Title: Betas-Select in Structural Equation Models and Linear Models
Description: It computes betas-select, coefficients after standardization in
structural equation models and regression models, standardizing only selected
variables. Supports models with moderation, with product terms formed after
standardization. It also offers confidence intervals that account for
standardization, including bootstrap confidence intervals as proposed by
Cheung et al. (2022) <doi:10.1037/hea0001188>. An introduction to the package
can be found in Sun et al. (2026) <doi:10.1080/00273171.2026.2672692>.
Author: Shu Fai Cheung [aut, cre] ,
Rong Wei Sun [aut] ,
Florbela Chang [aut] ,
Wendie Yang [aut] ,
Sing-Hang Cheung [aut]
Maintainer: Shu Fai Cheung <shufai.cheung@gmail.com>
Diff between betaselectr versions 0.1.4 dated 2026-04-07 and 0.2.1 dated 2026-06-09
DESCRIPTION | 11 MD5 | 142 NEWS.md | 7 R/lav_betaselect.R | 1372 ++--- R/lm_betaselect.R | 1567 +++--- R/lm_betaselect_methods.R | 5144 ++++++++++----------- README.md | 34 build/partial.rdb |binary build/vignette.rds |binary inst/CITATION |only inst/doc/betaselectr_glm.Rmd | 3 inst/doc/betaselectr_glm.html | 17 inst/doc/betaselectr_lav.Rmd | 7 inst/doc/betaselectr_lav.html | 20 inst/doc/betaselectr_lm.Rmd | 3 inst/doc/betaselectr_lm.html | 15 man/anova.lm_betaselect.Rd | 194 man/coef.lav_betaselect.Rd | 120 man/coef.lm_betaselect.Rd | 190 man/confint.lav_betaselect.Rd | 134 man/confint.lm_betaselect.Rd | 356 - man/data_test_medmod.Rd | 86 man/data_test_mod_cat.Rd | 70 man/data_test_mod_cat2.Rd | 76 man/data_test_mod_cat_binary.Rd | 68 man/figures |only man/getCall.lm_betaselect.Rd | 156 man/lav_betaselect.Rd | 811 +-- man/lm_betaselect.Rd | 969 +-- man/predict.glm_betaselect.Rd | 182 man/predict.lm_betaselect.Rd | 174 man/print.lav_betaselect.Rd | 298 - man/std_data.Rd | 90 man/summary.glm_betaselect.Rd | 524 +- man/summary.lm_betaselect.Rd | 444 - man/vcov.lm_betaselect.Rd | 282 - tests/testthat/test-lav_betaselect.R | 264 - tests/testthat/test-lav_betaselect_check.R | 96 tests/testthat/test-lav_betaselect_coef.R | 140 tests/testthat/test-lav_betaselect_confint.R | 84 tests/testthat/test-lav_betaselect_mg.R | 296 - tests/testthat/test-lav_betaselect_mg_eq.R | 288 - tests/testthat/test-lav_betaselect_mod.R | 200 tests/testthat/test-lav_betaselect_mod_Intercept.R | 180 tests/testthat/test-lav_betaselect_mod_boot_1.R | 140 tests/testthat/test-lav_betaselect_mod_boot_2.R | 114 tests/testthat/test-lav_betaselect_mod_boot_3.R | 104 tests/testthat/test-lav_betaselect_mod_boot_4.R | 110 tests/testthat/test-lav_betaselect_mod_colon.R | 200 tests/testthat/test-lav_betaselect_mod_mg.R | 240 tests/testthat/test-lav_betaselect_mod_no_center.R | 168 tests/testthat/test-lav_betaselect_one_iv.R | 204 tests/testthat/test-lav_betaselect_ord.R | 136 tests/testthat/test-lav_betaselect_parallel.R | 122 tests/testthat/test-lav_betaselect_print_ustd.R | 82 tests/testthat/test-lav_betaselect_tmp.R | 136 tests/testthat/test-lav_betaselect_user_1.R | 136 tests/testthat/test-lav_betaselect_user_2.R | 83 tests/testthat/test-lav_betaselect_user_boot_1.R | 168 tests/testthat/test_find_all_products_cats.R | 102 tests/testthat/test_glm_betaselect_skip_def.R | 28 vignettes/apa.csl | 3832 +++++++-------- vignettes/articles/apa.csl | 3832 +++++++-------- vignettes/articles/lav_betaselect_technical.Rmd | 495 +- vignettes/articles/lm_betaselect_technical.Rmd | 207 vignettes/articles/references.bib | 16 vignettes/betaselectr_glm.Rmd | 3 vignettes/betaselectr_glm.Rmd.original | 821 +-- vignettes/betaselectr_lav.Rmd | 7 vignettes/betaselectr_lav.Rmd.original | 811 +-- vignettes/betaselectr_lm.Rmd | 3 vignettes/betaselectr_lm.Rmd.original | 845 +-- vignettes/references.bib | 362 - 73 files changed, 14375 insertions(+), 14246 deletions(-)
Title: Soil Health Assessment Models for Assessing Soil Conditions and
Suitability
Description: Soil health assessment builds information to improve decision in
soil management. It facilitates assessment of soil conditions for crop suitability [such as those given by FAO
<https://www.fao.org/land-water/databases-and-software/crop-information/en/>],
groundwater recharge, fertility, erosion, salinization [<doi:10.1002/ldr.4211>],
carbon sequestration, irrigation potential, and status of soil resources.
Author: Christian Thine Omuto [aut, cre]
Maintainer: Christian Thine Omuto <thineomuto@yahoo.com>
Diff between soilassessment versions 1.3.0 dated 2026-04-22 and 1.3.1 dated 2026-06-09
DESCRIPTION | 8 ++++---- MD5 | 4 ++-- R/imageIndices.R | 21 ++++----------------- 3 files changed, 10 insertions(+), 23 deletions(-)
More information about soilassessment at CRAN
Permanent link
Title: Twin Support Vector Machines
Description: Provides twin support vector machine classifiers and visualization
tools for small to moderate classification problems. Includes one-vs-one
multi-class classification and a standard support vector machine baseline
for comparison.
Author: Shamika Tissera [aut, cre]
Maintainer: Shamika Tissera <nimeshshamika@gmail.com>
Diff between twinsvm versions 0.0.1 dated 2026-06-08 and 0.0.2 dated 2026-06-09
DESCRIPTION | 6 +++--- MD5 | 9 +++++---- NEWS.md |only README.md | 2 +- inst/doc/twinsvm.html | 6 +++--- tests/testthat/test-multiclass.R | 8 +++----- 6 files changed, 15 insertions(+), 16 deletions(-)
Title: Reproduce Statistical Analyses and Meta-Analyses
Description: Includes data analysis and meta-analysis functions (e.g., to
calculate effect sizes and 95% Confidence Intervals (CI) on Standardised
Effect Sizes (d) for AB/BA cross-over repeated-measures experimental
designs), data presentation functions (e.g., density curve overlaid on
histogram),and the data sets analyzed in different research papers in
software engineering (e.g., related to software defect prediction or multi-
site experiment concerning the extent to which structured abstracts were
clearer and more complete than conventional abstracts) to streamline
reproducible research in software engineering.
Author: Lech Madeyski [cre, aut, ctb] ,
Barbara Kitchenham [aut, ctb] ,
Tomasz Lewowski [aut, ctb] ,
Marian Jureczko [ctb] ,
David Budgen [ctb] ,
Pearl Brereton [ctb] ,
Jacky Keung [ctb] ,
Stuart Charters [ctb] ,
Shirley Gibbs [ctb] ,
Amnart Pohthong [ctb] , [...truncated...]
Maintainer: Lech Madeyski <lech.madeyski@gmail.com>
Diff between reproducer versions 0.5.3 dated 2023-10-18 and 0.6.0 dated 2026-06-09
DESCRIPTION | 20 +- MD5 | 24 +-- NAMESPACE | 3 NEWS.md | 11 + R/MetaAnalysisForFamiliesOfExperimentsSR.R | 4 R/MunzelBrunnerPairedRankTest.R |only R/rPaperFunctions.R | 2 R/reproducer.R | 10 - README.md | 168 +++++++++++++++++++++- data/MunzelBrunner02.PGI.rda |only inst/CITATION | 38 +--- man/MunzelBrunner02.PGI.Rd |only man/pairedRankTest.Rd |only man/pairedSignTest.Rd |only man/rSimulations.Rd | 6 tests/testthat/test-MunzelBrunnerPairedRankTest.R |only 16 files changed, 221 insertions(+), 65 deletions(-)
Title: Distance-Based Learning for Mixed-Type Data
Description: Provides tools for constructing, computing, and using distance
measures for numerical, categorical, and mixed-type data. The package
implements a flexible framework in which continuous and categorical
components can be combined under additive, commensurable, and
association-aware specifications. Supported methods include classical
distances such as Gower, Euclidean, Manhattan, and Mahalanobis-type
distances; categorical dissimilarities such as simple matching,
occurrence-frequency, and association-based measures; and mixed-type
presets designed to reduce biases due to variable type, scale,
distribution, redundancy, and number of categories. The package also
provides scaling options, supervised and unsupervised distance
constructions, leave-one-variable-out tools for distance-based variable
importance, and integration with distance-based learning workflows such
as nearest-neighbour prediction, partitioning around medoids, and
spectral clustering. Methods are motivated by van de Velden,
[...truncated...]
Author: Alfonso Iodice D'Enza [aut, cre],
Angelos Markos [aut],
Michel van de Velden [aut],
Carlo Cavicchia [aut]
Maintainer: Alfonso Iodice D'Enza <iodicede@unina.it>
Diff between manydist versions 0.4.9 dated 2026-02-04 and 0.5.0 dated 2026-06-09
manydist-0.4.9/manydist/man/cdist.Rd |only manydist-0.4.9/manydist/man/ndist.Rd |only manydist-0.5.0/manydist/DESCRIPTION | 67 manydist-0.5.0/manydist/MD5 | 85 manydist-0.5.0/manydist/NAMESPACE | 159 + manydist-0.5.0/manydist/NEWS.md |only manydist-0.5.0/manydist/R/all_dist_methods_specs.R |only manydist-0.5.0/manydist/R/benchmark_mdist.R |only manydist-0.5.0/manydist/R/cat_custom_delta.R | 363 +-- manydist-0.5.0/manydist/R/cat_delta.R | 474 ++-- manydist-0.5.0/manydist/R/cdist.R | 467 ++-- manydist-0.5.0/manydist/R/compare_lovo_mdist.R |only manydist-0.5.0/manydist/R/compare_lovo_mdist_methods.R |only manydist-0.5.0/manydist/R/congruence_coeff.R |only manydist-0.5.0/manydist/R/daisy_gower_dist.R |only manydist-0.5.0/manydist/R/delta_int_knn.R |only manydist-0.5.0/manydist/R/delta_knn_ba.R |only manydist-0.5.0/manydist/R/dist_methods_tbl.R |only manydist-0.5.0/manydist/R/dist_model_helpers.R |only manydist-0.5.0/manydist/R/dist_to_affinity.R |only manydist-0.5.0/manydist/R/dkss_preprocessing.R |only manydist-0.5.0/manydist/R/gen_mixed.R |only manydist-0.5.0/manydist/R/generate_dataset.R |only manydist-0.5.0/manydist/R/getCall_methods.R |only manydist-0.5.0/manydist/R/gower_recipe.R | 27 manydist-0.5.0/manydist/R/gudmm_calculate_R_MI.R |only manydist-0.5.0/manydist/R/gudmm_distance_categorical_exact.R |only manydist-0.5.0/manydist/R/gudmm_distance_dependency_mixed_matrix.R |only manydist-0.5.0/manydist/R/gudmm_jensen_shannon.R |only manydist-0.5.0/manydist/R/gudmm_mutual_info_classif.R |only manydist-0.5.0/manydist/R/gudmm_mutual_info_regression.R |only manydist-0.5.0/manydist/R/gudmm_mutual_info_score.R |only manydist-0.5.0/manydist/R/gudmm_preprocessing.R |only manydist-0.5.0/manydist/R/idist.R |only manydist-0.5.0/manydist/R/indicator_based.R | 904 ++----- manydist-0.5.0/manydist/R/knn_dist_functions.R |only manydist-0.5.0/manydist/R/knn_dist_parsnip_registration.R |only manydist-0.5.0/manydist/R/lovo_mdist.R |only manydist-0.5.0/manydist/R/lovo_mdist_methods.R |only manydist-0.5.0/manydist/R/lovo_method_spec.R |only manydist-0.5.0/manydist/R/make_mdist_recipe.R |only manydist-0.5.0/manydist/R/mdist.R | 1146 +++++++--- manydist-0.5.0/manydist/R/mdist_class.R |only manydist-0.5.0/manydist/R/mdist_summary_impl.R |only manydist-0.5.0/manydist/R/mg_gower_dist_modify.R |only manydist-0.5.0/manydist/R/mg_gower_fcn.R |only manydist-0.5.0/manydist/R/mg_gower_mod_matrix.R |only manydist-0.5.0/manydist/R/mg_normalized_MI.R |only manydist-0.5.0/manydist/R/mg_self_adaptive_distance.R |only manydist-0.5.0/manydist/R/ndist.R | 153 - manydist-0.5.0/manydist/R/nearest_neighbor_dist_tunable.R |only manydist-0.5.0/manydist/R/pam_dist_functions.R |only manydist-0.5.0/manydist/R/spectral_cluster.R |only manydist-0.5.0/manydist/R/spectral_dist_functions.R |only manydist-0.5.0/manydist/R/spectral_from_dist.R |only manydist-0.5.0/manydist/R/step_mdist_functions.R |only manydist-0.5.0/manydist/R/summary.MDist.R |only manydist-0.5.0/manydist/R/sysdata.rda |only manydist-0.5.0/manydist/R/z_preproc.R | 2 manydist-0.5.0/manydist/R/zzz.R |only manydist-0.5.0/manydist/R/zzz_imports.R |only manydist-0.5.0/manydist/man/compare_lovo_mdist.Rd |only manydist-0.5.0/manydist/man/congruence_coeff.Rd |only manydist-0.5.0/manydist/man/gen_mixed.Rd |only manydist-0.5.0/manydist/man/generate_dataset.Rd |only manydist-0.5.0/manydist/man/lovo_mdist.Rd |only manydist-0.5.0/manydist/man/lovo_method_spec.Rd |only manydist-0.5.0/manydist/man/make_mdist_recipe.Rd |only manydist-0.5.0/manydist/man/mdist.Rd | 245 +- manydist-0.5.0/manydist/man/mdist_summary_impl.Rd |only manydist-0.5.0/manydist/man/nearest_neighbor_dist.Rd |only manydist-0.5.0/manydist/man/pam_dist.Rd |only manydist-0.5.0/manydist/man/spectral_dist.Rd |only manydist-0.5.0/manydist/man/spectral_from_dist.Rd |only manydist-0.5.0/manydist/man/step_mdist.Rd |only 75 files changed, 2301 insertions(+), 1791 deletions(-)
Title: Confidence Curves and P-Value Functions for Meta-Analysis
Description: Provides tools for the combination of individual study results in
meta-analyses using 'p-value' functions. Implements various combination methods
including those by Fisher, Stouffer, Tippett, Edgington along with
weighted generalizations. Contains functionality for the visualization
and calculation of confidence curves and drapery plots to summarize
evidence across studies.
Author: Saverio Fontana [aut, cre] ,
Felix Hofmann [aut] ,
Leonhard Held [aut] ,
Samuel Pawel [aut]
Maintainer: Saverio Fontana <savefontana@gmail.com>
Diff between confMeta versions 0.1.0 dated 2026-04-20 and 0.1.1 dated 2026-06-09
DESCRIPTION | 6 +- MD5 | 16 +++---- NAMESPACE | 1 NEWS.md | 9 +++- R/autoplot_pfun.R | 96 ++++++++++++++++++++++++++++++++----------- R/confMeta.R | 62 +++++++++++++++------------ inst/doc/confMeta-usage.html | 8 +-- man/autoplot.confMeta.Rd | 5 ++ man/confMeta.Rd | 24 +++++++--- 9 files changed, 154 insertions(+), 73 deletions(-)
Title: Vertical Profiles of Biological Signals in Weather Radar Data
Description: 'R' implementation of the 'vol2bird' software for generating vertical profiles
of birds and other biological signals in weather radar data. See Dokter et al.
(2011) <doi:10.1098/rsif.2010.0116> for a paper describing the methodology.
Author: Anders Henja [aut] ,
Adriaan M. Dokter [aut, cre] ,
Alexander Tedeschi [ctb] ,
Tsung-Yu Lin [ctb] ,
Subranshu Maji [ctb] ,
Daniel Sheldon [ctb] ,
Bart Kranstauber [ctb] ,
Jurriaan H. Spaaks [ctb] ,
Lourens Veen [ctb] ,
Iwan Holleman [ctb] ,
Hidde Lei [...truncated...]
Maintainer: Adriaan M. Dokter <vol2birdr@cornell.edu>
Diff between vol2birdR versions 1.2.0 dated 2025-09-02 and 1.3.0 dated 2026-06-09
DESCRIPTION | 18 MD5 | 38 NEWS.md | 40 R/rsl2odim.R | 4 R/vol2bird_config.R | 4 README.md | 4 inst/COPYRIGHTS | 22 inst/librsl/wsr88d_locations.dat | 377 +++--- man/rsl2odim.Rd | 4 man/vol2birdR-package.Rd | 4 man/vol2bird_config.Rd | 4 src/RaveIO.cpp | 39 src/includes/libvol2bird/constants.h | 4 src/includes/libvol2bird/libvol2bird.h | 15 src/librsl/wsr88d.c | 6 src/librsl/wsr88d_m31.c | 17 src/libvol2bird/librsl.c | 7 src/libvol2bird/libvol2bird.c | 1764 +++++++++++++++-------------- src/mistnet.cpp | 8 tests/testthat/test-class_vol2birdconfig.R | 27 20 files changed, 1350 insertions(+), 1056 deletions(-)
Title: Water Quality Assessment and Environmental Compliance in Brazil
Description: Tools to import, clean, validate, and analyze freshwater quality data
in Brazil. Implements water quality indices including the Water Quality Index
('WQI'/'IQA') using the weighted geometric mean following 'CETESB' methodology,
the Trophic State Index ('TSI'/'IET') after Carlson (1977)
<doi:10.4319/lo.1977.22.2.0361> and Lamparelli (2004)
<https://teses.usp.br/teses/disponiveis/41/41134/tde-20032006-075813/publico/TeseLamparelli2004.pdf>,
and the National Sanitation Foundation Water Quality Index ('NSF WQI', Brown
(1970)). The package also checks compliance with Brazilian standard 'CONAMA'
Resolution 357/2005
<https://conama.mma.gov.br/?id=450&option=com_sisconama&task=arquivo.download>
including the legal frequency rule (Art. 15, 80% conformity over six or more
samples per year), and provides seasonal analysis with regional flow-season
calendars, pollutant load computation, exceedance probability estimation, 'IET'
visualization, and multivariate 'PCA' tools f [...truncated...]
