malanbos@gmail.com>

Diff between siera versions 0.5.4 dated 2025-09-25 and 0.5.5 dated 2025-12-01

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More information about siera at CRAN
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Package sgapi updated to version 1.1.2 with previous version 1.1.1 dated 2025-11-17

Title: Aid Querying 'nomis' and 'Office for National Statistics Open Geography' APIs
Description: Facilitates extraction of geospatial data from the 'Office for National Statistics Open Geography' and 'nomis' Application Programming Interfaces (APIs). Simplifies process of querying 'nomis' datasets <https://www.nomisweb.co.uk/> and extracting desired datasets in dataframe format. Extracts area shapefiles at chosen resolution from 'Office for National Statistics Open Geography' <https://geoportal.statistics.gov.uk/>.
Author: Michael Stocks [aut, cre], Andrew Christy [aut], James Macpherson [aut], Hadyn Jenkins [aut], Crown Copyright [cph]
Maintainer: Michael Stocks <sgapi.orhub@gmail.com>

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Package rags2ridges updated to version 2.2.9 with previous version 2.2.8 dated 2025-08-29

Title: Ridge Estimation of Precision Matrices from High-Dimensional Data
Description: Proper L2-penalized maximum likelihood estimators for precision matrices and supporting functions to employ these estimators in a graphical modeling setting. For details, see Peeters, Bilgrau, & van Wieringen (2022) <doi:10.18637/jss.v102.i04> and associated publications.
Author: Carel F.W. Peeters [aut, cre, cph] , Anders Ellern Bilgrau [aut, cph] , Wessel N. van Wieringen [aut]
Maintainer: Carel F.W. Peeters <carel.peeters@wur.nl>

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Package parsnip updated to version 1.4.0 with previous version 1.3.3 dated 2025-08-31

Title: A Common API to Modeling and Analysis Functions
Description: A common interface is provided to allow users to specify a model without having to remember the different argument names across different functions or computational engines (e.g. 'R', 'Spark', 'Stan', 'H2O', etc).
Author: Max Kuhn [cre, aut] , Davis Vaughan [aut], Emil Hvitfeldt [ctb], Posit Software, PBC [cph, fnd]
Maintainer: Max Kuhn <max@posit.co>

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 parsnip-1.4.0/parsnip/man/details_mlp_keras.Rd                         |   18 
 parsnip-1.4.0/parsnip/man/details_mlp_nnet.Rd                          |   18 
 parsnip-1.4.0/parsnip/man/details_multinom_reg_brulee.Rd               |   15 
 parsnip-1.4.0/parsnip/man/details_multinom_reg_glmnet.Rd               |   16 
 parsnip-1.4.0/parsnip/man/details_multinom_reg_h2o.Rd                  |   15 
 parsnip-1.4.0/parsnip/man/details_multinom_reg_keras.Rd                |   15 
 parsnip-1.4.0/parsnip/man/details_multinom_reg_nnet.Rd                 |   16 
 parsnip-1.4.0/parsnip/man/details_multinom_reg_spark.Rd                |   15 
 parsnip-1.4.0/parsnip/man/details_naive_Bayes_h2o.Rd                   |   15 
 parsnip-1.4.0/parsnip/man/details_naive_Bayes_klaR.Rd                  |   16 
 parsnip-1.4.0/parsnip/man/details_naive_Bayes_naivebayes.Rd            |   15 
 parsnip-1.4.0/parsnip/man/details_nearest_neighbor_kknn.Rd             |   17 
 parsnip-1.4.0/parsnip/man/details_pls_mixOmics.Rd                      |   17 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_gee.Rd                   |   15 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_glm.Rd                   |   15 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_glmer.Rd                 |   15 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_glmnet.Rd                |   15 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_h2o.Rd                   |   15 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_hurdle.Rd                |   15 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_stan.Rd                  |   17 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_stan_glmer.Rd            |   16 
 parsnip-1.4.0/parsnip/man/details_poisson_reg_zeroinfl.Rd              |   15 
 parsnip-1.4.0/parsnip/man/details_proportional_hazards_glmnet.Rd       |   17 
 parsnip-1.4.0/parsnip/man/details_proportional_hazards_survival.Rd     |   16 
 parsnip-1.4.0/parsnip/man/details_rand_forest_aorsf.Rd                 |   21 
 parsnip-1.4.0/parsnip/man/details_rand_forest_grf.Rd                   |only
 parsnip-1.4.0/parsnip/man/details_rand_forest_h2o.Rd                   |   17 
 parsnip-1.4.0/parsnip/man/details_rand_forest_partykit.Rd              |   18 
 parsnip-1.4.0/parsnip/man/details_rand_forest_randomForest.Rd          |   18 
 parsnip-1.4.0/parsnip/man/details_rand_forest_ranger.Rd                |   20 
 parsnip-1.4.0/parsnip/man/details_rand_forest_spark.Rd                 |   16 
 parsnip-1.4.0/parsnip/man/details_rule_fit_h2o.Rd                      |   17 
 parsnip-1.4.0/parsnip/man/details_rule_fit_xrf.Rd                      |   16 
 parsnip-1.4.0/parsnip/man/details_survival_reg_flexsurv.Rd             |   18 
 parsnip-1.4.0/parsnip/man/details_survival_reg_flexsurvspline.Rd       |   18 
 parsnip-1.4.0/parsnip/man/details_survival_reg_survival.Rd             |   18 
 parsnip-1.4.0/parsnip/man/details_svm_linear_LiblineaR.Rd              |   17 
 parsnip-1.4.0/parsnip/man/details_svm_linear_kernlab.Rd                |   17 
 parsnip-1.4.0/parsnip/man/details_svm_poly_kernlab.Rd                  |   17 
 parsnip-1.4.0/parsnip/man/details_svm_rbf_kernlab.Rd                   |   23 
 parsnip-1.4.0/parsnip/man/doc-tools.Rd                                 |    2 
 parsnip-1.4.0/parsnip/man/dot-get_prediction_column_names.Rd           |    2 
 parsnip-1.4.0/parsnip/man/dot-model_param_name_key.Rd                  |    2 
 parsnip-1.4.0/parsnip/man/extract-parsnip.Rd                           |    2 
 parsnip-1.4.0/parsnip/man/fit.Rd                                       |    2 
 parsnip-1.4.0/parsnip/man/fit_control.Rd                               |    2 
 parsnip-1.4.0/parsnip/man/gen_additive_mod.Rd                          |    2 
 parsnip-1.4.0/parsnip/man/get_model_env.Rd                             |    2 
 parsnip-1.4.0/parsnip/man/glm_grouped.Rd                               |    2 
 parsnip-1.4.0/parsnip/man/has_multi_predict.Rd                         |    2 
 parsnip-1.4.0/parsnip/man/linear_reg.Rd                                |    2 
 parsnip-1.4.0/parsnip/man/logistic_reg.Rd                              |    2 
 parsnip-1.4.0/parsnip/man/mars.Rd                                      |    2 
 parsnip-1.4.0/parsnip/man/max_mtry_formula.Rd                          |    2 
 parsnip-1.4.0/parsnip/man/min_cols.Rd                                  |    2 
 parsnip-1.4.0/parsnip/man/mlp.Rd                                       |    2 
 parsnip-1.4.0/parsnip/man/model_db.Rd                                  |    2 
 parsnip-1.4.0/parsnip/man/model_fit.Rd                                 |    2 
 parsnip-1.4.0/parsnip/man/multinom_reg.Rd                              |    2 
 parsnip-1.4.0/parsnip/man/nearest_neighbor.Rd                          |    2 
 parsnip-1.4.0/parsnip/man/null_model.Rd                                |   29 
 parsnip-1.4.0/parsnip/man/nullmodel.Rd                                 |    2 
 parsnip-1.4.0/parsnip/man/parsnip-package.Rd                           |    2 
 parsnip-1.4.0/parsnip/man/parsnip_update.Rd                            |   10 
 parsnip-1.4.0/parsnip/man/predict.model_fit.Rd                         |    2 
 parsnip-1.4.0/parsnip/man/proportional_hazards.Rd                      |    2 
 parsnip-1.4.0/parsnip/man/rand_forest.Rd                               |    2 
 parsnip-1.4.0/parsnip/man/repair_call.Rd                               |    2 
 parsnip-1.4.0/parsnip/man/required_pkgs.model_spec.Rd                  |    2 
 parsnip-1.4.0/parsnip/man/rmd/C5_rules_C5.0.Rmd                        |   10 
 parsnip-1.4.0/parsnip/man/rmd/C5_rules_C5.0.md                         |   16 
 parsnip-1.4.0/parsnip/man/rmd/aaa.md                                   |only
 parsnip-1.4.0/parsnip/man/rmd/auto_ml_h2o.Rmd                          |   19 
 parsnip-1.4.0/parsnip/man/rmd/auto_ml_h2o.md                           |   26 
 parsnip-1.4.0/parsnip/man/rmd/bag_mars_earth.Rmd                       |   10 
 parsnip-1.4.0/parsnip/man/rmd/bag_mars_earth.md                        |   17 
 parsnip-1.4.0/parsnip/man/rmd/bag_mlp_nnet.Rmd                         |   10 
 parsnip-1.4.0/parsnip/man/rmd/bag_mlp_nnet.md                          |   17 
 parsnip-1.4.0/parsnip/man/rmd/bag_tree_C5.0.Rmd                        |   10 
 parsnip-1.4.0/parsnip/man/rmd/bag_tree_C5.0.md                         |   13 
 parsnip-1.4.0/parsnip/man/rmd/bag_tree_rpart.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/bag_tree_rpart.md                        |   14 
 parsnip-1.4.0/parsnip/man/rmd/bart_dbarts.Rmd                          |   10 
 parsnip-1.4.0/parsnip/man/rmd/bart_dbarts.md                           |   23 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_C5.0.Rmd                      |   11 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_C5.0.md                       |   18 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_h2o.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_h2o.md                        |   24 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_lightgbm.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_lightgbm.md                   |   19 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_mboost.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_mboost.md                     |   18 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_spark.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_spark.md                      |   18 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_xgboost.Rmd                   |   13 
 parsnip-1.4.0/parsnip/man/rmd/boost_tree_xgboost.md                    |   22 
 parsnip-1.4.0/parsnip/man/rmd/cubist_rules_Cubist.Rmd                  |   10 
 parsnip-1.4.0/parsnip/man/rmd/cubist_rules_Cubist.md                   |   16 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_C5.0.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_C5.0.md                    |   18 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_partykit.Rmd               |   11 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_partykit.md                |   20 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_rpart.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_rpart.md                   |   22 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_spark.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/decision_tree_spark.md                   |   18 
 parsnip-1.4.0/parsnip/man/rmd/discrim_flexible_earth.Rmd               |   10 
 parsnip-1.4.0/parsnip/man/rmd/discrim_flexible_earth.md                |   17 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_MASS.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_MASS.md                   |   18 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_mda.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_mda.md                    |   18 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_sda.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_sda.md                    |   18 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_sparsediscrim.Rmd         |   11 
 parsnip-1.4.0/parsnip/man/rmd/discrim_linear_sparsediscrim.md          |   20 
 parsnip-1.4.0/parsnip/man/rmd/discrim_quad_MASS.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/discrim_quad_MASS.md                     |   18 
 parsnip-1.4.0/parsnip/man/rmd/discrim_quad_sparsediscrim.Rmd           |   11 
 parsnip-1.4.0/parsnip/man/rmd/discrim_quad_sparsediscrim.md            |   20 
 parsnip-1.4.0/parsnip/man/rmd/discrim_regularized_klaR.Rmd             |   10 
 parsnip-1.4.0/parsnip/man/rmd/discrim_regularized_klaR.md              |   17 
 parsnip-1.4.0/parsnip/man/rmd/gen_additive_mod_mgcv.Rmd                |   10 
 parsnip-1.4.0/parsnip/man/rmd/gen_additive_mod_mgcv.md                 |   21 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_brulee.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_brulee.md                     |   16 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_gee.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_gee.md                        |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_glm.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_glm.md                        |   18 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_glmer.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_glmer.md                      |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_glmnet.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_glmnet.md                     |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_gls.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_gls.md                        |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_h2o.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_h2o.md                        |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_keras.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_keras.md                      |   16 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_lm.Rmd                        |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_lm.md                         |   19 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_lme.Rmd                       |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_lme.md                        |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_lmer.Rmd                      |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_lmer.md                       |   17 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_quantreg.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_quantreg.md                   |   16 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_spark.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_spark.md                      |   16 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_stan.Rmd                      |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_stan.md                       |   19 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_stan_glmer.Rmd                |   11 
 parsnip-1.4.0/parsnip/man/rmd/linear_reg_stan_glmer.md                 |   18 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_LiblineaR.Rmd               |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_LiblineaR.md                |   18 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_brulee.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_brulee.md                   |   17 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_gee.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_gee.md                      |   18 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_glm.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_glm.md                      |   19 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_glmer.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_glmer.md                    |   17 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_glmnet.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_glmnet.md                   |   18 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_h2o.Rmd                     |   10 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_h2o.md                      |   16 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_keras.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_keras.md                    |   17 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_spark.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_spark.md                    |   17 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_stan.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_stan.md                     |   20 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_stan_glmer.Rmd              |   11 
 parsnip-1.4.0/parsnip/man/rmd/logistic_reg_stan_glmer.md               |   20 
 parsnip-1.4.0/parsnip/man/rmd/mars_earth.Rmd                           |   10 
 parsnip-1.4.0/parsnip/man/rmd/mars_earth.md                            |   19 
 parsnip-1.4.0/parsnip/man/rmd/mlp_brulee.Rmd                           |   11 
 parsnip-1.4.0/parsnip/man/rmd/mlp_brulee.md                            |   18 
 parsnip-1.4.0/parsnip/man/rmd/mlp_brulee_two_layer.Rmd                 |   11 
 parsnip-1.4.0/parsnip/man/rmd/mlp_brulee_two_layer.md                  |   18 
 parsnip-1.4.0/parsnip/man/rmd/mlp_h2o.Rmd                              |   10 
 parsnip-1.4.0/parsnip/man/rmd/mlp_h2o.md                               |   18 
 parsnip-1.4.0/parsnip/man/rmd/mlp_keras.Rmd                            |   11 
 parsnip-1.4.0/parsnip/man/rmd/mlp_keras.md                             |   20 
 parsnip-1.4.0/parsnip/man/rmd/mlp_nnet.Rmd                             |   11 
 parsnip-1.4.0/parsnip/man/rmd/mlp_nnet.md                              |   20 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_brulee.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_brulee.md                   |   17 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_glmnet.Rmd                  |   11 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_glmnet.md                   |   18 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_h2o.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_h2o.md                      |   17 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_keras.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_keras.md                    |   17 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_nnet.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_nnet.md                     |   18 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_spark.Rmd                   |   10 
 parsnip-1.4.0/parsnip/man/rmd/multinom_reg_spark.md                    |   16 
 parsnip-1.4.0/parsnip/man/rmd/naive_Bayes_h2o.Rmd                      |   11 
 parsnip-1.4.0/parsnip/man/rmd/naive_Bayes_h2o.md                       |   17 
 parsnip-1.4.0/parsnip/man/rmd/naive_Bayes_klaR.Rmd                     |   11 
 parsnip-1.4.0/parsnip/man/rmd/naive_Bayes_klaR.md                      |   18 
 parsnip-1.4.0/parsnip/man/rmd/naive_Bayes_naivebayes.Rmd               |   11 
 parsnip-1.4.0/parsnip/man/rmd/naive_Bayes_naivebayes.md                |   17 
 parsnip-1.4.0/parsnip/man/rmd/nearest_neighbor_kknn.Rmd                |   10 
 parsnip-1.4.0/parsnip/man/rmd/nearest_neighbor_kknn.md                 |   19 
 parsnip-1.4.0/parsnip/man/rmd/null-model.Rmd                           |    9 
 parsnip-1.4.0/parsnip/man/rmd/null-model.md                            |   18 
 parsnip-1.4.0/parsnip/man/rmd/pls_mixOmics.Rmd                         |   10 
 parsnip-1.4.0/parsnip/man/rmd/pls_mixOmics.md                          |   19 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_gee.Rmd                      |   11 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_gee.md                       |   17 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_glm.Rmd                      |   11 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_glm.md                       |   17 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_glmer.Rmd                    |   11 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_glmer.md                     |   17 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_glmnet.Rmd                   |   11 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_glmnet.md                    |   17 
 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_h2o.Rmd                      |   10 
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 parsnip-1.4.0/parsnip/man/rmd/poisson_reg_stan_glmer.md                |   18 
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 parsnip-1.4.0/parsnip/man/rmd/proportional_hazards_glmnet.md           |   20 
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 parsnip-1.4.0/parsnip/man/rmd/rand_forest_grf.Rmd                      |only
 parsnip-1.4.0/parsnip/man/rmd/rand_forest_grf.md                       |only
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 parsnip-1.4.0/parsnip/man/rmd/rand_forest_partykit.Rmd                 |   11 
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Package manifold readmission to version 0.1.2 with previous version 0.1.1 dated 2022-10-04

Title: Operations for Riemannian Manifolds
Description: Implements operations for Riemannian manifolds, e.g., geodesic distance, Riemannian metric, exponential and logarithm maps, etc. Also incorporates random object generator on the manifolds. See Dai, Lin, and Müller (2021) <doi:10.1111/biom.13385>.
Author: Xiongtao Dai [aut, cre, cph], Zhenhua Lin [aut]
Maintainer: Xiongtao Dai <xiongtao.dai@hotmail.com>