Author: Vinicius Saraiva Santos [aut, cre]
Maintainer: Vinicius Saraiva Santos <vinisaraiva@gmail.com>
Diff between tikatuwq versions 0.8.2 dated 2026-01-16 and 0.9.0 dated 2026-06-09
DESCRIPTION | 26 +++ MD5 | 66 +++++++--- NAMESPACE | 40 ++++++ NEWS.md | 67 ++++++++++ R/balnear.R |only R/conama_freq.R |only R/iqa.R | 171 +++++++++++++++----------- R/load_exceedance.R |only R/mk_seasonal.R |only R/nsfwqi.R | 217 ++++++++++++++++++--------------- R/plot_iet.R |only R/plot_map_quality.R |only R/seasonal.R |only R/testando.R | 5 R/tikatuwq-package.R | 2 R/wq_buranhem.R | 18 ++ R/wq_pca.R |only README.md | 105 ++++++++++++--- build/partial.rdb |only inst/ANALISE_TECNICA_TIKATUWQ.md |only inst/CRAN-SUBMISSION |only inst/README_install.md |only inst/doc/tikatuwq-methods.html | 39 +++-- inst/doc/tikatuwq-workflow.html | 92 ++++++------- inst/doc/tikatuwq.html | 11 - inst/extdata/conama_limits.csv | 110 ++++++++++++++-- inst/run_check_cran.R |only man/assign_season.Rd |only man/balnear_check.Rd |only man/compare_seasons.Rd |only man/compute_load.Rd |only man/conama_freq_check.Rd |only man/exceedance_prob.Rd |only man/iqa.Rd | 75 +++++++---- man/mk_seasonal.Rd |only man/nsfwqi.Rd | 90 ++++++++----- man/plot_iet.Rd |only man/plot_map_quality.Rd |only man/tikatuwq-package.Rd | 2 man/wq_demo.Rd | 13 + man/wq_pca.Rd |only tests/testthat/test-balnear.R |only tests/testthat/test-conama_freq.R |only tests/testthat/test-iqa-geometric.R |only tests/testthat/test-load_exceedance.R |only tests/testthat/test-mk_seasonal.R |only tests/testthat/test-plot_iet.R |only tests/testthat/test-plot_map_quality.R |only tests/testthat/test-seasonal.R |only tests/testthat/test-wq_pca.R |only 50 files changed, 782 insertions(+), 367 deletions(-)
Title: Savvy Parity Regression Model Estimation with 'savvyPR'
Description: Implements the Savvy Parity Regression 'savvyPR' methodology
for multivariate linear regression analysis. The package solves an
optimization problem that balances the contribution of each predictor
variable to ensure estimation stability in the presence of
multicollinearity. It supports two distinct parameterization methods,
a Budget-based approach that allocates a fixed loss contribution to
each predictor, and a Target-based approach (t-tuning) that utilizes
a relative elasticity weight for the response variable. The package
provides comprehensive tools for model estimation, risk distribution
analysis, and parameter tuning via cross-validation (PR1, PR2, and
PR3 model types) to optimize predictive accuracy. Methods are based
on Asimit, Chen, Ichim and Millossovich (2026)
<https://openaccess.city.ac.uk/id/eprint/37017/>.
Author: Ziwei Chen [aut, cre] ,
Vali Asimit [aut] ,
Pietro Millossovich [aut]
Maintainer: Ziwei Chen <Ziwei.Chen.3@citystgeorges.ac.uk>
Diff between savvyPR versions 0.1.1 dated 2026-04-07 and 0.1.2 dated 2026-06-09
savvyPR-0.1.1/savvyPR/tests/testthat/Rplots.pdf |only savvyPR-0.1.2/savvyPR/DESCRIPTION | 6 savvyPR-0.1.2/savvyPR/MD5 | 21 savvyPR-0.1.2/savvyPR/R/cv.savvyPR.R | 616 ++-- savvyPR-0.1.2/savvyPR/R/savvyPR.R | 582 ++-- savvyPR-0.1.2/savvyPR/build/vignette.rds |binary savvyPR-0.1.2/savvyPR/inst/doc/savvyPR_example.R | 302 +- savvyPR-0.1.2/savvyPR/inst/doc/savvyPR_example.html | 1620 ++++++------- savvyPR-0.1.2/savvyPR/man/cv.savvyPR.Rd | 16 savvyPR-0.1.2/savvyPR/man/savvyPR.Rd | 7 savvyPR-0.1.2/savvyPR/tests/testthat/test-plot_functions.R | 579 ++-- savvyPR-0.1.2/savvyPR/tests/testthat/test-savvyPR.R | 396 +-- 12 files changed, 2103 insertions(+), 2042 deletions(-)
Title: Personal Themes and Formatting Preferences
Description: A collection of utility functions, themes, and templates to
support personal data analysis workflows. Includes functions for
formatting numeric values as text, custom themes and color scales for
'ggplot2', and automatic formatting for tables created with 'gt'.
Author: W. Jake Thompson [aut, cre, cph]
Maintainer: W. Jake Thompson <wjakethompson@gmail.com>
Diff between wjake versions 1.0.0 dated 2026-05-20 and 1.0.1 dated 2026-06-09
DESCRIPTION | 6 +- MD5 | 10 +-- NEWS.md | 4 + README.md | 110 ++++++++++++++++++++--------------------- build/partial.rdb |binary tests/testthat/test-fmt-text.R | 22 ++++---- 6 files changed, 79 insertions(+), 73 deletions(-)
Title: 'Serpstat' API Wrapper
Description: The primary goal of 'Serpstat' API <https://api-docs.serpstat.com/docs/serpstat-public-api/jenasqbwtxdlr-introduction-to-serpstat-api>
is to reduce manual SEO (search engine optimization) and PPC (pay-per-click)
tasks. You can automate your keywords research or competitors analysis
with this API wrapper.
Author: Alex Danilin [aut, cre]
Maintainer: Alex Danilin <alexnikdanilin@gmail.com>
Diff between serpstatr versions 0.4.1 dated 2026-05-25 and 0.4.2 dated 2026-06-09
DESCRIPTION | 6 ++--- MD5 | 15 +++++++------- NAMESPACE | 1 NEWS.md | 4 +++ R/search_analytics.R | 46 +++++++++++++++++++++++++++++++++++++++++++ R/serpstatr.R | 18 +++------------- README.md | 1 man/serpstatr.Rd | 20 +++--------------- man/sst_sa_keyword_trends.Rd |only 9 files changed, 71 insertions(+), 40 deletions(-)
More information about stbimageheaders at CRAN
Permanent link
Title: Density-Based Spatial Clustering of Applications with Noise
(DBSCAN) and Related Algorithms
Description: A fast reimplementation of several density-based algorithms
of the DBSCAN family. Includes the clustering algorithms DBSCAN
(density-based spatial clustering of applications with noise) and
HDBSCAN (hierarchical DBSCAN), the ordering algorithm OPTICS (ordering
points to identify the clustering structure), shared nearest neighbor
clustering, and the outlier detection algorithms LOF (local outlier
factor) and GLOSH (global-local outlier score from hierarchies). The
implementations use the kd-tree data structure (from library ANN) for
faster k-nearest neighbor search. An R interface to fast kNN and
fixed-radius NN search is also provided. Hahsler, Piekenbrock and
Doran (2019) <doi:10.18637/jss.v091.i01>.
Author: Michael Hahsler [aut, cre, cph] ,
Matthew Piekenbrock [aut, cph],
Sunil Arya [ctb, cph],
David Mount [ctb, cph],
Claudia Malzer [ctb]
Maintainer: Michael Hahsler <mhahsler@lyle.smu.edu>
Diff between dbscan versions 1.2.4 dated 2025-12-19 and 1.2.5 dated 2026-06-09
DESCRIPTION | 8 ++++---- MD5 | 30 +++++++++++++++--------------- NEWS.md | 6 ++++++ R/dbscan.R | 8 ++++---- R/kNN.R | 7 ++++--- R/optics.R | 33 ++++++++++++++++----------------- R/reachability.R | 47 +++++++++++++++++++++++++---------------------- build/partial.rdb |binary build/vignette.rds |binary inst/doc/dbscan.pdf |binary inst/doc/hdbscan.html | 24 ++++++++++++------------ man/dbscan.Rd | 13 ++++++++----- man/kNN.Rd | 8 +++++--- man/optics.Rd | 36 +++++++++++++++++++----------------- man/reachability.Rd | 49 +++++++++++++++++++++++++++---------------------- vignettes/dbscan.bib | 5 +---- 16 files changed, 146 insertions(+), 128 deletions(-)
Title: Clustering-Based K-Nearest Neighbor Regression for Longitudinal
Data
Description: Implements the 'CKNNRLD' algorithm (Clustering-Based K-Nearest
Neighbor Regression for Longitudinal Data) for improving K-Nearest
Neighbor ('KNN') regression on longitudinal data through cluster-based
partitioning and localized prediction. Offers enhanced computational
efficiency and accuracy for high-volume longitudinal datasets. The
acronym 'KNN' stands for K-Nearest Neighbor. References: Loeloe MS,
Tabatabaei SM, Sefidkar R, Mehrparvar AH, Jambarsang S (2025).
"Boosting K-nearest neighbor regression performance for longitudinal
data through a novel learning approach." BMC Bioinformatics, 26, 232.
<doi:10.1186/s12859-025-06205-1>.
Author: Mohammad Sadegh Loeloe [aut, cre],
Seyyed Mohammad Tabatabaei [aut],
Reyhane Sefidkar [aut],
Amir Houshang Mehrparvar [aut],
Sara Jambarsang [aut, ths]
Maintainer: Mohammad Sadegh Loeloe <mslbiostat@gmail.com>
Diff between CKNNRLD versions 0.1.2 dated 2026-05-28 and 0.1.4 dated 2026-06-09
DESCRIPTION | 25 +++------ MD5 | 24 ++++---- NAMESPACE | 8 -- R/BestC.R | 127 +++++++++++------------------------------------ R/CKNNRLD.R | 52 +++++-------------- R/KNNRLD.R | 22 +++++--- R/Tuning_CKNNRLD.R | 140 +++++++++++----------------------------------------- R/Tuning_KNNRLD.R | 55 +++++++++++++------- man/BestC.Rd | 19 ++----- man/CKNNRLD.Rd | 24 +++----- man/CKNNRLD.tune.Rd | 30 ++++------- man/KNNRLD.Rd | 10 +-- man/KNNRLD.tune.Rd | 23 +++----- 13 files changed, 192 insertions(+), 367 deletions(-)
Title: Weighted Meta-Analysis with Pseudo-Populations
Description: Implementation of integrative weighting approaches for multiple observational studies and causal inferences. The package features three weighting approaches, each representing a special case of the unified weighting framework, introduced by Guha and Li (2024) <doi:10.1093/biomtc/ujae070>, which includes an extension of inverse probability weights for data integration settings.
Author: Subharup Guha [aut, cre],
Mengqi Xu [aut],
Chayce Reed [aut],
Kashish Priyam [aut],
Yi Li [aut]
Maintainer: Subharup Guha <Subharup.Guha@dartmouth.edu>
Diff between WMAP versions 1.3.0 dated 2026-06-05 and 1.3.1 dated 2026-06-09
DESCRIPTION | 6 - MD5 | 18 ++--- R/stage-1.R | 14 +++ R/stage-2.R | 48 ++++++++----- inst/doc/WMAP.R | 23 +----- inst/doc/WMAP.Rmd | 31 +------- inst/doc/WMAP.html | 166 +++++++++++++++++++++-------------------------- man/balancing.weights.Rd | 14 +++ man/causal.estimate.Rd | 47 +++++++------ vignettes/WMAP.Rmd | 31 +------- 10 files changed, 186 insertions(+), 212 deletions(-)
Title: Encapsulated 'REDCap' Projects for Synchronized Data Pipelines
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.
Author: Brandon Rose [cre, aut, cph] ,
Natalie Goulett [ctb]
Maintainer: Brandon Rose <thecodingdocs@gmail.com>
This is a re-admission after prior archival of version 0.1.0 dated 2026-05-21
Diff between REDCapSync versions 0.1.0 dated 2026-05-21 and 0.1.1 dated 2026-06-09
REDCapSync-0.1.0/REDCapSync/R/REDCap_API.R |only REDCapSync-0.1.0/REDCapSync/R/REDCap_log.R |only REDCapSync-0.1.0/REDCapSync/R/zzz.R |only REDCapSync-0.1.0/REDCapSync/tests/testthat/test-zzz.R |only REDCapSync-0.1.1/REDCapSync/DESCRIPTION | 10 REDCapSync-0.1.1/REDCapSync/MD5 | 80 ++-- REDCapSync-0.1.1/REDCapSync/NAMESPACE | 7 REDCapSync-0.1.1/REDCapSync/NEWS.md | 36 + REDCapSync-0.1.1/REDCapSync/R/REDCapSync-package.R | 7 REDCapSync-0.1.1/REDCapSync/R/REDCapSyncDataset.R | 15 REDCapSync-0.1.1/REDCapSync/R/cache.R | 11 REDCapSync-0.1.1/REDCapSync/R/config.R | 174 +++++++-- REDCapSync-0.1.1/REDCapSync/R/datasets.R | 9 REDCapSync-0.1.1/REDCapSync/R/project_helpers.R | 2 REDCapSync-0.1.1/REDCapSync/R/redcap_api.R |only REDCapSync-0.1.1/REDCapSync/R/redcap_log.R |only REDCapSync-0.1.1/REDCapSync/R/sync.R | 47 ++ REDCapSync-0.1.1/REDCapSync/R/tokens.R | 3 REDCapSync-0.1.1/REDCapSync/R/utils-assert.R | 4 REDCapSync-0.1.1/REDCapSync/R/utils-xlsx-csv.R | 208 ++++++----- REDCapSync-0.1.1/REDCapSync/R/utils.R | 6 REDCapSync-0.1.1/REDCapSync/README.md | 6 REDCapSync-0.1.1/REDCapSync/inst/WORDLIST | 2 REDCapSync-0.1.1/REDCapSync/inst/doc/Cache.R | 5 REDCapSync-0.1.1/REDCapSync/inst/doc/Cache.Rmd | 7 REDCapSync-0.1.1/REDCapSync/inst/doc/Cache.html | 21 - REDCapSync-0.1.1/REDCapSync/inst/doc/Datasets.R | 6 REDCapSync-0.1.1/REDCapSync/inst/doc/Datasets.Rmd | 6 REDCapSync-0.1.1/REDCapSync/inst/doc/Datasets.html | 24 - REDCapSync-0.1.1/REDCapSync/inst/doc/Projects.html | 40 +- REDCapSync-0.1.1/REDCapSync/inst/doc/REDCapSync.R | 4 REDCapSync-0.1.1/REDCapSync/inst/doc/REDCapSync.Rmd | 6 REDCapSync-0.1.1/REDCapSync/inst/doc/REDCapSync.html | 6 REDCapSync-0.1.1/REDCapSync/man/config.Rd | 135 +++++-- REDCapSync-0.1.1/REDCapSync/man/dataset.Rd | 21 + REDCapSync-0.1.1/REDCapSync/tests/testthat/test-cache.R | 2 REDCapSync-0.1.1/REDCapSync/tests/testthat/test-config.R | 130 +++++- REDCapSync-0.1.1/REDCapSync/tests/testthat/test-redcap_log.R | 42 +- REDCapSync-0.1.1/REDCapSync/tests/testthat/test-sync.R | 9 REDCapSync-0.1.1/REDCapSync/tests/testthat/test-tokens.R | 20 + REDCapSync-0.1.1/REDCapSync/tests/testthat/test-utils.R | 10 REDCapSync-0.1.1/REDCapSync/vignettes/Cache.Rmd | 7 REDCapSync-0.1.1/REDCapSync/vignettes/Datasets.Rmd | 6 REDCapSync-0.1.1/REDCapSync/vignettes/REDCapSync.Rmd | 6 44 files changed, 809 insertions(+), 331 deletions(-)
Title: LLM-Assisted Data Cleaning with Multi-Provider Support
Description: Detects and suggests fixes for semantic inconsistencies in data
frames by calling large language models (LLMs) through a unified,
provider-agnostic interface. Supported providers include 'OpenAI'
('GPT-4o', 'GPT-4o-mini') <https://platform.openai.com>,
'Anthropic' ('Claude') <https://www.anthropic.com>,
'Google' ('Gemini') <https://ai.google.dev>,
'Groq' (free-tier 'LLaMA' and 'Mixtral') <https://groq.com>,
and local 'Ollama' models <https://ollama.com>.
The package identifies issues that rule-based tools cannot detect:
abbreviation variants, typographic errors, case inconsistencies, and
malformed values. Results are returned as tidy data frames with column,
row index, detected value, issue type, suggested fix, and confidence
score. An offline fallback using statistical and fuzzy-matching methods
is provided for use without any application programming interface (API)
key. Interactive fix application with human review is supported via
'apply_fixes()'. Metho [...truncated...]
Author: Sadikul Islam [aut, cre] ,
Rajesh Kaushal [aut]
Maintainer: Sadikul Islam <sadikul.islamiasri@gmail.com>
Diff between llmclean versions 0.1.0 dated 2026-04-22 and 0.1.1 dated 2026-06-09
DESCRIPTION | 43 +++++++++++++++++++++++-------------------- MD5 | 6 +++--- inst/doc/llmclean-intro.html | 6 +++--- man/llmclean-package.Rd | 5 +++++ 4 files changed, 34 insertions(+), 26 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-11-08 1.0.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2019-11-15 0.1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2020-06-30 1.0.0
Title: Access Brazilian National Treasury Open Data APIs
Description: Provides a unified interface to access open data from the
Brazilian National Treasury ('Tesouro Nacional') and related government
APIs. Covers six data sources: 'SICONFI'
<https://apidatalake.tesouro.gov.br/docs/siconfi/> for fiscal reports
('RREO', 'RGF', 'DCA', 'MSC') and entity information; 'CUSTOS'
<https://apidatalake.tesouro.gov.br/docs/custos/> for federal
government cost data; 'SADIPEM'
<https://apidatalake.tesouro.gov.br/docs/sadipem/> for public debt and
credit operations; 'Transferencias Constitucionais'
<https://apiapex.tesouro.gov.br/aria/v1/transferencias_constitucionais/docs>
for constitutional transfers to states and municipalities; 'SIORG'
<https://estruturaorganizacional.dados.gov.br> for federal
organizational structure; and 'SIOPE' ('FNDE'/'MEC') for education
spending data. Features automatic pagination, in-memory caching,
retry logic, and tidy output.