This is a re-admission after prior archival of version 0.1.1 dated 2022-10-04

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Package exactextractr updated to version 0.10.1 with previous version 0.10.0 dated 2023-09-20

Title: Fast Extraction from Raster Datasets using Polygons
Description: Quickly and accurately summarizes raster values over polygonal areas ("zonal statistics").
Author: Daniel Baston [aut, cre], ISciences, LLC [cph]
Maintainer: Daniel Baston <dbaston@isciences.com>

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Package vitals updated to version 0.2.0 with previous version 0.1.0 dated 2025-06-24

Title: Large Language Model Evaluation
Description: A port of 'Inspect', a widely adopted 'Python' framework for large language model evaluation. Specifically aimed at 'ellmer' users who want to measure the effectiveness of their large language model-based products, the package supports prompt engineering, tool usage, multi-turn dialog, and model graded evaluations.
Author: Simon Couch [aut, cre] , Max Kuhn [ctb], Hadley Wickham [ctb] , Mine Cetinkaya-Rundel [ctb] , Posit Software, PBC [cph, fnd]
Maintainer: Simon Couch <simon.couch@posit.co>

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Package reactable updated to version 0.4.5 with previous version 0.4.4 dated 2023-03-12

Title: Interactive Data Tables for R
Description: Interactive data tables for R, based on the 'React Table' JavaScript library. Provides an HTML widget that can be used in 'R Markdown' or 'Quarto' documents, 'Shiny' applications, or viewed from an R console.
Author: Greg Lin [aut, cre], Tanner Linsley [ctb, cph] , Emotion team and other contributors [ctb, cph] , Kent Russell [ctb, cph] , Ramnath Vaidyanathan [ctb, cph] , Joe Cheng [ctb, cph] , JJ Allaire [ctb, cph] , Yihui Xie [ctb, cph] , Kenton Russell [ctb, c [...truncated...]
Maintainer: Greg Lin <glin@glin.io>

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Package polle updated to version 1.6.1 with previous version 1.6.0 dated 2025-10-30

Title: Policy Learning
Description: Package for learning and evaluating (subgroup) policies via doubly robust loss functions. Policy learning methods include doubly robust blip/conditional average treatment effect learning and sequential policy tree learning. Methods for (subgroup) policy evaluation include doubly robust cross-fitting and online estimation/sequential validation. See Nordland and Holst (2022) <doi:10.48550/arXiv.2212.02335> for documentation and references.
Author: Andreas Nordland [aut, cre], Klaus Holst [aut]
Maintainer: Andreas Nordland <andreasnordland@gmail.com>

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Package NPBayesImputeCat updated to version 0.6 with previous version 0.5 dated 2022-10-03

Title: Non-Parametric Bayesian Multiple Imputation for Categorical Data
Description: These routines create multiple imputations of missing at random categorical data, and create multiply imputed synthesis of categorical data, with or without structural zeros. Imputations and syntheses are based on Dirichlet process mixtures of multinomial distributions, which is a non-parametric Bayesian modeling approach that allows for flexible joint modeling, described in Manrique-Vallier and Reiter (2014) <doi:10.1080/10618600.2013.844700>.
Author: Quanli Wang [aut], Daniel Manrique-Vallier [aut], Jerome P. Reiter [aut], Jingchen Hu [aut, cre]
Maintainer: Jingchen Hu <jingchen.monika.hu@gmail.com>

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New package DSFM with initial version 1.0.1
Package: DSFM
Title: Distributed Skew Factor Model Estimation Methods
Version: 1.0.1
Author: Guangbao Guo [aut, cre], Yu Jin [aut]
Maintainer: Guangbao Guo <ggb11111111@163.com>
Description: Provides a distributed framework for simulating and estimating skew factor models under various skewed and heavy-tailed distributions. The methods support distributed data generation, aggregation of local estimators, and evaluation of estimation performance via mean squared error, relative error, and sparsity measures. The distributed principal component (PC) estimators implemented in the package include 'IPC' (Independent Principal Component),'PPC' (Project Principal Component), 'SPC' (Sparse Principal Component), and other related distributed PC methods. The methodological background follows Guo G. (2023) <doi:10.1007/s00180-022-01270-z>.
Encoding: UTF-8
Depends: R (>= 4.0.0)
Imports: MASS, matrixcalc, sn, stats, psych, elasticnet, SOPC
Suggests: ggplot2, cowplot, testthat (>= 3.0.0)
NeedsCompilation: no
Language: en-US
License: MIT + file LICENSE
Packaged: 2025-11-26 11:35:33 UTC; AIERXUAN
Repository: CRAN
Date/Publication: 2025-12-01 15:10:02 UTC

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Package causalweight updated to version 1.1.4 with previous version 1.1.3 dated 2025-03-26

Title: Estimation Methods for Causal Inference Based on Inverse Probability Weighting and Doubly Robust Estimation
Description: Various estimators of causal effects based on inverse probability weighting, doubly robust estimation, and double machine learning. Specifically, the package includes methods for estimating average treatment effects, direct and indirect effects in causal mediation analysis, and dynamic treatment effects. The models refer to studies of Froelich (2007) <doi:10.1016/j.jeconom.2006.06.004>, Huber (2012) <doi:10.3102/1076998611411917>, Huber (2014) <doi:10.1080/07474938.2013.806197>, Huber (2014) <doi:10.1002/jae.2341>, Froelich and Huber (2017) <doi:10.1111/rssb.12232>, Hsu, Huber, Lee, and Lettry (2020) <doi:10.1002/jae.2765>, and others.
Author: Hugo Bodory [aut, cre] , Martin Huber [aut] , Jannis Kueck [aut]
Maintainer: Hugo Bodory <hugo.bodory@unisg.ch>

Diff between causalweight versions 1.1.3 dated 2025-03-26 and 1.1.4 dated 2025-12-01

 DESCRIPTION            |   14 +++++++-------
 MD5                    |   40 ++++++++++++++++++++--------------------
 R/ATETDML.R            |    4 ++--
 R/RDDcovar.R           |    4 ++--
 R/didDML.R             |    4 ++--
 R/didcontDML.R         |    4 ++--
 R/didcontDMLpanel.R    |    8 ++++----
 R/functions.R          |   33 ++++++++++++++++++++++-----------
 R/medDML.R             |    4 ++--
 R/paneltestDML.R       |    1 -
 R/rkd.R                |    4 ++--
 R/testmedident.R       |    2 +-
 R/treatselDML.R        |    4 ++--
 man/ATETDML.Rd         |    2 +-
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 man/didcontDML.Rd      |    2 +-
 man/didcontDMLpanel.Rd |    2 +-
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 man/paneltestDML.Rd    |    1 -
 man/rkd.Rd             |    4 ++--
 man/treatselDML.Rd     |    4 ++--
 21 files changed, 78 insertions(+), 69 deletions(-)

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Package xml2 updated to version 1.5.1 with previous version 1.5.0 dated 2025-11-17

Title: Parse XML
Description: Bindings to 'libxml2' for working with XML data using a simple, consistent interface based on 'XPath' expressions. Also supports XML schema validation; for 'XSLT' transformations see the 'xslt' package.
Author: Hadley Wickham [aut], Jim Hester [aut], Jeroen Ooms [aut, cre], Posit Software, PBC [cph, fnd], R Foundation [ctb]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>

Diff between xml2 versions 1.5.0 dated 2025-11-17 and 1.5.1 dated 2025-12-01

 DESCRIPTION                |    6 +++---
 MD5                        |   14 +++++++-------
 NEWS.md                    |    4 ++++
 build/partial.rdb          |binary
 cleanup                    |    2 +-
 configure                  |    9 ++++++---
 inst/doc/modification.html |   12 ++++++------
 src/xml2_init.c            |   11 +++++++----
 8 files changed, 34 insertions(+), 24 deletions(-)

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Package vecmatch updated to version 1.3.0 with previous version 1.2.0 dated 2025-07-08

Title: Generalized Propensity Score Estimation and Matching for Multiple Groups
Description: Implements the Vector Matching algorithm to match multiple treatment groups based on previously estimated generalized propensity scores. The package includes tools for visualizing initial confounder imbalances, estimating treatment assignment probabilities using various methods, defining the common support region, performing matching across multiple groups, and evaluating matching quality. For more details, see Lopez and Gutman (2017) <doi:10.1214/17-STS612>.
Author: Mateusz Kolek [aut, cre, cph]
Maintainer: Mateusz Kolek <mati.kolek13@gmail.com>