Author: Andre Leite [aut, cre],
Marcos Wasilew [aut],
Hugo Vasconcelos [aut],
Carlos Amorin [aut],
Diogo Bezerra [aut],
Tiago Pereira [aut],
Fernando Barbalho [aut]
Maintainer: Andre Leite <leite@castlab.org>
Diff between tesouror versions 0.2.2 dated 2026-05-06 and 0.2.3 dated 2026-06-09
DESCRIPTION | 6 ++-- MD5 | 22 +++++++------- NEWS.md | 10 ++++++ R/siconfi.R | 23 +++++++++------ build/vignette.rds |binary inst/doc/siconfi.R | 10 ++++++ inst/doc/siconfi.Rmd | 19 ++++++++++++ inst/doc/siconfi.html | 48 ++++++++++++++++++++++---------- inst/doc/transferencias_pernambuco.html | 4 +- man/get_rreo.Rd | 17 +++++++---- tests/testthat/test-url-construction.R | 22 ++++++++++++++ vignettes/siconfi.Rmd | 19 ++++++++++++ 12 files changed, 153 insertions(+), 47 deletions(-)
Title: Robust Test Statistics for Structural Equation Models
Description: Supports penalized eigenvalue block-averaging and penalized
regression p-values (Foldnes, Moss, Grønneberg, 2024)
<doi:10.1080/10705511.2024.2372028>, including their extension to nested
model comparison (Foldnes, Grønneberg, Moss, 2026)
<doi:10.3758/s13428-026-02968-4>, as well as traditional p-values such as
Satorra-Bentler. All p-values can be calculated using unbiased or biased
gamma estimates (Du, Bentler, 2022) <doi:10.1080/10705511.2022.2063870> and
two choices of chi square statistics. The tests apply to any
minimum-discrepancy estimator -- ML, GLS, ULS, and categorical WLSMV/DWLS --
with experimental support for full-information maximum-likelihood (FIML) fits
under missing data.
Author: Jonas Moss [aut, cre] ,
Njal Foldnes [ctb] ,
Steffen Groenneberg [ctb]
Maintainer: Jonas Moss <jonas.moss.statistics@gmail.com>
Diff between semTests versions 0.7.1 dated 2025-10-09 and 0.9.0 dated 2026-06-09
semTests-0.7.1/semTests/R/derivatives.R |only semTests-0.7.1/semTests/man/laavan_tests.Rd |only semTests-0.7.1/semTests/man/sparsify.Rd |only semTests-0.9.0/semTests/DESCRIPTION | 32 semTests-0.9.0/semTests/MD5 | 112 - semTests-0.9.0/semTests/NAMESPACE | 9 semTests-0.9.0/semTests/NEWS.md |only semTests-0.9.0/semTests/R/checks.R |only semTests-0.9.0/semTests/R/fiml_fmg.R |only semTests-0.9.0/semTests/R/gamma.R | 451 +++--- semTests-0.9.0/semTests/R/get_a_matrix.R | 244 --- semTests-0.9.0/semTests/R/imhof.R |only semTests-0.9.0/semTests/R/lavaan_helper.R | 277 --- semTests-0.9.0/semTests/R/pvalues.R | 742 ++++++---- semTests-0.9.0/semTests/R/support.R |only semTests-0.9.0/semTests/R/tests.R | 194 +- semTests-0.9.0/semTests/R/utility.R | 193 +- semTests-0.9.0/semTests/README.md | 210 +- semTests-0.9.0/semTests/build |only semTests-0.9.0/semTests/inst |only semTests-0.9.0/semTests/man/check_lavaan.Rd |only semTests-0.9.0/semTests/man/check_supported.Rd |only semTests-0.9.0/semTests/man/check_supported_nested.Rd |only semTests-0.9.0/semTests/man/default.Rd | 24 semTests-0.9.0/semTests/man/eba_pvalue.Rd | 24 semTests-0.9.0/semTests/man/fiml_lambdas.Rd |only semTests-0.9.0/semTests/man/fiml_lambdas_nested.Rd |only semTests-0.9.0/semTests/man/fiml_saturated_moments.Rd |only semTests-0.9.0/semTests/man/fit_provenance.Rd |only semTests-0.9.0/semTests/man/gamma.Rd | 44 semTests-0.9.0/semTests/man/gamma_to_gamma_unbiased.Rd | 40 semTests-0.9.0/semTests/man/imhof_pvalue.Rd |only semTests-0.9.0/semTests/man/is_classic_nt.Rd |only semTests-0.9.0/semTests/man/is_fiml.Rd |only semTests-0.9.0/semTests/man/lambdas_nested.Rd |only semTests-0.9.0/semTests/man/lav_ugamma_nested_2000.Rd | 50 semTests-0.9.0/semTests/man/lavaan_tests.Rd |only semTests-0.9.0/semTests/man/nanull.Rd | 24 semTests-0.9.0/semTests/man/nested_factor_2000.Rd |only semTests-0.9.0/semTests/man/pall.Rd | 24 semTests-0.9.0/semTests/man/peba_pvalue.Rd | 24 semTests-0.9.0/semTests/man/pols_pvalue.Rd | 24 semTests-0.9.0/semTests/man/print.semTests_pvalues.Rd |only semTests-0.9.0/semTests/man/pvalue_all.Rd | 24 semTests-0.9.0/semTests/man/pvalue_internal.Rd | 55 semTests-0.9.0/semTests/man/pvalues.Rd | 273 ++- semTests-0.9.0/semTests/man/rescale_missing.Rd |only semTests-0.9.0/semTests/man/scaled_f.Rd | 40 semTests-0.9.0/semTests/man/semTests-support.Rd |only semTests-0.9.0/semTests/man/split_input.Rd | 30 semTests-0.9.0/semTests/man/trad_pvalue.Rd | 46 semTests-0.9.0/semTests/man/ugamma.Rd | 24 semTests-0.9.0/semTests/man/ugamma_nested.Rd | 24 semTests-0.9.0/semTests/man/warn_fiml_information.Rd |only semTests-0.9.0/semTests/tests/testthat.R | 8 semTests-0.9.0/semTests/tests/testthat/setup.R | 93 - semTests-0.9.0/semTests/tests/testthat/test-checks.R |only semTests-0.9.0/semTests/tests/testthat/test-errors.R |only semTests-0.9.0/semTests/tests/testthat/test-estimators.R |only semTests-0.9.0/semTests/tests/testthat/test-imhof.R |only semTests-0.9.0/semTests/tests/testthat/test-internals.R |only semTests-0.9.0/semTests/tests/testthat/test-methods.R |only semTests-0.9.0/semTests/tests/testthat/test-nested-reduction.R |only semTests-0.9.0/semTests/tests/testthat/test-one-lambda.R | 17 semTests-0.9.0/semTests/tests/testthat/test-pvalues.R | 17 semTests-0.9.0/semTests/tests/testthat/test-split-input.R |only semTests-0.9.0/semTests/tests/testthat/test-support.R |only semTests-0.9.0/semTests/tests/testthat/test-unbiased-new.R | 54 semTests-0.9.0/semTests/tests/testthat/test-utility.R | 166 +- semTests-0.9.0/semTests/tests/testthat/values_groups.Rds |binary semTests-0.9.0/semTests/tests/testthat/values_nested_groups.Rds |binary semTests-0.9.0/semTests/tests/testthat/values_nested_no_groups.Rds |binary semTests-0.9.0/semTests/tests/testthat/values_no_groups.Rds |binary semTests-0.9.0/semTests/vignettes |only 74 files changed, 1830 insertions(+), 1783 deletions(-)
Title: Convert Data among QTL Mapping Packages
Description: Functions to convert data structures among the 'qtl2', 'qtl', and 'DOQTL' packages for mapping quantitative trait loci (QTL).
Author: Karl W Broman [aut, cre]
Maintainer: Karl W Broman <broman@wisc.edu>
Diff between qtl2convert versions 0.32 dated 2026-04-30 and 0.34 dated 2026-06-09
DESCRIPTION | 10 +++++----- MD5 | 10 +++++----- NEWS.md | 9 +++++++++ R/probs_qtl_to_qtl2.R | 6 +++++- README.md | 20 +++++++++++++++++++- man/qtl2convert-package.Rd | 5 +++++ 6 files changed, 48 insertions(+), 12 deletions(-)
Title: Toolkit for Encryption, Signatures and Certificates Based on
OpenSSL
Description: Bindings to OpenSSL libssl and libcrypto, plus custom SSH key parsers.
Supports RSA, DSA and EC curves P-256, P-384, P-521, and curve25519. Cryptographic
signatures can either be created and verified manually or via x509 certificates.
AES can be used in cbc, ctr or gcm mode for symmetric encryption; RSA for asymmetric
(public key) encryption or EC for Diffie Hellman. High-level envelope functions
combine RSA and AES for encrypting arbitrary sized data. Other utilities include key
generators, hash functions (md5, sha1, sha256, etc), base64 encoder, a secure random
number generator, and 'bignum' math methods for manually performing crypto
calculations on large multibyte integers.
Author: Jeroen Ooms [aut, cre] ,
Oliver Keyes [ctb]
Maintainer: Jeroen Ooms <jeroenooms@gmail.com>
Diff between openssl versions 2.4.1 dated 2026-05-14 and 2.4.2 dated 2026-06-09
DESCRIPTION | 8 +++--- MD5 | 22 +++++++++--------- NAMESPACE | 2 + NEWS | 3 ++ R/rsa.R | 14 +++++++++++ inst/doc/bignum.html | 32 +++++++++++++-------------- inst/doc/crypto_hashing.html | 4 +-- inst/doc/keys.html | 48 ++++++++++++++++++++--------------------- inst/doc/secure_rng.html | 18 +++++++-------- man/rsa_encrypt.Rd | 9 +++++++ src/rsa.c | 27 +++++++++++++++++++++++ tests/testthat/test_keys_rsa.R | 9 ++++++- 12 files changed, 129 insertions(+), 67 deletions(-)
Title: Recommended Learners for 'mlr3'
Description: Recommended Learners for 'mlr3'. Extends 'mlr3' with
interfaces to essential machine learning packages on CRAN. This
includes, but is not limited to: (penalized) linear and logistic
regression, linear and quadratic discriminant analysis, k-nearest
neighbors, naive Bayes, support vector machines, and gradient
boosting.
Author: Michel Lang [aut] ,
Quay Au [aut] ,
Stefan Coors [aut] ,
Patrick Schratz [aut] ,
Marc Becker [cre, aut] ,
John Zobolas [aut] ,
Alexander Winterstetter [ctb],
Toby Hocking [ctb]
Maintainer: Marc Becker <marcbecker@posteo.de>
Diff between mlr3learners versions 0.14.0 dated 2025-12-13 and 0.15.0 dated 2026-06-09
DESCRIPTION | 24 + MD5 | 189 +++++++------- NEWS.md | 15 + R/LearnerClassifCVGlmnet.R | 142 ++++++---- R/LearnerClassifGlmnet.R | 112 ++++---- R/LearnerClassifKKNN.R | 30 +- R/LearnerClassifLDA.R | 12 R/LearnerClassifLogReg.R | 50 ++- R/LearnerClassifMultinom.R | 19 + R/LearnerClassifNaiveBayes.R | 27 +- R/LearnerClassifNnet.R | 16 - R/LearnerClassifQDA.R | 16 - R/LearnerClassifRanger.R | 40 ++- R/LearnerClassifSVM.R | 36 +- R/LearnerClassifXgboost.R | 261 ++++++++------------ R/LearnerRegrCVGlmnet.R | 117 +++++--- R/LearnerRegrGlmnet.R | 102 +++---- R/LearnerRegrKKNN.R | 29 +- R/LearnerRegrKM.R | 21 + R/LearnerRegrLM.R | 28 +- R/LearnerRegrNnet.R | 11 R/LearnerRegrRanger.R | 92 +++++-- R/LearnerRegrSVM.R | 32 +- R/LearnerRegrXgboost.R | 144 +++++------ R/bibentries.R | 5 R/helpers.R | 3 R/helpers_glmnet.R | 37 +- R/helpers_ranger.R | 4 R/helpers_xgboost.R |only R/zzz.R | 6 README.md | 2 build/partial.rdb |binary inst/paramtest/helper.R | 3 inst/paramtest/test_paramtest_classif.cv_glmnet.R | 46 ++- inst/paramtest/test_paramtest_classif.glmnet.R | 43 +-- inst/paramtest/test_paramtest_classif.kknn.R | 13 inst/paramtest/test_paramtest_classif.lda.R | 26 + inst/paramtest/test_paramtest_classif.logreg.R | 29 +- inst/paramtest/test_paramtest_classif.multinom.R | 13 inst/paramtest/test_paramtest_classif.naive_bayes.R | 26 + inst/paramtest/test_paramtest_classif.nnet.R | 13 inst/paramtest/test_paramtest_classif.qda.R | 26 + inst/paramtest/test_paramtest_classif.ranger.R | 27 +- inst/paramtest/test_paramtest_classif.svm.R | 26 + inst/paramtest/test_paramtest_classif.xgboost.R | 37 +- inst/paramtest/test_paramtest_regr.cv_glmnet.R | 46 ++- inst/paramtest/test_paramtest_regr.glmnet.R | 43 +-- inst/paramtest/test_paramtest_regr.kknn.R | 13 inst/paramtest/test_paramtest_regr.km.R | 26 + inst/paramtest/test_paramtest_regr.lm.R | 26 + inst/paramtest/test_paramtest_regr.nnet.R | 13 inst/paramtest/test_paramtest_regr.ranger.R | 27 +- inst/paramtest/test_paramtest_regr.svm.R | 26 + inst/paramtest/test_paramtest_regr.xgboost.R | 37 +- man/mlr3learners-package.Rd | 6 man/mlr_learners_classif.cv_glmnet.Rd | 216 +++++++++------- man/mlr_learners_classif.glmnet.Rd | 194 +++++++------- man/mlr_learners_classif.kknn.Rd | 90 +++--- man/mlr_learners_classif.lda.Rd | 90 +++--- man/mlr_learners_classif.log_reg.Rd | 102 ++++--- man/mlr_learners_classif.multinom.Rd | 90 +++--- man/mlr_learners_classif.naive_bayes.Rd | 90 +++--- man/mlr_learners_classif.nnet.Rd | 92 +++---- man/mlr_learners_classif.qda.Rd | 90 +++--- man/mlr_learners_classif.ranger.Rd | 153 ++++++----- man/mlr_learners_classif.svm.Rd | 90 +++--- man/mlr_learners_classif.xgboost.Rd | 175 ++++++------- man/mlr_learners_regr.cv_glmnet.Rd | 220 +++++++++------- man/mlr_learners_regr.glmnet.Rd | 199 +++++++-------- man/mlr_learners_regr.kknn.Rd | 90 +++--- man/mlr_learners_regr.km.Rd | 90 +++--- man/mlr_learners_regr.lm.Rd | 96 +++---- man/mlr_learners_regr.nnet.Rd | 92 +++---- man/mlr_learners_regr.ranger.Rd | 176 +++++++------ man/mlr_learners_regr.svm.Rd | 90 +++--- man/mlr_learners_regr.xgboost.Rd | 176 ++++++------- tests/testthat/helper.R | 16 - tests/testthat/setup.R | 1 tests/testthat/teardown.R | 1 tests/testthat/test_classif_cv_glmnet.R | 56 ++++ tests/testthat/test_classif_glmnet.R | 39 ++ tests/testthat/test_classif_log_reg.R | 19 - tests/testthat/test_classif_multinom.R | 11 tests/testthat/test_classif_naive_bayes.R | 4 tests/testthat/test_classif_nnet.R | 4 tests/testthat/test_classif_qda.R | 1 tests/testthat/test_classif_ranger.R | 2 tests/testthat/test_classif_svm.R | 2 tests/testthat/test_classif_xgboost.R | 137 ++++++---- tests/testthat/test_regr_cv_glmnet.R | 29 ++ tests/testthat/test_regr_glmnet.R | 28 ++ tests/testthat/test_regr_km.R | 8 tests/testthat/test_regr_nnet.R | 4 tests/testthat/test_regr_ranger.R | 21 - tests/testthat/test_regr_svm.R | 2 tests/testthat/test_regr_xgboost.R | 152 ++++++++--- 96 files changed, 3122 insertions(+), 2329 deletions(-)
Title: Roadmap Footers for 'Reveal.js' Slides in 'Quarto' and 'R
Markdown'
Description: Adds section-aware roadmap footers to 'Reveal.js' slide decks
created with 'Quarto' or 'R Markdown'. The footer highlights completed,
current, and upcoming sections as slides advance. Supports multiple
visual styles, inherited section tags, roadmap-free slides, and
configurable colors, size, and positioning options.
Author: Tiger Tang [aut, cre]
Maintainer: Tiger Tang <tigerloveslobsters@gmail.com>
Diff between deckroadmap versions 0.1.4 dated 2026-04-21 and 0.1.5 dated 2026-06-09
DESCRIPTION | 9 +- MD5 | 19 +++--- NEWS.md | 12 +++ R/use_roadmap.R | 8 ++ README.md | 74 +++++++++++++++++++---- inst/assets/roadmap.js | 72 ++++++++++++++++++++-- inst/doc/get-started.Rmd | 53 +++++++++++++--- inst/doc/get-started.html | 129 +++++++++++++++++++++++++---------------- man/figures/slide_example4.gif |only man/use_roadmap.Rd | 7 +- vignettes/get-started.Rmd | 53 +++++++++++++--- 11 files changed, 329 insertions(+), 107 deletions(-)
Title: Computed ABC Analysis
Description: Identify the most relative data points by dividing a numeric data set into three classes A, B, and C, where class A items are the "import few", class C items are the "trivial many" with class B items being something in between, resembling the idea of the Pareto principle.
This ABC classification is done using an ABC curve, which plots cumulative "Yield" against "Effort", similar to a Lorenz curve. Class borders are then precisely mathematically defined on that curve, aiding in interpretation. Based on: Ultsch A, Lotsch J (2015) "Computed ABC Analysis for rational Selection of most informative Variables in multivariate Data". PLoS ONE 10(6): e0129767. <doi:10.1371/journal.pone.0129767>.
Author: Jorn Lotsch [aut] ,
Andre Himmelspach [aut, cre]
Maintainer: Andre Himmelspach <himmelspach@med.uni-frankfurt.de>
Diff between cABCanalysis versions 1.0 dated 2026-04-28 and 1.0.1 dated 2026-06-09
DESCRIPTION | 8 ++++---- MD5 | 10 +++++----- R/cABC_analysis.R | 2 +- R/cABC_special_cases.R | 2 +- README.md | 19 +++++++++++++++---- tests/testthat/test-cABC_analysis.R | 18 ++++++++++++++++++ 6 files changed, 44 insertions(+), 15 deletions(-)
Title: Most Likely Transformations: Documentation and Regression Tests
Description: Additional documentation, a package vignette and
regression tests for package mlt.
Author: Torsten Hothorn [aut, cre]
Maintainer: Torsten Hothorn <Torsten.Hothorn@R-project.org>
Diff between mlt.docreg versions 1.1-12 dated 2025-12-08 and 1.1-13 dated 2026-06-09
DESCRIPTION | 8 ++++---- MD5 | 18 +++++++++--------- build/vignette.rds |binary inst/NEWS.Rd | 7 +++++++ inst/doc/mlt.Rnw | 2 +- inst/doc/mlt.pdf |binary tests/AFT-Ex.R | 5 +++-- tests/AFT-Ex.Rout.save | 16 +++++++--------- vignettes/mlt.Rnw | 2 +- vignettes/mlt.bib | 27 +++++++++++++++------------ 10 files changed, 47 insertions(+), 38 deletions(-)
Title: Dynamic Time Warping Algorithms
Description: A comprehensive implementation of dynamic time warping
(DTW) algorithms in R. DTW computes the optimal (least cumulative
distance) alignment between points of two time series. Common DTW
variants covered include local (slope) and global (window)
constraints, subsequence matches, arbitrary distance definitions,
normalizations, minimum variance matching, and so on. Provides
cumulative distances, alignments, specialized plot styles, etc.,
as described in Giorgino (2009) <doi:10.18637/jss.v031.i07>.
Author: Toni Giorgino [aut, cre]
Maintainer: Toni Giorgino <toni.giorgino@gmail.com>
Diff between dtw versions 1.23-2 dated 2026-04-09 and 1.23-3 dated 2026-06-09
DESCRIPTION | 10 +++--- MD5 | 30 +++++++++--------- R/mvm.R | 1 R/stepPattern.R | 65 ++++++++++++++++++++++++++++++++++----- R/window.R | 5 --- build/partial.rdb |binary build/vignette.rds |binary inst/doc/dtw.R | 2 - inst/doc/dtw.pdf |binary man/dtwPlot.Rd | 8 ++-- man/dtwPlotDensity.Rd | 8 ++-- man/dtwPlotThreeWay.Rd | 8 ++-- man/dtwPlotTwoWay.Rd | 8 ++-- man/dtwWindowingFunctions.Rd | 5 +-- man/mvm.Rd | 4 ++ man/stepPattern.Rd | 70 +++++++++++++++++++++++++++++++++++++++---- 16 files changed, 165 insertions(+), 59 deletions(-)
Title: Global Value Chain Decomposition
Description: Four global value chain (GVC) decompositions are implemented.
The Leontief decomposition derives the value added origin of exports by
country and industry as in Hummels, Ishii and Yi (2001). The Koopman,
Wang and Wei (2014) decomposition splits country-level exports into 9
value added components, and the Wang, Wei and Zhu (2013) decomposition
splits bilateral exports into 16 value added components. The Borin and
Mancini (2019) decomposition splits country-, sector- or bilateral-level
exports into up to 13 value added and GVC components. Various GVC
indicators based on these decompositions are computed in the
complimentary 'gvc' package.
--- References: ---
Hummels, D., Ishii, J., & Yi, K. M. (2001). The nature and growth of
vertical specialization in world trade. Journal of international
Economics, 54(1), 75-96.
Koopman, R., Wang, Z., & Wei, S. J. (2014). Tracing value-added and double
counting in gross exports. American Economic Review, 104(2), 459-94.
Wang, Z., Wei, S. J., &a [...truncated...]
Author: Bastiaan Quast [aut, cre] ,
Fei Wang [aut],
Victor Stolzenburg [aut],
Oliver Reiter [ctb],
Sebastian Krantz [ctb]
Maintainer: Bastiaan Quast <bquast@gmail.com>
Diff between decompr versions 6.4.0 dated 2022-06-19 and 6.9.0 dated 2026-06-09
DESCRIPTION | 44 +++++++------- MD5 | 41 +++++++------ NAMESPACE | 1 NEWS.md | 12 +++ R/bm.R |only R/decomp.R | 19 +++--- R/decompr.R | 17 +++-- R/kww.R | 14 ++++ R/leontief.R | 2 R/load_tables_vectors.R | 2 R/wwz.R | 2 README.md | 4 - build/vignette.rds |binary inst/CITATION | 2 inst/doc/decompr.html | 141 +++++++++++++++++++++++---------------------- man/bm.Rd |only man/decomp.Rd | 12 ++- man/decompr-package.Rd | 16 +++-- man/kww.Rd | 16 ++++- man/leontief.Rd | 2 man/load_tables_vectors.Rd | 2 man/wwz.Rd | 2 tests/testthat/test_bm.R |only 23 files changed, 213 insertions(+), 138 deletions(-)
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-03-25 0.2.1
2026-03-23 0.2.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-02-25 0.1.2
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-04-01 1.0.4
2026-03-26 1.0.3
2026-02-03 1.0.2
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-04-20 2.0.1
2026-04-10 2.0.0
2026-01-19 1.6.2
2025-11-11 1.6.1
2025-07-29 1.6.0
2025-06-12 1.5.3
2025-05-04 1.5.2
2025-05-01 1.5.1
2025-03-17 1.5.0
2024-01-21 1.4.0
2023-09-11 1.3.0
2023-01-08 1.2.0
2022-06-10 1.1.0
2021-11-06 1.0.6
2021-10-29 1.0.5
2021-10-25 1.0.4
2021-09-03 1.0.3
2021-04-21 1.0.2
2021-03-02 1.0.1
2021-03-01 1.0.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2025-10-24 1.2.2
2025-06-05 1.2.1
2025-01-10 1.1.1
2024-12-19 1.1.0
2024-08-20 1.0.2
2024-04-08 1.0.1
2024-02-08 1.0.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2024-09-30 0.1.2
2023-09-07 0.1.1
2023-02-11 0.1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2025-09-02 2.0.1
2023-11-14 1.2.2
2023-05-19 1.1.2
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-04-02 1.0.0
2026-03-19 0.1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2025-12-09 1.0.1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-04-21 4.3.2
2026-04-07 4.3.1
2026-04-02 4.3.0
2026-01-08 4.2.3
2025-11-06 4.2.2
2025-06-02 4.2.1
2025-05-28 4.2.0
2024-07-09 4.1.2
2024-03-05 4.1.1
2024-02-01 4.1.0
2023-09-07 4.0.4
2023-03-09 4.0.3
2022-12-15 4.0.2
2022-05-04 4.0.1
2022-02-18 4.0.0
2021-11-13 3.2.3
2021-10-20 3.2.2
2021-09-29 3.2.1
2021-09-26 3.2.0
2021-06-21 3.1.4
2021-05-20 3.1.3
2021-03-16 3.1.2
2021-01-27 3.1.1
2021-01-18 3.1.0
2020-10-10 3.0.4
2020-08-03 3.0.3
2020-07-05 3.0.2
2020-06-18 3.0.1
2020-06-08 3.0.0
2020-05-11 2.2.5
2020-04-23 2.2.4
2020-03-02 2.2.3
2020-01-28 2.2.2
2020-01-21 2.2.1
2020-01-08 2.2.0
2019-10-15 2.1.4
2019-09-10 2.1.3
2019-08-08 2.1.2
2019-08-06 2.1.1
2019-07-12 2.1.0
2019-05-09 2.0.3
2019-03-03 2.0.2
2019-02-02 2.0.1
2019-01-02 2.0.0
2018-08-22 1.6.1
2018-07-26 1.6.0
2018-06-14 1.5.1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-01-18 0.1.1
2025-12-14 0.1.0
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2025-10-30 0.1.1
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-02-17 0.2.0
2025-10-28 0.1.2
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2026-06-02 1.9.3
2026-05-21 1.9.2
2026-05-14 1.9.1
2026-05-09 1.9.0
2026-04-03 1.8.6
2026-04-02 1.8.5
2026-01-29 1.8.4
2026-01-28 1.8.3
2025-05-16 1.8.2
2024-07-16 1.8.0
2023-12-11 1.7.0
2023-03-17 1.6.3
2023-01-06 1.6.2
2022-10-18 1.6.1
2022-05-26 1.6.0
2022-03-18 1.5.3
2022-02-14 1.5.2
2022-02-09 1.5.1
2021-06-02 1.5.0
2021-03-23 1.4.0
2021-01-11 1.3.9
2020-12-14 1.3.8
2020-11-11 1.3.7
2020-06-02 1.3.6
2020-02-04 1.3.5
2019-09-19 1.3.4
2019-08-30 1.3.3
2019-04-27 1.3.2
2019-02-08 1.3.1
2019-02-04 1.3.0
2018-10-25 1.2.9
2018-08-21 1.2.7
2018-06-11 1.2.4
Previous versions (as known to CRANberries) which should be available via the Archive link are:
2025-01-23 4.0.8
2023-04-07 4.0.5
2022-07-19 4.0.3
2022-07-18 4.0.2
2022-05-23 4.0.1
2021-12-09 3.1.2
2021-07-30 3.1.0
2021-04-10 3.0.2
2021-04-10 3.0.3
Title: Reinforcement Learning Tools for Multi-Armed Bandit
Description: A flexible general-purpose toolbox for implementing Rescorla-Wagner models
in multi-armed bandit tasks.
As the successor and functional extension of the 'binaryRL' package,
'multiRL' modularizes the Markov Decision Process (MDP) into six core
components. This framework enables users to construct custom models via
intuitive if-else syntax and define latent learning rules for agents.
For parameter estimation, it provides both likelihood-based
inference (MLE and MAP) and simulation-based inference (ABC and
RNN), with full support for parallel processing across subjects.
The workflow is highly standardized, featuring four main functions
that strictly follow the four-step protocol (and ten rules)
proposed by Wilson & Collins (2019) <doi:10.7554/eLife.49547>.
Beyond the three built-in models (TD, RSTD, and Utility), users
can easily derive new variants by declaring which variables are
treated as free parameters.
Author: YuKi [aut, cre] ,
Xinyu [aut]
Maintainer: YuKi <hmz1969a@gmail.com>
Diff between multiRL versions 0.3.7 dated 2026-03-31 and 0.4.5 dated 2026-06-09
DESCRIPTION | 6 MD5 | 135 ++--- R/base_setClass.R | 4 R/base_summary.R | 4 R/document_behrule.R | 19 R/document_control.R | 30 + R/document_params.R | 35 + R/document_priors.R | 6 R/engine_RNN.R | 62 +- R/engine_RNN3.R | 62 +- R/estimate_2_RNN.R | 65 ++ R/func_alpha.R | 87 ++- R/func_beta.R | 48 + R/func_delta.R | 47 + R/func_epsilon.R | 30 + R/func_gamma.R | 35 + R/func_zeta.R | 63 ++ R/process_1_input.R | 9 R/process_2_behrule.R | 13 R/process_3_record.R | 13 R/process_4_output.R | 145 +++-- R/process_5_metric.R | 5 R/step_1_run_m.R | 4 R/tool_fake_block.R |only data/WMT.rda |only man/RSTD.Rd | 118 ++-- man/TD.Rd | 116 ++-- man/Utility.Rd | 124 ++--- man/WMT.Rd |only man/algorithm.Rd | 82 +-- man/behrule.Rd | 151 +++--- man/colnames.Rd | 180 +++---- man/control.Rd | 892 ++++++++++++++++++------------------ man/data.Rd | 160 +++--- man/engine_ABC.Rd | 110 ++-- man/engine_RNN.Rd | 158 +++--- man/estimate_0_ENV.Rd | 102 ++-- man/estimate_1_LBI.Rd | 72 +- man/estimate_1_MAP.Rd | 134 ++--- man/estimate_1_MLE.Rd | 126 ++--- man/estimate_2_ABC.Rd | 124 ++--- man/estimate_2_RNN.Rd | 124 ++--- man/estimate_2_SBI.Rd | 68 +- man/estimation_methods.Rd | 136 ++--- man/fit_p.Rd | 184 +++---- man/func_alpha.Rd | 71 ++ man/func_beta.Rd | 38 + man/func_delta.Rd | 37 + man/func_epsilon.Rd | 25 - man/func_gamma.Rd | 31 + man/func_zeta.Rd | 60 ++ man/layer.Rd | 196 +++---- man/params.Rd | 769 +++++++++++++++---------------- man/plot.multiRL.replay.Rd | 56 +- man/policy.Rd | 122 ++-- man/priors.Rd | 6 man/process_1_input.Rd | 182 +++---- man/process_2_behrule.Rd | 68 +- man/process_3_record.Rd | 78 +-- man/process_4_output_cpp.Rd | 74 +- man/process_4_output_r.Rd | 74 +- man/process_5_metric.Rd | 82 +-- man/rcv_d.Rd | 240 ++++----- man/reduction.Rd | 120 ++-- man/rpl_e.Rd | 204 ++++---- man/run_m.Rd | 260 +++++----- man/settings.Rd | 194 +++---- man/summary-multiRL.model-method.Rd | 38 - man/system.Rd | 154 +++--- src/process_4_output.cpp | 319 +++++++----- 70 files changed, 4176 insertions(+), 3410 deletions(-)
Title: Tidy and Streamlined Metabolomics Data Workflows
Description: Facilitate tasks typically encountered during metabolomics data analysis including data import, filtering, missing value imputation (Stacklies et al. (2007) <doi:10.1093/bioinformatics/btm069>, Stekhoven et al. (2012) <doi:10.1093/bioinformatics/btr597>, Tibshirani et al. (2017) <doi:10.18129/B9.BIOC.IMPUTE>, Troyanskaya et al. (2001) <doi:10.1093/bioinformatics/17.6.520>), normalization (Bolstad et al. (2003) <doi:10.1093/bioinformatics/19.2.185>, Dieterle et al. (2006) <doi:10.1021/ac051632c>, Zhao et al. (2020) <doi:10.1038/s41598-020-72664-6>) transformation, centering and scaling (Van Den Berg et al. (2006) <doi:10.1186/1471-2164-7-142>) as well as statistical tests and plotting. 'metamorphr' introduces a tidy (Wickham et al. (2019) <doi:10.21105/joss.01686>) format for metabolomics data and is designed to make it easier to build elaborate analysis workflows and to integrate them with 'tidyverse' packages including 'dplyr' and [...truncated...]
Author: Yannik Schermer [aut, cre, cph]
Maintainer: Yannik Schermer <yannik.schermer@chem.rptu.de>
Diff between metamorphr versions 0.3.0 dated 2026-03-04 and 0.4.0 dated 2026-06-09
DESCRIPTION | 6 MD5 | 38 +- NAMESPACE | 4 NEWS.md | 9 R/convert.R |only R/internal_functions.R | 8 R/io.R | 148 ++++++-- R/misc.R | 55 +++ R/sysdata.rda |binary README.md | 10 inst/doc/conjugate-screening.html | 4 inst/extdata/toy_mzmine.csv |only man/calc_kmd.Rd | 2 man/convert_from_matrix.Rd |only man/convert_from_wide.Rd |only man/figures/functions.svg | 2 man/read_featuretable.Rd | 16 man/read_featuretable_mzmine.Rd |only man/remove_empty_cols.Rd |only tests/testthat/data/test_read_featuretable_empty_cols.csv |only tests/testthat/data/test_read_featuretable_mzmine_no_empty_cols.csv |only tests/testthat/test-convert_from_matrix.R |only tests/testthat/test-convert_from_wide.R |only tests/testthat/test-read_featuretable.R | 167 ++++++---- tests/testthat/test-read_featuretable_mzmine.R |only tests/testthat/test-remove_empty_cols.R |only 26 files changed, 345 insertions(+), 124 deletions(-)
Title: Online Changepoint Detection in Univariate and Multivariate Data
Streams
Description: Provides high-performance online changepoint detection in univariate and multivariate data
streams. Implements efficient 'C++' backends for the 'focus', 'md-focus' and 'np-focus'
algorithms, with an 'R' interface for real-time monitoring and offline analysis.
The package bundles code from 'Qhull' <http://www.qhull.org/>, by C. B. Barber and
The Geometry Center. See 'inst/COPYRIGHTS' for details.
Author: Gaetano Romano [aut, cre, trl],
Kes Ward [aut],
Yuntang Fan [aut],
Guillem Rigaill [aut],
Vincent Runge [aut],
Paul Fearnhead [aut],
Idris A. Eckley [aut],
C. B. Barber [ctb, cph] ,
The Geometry Center [cph]
Maintainer: Gaetano Romano <g.romano@lancaster.ac.uk>
Diff between focus versions 0.1.5 dated 2026-05-06 and 0.1.6 dated 2026-06-09
DESCRIPTION | 8 +++---- MD5 | 24 +++++++++++----------- R/RcppExports.R | 7 ++++-- README.md | 21 ++++++++++--------- man/detector_update.Rd | 6 ++++- src/ARpInfo.h | 6 ++--- src/Candidate.h | 8 +++---- src/Info.h | 50 +++++++++++++++++++++++----------------------- src/MultivariateInfo.h | 2 - src/NonparametricInfo.h | 4 +-- src/RcppExports.cpp | 9 ++++---- src/focus_ARp.cpp | 4 +-- src/focus_rcpp_module.cpp | 10 ++++++--- 13 files changed, 86 insertions(+), 73 deletions(-)
Title: Cross-Validating Regression Models
Description: Cross-validation methods of regression models that exploit features of various
modeling functions to improve speed. Some of the methods implemented in the package are
novel, as described in Fox and Monette (2026) <doi:10.18637/jss.v116.i08>,
and the package vignettes. For general introductions to cross-validation,
see, for example, Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
(2021, ISBN 978-1-0716-1417-4, Secs. 5.1, 5.3), "An Introduction to Statistical Learning with
Applications in R, Second Edition", and Trevor Hastie, Robert Tibshirani,
and Jerome Friedman (2009, ISBN 978-0-387-84857-0, Sec. 7.10), "The Elements of Statistical
Learning, Second Edition".