Diff between vecmatch versions 1.2.0 dated 2025-07-08 and 1.3.0 dated 2025-12-01

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 vecmatch-1.3.0/vecmatch/MD5                                         |   97 
 vecmatch-1.3.0/vecmatch/NAMESPACE                                   |   32 
 vecmatch-1.3.0/vecmatch/NEWS.md                                     |   26 
 vecmatch-1.3.0/vecmatch/R/balqual.R                                 |  300 -
 vecmatch-1.3.0/vecmatch/R/chk-utils.R                               |  113 
 vecmatch-1.3.0/vecmatch/R/csregion.R                                |  365 +
 vecmatch-1.3.0/vecmatch/R/estimate_gps.R                            |  407 +
 vecmatch-1.3.0/vecmatch/R/estimate_gps_multinom.R                   |    1 
 vecmatch-1.3.0/vecmatch/R/match_gps.R                               |  387 +
 vecmatch-1.3.0/vecmatch/R/methods.R                                 |    2 
 vecmatch-1.3.0/vecmatch/R/mosaic.R                                  |  874 +--
 vecmatch-1.3.0/vecmatch/R/optimize_gps.R                            | 2555 ++++++----
 vecmatch-1.3.0/vecmatch/R/plot_utils.R                              |   85 
 vecmatch-1.3.0/vecmatch/R/raincloud.R                               | 1255 ++--
 vecmatch-1.3.0/vecmatch/R/utils.R                                   |  121 
 vecmatch-1.3.0/vecmatch/R/vecmatch-package.R                        |   34 
 vecmatch-1.3.0/vecmatch/README.md                                   |   61 
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 vecmatch-1.3.0/vecmatch/inst/WORDLIST                               |    9 
 vecmatch-1.3.0/vecmatch/inst/doc/optimizing-matching.R              |   51 
 vecmatch-1.3.0/vecmatch/inst/doc/optimizing-matching.Rmd            |   75 
 vecmatch-1.3.0/vecmatch/inst/doc/optimizing-matching.html           |  297 -
 vecmatch-1.3.0/vecmatch/inst/doc/vecmatch.html                      |   55 
 vecmatch-1.3.0/vecmatch/man/balqual.Rd                              |   17 
 vecmatch-1.3.0/vecmatch/man/cancer.Rd                               |   12 
 vecmatch-1.3.0/vecmatch/man/csregion.Rd                             |    2 
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 vecmatch-1.3.0/vecmatch/tests/testthat/test-csregion.R              |  227 
 vecmatch-1.3.0/vecmatch/tests/testthat/test-estimate_gps.R          |  474 +
 vecmatch-1.3.0/vecmatch/tests/testthat/test-estimate_gps_multinom.R |    1 
 vecmatch-1.3.0/vecmatch/tests/testthat/test-match_gps.R             |  259 -
 vecmatch-1.3.0/vecmatch/tests/testthat/test-optimize_gps.R          |  609 ++
 vecmatch-1.3.0/vecmatch/tests/testthat/test-raincloud.R             |  137 
 vecmatch-1.3.0/vecmatch/tests/testthat/test-utils.R                 |   32 
 vecmatch-1.3.0/vecmatch/vignettes/optimizing-matching.Rmd           |   75 
 52 files changed, 6681 insertions(+), 2762 deletions(-)

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New package trunmnt with initial version 1.0.0
Package: trunmnt
Title: Moments of Truncated Multivariate Normal Distribution
Version: 1.0.0
Date: 2025-11-8
Description: Computes the product moments of the truncated multivariate normal distribution, particularly for cases involving patterned variance-covariance matrices. It also has the capability to calculate these moments with arbitrary positive-definite matrices, although performance may degrade for high-dimensional variables.
License: GPL-2
Depends: R (>= 4.1.0)
Imports: fastGHQuad, Rcpp, RcppArmadillo
Suggests: MomTrunc (>= 6.1), truncnorm (>= 1.0.9), tmvtnorm (>= 1.7), testthat, R.rsp
LinkingTo: Rcpp, RcppArmadillo, fastGHQuad
NeedsCompilation: yes
VignetteBuilder: R.rsp
Encoding: UTF-8
Packaged: 2025-11-25 19:19:18 UTC; LeeSeung
Author: Seung-Chun Lee [aut, cre]
Maintainer: Seung-Chun Lee <seung@hs.ac.kr>
Repository: CRAN
Date/Publication: 2025-12-01 14:40:08 UTC

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New package SpuriousMemory with initial version 1.0.0
Package: SpuriousMemory
Title: Testing True Long Memory Against Spurious Long Memory
Version: 1.0.0
Maintainer: Zhongjun Qu <qu@bu.edu>
Description: Implements a test for distinguishing between true long memory and spurious long memory. Reference: Qu, Z. (2011). "A Test Against Spurious Long Memory." Journal of Business & Economic Statistics, 29(3), 423–438. <doi:10.1198/jbes.2010.09153>.
License: GPL (>= 3)
Depends: R (>= 4.3.0)
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
Encoding: UTF-8
NeedsCompilation: no
Imports: fracdiff, stats
LazyData: true
Packaged: 2025-11-25 18:47:36 UTC; qu
Author: Zhongjun Qu [aut, cre], Cheolju Kim [aut]
Repository: CRAN
Date/Publication: 2025-12-01 14:40:21 UTC

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New package secrfunc with initial version 1.0.0
Package: secrfunc
Title: Helper Functions for Package 'secr'
Version: 1.0.0
Date: 2025-11-26
Description: Functions are provided for internal use by the spatial capture-recapture package 'secr' (from version 5.4.0). The idea is to speed up the installation of 'secr', and possibly reduce its size. Initially the functions are those for area and transect search that use numerical integration code from 'RcppNumerical' and 'RcppEigen'. The functions are not intended to be user-friendly and require considerable preprocessing of data.
Depends: R (>= 3.5.0)
Imports: Rcpp (>= 0.12.14), RcppNumerical, RcppParallel (>= 5.1.1)
Suggests: knitr, rmarkdown, testthat
LinkingTo: BH, Rcpp, RcppEigen, RcppNumerical, RcppParallel
License: GPL (>= 2)
SystemRequirements: GNU make
URL: https://www.otago.ac.nz/density/
Encoding: UTF-8
NeedsCompilation: yes
Packaged: 2025-11-25 23:57:24 UTC; murra
Author: Murray Efford [aut, cre] , Philipp Jund [ctb] )
Maintainer: Murray Efford <murray.efford@otago.ac.nz>
Repository: CRAN
Date/Publication: 2025-12-01 14:50:02 UTC

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New package odiffr with initial version 0.1.0
Package: odiffr
Title: Fast Pixel-by-Pixel Image Comparison Using 'odiff'
Version: 0.1.0
Description: R bindings to 'odiff', a blazing-fast pixel-by-pixel image comparison tool <https://github.com/dmtrKovalenko/odiff>. Supports PNG, JPEG, WEBP, and TIFF with configurable thresholds, antialiasing detection, and region ignoring. Requires system installation of 'odiff'. Ideal for visual regression testing in automated workflows.
SystemRequirements: odiff (>= 3.0.0) - https://github.com/dmtrKovalenko/odiff
License: MIT + file LICENSE
URL: https://github.com/BenWolst/odiffr
BugReports: https://github.com/BenWolst/odiffr/issues
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: tools
Suggests: knitr, magick, png, rmarkdown, testthat (>= 3.0.0), tibble, withr
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-26 12:45:00 UTC; benwolstenholme
Author: Ben Wolstenholme [aut, cre]
Maintainer: Ben Wolstenholme <odiffr@benwolst.dev>
Repository: CRAN
Date/Publication: 2025-12-01 15:00:02 UTC

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New package MLFDR with initial version 0.1.0
Package: MLFDR
Title: High Dimensional Mediation Analysis using Local False Discovery Rates
Version: 0.1.0
Description: Implements a high dimensional mediation analysis algorithm using Local False Discovery Rates. The methodology is described in Roy and Zhang (2024) <doi:10.48550/arXiv.2402.13933>.
License: GPL-2
Encoding: UTF-8
Imports: NMOF, stats
NeedsCompilation: no
Packaged: 2025-11-25 19:04:51 UTC; asmitaroy
Author: Asmita Roy [aut, cre]
Maintainer: Asmita Roy <aroy38@jh.edu>
Repository: CRAN
Date/Publication: 2025-12-01 14:40:27 UTC