Author: John Fox [aut] ,
Georges Monette [aut, cre]
Maintainer: Georges Monette <georges+cv@yorku.ca>
Diff between cv versions 2.0.4 dated 2025-06-16 and 2.0.6 dated 2026-06-09
DESCRIPTION | 29 +-- MD5 | 86 ++++++---- NEWS.md | 4 R/Pigs.R | 5 R/cv-select.R | 56 +++--- R/cv.R | 11 - R/cv.modList.R | 49 ++--- build/vignette.rds |binary inst/CITATION |only inst/WORDLIST | 14 + inst/doc/cv-extend.html | 60 +++--- inst/doc/cv-mixed.html | 47 ++--- inst/doc/cv-notes.html | 38 +--- inst/doc/cv-selection.html | 29 +-- inst/doc/cv.Rmd | 4 inst/doc/cv.html | 66 +++---- man/Pigs.Rd | 5 man/cv.Rd | 4 man/cv.function.Rd | 55 +++--- man/cv.modList.Rd | 48 ++--- vignettes/cv-notes_cache/html/__packages | 10 - vignettes/cv-notes_cache/html/cv.lm.timings_e03718670033c66a4f3c39e76a71dbfc.RData |binary vignettes/cv-notes_cache/html/cv.lm.timings_e03718670033c66a4f3c39e76a71dbfc.rdb |binary vignettes/cv-notes_cache/html/cv.lm.timings_e03718670033c66a4f3c39e76a71dbfc.rdx |binary vignettes/cv-notes_cache/html/glm.timings_2b7c8d05fe831884caced4b0ec3053df.RData |binary vignettes/cv-notes_cache/html/glm.timings_2b7c8d05fe831884caced4b0ec3053df.rdx |binary vignettes/cv-selection_cache/html/__packages | 11 - vignettes/cv-selection_cache/html/cvSelect-artificial-data_9ad06ef148cf54d6b84209620167407e.RData |binary vignettes/cv-selection_cache/html/cvSelect-artificial-data_9ad06ef148cf54d6b84209620167407e.rdb |binary vignettes/cv-selection_cache/html/cvSelect-artificial-data_9ad06ef148cf54d6b84209620167407e.rdx |binary vignettes/cv.Rmd | 4 vignettes/fig |only 32 files changed, 339 insertions(+), 296 deletions(-)
Title: Multidimensional Penalized Splines for (Excess) Hazard Models,
Relative Mortality Ratio Models and Marginal Intensity Models
Description: Fits (excess) hazard, relative mortality ratio or marginal intensity models with multidimensional penalized splines allowing for
time-dependent effects, non-linear effects and interactions between several continuous covariates. In survival and net survival analysis, in addition to modelling the effect of time (via the baseline hazard), one has often to deal with several continuous covariates and model their functional forms, their time-dependent effects, and their interactions. Model specification becomes therefore a complex problem and penalized regression splines represent an appealing solution to that problem as splines offer the required flexibility while penalization limits overfitting issues. Current implementations of penalized survival models can be slow or unstable and sometimes lack some key features like taking into account expected mortality to provide net survival and excess hazard estimates. In contrast, survPen provides an automated, fast, and stable implementation (than [...truncated...]
Author: Mathieu Fauvernier [aut, cre],
Laurent Roche [aut],
Laurent Remontet [aut],
Zoe Uhry [ctb],
Nadine Bossard [ctb],
Elsa Coz [ctb]
Maintainer: Mathieu Fauvernier <mathieu.fauvernier@gmail.com>
Diff between survPen versions 2.0.4 dated 2026-05-09 and 2.0.5 dated 2026-06-09
survPen-2.0.4/survPen/R/survPenV2_04.r |only survPen-2.0.5/survPen/DESCRIPTION | 6 survPen-2.0.5/survPen/MD5 | 88 - survPen-2.0.5/survPen/NEWS | 11 survPen-2.0.5/survPen/R/survPenV2_05.r |only survPen-2.0.5/survPen/build/vignette.rds |binary survPen-2.0.5/survPen/inst/doc/survival_analysis_with_survPen.R | 29 survPen-2.0.5/survPen/inst/doc/survival_analysis_with_survPen.Rmd | 40 survPen-2.0.5/survPen/inst/doc/survival_analysis_with_survPen.html | 564 +++++++--- survPen-2.0.5/survPen/man/HeartFailure.Rd | 2 survPen-2.0.5/survPen/man/NR.beta.Rd | 2 survPen-2.0.5/survPen/man/NR.rho.Rd | 2 survPen-2.0.5/survPen/man/constraint.Rd | 2 survPen-2.0.5/survPen/man/cor.var.Rd | 2 survPen-2.0.5/survPen/man/crs.FP.Rd | 2 survPen-2.0.5/survPen/man/crs.Rd | 2 survPen-2.0.5/survPen/man/datCancer.Rd | 2 survPen-2.0.5/survPen/man/design.matrix.Rd | 2 survPen-2.0.5/survPen/man/expected.table.Rd | 2 survPen-2.0.5/survPen/man/instr.Rd | 2 survPen-2.0.5/survPen/man/inv.repam.Rd | 2 survPen-2.0.5/survPen/man/list.wicss.Rd | 2 survPen-2.0.5/survPen/man/model.cons.Rd | 2 survPen-2.0.5/survPen/man/predSNS.Rd | 2 survPen-2.0.5/survPen/man/predict.survPen.Rd | 2 survPen-2.0.5/survPen/man/print.summary.survPen.Rd | 2 survPen-2.0.5/survPen/man/pwcst.Rd | 2 survPen-2.0.5/survPen/man/rd.Rd | 2 survPen-2.0.5/survPen/man/repam.Rd | 2 survPen-2.0.5/survPen/man/robust.var.Rd | 2 survPen-2.0.5/survPen/man/smf.Rd | 2 survPen-2.0.5/survPen/man/smooth.cons.Rd | 2 survPen-2.0.5/survPen/man/smooth.cons.integral.Rd | 2 survPen-2.0.5/survPen/man/smooth.spec.Rd | 2 survPen-2.0.5/survPen/man/splitmult.Rd | 2 survPen-2.0.5/survPen/man/summary.survPen.Rd | 2 survPen-2.0.5/survPen/man/survPen.Rd | 2 survPen-2.0.5/survPen/man/survPen.fit.Rd | 2 survPen-2.0.5/survPen/man/survPenObject.Rd | 2 survPen-2.0.5/survPen/man/tensor.in.Rd | 2 survPen-2.0.5/survPen/man/tensor.prod.S.Rd | 2 survPen-2.0.5/survPen/man/tensor.prod.X.Rd | 2 survPen-2.0.5/survPen/vignettes/survival_analysis_with_survPen.Rmd | 40 survPen-2.0.5/survPen/vignettes/survival_analysis_with_survPen_files/figure-html/unnamed-chunk-55-1.png |binary survPen-2.0.5/survPen/vignettes/survival_analysis_with_survPen_files/figure-html/unnamed-chunk-56-1.png |binary survPen-2.0.5/survPen/vignettes/survival_analysis_with_survPen_files/figure-html/unnamed-chunk-57-1.png |only survPen-2.0.5/survPen/vignettes/survival_analysis_with_survPen_files/figure-html/unnamed-chunk-58-1.png |only 47 files changed, 594 insertions(+), 250 deletions(-)
Title: Prediction Rule Ensembles
Description: Derives prediction rule ensembles (PREs). Largely follows the
procedure for deriving PREs as described in Friedman & Popescu (2008;
<DOI:10.1214/07-AOAS148>), with adjustments and improvements described in
Fokkema (2020; <DOI:10.18637/jss.v092.i12>) and Fokkema & Strobl
(2020; <DOI:10.1037/met0000256>). The main function pre() derives
prediction rule ensembles consisting of rules and/or linear terms for
continuous, binary, count, multinomial, survival and multivariate
continuous responses. Function gpe() derives generalized prediction
ensembles, consisting of rules, hinge and linear functions of the
predictor variables.
Author: Marjolein Fokkema [aut, cre],
Benjamin Christoffersen [aut]
Maintainer: Marjolein Fokkema <m.fokkema@fsw.leidenuniv.nl>
Diff between pre versions 1.0.8 dated 2025-09-06 and 1.0.9 dated 2026-06-09
DESCRIPTION | 8 MD5 | 40 +- NEWS.md | 305 +++++++++----------- R/pre.R | 4 build/partial.rdb |binary build/vignette.rds |binary inst/doc/Missingness.R | 112 +++---- inst/doc/Missingness.html | 44 +- inst/doc/Tuning.R | 24 - inst/doc/Tuning.Rmd | 2 inst/doc/Tuning.html | 4 inst/doc/relaxed.R | 2 inst/doc/relaxed.Rmd | 2 inst/doc/relaxed.html | 75 ++-- inst/doc/speed.R | 16 - inst/doc/speed.html | 12 man/caret_pre_model.Rd | 5 tests/testthat/previous_results/lung_w_pre_surv.RDS |binary tests/testthat/tests_pre.R | 3 vignettes/Tuning.Rmd | 2 vignettes/relaxed.Rmd | 2 21 files changed, 319 insertions(+), 343 deletions(-)
Title: Multivariate Generalized Linear Mixed Models for Ranking Sports
Teams
Description: Maximum likelihood estimates are obtained via an EM algorithm with either a first-order or a fully exponential Laplace approximation as documented by Broatch and Karl (2018) <doi:10.48550/arXiv.1710.05284>,
Karl, Yang, and Lohr (2014) <doi:10.1016/j.csda.2013.11.019>, and by
Karl (2012) <doi:10.1515/1559-0410.1471>. Karl and Zimmerman <doi:10.1016/j.jspi.2020.06.004> use this package to illustrate how the home field effect estimator from a mixed model can be biased under nonrandom scheduling.
Author: Andrew T. Karl [cre, aut] ,
Jennifer Broatch [aut]
Maintainer: Andrew T. Karl <akarl@asu.edu>
Diff between mvglmmRank versions 1.2-4 dated 2023-01-07 and 1.2-5 dated 2026-06-09
DESCRIPTION | 13 + MD5 | 27 ++- NAMESPACE | 25 +-- NEWS | 29 +++ NEWS.md |only R/NB_mov.r | 29 +-- R/N_mov.r | 34 +--- R/PB_cre.R | 20 +- R/game.pred.R | 57 +++++++ R/mvglmmRank-package.R |only R/mvglmmRank.R | 163 +++++++++++++++++++++ build |only inst |only man/game.pred.Rd | 126 ++++++++-------- man/mvglmmRank-package.Rd | 94 ++++++------ man/mvglmmRank.Rd | 350 +++++++++++++++++++++++++--------------------- tests |only 17 files changed, 621 insertions(+), 346 deletions(-)
Title: 'Fish Bioenergetics 4.0' Model Implementation with
High-Performance 'TMB' Backend
Description: An implementation of the 'Fish Bioenergetics 4.0' framework
described in Deslauriers et al. (2017)
<doi:10.1080/03632415.2017.1377558>. Provides automated parameter
optimization, multi-prey diet modeling, and comprehensive energy budget
simulations for fisheries research and aquaculture applications. An
optional 'TMB' (Template Model Builder) backend delivers 10-50x speedup
in maximum likelihood estimation while maintaining full backward
compatibility. Includes species-specific parameter databases and tools
for modeling fish growth, consumption, and metabolism under varying
environmental conditions.
Author: Hans Ttito [aut, cre]
Maintainer: Hans Ttito <kvttitos@gmail.com>
Diff between fb4package versions 2.0.0 dated 2026-05-07 and 2.1.0 dated 2026-06-09
DESCRIPTION | 9 - MD5 | 49 ++++--- NEWS.md | 40 +++++ R/10-data-processing.R | 190 ++++++++++++++++++++++++++-- R/11.3-data-validators.R | 5 R/12-simulation-engine.R | 209 ++++++++++++++++++++++++------- R/13.0-bioenergetic-classes.R | 29 ++++ R/14.0-tmb-shared.R | 2 R/14.1-strategy-interface.R | 20 +- R/14.3-result-builders.R | 9 + README.md | 6 build/vignette.rds |binary inst/WORDLIST | 6 inst/doc/fb4-case-study-chinook.html | 6 inst/doc/fb4-introduction.html | 6 inst/doc/fb4-shiny-validation.R |only inst/doc/fb4-shiny-validation.Rmd |only inst/doc/fb4-shiny-validation.html |only inst/doc/fb4-species-database.html | 4 inst/doc/fb4-statistical-estimation.html | 4 inst/doc/fb4-temperature-climate.html | 4 man/Bioenergetic.Rd | 13 + man/execute_daily_simulation.Rd | 6 man/figures/logo.png |only man/process_contaminant_data.Rd |only man/process_nutrient_data.Rd |only tests/testthat/test-12-simulation.R | 4 tests/testthat/test-13-nutrients.R |only tests/testthat/test-14c-contaminants.R |only vignettes/fb4-shiny-validation.Rmd |only 30 files changed, 513 insertions(+), 108 deletions(-)
Title: Statistical Tools for Modelling Climate-Health Impacts
Description: Tools for producing climate-health indicators and supporting
official statistics from health and climate data. Implements analytical
workflows for temperature-related mortality, wildfire smoke exposure,
air pollution, suicides related to extreme heat, malaria, and
diarrhoeal disease outcomes, with utilities for descriptive statistics, model
validation, attributable fraction and attributable number estimation,
relative risk estimation, minimum mortality temperature estimation,
and plotting for reporting. These six indicators are endorsed by
the United Nations Statistical Commission for inclusion in the
Global Set of Environment and Climate Change Statistics.
Implemented methods include distributed lag non-linear models (DLNM),
quasi-Poisson time-series regression, case-crossover analysis,
Bayesian spatio-temporal models using the Integrated Nested Laplace
Approximation ('INLA'), and multivariate meta-analysis for
sub-national estimates. The package is based on methods developed
in the S [...truncated...]
Author: Charlie Browning [aut],
Kenechi Omeke [aut, cre],
Etse Yawo Dzakpa [aut],
Gladin Jose [aut],
Matt Pearce [aut],
Ellie Watkins [aut],
Claire Hunt [aut],
Beatrice Byukusenge [aut],
Cassien Habyarimana [aut],
Venuste Nyagahakwa [aut],
Felix Scarbrough [ [...truncated...]
Maintainer: Kenechi Omeke <climate.health@ons.gov.uk>
Diff between climatehealth versions 1.0.1 dated 2026-04-08 and 1.0.2 dated 2026-06-09
climatehealth-1.0.1/climatehealth/man/calculate_air_pollution_grid_dims.Rd |only climatehealth-1.0.1/climatehealth/man/create_grid.Rd |only climatehealth-1.0.1/climatehealth/man/create_temperature_splines.Rd |only climatehealth-1.0.1/climatehealth/man/descriptive_stats.Rd |only climatehealth-1.0.1/climatehealth/man/get_alpha_colour.Rd |only climatehealth-1.0.1/climatehealth/man/save_air_pollution_plot.Rd |only climatehealth-1.0.2/climatehealth/DESCRIPTION | 30 climatehealth-1.0.2/climatehealth/MD5 | 157 climatehealth-1.0.2/climatehealth/NEWS.md | 157 climatehealth-1.0.2/climatehealth/R/air_pollution.R | 1724 ++++---- climatehealth-1.0.2/climatehealth/R/climatehealth-package.R | 14 climatehealth-1.0.2/climatehealth/R/descriptive_stats.R | 173 climatehealth-1.0.2/climatehealth/R/diarrhea.R | 84 climatehealth-1.0.2/climatehealth/R/diseases_shared.R | 1385 ++++-- climatehealth-1.0.2/climatehealth/R/dlnm_shared.R | 3 climatehealth-1.0.2/climatehealth/R/graph_utils.R | 877 ++-- climatehealth-1.0.2/climatehealth/R/malaria.R | 85 climatehealth-1.0.2/climatehealth/R/mental_health.R | 1572 +++++-- climatehealth-1.0.2/climatehealth/R/plot_accessibility_helpers.R |only climatehealth-1.0.2/climatehealth/R/temp_mortality.R | 2079 ++++++--- climatehealth-1.0.2/climatehealth/R/wildfire.R | 1233 ++++- climatehealth-1.0.2/climatehealth/README.md | 26 climatehealth-1.0.2/climatehealth/inst/extdata/soschi_logo.png |only climatehealth-1.0.2/climatehealth/inst/plumber/plumber.R | 46 climatehealth-1.0.2/climatehealth/man/accessible_plot_annotation.Rd |only climatehealth-1.0.2/climatehealth/man/add_accessible_alt_text.Rd |only climatehealth-1.0.2/climatehealth/man/add_accessible_outer_title.Rd |only climatehealth-1.0.2/climatehealth/man/add_figure_legend.Rd |only climatehealth-1.0.2/climatehealth/man/add_ggplot_alt_caption.Rd |only climatehealth-1.0.2/climatehealth/man/add_ggplot_logo.Rd |only climatehealth-1.0.2/climatehealth/man/add_plot_logo.Rd |only climatehealth-1.0.2/climatehealth/man/add_right_axis_label.Rd |only climatehealth-1.0.2/climatehealth/man/air_pollution_do_analysis.Rd | 17 climatehealth-1.0.2/climatehealth/man/air_pollution_meta_analysis.Rd | 6 climatehealth-1.0.2/climatehealth/man/calculate_daily_AF_AN.Rd | 17 climatehealth-1.0.2/climatehealth/man/calculate_qaic.Rd | 12 climatehealth-1.0.2/climatehealth/man/calculate_wildfire_rr_by_region.Rd | 14 climatehealth-1.0.2/climatehealth/man/casecrossover_quasipoisson.Rd | 13 climatehealth-1.0.2/climatehealth/man/check_wildfire_vif.Rd | 9 climatehealth-1.0.2/climatehealth/man/climatehealth-package.Rd | 14 climatehealth-1.0.2/climatehealth/man/close_diag_pdf.Rd |only climatehealth-1.0.2/climatehealth/man/diarrhea_do_analysis.Rd | 37 climatehealth-1.0.2/climatehealth/man/dlnm_predict_nat.Rd | 3 climatehealth-1.0.2/climatehealth/man/figures |only climatehealth-1.0.2/climatehealth/man/fit_air_pollution_gam.Rd | 6 climatehealth-1.0.2/climatehealth/man/get_accessible_ggplot_grid.Rd |only climatehealth-1.0.2/climatehealth/man/get_accessible_ggplot_size.Rd |only climatehealth-1.0.2/climatehealth/man/get_accessible_palette.Rd |only climatehealth-1.0.2/climatehealth/man/get_accessible_plot_colours.Rd |only climatehealth-1.0.2/climatehealth/man/get_layout_matrix.Rd |only climatehealth-1.0.2/climatehealth/man/get_month_labels.Rd |only climatehealth-1.0.2/climatehealth/man/get_pdf_size.Rd |only climatehealth-1.0.2/climatehealth/man/get_plot_grid.Rd |only climatehealth-1.0.2/climatehealth/man/get_wildfire_lag_columns.Rd |only climatehealth-1.0.2/climatehealth/man/hc_attr.Rd | 6 climatehealth-1.0.2/climatehealth/man/hc_quasipoisson_dlnm.Rd | 15 climatehealth-1.0.2/climatehealth/man/make_safe_plot_filename.Rd |only climatehealth-1.0.2/climatehealth/man/malaria_do_analysis.Rd | 39 climatehealth-1.0.2/climatehealth/man/mh_add_national_data.Rd | 2 climatehealth-1.0.2/climatehealth/man/mh_attr.Rd | 7 climatehealth-1.0.2/climatehealth/man/mh_predict_reg.Rd | 2 climatehealth-1.0.2/climatehealth/man/open_accessible_pdf.Rd |only climatehealth-1.0.2/climatehealth/man/open_diag_pdf.Rd |only climatehealth-1.0.2/climatehealth/man/plot_aggregated_AF.Rd | 9 climatehealth-1.0.2/climatehealth/man/plot_air_pollution_an_ar_by_region.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_air_pollution_an_ar_by_year.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_air_pollution_an_ar_monthly.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_air_pollution_forest_by_lag.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_air_pollution_forest_by_region.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_air_pollution_monthly_histograms.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_ar_pm_monthly.Rd | 9 climatehealth-1.0.2/climatehealth/man/plot_avg_monthly.Rd | 7 climatehealth-1.0.2/climatehealth/man/plot_correlation_matrix.Rd | 7 climatehealth-1.0.2/climatehealth/man/plot_monthly_random_effects.Rd | 2 climatehealth-1.0.2/climatehealth/man/plot_moving_average.Rd | 7 climatehealth-1.0.2/climatehealth/man/read_and_format_data.Rd | 3 climatehealth-1.0.2/climatehealth/man/resolve_input_column_name.Rd |only climatehealth-1.0.2/climatehealth/man/run_accessible_pdf_plot.Rd |only climatehealth-1.0.2/climatehealth/man/run_descriptive_stats.Rd | 6 climatehealth-1.0.2/climatehealth/man/save_accessible_ggplot.Rd |only climatehealth-1.0.2/climatehealth/man/save_wildfire_results.Rd | 5 climatehealth-1.0.2/climatehealth/man/setup_accessible_par.Rd |only climatehealth-1.0.2/climatehealth/man/suicides_heat_do_analysis.Rd | 45 climatehealth-1.0.2/climatehealth/man/temp_mortality_do_analysis.Rd | 47 climatehealth-1.0.2/climatehealth/man/theme_accessible_ggplot.Rd |only climatehealth-1.0.2/climatehealth/man/theme_accessible_ggplot_panel.Rd |only climatehealth-1.0.2/climatehealth/man/wildfire_do_analysis.Rd | 68 climatehealth-1.0.2/climatehealth/tests/testthat/setup-api_mode.R |only climatehealth-1.0.2/climatehealth/tests/testthat/test_air_pollution.R | 2094 +++++++--- climatehealth-1.0.2/climatehealth/tests/testthat/test_descriptive_do_analysis_args.R |only climatehealth-1.0.2/climatehealth/tests/testthat/test_descriptive_stats.R | 16 climatehealth-1.0.2/climatehealth/tests/testthat/test_diarrhea.R | 88 climatehealth-1.0.2/climatehealth/tests/testthat/test_diseases_shared.R | 138 climatehealth-1.0.2/climatehealth/tests/testthat/test_graph_utils.R | 30 climatehealth-1.0.2/climatehealth/tests/testthat/test_malaria.R | 89 climatehealth-1.0.2/climatehealth/tests/testthat/test_mental_health.R | 270 - climatehealth-1.0.2/climatehealth/tests/testthat/test_plot_accessibility_helpers.R |only climatehealth-1.0.2/climatehealth/tests/testthat/test_temp_mortality.R | 160 climatehealth-1.0.2/climatehealth/tests/testthat/test_wildfire.R | 888 ++-- 99 files changed, 9649 insertions(+), 4215 deletions(-)
Title: Estimation of Pleiotropic Heritability from Genome-Wide
Association Studies (GWAS) Summary Statistics
Description: Provides tools to compute unbiased pleiotropic heritability estimates of complex diseases from genome-wide association studies (GWAS) summary statistics. We estimate pleiotropic heritability from GWAS summary statistics by estimating the proportion of variance explained from an estimated genetic correlation matrix (Bulik-Sullivan et al. 2015 <doi:10.1038/ng.3406>) and employing a Monte-Carlo bias correction procedure to account for sampling noise in genetic correlation estimates.