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New package LBBNN with initial version 0.1.1
Package: LBBNN
Title: Latent Binary Bayesian Neural Networks Using 'torch'
Version: 0.1.1
Maintainer: Lars Skaaret-Lund <lars.skaaret-lund@nmbu.no>
Description: Latent binary Bayesian neural networks (LBBNNs) are implemented using 'torch', an R interface to the LibTorch backend. Supports mean-field variational inference as well as flexible variational posteriors using normalizing flows. The standard LBBNN implementation follows Hubin and Storvik (2024) <doi:10.3390/math12060788>, using the local reparametrization trick as in Skaaret-Lund et al. (2024) <https://openreview.net/pdf?id=d6kqUKzG3V>. Input-skip connections are also supported, as described in Høyheim et al. (2025) <doi:10.48550/arXiv.2503.10496>.
License: MIT + file LICENSE
Encoding: UTF-8
Language: en-US
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
Depends: R (>= 3.5)
LazyData: true
VignetteBuilder: knitr
Imports: ggplot2, torch, igraph, coro, svglite
NeedsCompilation: no
Packaged: 2025-11-25 10:49:33 UTC; larsskaaret-lund
Author: Lars Skaaret-Lund [aut, cre], Aliaksandr Hubin [aut], Eirik Hoeyheim [aut]
Repository: CRAN
Date/Publication: 2025-12-01 14:10:17 UTC

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New package heavytails with initial version 0.1.1
Package: heavytails
Title: Estimators and Algorithms for Heavy-Tailed Distributions
Version: 0.1.1
Description: Implements the estimators and algorithms described in Chapters 8 and 9 of the book "The Fundamentals of Heavy Tails: Properties, Emergence, and Estimation" by Nair et al. (2022, ISBN:9781009053730). These include the Hill estimator, Moments estimator, Pickands estimator, Peaks-over-Threshold (POT) method, Power-law fit, and the Double Bootstrap algorithm.
License: MIT + file LICENSE
URL: https://github.com/0diraf/heavytails
Depends: R (>= 3.5.0)
Encoding: UTF-8
Imports: stats
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-11-25 17:54:07 UTC; diraF
Author: Farid Rohan [aut, cre]
Maintainer: Farid Rohan <frohan@ur.rochester.edu>
Repository: CRAN
Date/Publication: 2025-12-01 14:30:02 UTC

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New package ExpBites with initial version 0.1.3
Package: ExpBites
Title: Analyzing Human Exposure to Mosquito Biting
Version: 0.1.3
Description: Tools to analyse human and mosquito behavioral interactions and to compute exposure to mosquito bites estimates. Using behavioral data for human individuals and biting patterns for mosquitoes, you will be able to compute hourly exposure for bed net users and non-users, and summarize (e.g. proportion indoors and outdoors, proportion per time periods, and proportion prevented by bed nets) or visualize these dynamics across a 24-hour cycle.
License: GPL-3
Encoding: UTF-8
Imports: dplyr, tidyr, ggplot2, Rdpack (>= 0.7)
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
Depends: R (>= 4.1.0)
URL: https://github.com/Nmoiroux/ExpBites
BugReports: https://github.com/Nmoiroux/ExpBites/issues
NeedsCompilation: no
Packaged: 2025-11-26 10:14:56 UTC; nicolasmoiroux
Author: Nicolas Moiroux [aut, cre]
Maintainer: Nicolas Moiroux <nicolas.moiroux@ird.fr>
Repository: CRAN
Date/Publication: 2025-12-01 15:00:08 UTC

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New package energyGOF with initial version 0.1
Package: energyGOF
Title: Goodness-of-Fit Tests for Univariate Data via Energy
Version: 0.1
Description: Conduct one- and two-sample goodness-of-fit tests for univariate data. In the one-sample case, normal, uniform, exponential, Bernoulli, binomial, geometric, beta, Poisson, lognormal, Laplace, asymmetric Laplace, inverse Gaussian, half-normal, chi-squared, gamma, F, Weibull, Cauchy, and Pareto distributions are supported. egof.test() can also test goodness-of-fit to any distribution with a continuous distribution function. A subset of the available distributions can be tested for the composite goodness-of-fit hypothesis, that is, one can test for distribution fit with unknown parameters. P-values are calculated via parametric bootstrap.
License: GPL (>= 3)
Encoding: UTF-8
Imports: energy, gsl, boot, fitdistrplus, statmod
URL: https://github.com/jthaman/energyGOF
Suggests: testthat (>= 3.0.0)
NeedsCompilation: no
Packaged: 2025-11-25 19:44:35 UTC; john
Author: John Haman [aut, cre]
Maintainer: John Haman <mail@johnhaman.org>
Repository: CRAN
Date/Publication: 2025-12-01 14:40:15 UTC

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New package distionary with initial version 0.1.0
Package: distionary
Title: Create and Evaluate Probability Distributions
Version: 0.1.0
Description: Create and evaluate probability distribution objects from a variety of families or define custom distributions. Automatically compute distributional properties, even when they have not been specified. This package supports statistical modeling and simulations, and forms the core of the probaverse suite of R packages.
License: MIT + file LICENSE
Suggests: covr, knitr, rmarkdown, testthat (>= 3.0.0), tibble
Encoding: UTF-8
Imports: checkmate, ellipsis, rlang, stats, vctrs
VignetteBuilder: knitr
URL: https://distionary.probaverse.com/, https://github.com/probaverse/distionary
BugReports: https://github.com/probaverse/distionary/issues
Depends: R (>= 2.10)
NeedsCompilation: no
Packaged: 2025-11-25 12:28:01 UTC; vcoia
Author: Vincenzo Coia [aut, cre, cph], Amogh Joshi [ctb], Shuyi Tan [ctb], Zhipeng Zhu [ctb]
Maintainer: Vincenzo Coia <vincenzo.coia@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-01 14:10:09 UTC

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Package BoundEdgeworth updated to version 0.1.3 with previous version 0.1.2.1 dated 2023-06-16

Title: Bound on the Error of the First-Order Edgeworth Expansion
Description: Computes uniform bounds on the distance between the cumulative distribution function of a standardized sum of random variables and its first-order Edgeworth expansion, following the article Derumigny, Girard, Guyonvarch (2023) <doi:10.1007/s13171-023-00320-y>.
Author: Alexis Derumigny [aut, cre] , Lucas Girard [aut], Yannick Guyonvarch [aut]
Maintainer: Alexis Derumigny <a.f.f.derumigny@tudelft.nl>

Diff between BoundEdgeworth versions 0.1.2.1 dated 2023-06-16 and 0.1.3 dated 2025-12-01

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 BoundEdgeworth-0.1.3/BoundEdgeworth/MD5                             |   24 +--
 BoundEdgeworth-0.1.3/BoundEdgeworth/NAMESPACE                       |    1 
 BoundEdgeworth-0.1.3/BoundEdgeworth/NEWS.md                         |   11 +
 BoundEdgeworth-0.1.3/BoundEdgeworth/R/Bound_BE.R                    |   34 +---
 BoundEdgeworth-0.1.3/BoundEdgeworth/R/Bound_EE1.R                   |   76 ++++------
 BoundEdgeworth-0.1.3/BoundEdgeworth/R/Gauss_test_power.R            |   54 ++++---
 BoundEdgeworth-0.1.3/BoundEdgeworth/README.md                       |   37 +++-
 BoundEdgeworth-0.1.3/BoundEdgeworth/build/partial.rdb               |only
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 BoundEdgeworth-0.1.3/BoundEdgeworth/man/Bound_BE.Rd                 |   61 +++-----
 BoundEdgeworth-0.1.3/BoundEdgeworth/man/Bound_EE1.Rd                |   72 ++++-----
 BoundEdgeworth-0.1.3/BoundEdgeworth/man/Gauss_test_powerAnalysis.Rd |   52 ++++--
 15 files changed, 236 insertions(+), 205 deletions(-)

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New package bigPLSR with initial version 0.7.2
Package: bigPLSR
Version: 0.7.2
Date: 2025-11-26
Depends: R (>= 4.0.0)
Imports: Rcpp, bigmemory
LinkingTo: Rcpp, RcppArmadillo, BH, bigmemory
Suggests: bench, dplyr, forcats, future, future.apply, ggplot2, knitr, pls, plsRglm, rmarkdown, RhpcBLASctl, svglite, testthat (>= 3.0.0), tidyr, withr
VignetteBuilder: knitr
Title: Partial Least Squares Regression Models with Big Matrices
Author: Frederic Bertrand [cre, aut] , Myriam Maumy [aut]
Maintainer: Frederic Bertrand <frederic.bertrand@lecnam.net>
Description: Fast partial least squares (PLS) for dense and out-of-core data. Provides SIMPLS (straightforward implementation of a statistically inspired modification of the PLS method) and NIPALS (non-linear iterative partial least-squares) solvers, plus kernel-style PLS variants ('kernelpls' and 'widekernelpls') with parity to 'pls'. Optimized for 'bigmemory'-backed matrices with streamed cross-products and chunked BLAS (Basic Linear Algebra Subprograms) (XtX/XtY and XXt/YX), optional file-backed score sinks, and deterministic testing helpers. Includes an auto-selection strategy that chooses between XtX SIMPLS, XXt (wide) SIMPLS, and NIPALS based on (n, p) and a configurable memory budget. About the package, Bertrand and Maumy (2023) <https://hal.science/hal-05352069>, and <https://hal.science/hal-05352061> highlighted fitting and cross-validating PLS regression models to big data. For more details about some of the techniques featured in the package, Dayal and MacGregor (1997) <d [...truncated...]
License: GPL-3
Encoding: UTF-8
URL: https://fbertran.github.io/bigPLSR/, https://github.com/fbertran/bigPLSR
BugReports: https://github.com/fbertran/bigPLSR/issues
Classification/MSC: 62N01, 62N02, 62N03, 62N99
LazyData: true
SystemRequirements: C++17, Optional CBLAS (detected at compile time)
NeedsCompilation: yes
Packaged: 2025-11-26 01:52:43 UTC; bertran7
Repository: CRAN
Date/Publication: 2025-12-01 14:50:07 UTC

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New package TopicTestlet with initial version 0.1.0
Package: TopicTestlet
Title: A Topic Testlet Model for Calibrating Testlet Constructed Responses
Version: 0.1.0
Description: Implements the Topic Testlet Model (TTM) as described by Xiong et al. (2025) <doi:10.1111/jedm.70001>. The package integrates Latent Dirichlet Allocation (LDA) with the Partial Credit Model to account for local item dependence in testlets using latent topics from student textual responses.
Depends: R (>= 4.0.0)
Imports: topicmodels, tm, stats
License: GPL (>= 3)
Encoding: UTF-8
Suggests: knitr, rmarkdown
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-25 03:35:49 UTC; jx
Author: Jiawei Xiong [aut, cre], Cheng Tang [ctb], Qidi Liu [ctb]
Maintainer: Jiawei Xiong <jiawei.xiong@uga.edu>
Repository: CRAN
Date/Publication: 2025-12-01 14:00:02 UTC

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New package stoichUtilities with initial version 1.0.2
Package: stoichUtilities
Title: User Tools for Accessing the STOICH Project Database
Version: 1.0.2
Description: User tools for working with The STOICH (Stoichiometric Traits of Organisms in their Chemical Habitats) Project database <https://snr-stoich.unl.edu/>. This package is designed to aid in data discovery, filtering, pairing water samples with organism samples, and merging data tables to assist users in preparing data for analyses. For additional examples see "Additional Examples" and the readme file at <https://github.com/STOICH-project/STOICH-utilities>.
URL: https://github.com/STOICH-project/STOICH-utilities, https://snr-stoich.unl.edu/, https://stoichproject.wordpress.com/
BugReports: https://github.com/STOICH-project/STOICH-utilities/issues
License: GPL (>= 3)
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: tibble, tidyr, dplyr, readr, stringr, purrr, magrittr, lubridate, sf, rlang, units, stats, jsonlite
Suggests: tidyverse, maps, knitr, rmarkdown, gt, glue, gluedown, kableExtra, testthat (>= 3.0.0)
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-24 19:28:30 UTC; Chad
Author: Chad Petersen [aut, cre], Jessica Corman [ctb], Halvor Halvorson [ctb], Casey Brucker [ctb], Eli Wess [ctb], U.S. National Science Foundation [fnd]
Maintainer: Chad Petersen <cpetersen4@unl.edu>
Repository: CRAN
Date/Publication: 2025-12-01 13:40:02 UTC

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New package PSPI with initial version 1.1
Package: PSPI
Title: Propensity Score Predictive Inference for Generalizability
Version: 1.1
Date: 2025-11-15
Author: Jungang Zou [aut, cre], Qixuan Chen [aut], Joseph Schwartz [aut], Nathalie Moise [aut], Roderick Little [aut], Robert McCulloch [ctb], Rodney Sparapani [ctb], Charles Spanbauer [ctb], Robert Gramacy [ctb], Jean-Sebastien Roy [ctb]
Maintainer: Jungang Zou <jungang.zou@gmail.com>
Description: Provides a suite of Propensity Score Predictive Inference (PSPI) methods to generalize treatment effects in trials to target populations. The package includes an existing model Bayesian Causal Forest (BCF) and four PSPI models (BCF-PS, FullBART, SplineBART, DSplineBART). These methods leverage Bayesian Additive Regression Trees (BART) to adjust for high-dimensional covariates and nonlinear associations, while SplineBART and DSplineBART further use propensity score based splines to address covariate shift between trial data and target population.
License: GPL-2
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: Rcpp, arm, dplyr, mvtnorm, stringr, stats, nnet, methods
LinkingTo: Rcpp, RcppArmadillo, RcppDist, RcppProgress, pg
SystemRequirements: GNU make
Suggests: knitr, rmarkdown, mitml
NeedsCompilation: yes
Packaged: 2025-11-24 21:25:55 UTC; jz3183
Repository: CRAN
Date/Publication: 2025-12-01 13:50:05 UTC

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Package omopgenerics updated to version 1.3.4 with previous version 1.3.3 dated 2025-11-11

Title: Methods and Classes for the OMOP Common Data Model
Description: Provides definitions of core classes and methods used by analytic pipelines that query the OMOP (Observational Medical Outcomes Partnership) common data model.
Author: Marti Catala [aut, cre] , Edward Burn [aut] , Mike Du [ctb] , Yuchen Guo [ctb] , Adam Black [ctb] , Marta Alcalde-Herraiz [ctb]
Maintainer: Marti Catala <marti.catalasabate@ndorms.ox.ac.uk>

Diff between omopgenerics versions 1.3.3 dated 2025-11-11 and 1.3.4 dated 2025-12-01

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Package dunlin updated to version 0.1.12 with previous version 0.1.11 dated 2025-08-22

Title: Preprocessing Tools for Clinical Trial Data
Description: A collection of functions to preprocess data and organize them in a format amenable to use by chevron.
Author: Liming Li [aut] , Benoit Falquet [aut] , Xiaoli Duan [ctb], Pawel Rucki [ctb], Joe Zhu [cre] , F. Hoffmann-La Roche AG [cph, fnd]
Maintainer: Joe Zhu <joe.zhu@roche.com>

Diff between dunlin versions 0.1.11 dated 2025-08-22 and 0.1.12 dated 2025-12-01

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More information about dunlin at CRAN
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Package dRiftDM updated to version 0.3.1 with previous version 0.2.2 dated 2025-03-04

Title: Estimating (Time-Dependent) Drift Diffusion Models
Description: Fit and explore Drift Diffusion Models (DDMs), a common tool in psychology for describing decision processes in simple tasks. It can handle both time-independent and time-dependent DDMs. You either choose prebuilt models or create your own, and the package takes care of model predictions and parameter estimation. Model predictions are derived via the numerical solutions provided by Richter, Ulrich, and Janczyk (2023, <doi:10.1016/j.jmp.2023.102756>).
Author: Valentin Koob [cre, aut, cph], Thomas Richter [aut, cph], Markus Janczyk [aut]
Maintainer: Valentin Koob <v.koob@web.de>

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New package convergenceDFM with initial version 0.1.4
Package: convergenceDFM
Title: Convergence and Dynamic Factor Models
Version: 0.1.4
Description: Tests convergence in macro-financial panels combining Dynamic Factor Models (DFM) and mean-reverting Ornstein-Uhlenbeck (OU) processes. Provides: (i) static/approximate DFMs for large panels with VAR/VECM stability checks, Portmanteau tests and rolling out-of-sample R^2, following Stock and Watson (2002) <doi:10.1198/073500102317351921> and the Generalized Dynamic Factor Model of Forni, Hallin, Lippi and Reichlin (2000) <doi:10.1162/003465300559037>; (ii) cointegration analysis à la Johansen (1988) <doi:10.1016/0165-1889(88)90041-3>; (iii) OU-based convergence and half-life summaries grounded in Uhlenbeck and Ornstein (1930) <doi:10.1103/PhysRev.36.823> and Vasicek (1977) <doi:10.1016/0304-405X(77)90016-2>; (iv) robust inference via 'sandwich' HC/HAC estimators (Zeileis (2004) <doi:10.18637/jss.v011.i10>) and regression diagnostics ('lmtest'); and (v) optional PLS-based factor preselection (Mevik and Wehrens (2007) <doi:10.18637/jss.v018.i02>). [...truncated...]
License: GPL-3
Encoding: UTF-8
Depends: R (>= 4.1)
Imports: stats, methods, pls, vars, urca, readxl, dplyr, tidyr, stringr, magrittr, zoo
Suggests: testthat (>= 3.0.0), knitr, rmarkdown, cmdstanr, posterior, rstan
Additional_repositories: https://mc-stan.org/r-packages/
VignetteBuilder: knitr
NeedsCompilation: no
Packaged: 2025-11-24 17:07:32 UTC; ROG
Author: Jose Mauricio Gomez Julian [aut, cre]
Maintainer: Jose Mauricio Gomez Julian <isadorenabi@pm.me>
Repository: CRAN
Date/Publication: 2025-12-01 13:40:07 UTC