Author: Yujie Zhao [aut, cre]
Maintainer: Yujie Zhao <yujiezhao@hsph.harvard.edu>
Diff between pleioh2g versions 0.1.2 dated 2026-03-09 and 0.1.3 dated 2026-06-09
DESCRIPTION | 6 +++--- MD5 | 12 ++++++------ R/Cal_rg_h2g_alltraits.R | 7 ++++--- R/Cal_rg_h2g_jk_alltraits.R | 11 +++++++---- R/ldsc_h2.R | 7 ++++++- R/ldsc_rg.R | 9 +++++++-- R/pruning_pleioh2g_wrapper.R | 25 +++++++++++++++++-------- 7 files changed, 50 insertions(+), 27 deletions(-)
Title: Shared Memory for R Objects
Description: Share R objects across processes on the same machine via a
single copy in 'POSIX' shared memory (Linux, macOS) or a 'Win32' file
mapping (Windows). Every process reads from the same physical pages
through the R Alternative Representation ('ALTREP') framework, giving
lazy, zero-copy access. Shared objects serialize compactly as their
shared memory name rather than their full contents.
Author: Charlie Gao [aut, cre] ,
Posit Software, PBC [cph, fnd]
Maintainer: Charlie Gao <charlie.gao@posit.co>
Diff between mori versions 0.2.0 dated 2026-05-08 and 0.2.1 dated 2026-06-09
DESCRIPTION | 6 MD5 | 33 +-- NAMESPACE | 1 NEWS.md | 5 R/import-standalone-defer.R |only R/share.R | 68 +++++- README.md | 25 +- man/is_shared.Rd | 5 man/map_shared.Rd | 7 man/prune_shared.Rd |only man/share.Rd | 14 - man/shared_name.Rd | 6 src/altrep.c | 64 ++++-- src/init.c | 2 src/mori.h | 14 + src/shm.c | 401 +++++++++++++++++++++++++++++++++++---- tests/testthat/test-corruption.R |only tests/testthat/test-create.R |only tests/testthat/test-prune.R |only tests/testthat/test-strings.R | 9 20 files changed, 561 insertions(+), 99 deletions(-)
Title: Design and Analysis of Consistency Tests Based on Kappa
Statistic
Description: Provides a 'Shiny' application and supporting functions for the
design and analysis of consistency tests based on Kappa statistic with
categorical responses. Wraps 'irr' and 'kappaSize' packages.
Author: Gai Zheng [aut, cre],
Xincheng Li [aut],
Yingjie Jiangwang [aut],
Panwei Zhao [aut]
Maintainer: Gai Zheng <z2118778229@163.com>
Diff between catekappa versions 0.1.0 dated 2026-06-02 and 0.1.1 dated 2026-06-09
DESCRIPTION | 6 ++-- MD5 | 5 ++-- NEWS.md |only inst/shinyapp/app.R | 65 +++++++++++++++++++++++++++++++++++++--------------- 4 files changed, 53 insertions(+), 23 deletions(-)
More information about NeutroCODsAnalysis at CRAN
Permanent link
Title: Extinction Risk Estimation
Description: Estimates extinction risk from population time series under a
drifted Wiener process using MLE and
observation-error-and-autocovariance-robust estimators, with
confidence intervals based on the w-z method.
Author: Hiroshi Hakoyama [aut, cre, cph]
Maintainer: Hiroshi Hakoyama <hiroshi.hakoyama@gmail.com>
Diff between extr versions 1.1.0 dated 2026-03-17 and 1.1.1 dated 2026-06-09
DESCRIPTION | 8 ++++---- MD5 | 14 +++++++------- NEWS.md | 8 ++++++++ R/ext_di.R | 26 ++++++++++++++++++++++++++ README.md | 39 +++++++++++++++++++++++++++++++++++++++ inst/CITATION | 7 +++++-- man/ext_di.Rd | 26 ++++++++++++++++++++++++++ man/extr-package.Rd | 5 +++++ 8 files changed, 120 insertions(+), 13 deletions(-)
Title: Count Transformation Models
Description: Count transformation models featuring
parameters interpretable as discrete hazard ratios, odds ratios,
reverse-time discrete hazard ratios, or transformed expectations.
An appropriate data transformation for a count outcome and
regression coefficients are simultaneously estimated by maximising
the exact discrete log-likelihood using the computational framework
provided in package 'mlt', technical details are given in
Siegfried & Hothorn (2020) <DOI:10.1111/2041-210X.13383>.
The package also features
joint count transformation models with covariate-dependent correlations
applied to a species community of three aquatic birds
<DOI:10.48550/arXiv.2201.13095>.
Author: Sandra Siegfried [aut, cre] ,
Luisa Barbanti [aut] ,
Lukas Graz [aut] ,
Torsten Hothorn [aut]
Maintainer: Sandra Siegfried <sandra.siegfried@alumni.uzh.ch>
Diff between cotram versions 0.6-0 dated 2025-11-19 and 0.6-1 dated 2026-06-09
DESCRIPTION | 34 - MD5 | 21 build/partial.rdb |binary build/vignette.rds |binary demo/00Index | 2 demo/aquabirds.R | 1035 +++++++++++++++++++++++++++++------------- demo/aquabirds.Rout.save | 1067 ++++++++++++++++++++++++++++++-------------- inst/NEWS.Rd | 6 inst/doc/cotram.pdf |binary inst/simulation/SIM-JCTM.R |only man/mcotram.Rd | 2 tests/confband-Ex.Rout.save | 2 12 files changed, 1503 insertions(+), 666 deletions(-)
More information about consolidatePacks at CRAN
Permanent link
Title: Synthetic Tabular Data Generation with Gaussian Copulas
Description: Generates synthetic tabular data from real datasets using
Gaussian copula models, with parametric marginal selection for
numerical columns and a cumulative-frequency embedding that brings
categorical and boolean columns into the same joint copula. Includes
a metadata system with column types and primary keys, declarative
constraints enforced via rejection sampling, conditional sampling,
and quality, validity and privacy reports modeled on those of the
'SDMetrics' library. Inspired by the Python 'SDV' (Synthetic Data
Vault) library by 'DataCebo'; see Patki, Wedge and Veeramachaneni
(2016) "The Synthetic Data Vault" <doi:10.1109/DSAA.2016.49>.
Author: Kailas Venkitasubramanian [aut, cre]
Maintainer: Kailas Venkitasubramanian <kailasv@gmail.com>
Diff between rsdv versions 0.1.0 dated 2026-06-08 and 0.2.0 dated 2026-06-09
DESCRIPTION | 6 MD5 | 83 +++++----- NAMESPACE | 4 NEWS.md | 217 +++++++++++++++++++------- R/constraints.R | 144 +++++++++++++++-- R/diagnostic_report.R | 43 +++-- R/gaussian_copula.R | 44 +++++ R/metadata.R | 216 ++++++++++++++------------ R/metadata_io.R | 205 ++++++++++++++++--------- R/privacy_metrics.R | 53 +++++- R/privacy_report.R | 126 ++++++++------- R/quality_metrics.R | 91 ++++++++--- R/synthesizer.R | 146 ++++++++--------- R/utils.R | 18 +- README.md | 38 ++-- inst/CITATION |only inst/WORDLIST | 12 + inst/doc/getting-started.Rmd | 67 ++++---- inst/doc/getting-started.html | 237 +++++++++++++++-------------- man/attribute_disclosure_risk.Rd | 71 ++++---- man/contingency_similarity.Rd | 6 man/correlation_similarity.Rd | 6 man/custom_constraint.Rd | 52 +++--- man/equality_constraint.Rd | 48 +++-- man/metadata_from_json.Rd | 46 +++-- man/metadata_to_json.Rd | 49 +++-- man/ml_efficacy.Rd | 85 +++++----- man/nndr.Rd | 60 ++++--- man/print.custom_constraint.Rd |only man/print.equality_constraint.Rd |only man/print.fixed_combinations_constraint.Rd |only man/print.inequality_constraint.Rd |only man/sample.Rd | 80 ++++----- man/set_column_type.Rd | 57 +++--- tests/testthat/helper.R | 42 ++--- tests/testthat/test-conditional-sampling.R | 50 ++++++ tests/testthat/test-constraints.R | 103 ++++++++++++ tests/testthat/test-diagnostic-report.R | 24 ++ tests/testthat/test-gaussian-copula.R | 39 ++++ tests/testthat/test-metadata-io.R | 133 +++++++++++----- tests/testthat/test-metadata.R | 93 ++++++----- tests/testthat/test-privacy-metrics.R | 66 ++++++++ tests/testthat/test-privacy-report.R | 84 +++++----- tests/testthat/test-quality-metrics.R | 126 +++++++++++++++ vignettes/getting-started.Rmd | 67 ++++---- 45 files changed, 2086 insertions(+), 1051 deletions(-)
Title: Understanding Nonlinear Mixed Effects Modeling for Population
Pharmacokinetics
Description: This shows how 'NONMEM' (Beal SL, Sheiner LB, Boeckmann AJ,
Bauer RJ. NONMEM 7.5 Users Guides. Icon plc, 2020) software works.
'NONMEM' classical estimation methods such as 'First Order (FO)
approximation', 'First Order Conditional Estimation (FOCE)', and
'Laplacian approximation' are explained. Functions are also provided
for post-run processing of NONMEM output files, generating PDF
diagnostic reports including objective function value analysis,
parameter estimates, prediction and residual diagnostics, empirical
Bayes estimate (EBE) analysis, input data summary, and individual
pharmacokinetic parameter distributions. Helper utilities for
building NONMEM-ready datasets from SDTM-style source tables are
also included.
Author: Kyun-Seop Bae [aut, cre]
Maintainer: Kyun-Seop Bae <k@acr.kr>
Diff between nmw versions 0.3.0 dated 2026-05-07 and 0.3.1 dated 2026-06-09
nmw-0.3.0/nmw/tests |only nmw-0.3.1/nmw/DESCRIPTION | 28 ++++++++++++++++----------- nmw-0.3.1/nmw/MD5 | 20 ++++++------------- nmw-0.3.1/nmw/R/nm_read.R | 8 +++++-- nmw-0.3.1/nmw/R/nm_summary.R | 23 ++++++++++++++++------ nmw-0.3.1/nmw/R/report_ebe.R | 42 ++++++++++++++++++++++++++++++----------- nmw-0.3.1/nmw/R/utils_string.R | 4 ++- nmw-0.3.1/nmw/inst/NEWS.Rd | 13 ++++++++++++ nmw-0.3.1/nmw/man/SumOut.Rd | 2 - 9 files changed, 95 insertions(+), 45 deletions(-)
Title: Tools for Multivariate Nonparametrics
Description: Tools for multivariate nonparametrics, as location tests based on marginal ranks, spatial median and spatial signs computation, Hotelling's T-test, estimates of shape are implemented.
Author: Klaus Nordhausen [aut, cre] ,
Seija Sirkia [aut],
Hannu Oja [aut] ,
David E. Tyler [aut]
Maintainer: Klaus Nordhausen <klausnordhausenR@gmail.com>
Diff between ICSNP versions 1.1-2 dated 2023-09-18 and 1.1-3 dated 2026-06-09
ICSNP-1.1-2/ICSNP/data/LASERI.txt.gz |only ICSNP-1.1-2/ICSNP/man/LASERI.Rd |only ICSNP-1.1-3/ICSNP/DESCRIPTION | 13 +++++++------ ICSNP-1.1-3/ICSNP/MD5 | 10 ++++------ ICSNP-1.1-3/ICSNP/build/partial.rdb |binary ICSNP-1.1-3/ICSNP/data/pulmonary.rda |binary ICSNP-1.1-3/ICSNP/inst/ChangeLog | 5 +++++ 7 files changed, 16 insertions(+), 12 deletions(-)
Title: A Predictive Haplotyping Package
Description: Used for predicting a genotype's allelic state at a specific locus/QTL/gene. This is accomplished by using both a genotype matrix and a separate file which has categorizations about loci/QTL/genes of interest for the individuals in the genotypic matrix. A training population can be created from a panel of individuals who have been previously screened for specific loci/QTL/genes, and this previous screening could be summarized into a category. Using the categorization of individuals which have been genotyped using a genome wide marker platform, a model can be trained to predict what category (haplotype) an individual belongs in based on their genetic sequence in the region associated with the locus/QTL/gene. These trained models can then be used to predict the haplotype of a locus/QTL/gene for individuals which have been genotyped with a genome wide platform yet not genotyped for the specific locus/QTL/gene. This package is based off work done by Winn et al 2021. For more specific infor [...truncated...]
Author: Zachary Winn [aut, cre]
Maintainer: Zachary Winn <zwinn@outlook.com>
Diff between HaploCatcher versions 1.0.4 dated 2023-04-21 and 2.0.1 dated 2026-06-09
DESCRIPTION | 21 LICENSE | 4 MD5 | 62 +- NAMESPACE | 5 R/HaploCatcher-package.R |only R/auto_locus.R | 501 ++++++--------------- R/gene_comp.R | 46 - R/geno_mat.R | 22 R/locus_cv.R | 778 +++++---------------------------- R/locus_perm_cv.R | 671 +++++----------------------- R/locus_pred.R | 127 +---- R/locus_train.R | 469 +++++-------------- R/marker_info.R | 38 - R/plot_locus_perm_cv.R | 168 ++----- R/utils-internal.R |only README.md | 33 + build/vignette.rds |binary inst/doc/An_Intro_to_HaploCatcher.R | 30 - inst/doc/An_Intro_to_HaploCatcher.Rmd | 604 ++++++++++++------------- inst/doc/An_Intro_to_HaploCatcher.html | 117 ++-- man/HaploCatcher-package.Rd |only man/auto_locus.Rd | 188 ++++--- man/figures |only man/gene_comp.Rd | 68 +- man/geno_mat.Rd | 44 - man/locus_cv.Rd | 176 +++---- man/locus_perm_cv.Rd | 187 ++++--- man/locus_pred.Rd | 144 +++--- man/locus_train.Rd | 211 ++++---- man/marker_info.Rd | 60 +- man/plot_locus_perm_cv.Rd | 62 +- tests/testthat.R | 4 tests/testthat/test-auto_locus.R | 106 +++- vignettes/An_Intro_to_HaploCatcher.Rmd | 604 ++++++++++++------------- 34 files changed, 2129 insertions(+), 3421 deletions(-)
Title: Disciplined Convex Optimization
Description: An object-oriented modeling language for disciplined
convex programming (DCP) as described in Fu, Narasimhan, and Boyd
(2020, <doi:10.18637/jss.v094.i14>). It allows the user to
formulate convex optimization problems in a natural way following
mathematical convention and DCP rules. The system analyzes the
problem, verifies its convexity, converts it into a canonical
form, and hands it off to an appropriate solver to obtain the
solution. This version uses the S7 object system for improved
performance and maintainability.
Author: Anqi Fu [aut, cre],
Balasubramanian Narasimhan [aut],
Steven Diamond [aut],
John Miller [aut],
Stephen Boyd [ctb]
Maintainer: Anqi Fu <anqif@alumni.stanford.edu>
Diff between CVXR versions 1.8.2 dated 2026-04-04 and 1.9.1 dated 2026-06-09
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CVXR-1.8.2/CVXR/R/164_reductions_dcp2cone_canonicalizers_pnorm_canon.R |only CVXR-1.8.2/CVXR/R/165_reductions_dcp2cone_canonicalizers_power_canon.R |only CVXR-1.8.2/CVXR/R/166_reductions_dcp2cone_canonicalizers_quad_form_canon.R |only CVXR-1.8.2/CVXR/R/167_reductions_dcp2cone_canonicalizers_quad_over_lin_canon.R |only CVXR-1.8.2/CVXR/R/168_reductions_dcp2cone_canonicalizers_rel_entr_canon.R |only CVXR-1.8.2/CVXR/R/169_reductions_dcp2cone_canonicalizers_sigma_max_canon.R |only CVXR-1.8.2/CVXR/R/170_reductions_dcp2cone_canonicalizers_tr_inv_canon.R |only CVXR-1.8.2/CVXR/R/171_reductions_dcp2cone_canonicalizers_xexp_canon.R |only CVXR-1.8.2/CVXR/R/172_reductions_dcp2cone_canonicalizers_perspective_canon.R |only CVXR-1.8.2/CVXR/R/173_reductions_dcp2cone_canonicalizers_logic_canon.R |only CVXR-1.8.2/CVXR/R/174_reductions_dcp2cone_canonicalizers_indicator_canon.R |only CVXR-1.8.2/CVXR/R/175_reductions_dcp2cone_canonicalizers_quad_huber_canon.R |only CVXR-1.8.2/CVXR/R/176_reductions_dcp2cone_canonicalizers_quad_power_canon.R |only CVXR-1.8.2/CVXR/R/177_reductions_dcp2cone_canonicalizers_quad_quad_form_canon.R |only CVXR-1.8.2/CVXR/R/178_reductions_dcp2cone_canonicalizers_quad_quad_over_lin_canon.R |only CVXR-1.8.2/CVXR/R/179_reductions_solution.R |only CVXR-1.8.2/CVXR/R/180_reductions_utilities.R |only CVXR-1.8.2/CVXR/R/181_reductions_chain.R |only CVXR-1.8.2/CVXR/R/182_reductions_complex2real_canonicalizers_constant_canon.R |only CVXR-1.8.2/CVXR/R/183_reductions_complex2real_canonicalizers_param_canon.R |only CVXR-1.8.2/CVXR/R/184_reductions_complex2real_canonicalizers_variable_canon.R |only CVXR-1.8.2/CVXR/R/185_reductions_complex2real_canonicalizers_aff_canon.R |only CVXR-1.8.2/CVXR/R/186_reductions_complex2real_canonicalizers_abs_canon.R |only CVXR-1.8.2/CVXR/R/187_reductions_complex2real_canonicalizers_pnorm_canon.R |only CVXR-1.8.2/CVXR/R/188_reductions_complex2real_canonicalizers_matrix_canon.R |only CVXR-1.8.2/CVXR/R/189_reductions_complex2real_canonicalizers_psd_canon.R |only CVXR-1.8.2/CVXR/R/190_reductions_complex2real_canonicalizers_soc_canon.R |only CVXR-1.8.2/CVXR/R/191_reductions_complex2real_canonicalizers_equality_canon.R |only CVXR-1.8.2/CVXR/R/192_reductions_complex2real_canonicalizers_inequality_canon.R |only CVXR-1.8.2/CVXR/R/193_reductions_complex2real_complex2real.R |only CVXR-1.8.2/CVXR/R/194_reductions_dgp2dcp_util.R |only CVXR-1.8.2/CVXR/R/195_reductions_dgp2dcp_canonicalizers_constant_canon.R |only CVXR-1.8.2/CVXR/R/196_reductions_dgp2dcp_canonicalizers_add_canon.R |only CVXR-1.8.2/CVXR/R/197_reductions_dgp2dcp_canonicalizers_div_canon.R |only CVXR-1.8.2/CVXR/R/198_reductions_dgp2dcp_canonicalizers_mul_canon.R |only CVXR-1.8.2/CVXR/R/199_reductions_dgp2dcp_canonicalizers_mulexpression_canon.R |only CVXR-1.8.2/CVXR/R/200_reductions_dgp2dcp_canonicalizers_power_canon.R |only CVXR-1.8.2/CVXR/R/201_reductions_dgp2dcp_canonicalizers_sum_canon.R |only CVXR-1.8.2/CVXR/R/202_reductions_dgp2dcp_canonicalizers_exp_canon.R |only CVXR-1.8.2/CVXR/R/203_reductions_dgp2dcp_canonicalizers_log_canon.R |only CVXR-1.8.2/CVXR/R/204_reductions_dgp2dcp_canonicalizers_prod_canon.R |only CVXR-1.8.2/CVXR/R/205_reductions_dgp2dcp_canonicalizers_trace_canon.R |only CVXR-1.8.2/CVXR/R/206_reductions_dgp2dcp_canonicalizers_pnorm_canon.R |only CVXR-1.8.2/CVXR/R/207_reductions_dgp2dcp_canonicalizers_norm1_canon.R |only CVXR-1.8.2/CVXR/R/208_reductions_dgp2dcp_canonicalizers_norm_inf_canon.R |only CVXR-1.8.2/CVXR/R/209_reductions_dgp2dcp_canonicalizers_geo_mean_canon.R |only CVXR-1.8.2/CVXR/R/210_reductions_dgp2dcp_canonicalizers_quad_form_canon.R |only CVXR-1.8.2/CVXR/R/211_reductions_dgp2dcp_canonicalizers_quad_over_lin_canon.R |only CVXR-1.8.2/CVXR/R/212_reductions_dgp2dcp_canonicalizers_xexp_canon.R |only CVXR-1.8.2/CVXR/R/213_reductions_dgp2dcp_canonicalizers_cumprod_canon.R |only CVXR-1.8.2/CVXR/R/214_reductions_dgp2dcp_canonicalizers_one_minus_pos_canon.R |only CVXR-1.8.2/CVXR/R/215_reductions_dgp2dcp_canonicalizers_eye_minus_inv_canon.R |only CVXR-1.8.2/CVXR/R/216_reductions_dgp2dcp_canonicalizers_pf_eigenvalue_canon.R |only CVXR-1.8.2/CVXR/R/217_reductions_dgp2dcp_canonicalizers_gmatmul_canon.R |only CVXR-1.8.2/CVXR/R/218_reductions_dgp2dcp_canonicalizers_dgp_canonicalizers.R |only CVXR-1.8.2/CVXR/R/219_reductions_dgp2dcp_canonicalizers_finite_set_canon.R |only CVXR-1.8.2/CVXR/R/220_reductions_dgp2dcp_dgp2dcp.R |only CVXR-1.8.2/CVXR/R/221_reductions_dqcp2dcp_inverse.R |only CVXR-1.8.2/CVXR/R/222_reductions_dqcp2dcp_sets.R |only CVXR-1.8.2/CVXR/R/223_reductions_dqcp2dcp_tighten.R |only CVXR-1.8.2/CVXR/R/224_reductions_dqcp2dcp_dqcp2dcp.R |only CVXR-1.8.2/CVXR/R/225_reductions_discrete2mixedint_valinvec2mixedint.R |only CVXR-1.8.2/CVXR/R/226_reductions_solvers_bisection.R |only CVXR-1.8.2/CVXR/R/227_utilities_replace_quad_forms.R |only CVXR-1.8.2/CVXR/R/228_utilities_coeff_extractor.R |only CVXR-1.8.2/CVXR/R/229_utilities_perspective_utils.R |only CVXR-1.8.2/CVXR/R/230_reductions_dcp2cone_cone_matrix_stuffing.R |only CVXR-1.8.2/CVXR/R/231_reductions_cvx_attr2constr.R |only CVXR-1.8.2/CVXR/R/232_reductions_solvers_utilities.R |only CVXR-1.8.2/CVXR/R/233_reductions_solvers_solver.R |only CVXR-1.8.2/CVXR/R/234_reductions_solvers_constant_solver.R |only CVXR-1.8.2/CVXR/R/235_reductions_solvers_qp_solvers_qp_solver.R |only CVXR-1.8.2/CVXR/R/236_reductions_solvers_conic_solvers_conic_solver.R |only CVXR-1.8.2/CVXR/R/237_reductions_solvers_conic_solvers_scs_conif.R |only CVXR-1.8.2/CVXR/R/238_reductions_solvers_conic_solvers_clarabel_conif.R |only CVXR-1.8.2/CVXR/R/239_reductions_solvers_conic_solvers_mosek_conif.R |only CVXR-1.8.2/CVXR/R/240_reductions_solvers_conic_solvers_gurobi_conif.R |only CVXR-1.8.2/CVXR/R/241_reductions_solvers_conic_solvers_highs_conif.R |only CVXR-1.8.2/CVXR/R/242_reductions_solvers_conic_solvers_glpk_conif.R |only CVXR-1.8.2/CVXR/R/243_reductions_solvers_conic_solvers_glpk_mi_conif.R |only CVXR-1.8.2/CVXR/R/244_reductions_solvers_conic_solvers_ecos_conif.R |only CVXR-1.8.2/CVXR/R/245_reductions_solvers_conic_solvers_ecos_bb_conif.R |only CVXR-1.8.2/CVXR/R/246_reductions_solvers_conic_solvers_cvxopt_conif.R |only CVXR-1.8.2/CVXR/R/247_reductions_solvers_conic_solvers_scip_conif.R |only CVXR-1.8.2/CVXR/R/248_reductions_solvers_conic_solvers_xpress_conif.R |only CVXR-1.8.2/CVXR/R/249_reductions_solvers_qp_solvers_osqp_qpif.R |only CVXR-1.8.2/CVXR/R/250_reductions_solvers_qp_solvers_highs_qpif.R |only CVXR-1.8.2/CVXR/R/251_reductions_solvers_qp_solvers_gurobi_qpif.R |only CVXR-1.8.2/CVXR/R/252_reductions_solvers_qp_solvers_cplex_qpif.R |only CVXR-1.8.2/CVXR/R/253_reductions_solvers_qp_solvers_piqp_qpif.R |only CVXR-1.8.2/CVXR/R/254_reductions_solvers_qp_solvers_xpress_qpif.R |only CVXR-1.8.2/CVXR/R/255_reductions_solvers_solving_chain.R |only CVXR-1.8.2/CVXR/R/256_zzz_R_specific_visualize_annotations.R |only CVXR-1.8.2/CVXR/R/257_zzz_R_specific_visualize_html.R |only CVXR-1.8.2/CVXR/R/258_zzz_R_specific_visualize.R |only CVXR-1.8.2/CVXR/R/259_zzz_R_specific_to_latex.R |only CVXR-1.8.2/CVXR/R/260_zzz_R_specific_solver_opts.R |only CVXR-1.8.2/CVXR/R/261_zzz_R_specific_exports.R |only CVXR-1.8.2/CVXR/R/262_zzz_R_specific_math_atoms.R |only CVXR-1.8.2/CVXR/R/263_zzz_R_specific_masking.R |only CVXR-1.8.2/CVXR/R/264_zzz_R_specific_aliases.R |only CVXR-1.8.2/CVXR/R/265_zzz_R_specific_data.R |only CVXR-1.8.2/CVXR/inst/all_files.csv |only CVXR-1.8.2/CVXR/inst/copy_r_source.R |only CVXR-1.8.2/CVXR/inst/cran_tests.csv |only CVXR-1.9.1/CVXR/DESCRIPTION | 17 CVXR-1.9.1/CVXR/MD5 | 1158 +++++----- CVXR-1.9.1/CVXR/NAMESPACE | 38 CVXR-1.9.1/CVXR/NEWS.md | 206 + CVXR-1.9.1/CVXR/R/002_zzz_R_specific_globals.R | 2 CVXR-1.9.1/CVXR/R/003_zzz_R_specific_s7_dispatch_perf.R |only CVXR-1.9.1/CVXR/R/004_utilities_scopes.R |only CVXR-1.9.1/CVXR/R/005_zzz_R_specific_generics.R |only CVXR-1.9.1/CVXR/R/006_zzz_R_specific_utility.R |only CVXR-1.9.1/CVXR/R/007_utilities_sign.R |only CVXR-1.9.1/CVXR/R/008_utilities_shape.R |only CVXR-1.9.1/CVXR/R/009_utilities_error.R |only CVXR-1.9.1/CVXR/R/010_utilities_power_tools.R |only CVXR-1.9.1/CVXR/R/011_utilities_grad.R |only CVXR-1.9.1/CVXR/R/012_utilities_solver_context.R |only CVXR-1.9.1/CVXR/R/013_utilities_bounds.R |only CVXR-1.9.1/CVXR/R/014_settings.R |only CVXR-1.9.1/CVXR/R/015_lin_ops_LinOp.R |only CVXR-1.9.1/CVXR/R/016_lin_ops_LinOpVector.R |only CVXR-1.9.1/CVXR/R/017_lin_ops_RcppExports.R |only CVXR-1.9.1/CVXR/R/018_lin_ops_CVXcanon.R |only CVXR-1.9.1/CVXR/R/019_cvxcore_r_canonInterface.R |only CVXR-1.9.1/CVXR/R/020_zzz_R_specific_rcppUtils.R |only CVXR-1.9.1/CVXR/R/021_zzz_R_specific_sparse_utils.R |only CVXR-1.9.1/CVXR/R/022_zzz_R_specific_coll_utils.R |only CVXR-1.9.1/CVXR/R/023_interface_matrix_utilities.R |only CVXR-1.9.1/CVXR/R/024_lin_ops_lin_utils.R |only CVXR-1.9.1/CVXR/R/025_utilities_canonical.R |only CVXR-1.9.1/CVXR/R/026_expressions_expression.R |only CVXR-1.9.1/CVXR/R/027_expressions_leaf.R |only CVXR-1.9.1/CVXR/R/028_expressions_variable.R |only CVXR-1.9.1/CVXR/R/029_expressions_constants_constant.R |only CVXR-1.9.1/CVXR/R/030_expressions_constants_parameter.R |only CVXR-1.9.1/CVXR/R/031_expressions_constants_callback_param.R |only CVXR-1.9.1/CVXR/R/032_atoms_atom.R |only CVXR-1.9.1/CVXR/R/033_atoms_affine_affine_atom.R |only CVXR-1.9.1/CVXR/R/034_atoms_affine_conj.R |only CVXR-1.9.1/CVXR/R/035_atoms_affine_real.R |only CVXR-1.9.1/CVXR/R/036_atoms_affine_imag.R |only CVXR-1.9.1/CVXR/R/037_atoms_affine_wraps.R |only CVXR-1.9.1/CVXR/R/038_atoms_elementwise_elementwise.R |only CVXR-1.9.1/CVXR/R/039_atoms_axis_atom.R |only CVXR-1.9.1/CVXR/R/040_atoms_affine_axis_aff_atom.R |only CVXR-1.9.1/CVXR/R/041_atoms_affine_promote.R |only CVXR-1.9.1/CVXR/R/042_atoms_affine_unary_operators.R |only CVXR-1.9.1/CVXR/R/043_atoms_affine_add_expr.R |only CVXR-1.9.1/CVXR/R/044_atoms_affine_binary_operators.R |only CVXR-1.9.1/CVXR/R/045_atoms_affine_index.R |only CVXR-1.9.1/CVXR/R/046_atoms_affine_transpose.R |only CVXR-1.9.1/CVXR/R/047_atoms_affine_sum.R |only CVXR-1.9.1/CVXR/R/048_atoms_affine_reshape.R |only CVXR-1.9.1/CVXR/R/049_atoms_affine_diag.R |only CVXR-1.9.1/CVXR/R/050_atoms_affine_trace.R |only CVXR-1.9.1/CVXR/R/051_atoms_affine_partial_trace.R |only CVXR-1.9.1/CVXR/R/052_atoms_affine_partial_transpose.R |only CVXR-1.9.1/CVXR/R/053_atoms_affine_hstack.R |only CVXR-1.9.1/CVXR/R/054_atoms_affine_vstack.R |only CVXR-1.9.1/CVXR/R/055_atoms_affine_kron.R |only CVXR-1.9.1/CVXR/R/056_atoms_affine_upper_tri.R |only CVXR-1.9.1/CVXR/R/057_atoms_affine_conv.R |only CVXR-1.9.1/CVXR/R/058_atoms_affine_cumsum.R |only CVXR-1.9.1/CVXR/R/059_atoms_affine_diff.R |only CVXR-1.9.1/CVXR/R/060_atoms_affine_bmat.R |only CVXR-1.9.1/CVXR/R/061_atoms_elementwise_abs.R |only CVXR-1.9.1/CVXR/R/062_atoms_elementwise_exp.R |only CVXR-1.9.1/CVXR/R/063_atoms_elementwise_log.R |only CVXR-1.9.1/CVXR/R/064_atoms_elementwise_power.R |only CVXR-1.9.1/CVXR/R/065_atoms_elementwise_entr.R |only CVXR-1.9.1/CVXR/R/066_atoms_elementwise_huber.R |only CVXR-1.9.1/CVXR/R/067_atoms_elementwise_maximum.R |only CVXR-1.9.1/CVXR/R/068_atoms_elementwise_minimum.R |only CVXR-1.9.1/CVXR/R/069_atoms_elementwise_kl_div.R |only CVXR-1.9.1/CVXR/R/070_atoms_elementwise_rel_entr.R |only