More information about convergenceDFM at CRAN
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New package barry with initial version 0.2.1
Package: barry
Title: Your Go-to Motif Accountant
Version: 0.2.1
Depends: R (>= 4.1.0)
Description: Provides the 'C++' header-only library 'barry' for use in R packages. 'barry' is a 'C++' template library for counting sufficient statistics on binary arrays and building discrete exponential-family models. It provides tools for sparse arrays, user-defined count statistics, support set constraints, power set generation, and includes modules for Discrete Exponential Family Models (DEFMs) and network statistics. By placing these headers in this package, we offer an efficient distribution system for CRAN as replication of this code in the sources of other packages is avoided. This package follows the same approach as the 'BH' package which provides 'Boost' headers for R packages.
URL: https://github.com/USCbiostats/barryr, https://uscbiostats.github.io/barryr/
BugReports: https://github.com/USCbiostats/barryr/issues
License: MIT + file LICENSE
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2025-11-24 20:51:09 UTC; runner
Author: George Vega Yon [aut, cre]
Maintainer: George Vega Yon <g.vegayon@gmail.com>
Repository: CRAN
Date/Publication: 2025-12-01 13:50:02 UTC

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Package primarycensored updated to version 1.3.0 with previous version 1.2.0 dated 2025-06-09

Title: Primary Event Censored Distributions
Description: Provides functions for working with primary event censored distributions and 'Stan' implementations for use in Bayesian modeling. Primary event censored distributions are useful for modeling delayed reporting scenarios in epidemiology and other fields (Charniga et al. (2024) <doi:10.48550/arXiv.2405.08841>). It also provides support for arbitrary delay distributions, a range of common primary distributions, and allows for truncation and secondary event censoring to be accounted for (Park et al. (2024) <doi:10.1101/2024.01.12.24301247>). A subset of common distributions also have analytical solutions implemented, allowing for faster computation. In addition, it provides multiple methods for fitting primary event censored distributions to data via optional dependencies.
Author: Sam Abbott [aut, cre, cph] , Sam Brand [aut] , Adam Howes [ctb] , James Mba Azam [aut] , Carl Pearson [aut] , Sebastian Funk [aut] , Kelly Charniga [aut]
Maintainer: Sam Abbott <contact@samabbott.co.uk>

Diff between primarycensored versions 1.2.0 dated 2025-06-09 and 1.3.0 dated 2025-12-01

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Package geeLite updated to version 1.0.4 with previous version 1.0.3 dated 2025-11-22

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

Diff between geeLite versions 1.0.3 dated 2025-11-22 and 1.0.4 dated 2025-12-01

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More information about geeLite at CRAN
Permanent link

Package performance updated to version 0.15.3 with previous version 0.15.2 dated 2025-10-06

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 0.15.2 dated 2025-10-06 and 0.15.3 dated 2025-12-01

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Package bupaR updated to version 1.0.0 with previous version 0.5.5 dated 2025-07-07

Title: Business Process Analysis in R
Description: Comprehensive Business Process Analysis toolkit. Creates S3-class for event log objects, and related handler functions. Imports related packages for filtering event data, computation of descriptive statistics, handling of 'Petri Net' objects and visualization of process maps. See also packages 'edeaR','processmapR', 'eventdataR' and 'processmonitR'.
Author: Benoît Depaire [cre], Gert Janssenswillen [aut], Gerard van Hulzen [ctb], Felix Mannhardt [ctb], Niels Martin [ctb], Greg Van Houdt [ctb], Hasselt University [cph]
Maintainer: Benoît Depaire <benoit.depaire@uhasselt.be>

Diff between bupaR versions 0.5.5 dated 2025-07-07 and 1.0.0 dated 2025-12-01

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Package tableHTML updated to version 2.1.3 with previous version 2.1.2 dated 2023-04-17

Title: A Tool to Create HTML Tables
Description: A tool to create and style HTML tables with CSS. These can be exported and used in any application that accepts HTML (e.g. 'shiny', 'rmarkdown', 'PowerPoint'). It also provides functions to create CSS files (which also work with shiny).
Author: Theo Boutaris [aut, cre, cph], Clemens Zauchner [aut], Dana Jomar [aut]
Maintainer: Theo Boutaris <teoboot2007@hotmail.com>

Diff between tableHTML versions 2.1.2 dated 2023-04-17 and 2.1.3 dated 2025-12-01

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Permanent link

Package ast2ast (with last version 0.3.2) was removed from CRAN

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

2023-12-09 0.3.2
2023-04-11 0.3.1

Permanent link
Package dfdr (with last version 0.2.0) was removed from CRAN

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

2023-02-23 0.2.0
2022-12-21 0.1.0

Permanent link
Package rank updated to version 0.2.0 with previous version 0.1.1 dated 2024-12-01

Title: Customisable Ranking of Numerical and Categorical Data
Description: Provides a flexible alternative to the built-in rank() function called smartrank(). Optionally rank categorical variables by frequency (instead of in alphabetical order), and control whether ranking is based on descending/ascending order. smartrank() is suitable for both numerical and categorical data.
Author: Sam El-Kamand [aut, cre, cph]
Maintainer: Sam El-Kamand <sam.elkamand@gmail.com>

Diff between rank versions 0.1.1 dated 2024-12-01 and 0.2.0 dated 2025-12-01

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More information about rank at CRAN
Permanent link

Package pak updated to version 0.9.1 with previous version 0.9.0 dated 2025-05-27

Title: Another Approach to Package Installation
Description: The goal of 'pak' is to make package installation faster and more reliable. In particular, it performs all HTTP operations in parallel, so metadata resolution and package downloads are fast. Metadata and package files are cached on the local disk as well. 'pak' has a dependency solver, so it finds version conflicts before performing the installation. This version of 'pak' supports CRAN, 'Bioconductor' and 'GitHub' packages as well.
Author: Gabor Csardi [aut, cre], Jim Hester [aut], Posit Software, PBC [cph, fnd] , Winston Chang [ctb] , Ascent Digital Services [cph, fnd] , Hadley Wickham [ctb, cph] , Jeroen Ooms [ctb] , Maelle Salmon [ctb] , Duncan Temple Lang [ctb] , Lloyd Hilaiel [cph [...truncated...]
Maintainer: Gabor Csardi <csardi.gabor@gmail.com>

Diff between pak versions 0.9.0 dated 2025-05-27 and 0.9.1 dated 2025-12-01

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Permanent link

Package mirai updated to version 2.5.3 with previous version 2.5.2 dated 2025-11-05

Title: Minimalist Async Evaluation Framework for R
Description: Designed for simplicity, a 'mirai' evaluates an R expression asynchronously, locally or distributed over the network. Built on 'nanonext' and 'NNG' for modern networking and concurrency, scales efficiently to millions of tasks over thousands of parallel processes. Provides optimal scheduling over fast 'IPC', TCP, and TLS connections, integrating with SSH or cluster managers. Implements event-driven promises for reactive programming, and supports custom serialization for cross-language data types.
Author: Charlie Gao [aut, cre] , Joe Cheng [ctb], Posit Software, PBC [cph, fnd] , Hibiki AI Limited [cph]
Maintainer: Charlie Gao <charlie.gao@posit.co>

Diff between mirai versions 2.5.2 dated 2025-11-05 and 2.5.3 dated 2025-12-01

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Permanent link

Package SSBtools updated to version 1.8.6 with previous version 1.8.4 dated 2025-10-31

Title: Algorithms and Tools for Tabular Statistics and Hierarchical Computations
Description: Includes general data manipulation functions, algorithms for statistical disclosure control (Langsrud, 2024) <doi:10.1007/978-3-031-69651-0_6> and functions for hierarchical computations by sparse model matrices (Langsrud, 2023) <doi:10.32614/RJ-2023-088>.
Author: Oeyvind Langsrud [aut, cre] , Daniel Lupp [aut] , Bjoern-Helge Mevik [ctb], Vidar Norstein Klungre [rev] , Statistics Norway [cph]
Maintainer: Oeyvind Langsrud <oyl@ssb.no>

Diff between SSBtools versions 1.8.4 dated 2025-10-31 and 1.8.6 dated 2025-12-01

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Permanent link

Package spectre updated to version 1.0.5 with previous version 1.0.2 dated 2021-07-17

Title: Predict Regional Community Composition
Description: Predict regional community composition at a fine spatial resolution using only sparse biological and environmental data. See Simpkins et al. (2022) <doi:10.1111/ecog.06272> for full details on the algorithm underlying the package.
Author: Craig Simpkins [aut, cre], Sebastian Hanss [aut], Maximilian Hesselbarth [aut], Matthias Spangenberg [aut], Jan Salecker [aut]
Maintainer: Craig Simpkins <simpkinscraig063@gmail.com>

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More information about spectre at CRAN
Permanent link

Package o2plsda readmission to version 0.0.26 with previous version 0.0.25 dated 2024-07-18

Title: Multiomics Data Integration
Description: Provides functions to do 'O2PLS-DA' analysis for multiple omics data integration. The algorithm came from "O2-PLS, a two-block (X±Y) latent variable regression (LVR) method with an integral OSC filter" which published by Johan Trygg and Svante Wold at 2003 <doi:10.1002/cem.775>. 'O2PLS' is a bidirectional multivariate regression method that aims to separate the covariance between two data sets (it was recently extended to multiple data sets) (Löfstedt and Trygg, 2011 <doi:10.1002/cem.1388>; Löfstedt et al., 2012 <doi:10.1016/j.aca.2013.06.026>) from the systematic sources of variance being specific for each data set separately.
Author: Kai Guo [aut, cre], Junguk Hur [aut], Eva Feldman [aut]
Maintainer: Kai Guo <guokai8@gmail.com>

This is a re-admission after prior archival of version 0.0.25 dated 2024-07-18

Diff between o2plsda versions 0.0.25 dated 2024-07-18 and 0.0.26 dated 2025-12-01

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Permanent link

Package NutrienTrackeR updated to version 1.4.0 with previous version 1.3.0 dated 2023-07-10

Title: Food Composition Information and Dietary Assessment
Description: Provides a tool set for food information and dietary assessment. It uses food composition data from several reference databases, including: 'USDA' (United States), 'CIQUAL' (France), 'BEDCA' (Spain), 'CNF' (Canada) and 'STFCJ' (Japan). 'NutrienTrackeR' calculates the intake levels for both macronutrient and micronutrients, and compares them with the recommended dietary allowances (RDA). It includes a number of visualization tools, such as time series plots of nutrient intake, and pie-charts showing the main foods contributing to the intake level of a given nutrient. A shiny app exposing the main functionalities of the package is also provided.
Author: Andrea Rodriguez-Martinez [aut], Rafael Ayala [aut, cre] , Mark Balchunas [aut], Pablo Hernandez [aut] , Lara Selles Vidal [aut]
Maintainer: Rafael Ayala <rafaelayalahernandez@gmail.com>

Diff between NutrienTrackeR versions 1.3.0 dated 2023-07-10 and 1.4.0 dated 2025-12-01

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Package and updated to version 0.1.7 with previous version 0.1.6 dated 2025-02-25

Title: Construct Natural-Language Lists with Internationalization
Description: Construct language-aware lists. Make "and"-separated and "or"-separated lists that automatically conform to the user's language settings.
Author: Alexander Rossell Hayes [aut, cre, cph] , Unicode, Inc. [dtc] , Flavia Rossell Hayes [ill]
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

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Package ISEtools (with last version 3.2.0) was removed from CRAN

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

2022-10-19 3.2.0

Permanent link
Package emend (with last version 0.1.0) was removed from CRAN

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

2025-04-01 0.1.0

Permanent link
Package bindr updated to version 0.1.3 with previous version 0.1.2 dated 2024-11-21

Title: Parametrized Active Bindings
Description: Provides a simple interface for creating active bindings where the bound function accepts additional arguments.
Author: Kirill Mueller [aut, cre] , RStudio [cph, fnd]
Maintainer: Kirill Mueller <kirill@cynkra.com>

Diff between bindr versions 0.1.2 dated 2024-11-21 and 0.1.3 dated 2025-12-01

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Permanent link

Package yulab.utils updated to version 0.2.2 with previous version 0.2.1 dated 2025-08-19

Title: Supporting Functions for Packages Maintained by 'YuLab-SMU'
Description: Miscellaneous functions commonly used by 'YuLab-SMU'.
Author: Guangchuang Yu [aut, cre]
Maintainer: Guangchuang Yu <guangchuangyu@gmail.com>

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Package text2vec updated to version 0.6.6 with previous version 0.6.4 dated 2023-11-09

Title: Modern Text Mining Framework for R
Description: Fast and memory-friendly tools for text vectorization, topic modeling (LDA, LSA), word embeddings (GloVe), similarities. This package provides a source-agnostic streaming API, which allows researchers to perform analysis of collections of documents which are larger than available RAM. All core functions are parallelized to benefit from multicore machines.
Author: Dmitriy Selivanov [aut, cre, cph], Manuel Bickel [aut, cph] , Qing Wang [aut, cph]
Maintainer: Dmitriy Selivanov <selivanov.dmitriy@gmail.com>

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Package ssdtools updated to version 2.5.0 with previous version 2.4.0 dated 2025-09-12

Title: Species Sensitivity Distributions
Description: Species sensitivity distributions are cumulative probability distributions which are fitted to toxicity concentrations for different species as described by Posthuma et al.(2001) <isbn:9781566705783>. The ssdtools package uses Maximum Likelihood to fit distributions such as the gamma, log-logistic, log-normal and log-normal log-normal mixture. Multiple distributions can be averaged using Akaike Information Criteria. Confidence intervals on hazard concentrations and proportions are produced by bootstrapping.
Author: Joe Thorley [aut, cre] , Rebecca Fisher [aut], David Fox [aut], Carl Schwarz [aut], Angeline Tillmanns [ctb], Seb Dalgarno [ctb] , Kathleen McTavish [ctb], Heather Thompson [ctb], Doug Spry [ctb], Rick van Dam [ctb], Graham Batley [ctb], Ali Azizishi [...truncated...]
Maintainer: Joe Thorley <joe@poissonconsulting.ca>

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Package spatstat updated to version 3.5-0 with previous version 3.4-1 dated 2025-09-28

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

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Package Sequential updated to version 4.5.2 with previous version 4.5.1 dated 2025-10-29

Title: Exact Sequential Analysis for Poisson and Binomial Data
Description: Functions to calculate exact critical values, statistical power, expected time to signal, and required sample sizes for performing exact sequential analysis. All these calculations can be done for either Poisson or binomial data, for continuous or group sequential analyses, and for different types of rejection boundaries. In case of group sequential analyses, the group sizes do not have to be specified in advance and the alpha spending can be arbitrarily settled. For regression versions of the methods, Monte Carlo and asymptotic methods are used.
Author: Ivair Ramos Silva [aut, cre], Martin Kulldorff [aut]
Maintainer: Ivair Ramos Silva <ivair@ufop.edu.br>

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Package runner updated to version 0.4.5 with previous version 0.4.4 dated 2024-03-03

Title: Running Operations for Vectors
Description: Lightweight library for rolling windows operations. Package enables full control over the window length, window lag and a time indices. With a runner one can apply any R function on a rolling windows. The package eases work with equally and unequally spaced time series.
Author: Dawid Kaledkowski [aut, cre]
Maintainer: Dawid Kaledkowski <dawid.kaledkowski@gmail.com>

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Package fracture updated to version 0.2.2 with previous version 0.2.1 dated 2022-05-21

Title: Convert Decimals to Fractions
Description: Provides functions for converting decimals to a matrix of numerators and denominators or a character vector of fractions. Supports mixed or improper fractions, finding common denominators for vectors of fractions, limiting denominators to powers of ten, and limiting denominators to a maximum value. Also includes helper functions for finding the least common multiple and greatest common divisor for a vector of integers. Implemented using C++ for maximum speed.
Author: Alexander Rossell Hayes [aut, cre, cph]
Maintainer: Alexander Rossell Hayes <alexander@rossellhayes.com>

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Package CBPS updated to version 0.24 with previous version 0.23 dated 2022-01-18

Title: Covariate Balancing Propensity Score
Description: Implements the covariate balancing propensity score (CBPS) proposed by Imai and Ratkovic (2014) <DOI:10.1111/rssb.12027>. The propensity score is estimated such that it maximizes the resulting covariate balance as well as the prediction of treatment assignment. The method, therefore, avoids an iteration between model fitting and balance checking. The package also implements optimal CBPS from Fan et al. (in-press) <DOI:10.1080/07350015.2021.2002159>, several extensions of the CBPS beyond the cross-sectional, binary treatment setting. They include the CBPS for longitudinal settings so that it can be used in conjunction with marginal structural models from Imai and Ratkovic (2015) <DOI:10.1080/01621459.2014.956872>, treatments with three- and four-valued treatment variables, continuous-valued treatments from Fong, Hazlett, and Imai (2018) <DOI:10.1214/17-AOAS1101>, propensity score estimation with a large number of covariates from Ning, Peng, and Imai (2020) <D [...truncated...]
Author: Christian Fong [aut, cre], Marc Ratkovic [aut], Kosuke Imai [aut], Chad Hazlett [ctb], Xiaolin Yang [ctb], Sida Peng [ctb], Inbeom Lee [ctb]
Maintainer: Christian Fong <cjfong@umich.edu>

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