CVXR-1.9.1/CVXR/R/071_atoms_elementwise_log1p.R |only CVXR-1.9.1/CVXR/R/072_atoms_elementwise_xexp.R |only CVXR-1.9.1/CVXR/R/073_atoms_elementwise_logistic.R |only CVXR-1.9.1/CVXR/R/074_atoms_elementwise_square.R |only CVXR-1.9.1/CVXR/R/075_atoms_elementwise_pos.R |only CVXR-1.9.1/CVXR/R/076_atoms_elementwise_neg.R |only CVXR-1.9.1/CVXR/R/077_atoms_elementwise_inv_pos.R |only CVXR-1.9.1/CVXR/R/078_atoms_elementwise_scalene.R |only CVXR-1.9.1/CVXR/R/079_atoms_elementwise_loggamma.R |only CVXR-1.9.1/CVXR/R/080_atoms_elementwise_log_normcdf.R |only CVXR-1.9.1/CVXR/R/081_atoms_elementwise_normcdf.R |only CVXR-1.9.1/CVXR/R/082_atoms_elementwise_trig.R |only CVXR-1.9.1/CVXR/R/083_atoms_elementwise_hyperbolic.R |only CVXR-1.9.1/CVXR/R/084_atoms_elementwise_ceil.R |only CVXR-1.9.1/CVXR/R/085_atoms_elementwise_logic.R |only CVXR-1.9.1/CVXR/R/086_atoms_affine_vec.R |only CVXR-1.9.1/CVXR/R/087_atoms_total_variation.R |only CVXR-1.9.1/CVXR/R/088_atoms_sum_smallest.R |only CVXR-1.9.1/CVXR/R/089_atoms_harmonic_mean.R |only CVXR-1.9.1/CVXR/R/090_atoms_mixed_norm.R |only CVXR-1.9.1/CVXR/R/091_atoms_cvar.R |only CVXR-1.9.1/CVXR/R/092_atoms_ptp.R |only CVXR-1.9.1/CVXR/R/093_atoms_stats.R |only CVXR-1.9.1/CVXR/R/094_atoms_inv_prod.R |only CVXR-1.9.1/CVXR/R/095_zzz_R_specific_convenience.R |only CVXR-1.9.1/CVXR/R/096_atoms_norm1.R |only CVXR-1.9.1/CVXR/R/097_atoms_norm_inf.R |only CVXR-1.9.1/CVXR/R/098_atoms_pnorm.R |only CVXR-1.9.1/CVXR/R/099_atoms_max.R |only CVXR-1.9.1/CVXR/R/100_atoms_min.R |only CVXR-1.9.1/CVXR/R/101_atoms_norm.R |only CVXR-1.9.1/CVXR/R/102_atoms_geo_mean.R |only CVXR-1.9.1/CVXR/R/103_atoms_quad_form.R |only CVXR-1.9.1/CVXR/R/104_atoms_symbolic_quad_form.R |only CVXR-1.9.1/CVXR/R/105_atoms_quad_over_lin.R |only CVXR-1.9.1/CVXR/R/106_atoms_log_sum_exp.R |only CVXR-1.9.1/CVXR/R/107_atoms_sum_largest.R |only CVXR-1.9.1/CVXR/R/108_atoms_lambda_max.R |only CVXR-1.9.1/CVXR/R/109_atoms_sigma_max.R |only CVXR-1.9.1/CVXR/R/110_atoms_norm_nuc.R |only CVXR-1.9.1/CVXR/R/111_atoms_matrix_frac.R |only CVXR-1.9.1/CVXR/R/112_atoms_tr_inv.R |only CVXR-1.9.1/CVXR/R/113_atoms_lambda_sum_largest.R |only CVXR-1.9.1/CVXR/R/114_atoms_log_det.R |only CVXR-1.9.1/CVXR/R/115_atoms_cummax.R |only CVXR-1.9.1/CVXR/R/116_atoms_dotsort.R |only CVXR-1.9.1/CVXR/R/117_atoms_prod.R |only CVXR-1.9.1/CVXR/R/118_atoms_cumprod.R |only CVXR-1.9.1/CVXR/R/119_atoms_one_minus_pos.R |only CVXR-1.9.1/CVXR/R/120_atoms_eye_minus_inv.R |only CVXR-1.9.1/CVXR/R/121_atoms_pf_eigenvalue.R |only CVXR-1.9.1/CVXR/R/122_atoms_gmatmul.R |only CVXR-1.9.1/CVXR/R/123_atoms_perspective.R |only CVXR-1.9.1/CVXR/R/124_atoms_length.R |only CVXR-1.9.1/CVXR/R/125_atoms_condition_number.R |only CVXR-1.9.1/CVXR/R/126_atoms_gen_lambda_max.R |only CVXR-1.9.1/CVXR/R/127_atoms_dist_ratio.R |only CVXR-1.9.1/CVXR/R/128_atoms_sign.R |only CVXR-1.9.1/CVXR/R/129_zzz_R_specific_operators.R |only CVXR-1.9.1/CVXR/R/130_constraints_constraint.R |only CVXR-1.9.1/CVXR/R/131_constraints_zero.R |only CVXR-1.9.1/CVXR/R/132_constraints_nonpos.R |only CVXR-1.9.1/CVXR/R/133_constraints_cones.R |only CVXR-1.9.1/CVXR/R/134_constraints_second_order.R |only CVXR-1.9.1/CVXR/R/135_constraints_psd.R |only CVXR-1.9.1/CVXR/R/136_constraints_exponential.R |only CVXR-1.9.1/CVXR/R/137_constraints_power.R |only CVXR-1.9.1/CVXR/R/138_constraints_finite_set.R |only CVXR-1.9.1/CVXR/R/139_transforms_indicator.R |only CVXR-1.9.1/CVXR/R/140_problems_objective.R |only 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CVXR-1.9.1/CVXR/man/dot-constant_grad.Rd |only CVXR-1.9.1/CVXR/man/dot-error_grad.Rd |only CVXR-1.9.1/CVXR/man/dot-grad.Rd |only CVXR-1.9.1/CVXR/man/dotsort.Rd | 2 CVXR-1.9.1/CVXR/man/dpp_scope_active.Rd | 2 CVXR-1.9.1/CVXR/man/dspop.Rd | 2 CVXR-1.9.1/CVXR/man/dssamp.Rd | 2 CVXR-1.9.1/CVXR/man/dual_cone.Rd | 2 CVXR-1.9.1/CVXR/man/dual_residual.Rd | 2 CVXR-1.9.1/CVXR/man/dual_value.Rd | 2 CVXR-1.9.1/CVXR/man/entr.Rd | 2 CVXR-1.9.1/CVXR/man/expr_H.Rd | 2 CVXR-1.9.1/CVXR/man/expr_copy.Rd | 2 CVXR-1.9.1/CVXR/man/expr_name.Rd | 2 CVXR-1.9.1/CVXR/man/expr_sign.Rd | 2 CVXR-1.9.1/CVXR/man/eye_minus_inv.Rd | 2 CVXR-1.9.1/CVXR/man/floor_expr.Rd | 2 CVXR-1.9.1/CVXR/man/format_labeled.Rd |only CVXR-1.9.1/CVXR/man/gen_lambda_max.Rd | 2 CVXR-1.9.1/CVXR/man/geo_mean.Rd | 2 CVXR-1.9.1/CVXR/man/get_bounds.Rd |only CVXR-1.9.1/CVXR/man/get_data.Rd | 2 CVXR-1.9.1/CVXR/man/get_problem_data.Rd | 21 CVXR-1.9.1/CVXR/man/gmatmul.Rd | 2 CVXR-1.9.1/CVXR/man/grad.Rd | 2 CVXR-1.9.1/CVXR/man/gradient.Rd |only CVXR-1.9.1/CVXR/man/grapes-greater-than-greater-than-grapes.Rd | 2 CVXR-1.9.1/CVXR/man/grapes-less-than-less-than-grapes.Rd | 2 CVXR-1.9.1/CVXR/man/graph_implementation.Rd | 2 CVXR-1.9.1/CVXR/man/harmonic_mean.Rd | 2 CVXR-1.9.1/CVXR/man/has_quadratic_term.Rd | 2 CVXR-1.9.1/CVXR/man/hstack.Rd | 2 CVXR-1.9.1/CVXR/man/huber.Rd | 2 CVXR-1.9.1/CVXR/man/id.Rd | 2 CVXR-1.9.1/CVXR/man/iff.Rd | 2 CVXR-1.9.1/CVXR/man/imag_expr.Rd | 2 CVXR-1.9.1/CVXR/man/implies.Rd | 2 CVXR-1.9.1/CVXR/man/indicator.Rd | 2 CVXR-1.9.1/CVXR/man/installed_solvers.Rd | 2 CVXR-1.9.1/CVXR/man/intf_convert.Rd | 2 CVXR-1.9.1/CVXR/man/intf_is_hermitian.Rd | 2 CVXR-1.9.1/CVXR/man/intf_is_psd.Rd | 2 CVXR-1.9.1/CVXR/man/intf_is_skew_symmetric.Rd | 2 CVXR-1.9.1/CVXR/man/intf_is_sparse.Rd | 2 CVXR-1.9.1/CVXR/man/intf_shape.Rd | 2 CVXR-1.9.1/CVXR/man/intf_sign.Rd | 2 CVXR-1.9.1/CVXR/man/inv_pos.Rd | 2 CVXR-1.9.1/CVXR/man/inv_prod.Rd | 2 CVXR-1.9.1/CVXR/man/is_affine.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_concave.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_convex.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_log_log_concave.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_log_log_convex.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_quasiconcave.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_quasiconvex.Rd | 2 CVXR-1.9.1/CVXR/man/is_atom_smooth.Rd |only CVXR-1.9.1/CVXR/man/is_complex.Rd | 2 CVXR-1.9.1/CVXR/man/is_concave.Rd | 2 CVXR-1.9.1/CVXR/man/is_constant.Rd | 2 CVXR-1.9.1/CVXR/man/is_convex.Rd | 2 CVXR-1.9.1/CVXR/man/is_dcp.Rd | 2 CVXR-1.9.1/CVXR/man/is_decr.Rd | 2 CVXR-1.9.1/CVXR/man/is_dgp.Rd | 2 CVXR-1.9.1/CVXR/man/is_dnlp.Rd |only CVXR-1.9.1/CVXR/man/is_dpp.Rd | 8 CVXR-1.9.1/CVXR/man/is_dqcp.Rd | 2 CVXR-1.9.1/CVXR/man/is_hermitian.Rd | 2 CVXR-1.9.1/CVXR/man/is_imag.Rd | 2 CVXR-1.9.1/CVXR/man/is_incr.Rd | 2 CVXR-1.9.1/CVXR/man/is_linearizable_concave.Rd |only CVXR-1.9.1/CVXR/man/is_linearizable_convex.Rd |only CVXR-1.9.1/CVXR/man/is_log_log_affine.Rd | 2 CVXR-1.9.1/CVXR/man/is_log_log_concave.Rd | 2 CVXR-1.9.1/CVXR/man/is_log_log_convex.Rd | 2 CVXR-1.9.1/CVXR/man/is_lp.Rd | 2 CVXR-1.9.1/CVXR/man/is_matrix.Rd | 2 CVXR-1.9.1/CVXR/man/is_mixed_integer.Rd | 2 CVXR-1.9.1/CVXR/man/is_nonneg.Rd | 2 CVXR-1.9.1/CVXR/man/is_nonpos.Rd | 2 CVXR-1.9.1/CVXR/man/is_nsd.Rd | 2 CVXR-1.9.1/CVXR/man/is_param_affine.Rd | 2 CVXR-1.9.1/CVXR/man/is_param_free.Rd | 2 CVXR-1.9.1/CVXR/man/is_pos.Rd | 2 CVXR-1.9.1/CVXR/man/is_psd.Rd | 2 CVXR-1.9.1/CVXR/man/is_pwl.Rd | 4 CVXR-1.9.1/CVXR/man/is_qp.Rd | 2 CVXR-1.9.1/CVXR/man/is_qpwa.Rd | 2 CVXR-1.9.1/CVXR/man/is_quadratic.Rd | 2 CVXR-1.9.1/CVXR/man/is_quasiconcave.Rd | 2 CVXR-1.9.1/CVXR/man/is_quasiconvex.Rd | 2 CVXR-1.9.1/CVXR/man/is_quasilinear.Rd | 2 CVXR-1.9.1/CVXR/man/is_real.Rd | 2 CVXR-1.9.1/CVXR/man/is_scalar.Rd | 2 CVXR-1.9.1/CVXR/man/is_skew_symmetric.Rd | 2 CVXR-1.9.1/CVXR/man/is_smooth.Rd |only CVXR-1.9.1/CVXR/man/is_symmetric.Rd | 2 CVXR-1.9.1/CVXR/man/is_vector.Rd | 2 CVXR-1.9.1/CVXR/man/is_zero.Rd | 2 CVXR-1.9.1/CVXR/man/kl_div.Rd | 2 CVXR-1.9.1/CVXR/man/kron.Rd | 2 CVXR-1.9.1/CVXR/man/label-set.Rd |only CVXR-1.9.1/CVXR/man/label.Rd |only CVXR-1.9.1/CVXR/man/lambda_max.Rd | 2 CVXR-1.9.1/CVXR/man/lambda_min.Rd | 2 CVXR-1.9.1/CVXR/man/lambda_sum_largest.Rd | 2 CVXR-1.9.1/CVXR/man/lambda_sum_smallest.Rd | 2 CVXR-1.9.1/CVXR/man/length_expr.Rd | 2 CVXR-1.9.1/CVXR/man/linop_args_push_back.Rd | 2 CVXR-1.9.1/CVXR/man/linop_new.Rd | 2 CVXR-1.9.1/CVXR/man/linop_set_data_ndim.Rd | 2 CVXR-1.9.1/CVXR/man/linop_set_dense_data.Rd | 2 CVXR-1.9.1/CVXR/man/linop_set_linop_data.Rd | 2 CVXR-1.9.1/CVXR/man/linop_set_sparse_data.Rd | 2 CVXR-1.9.1/CVXR/man/linop_set_type.Rd | 2 CVXR-1.9.1/CVXR/man/linop_size_push_back.Rd | 2 CVXR-1.9.1/CVXR/man/linop_slice_push_back.Rd | 2 CVXR-1.9.1/CVXR/man/log1p_atom.Rd | 4 CVXR-1.9.1/CVXR/man/log_det.Rd | 2 CVXR-1.9.1/CVXR/man/log_normcdf.Rd | 2 CVXR-1.9.1/CVXR/man/log_sum_exp.Rd | 2 CVXR-1.9.1/CVXR/man/loggamma.Rd | 2 CVXR-1.9.1/CVXR/man/logistic.Rd | 2 CVXR-1.9.1/CVXR/man/make_sparse_diagonal_matrix.Rd | 2 CVXR-1.9.1/CVXR/man/math_atoms.Rd | 4 CVXR-1.9.1/CVXR/man/matrix_frac.Rd | 2 CVXR-1.9.1/CVXR/man/matrix_trace.Rd | 2 CVXR-1.9.1/CVXR/man/max_elemwise.Rd | 2 CVXR-1.9.1/CVXR/man/max_entries.Rd | 2 CVXR-1.9.1/CVXR/man/min_elemwise.Rd | 2 CVXR-1.9.1/CVXR/man/min_entries.Rd | 2 CVXR-1.9.1/CVXR/man/mixed_norm.Rd | 2 CVXR-1.9.1/CVXR/man/mul_sign.Rd | 2 CVXR-1.9.1/CVXR/man/multiply.Rd | 2 CVXR-1.9.1/CVXR/man/name.Rd | 2 CVXR-1.9.1/CVXR/man/neg.Rd | 2 CVXR-1.9.1/CVXR/man/norm1.Rd | 2 CVXR-1.9.1/CVXR/man/norm2.Rd | 2 CVXR-1.9.1/CVXR/man/norm_inf.Rd | 2 CVXR-1.9.1/CVXR/man/norm_nuc.Rd | 2 CVXR-1.9.1/CVXR/man/normcdf.Rd |only CVXR-1.9.1/CVXR/man/num_cones.Rd | 2 CVXR-1.9.1/CVXR/man/numeric_value.Rd | 2 CVXR-1.9.1/CVXR/man/objective.Rd | 2 CVXR-1.9.1/CVXR/man/one_minus_pos.Rd | 2 CVXR-1.9.1/CVXR/man/p_norm.Rd | 2 CVXR-1.9.1/CVXR/man/param_dict.Rd |only CVXR-1.9.1/CVXR/man/parameters.Rd | 2 CVXR-1.9.1/CVXR/man/partial_optimize.Rd |only CVXR-1.9.1/CVXR/man/partial_trace.Rd | 2 CVXR-1.9.1/CVXR/man/partial_transpose.Rd | 2 CVXR-1.9.1/CVXR/man/perspective.Rd | 2 CVXR-1.9.1/CVXR/man/pf_eigenvalue.Rd | 2 CVXR-1.9.1/CVXR/man/pos.Rd | 2 CVXR-1.9.1/CVXR/man/power.Rd | 11 CVXR-1.9.1/CVXR/man/problem_data.Rd | 21 CVXR-1.9.1/CVXR/man/problem_solution.Rd | 2 CVXR-1.9.1/CVXR/man/problem_status.Rd | 2 CVXR-1.9.1/CVXR/man/problem_unpack_results.Rd | 2 CVXR-1.9.1/CVXR/man/prod_entries.Rd | 2 CVXR-1.9.1/CVXR/man/project.Rd | 2 CVXR-1.9.1/CVXR/man/psolve.Rd | 29 CVXR-1.9.1/CVXR/man/ptp.Rd | 2 CVXR-1.9.1/CVXR/man/quad_form.Rd | 2 CVXR-1.9.1/CVXR/man/quad_form_dpp_scope_active.Rd |only CVXR-1.9.1/CVXR/man/quad_over_lin.Rd | 2 CVXR-1.9.1/CVXR/man/real_expr.Rd | 2 CVXR-1.9.1/CVXR/man/reduction-chain-rule.Rd |only CVXR-1.9.1/CVXR/man/reduction-id-map.Rd |only CVXR-1.9.1/CVXR/man/reduction_accepts.Rd | 2 CVXR-1.9.1/CVXR/man/reduction_apply.Rd | 2 CVXR-1.9.1/CVXR/man/reduction_invert.Rd | 2 CVXR-1.9.1/CVXR/man/rel_entr.Rd | 2 CVXR-1.9.1/CVXR/man/reshape_expr.Rd | 2 CVXR-1.9.1/CVXR/man/residual.Rd | 2 CVXR-1.9.1/CVXR/man/resolvent.Rd | 2 CVXR-1.9.1/CVXR/man/sample_bounds.Rd |only CVXR-1.9.1/CVXR/man/save_dual_value.Rd | 2 CVXR-1.9.1/CVXR/man/scalar_product.Rd | 2 CVXR-1.9.1/CVXR/man/scalarize.Rd |only CVXR-1.9.1/CVXR/man/scalene.Rd | 2 CVXR-1.9.1/CVXR/man/set_label.Rd | 41 CVXR-1.9.1/CVXR/man/shape_from_args.Rd | 2 CVXR-1.9.1/CVXR/man/sigma_max.Rd | 2 CVXR-1.9.1/CVXR/man/sign_from_args.Rd | 2 CVXR-1.9.1/CVXR/man/size.Rd | 2 CVXR-1.9.1/CVXR/man/size_metrics.Rd |only CVXR-1.9.1/CVXR/man/smith_annotation.Rd | 2 CVXR-1.9.1/CVXR/man/solution.Rd | 2 CVXR-1.9.1/CVXR/man/solve_via_data.Rd | 9 CVXR-1.9.1/CVXR/man/solver-constants.Rd | 50 CVXR-1.9.1/CVXR/man/solver_default_param.Rd | 2 CVXR-1.9.1/CVXR/man/solver_name.Rd | 2 CVXR-1.9.1/CVXR/man/solver_opts.Rd | 2 CVXR-1.9.1/CVXR/man/solver_stats.Rd | 2 CVXR-1.9.1/CVXR/man/split_adjoint.Rd |only CVXR-1.9.1/CVXR/man/split_solution.Rd |only CVXR-1.9.1/CVXR/man/square.Rd | 2 CVXR-1.9.1/CVXR/man/status-constants.Rd | 23 CVXR-1.9.1/CVXR/man/status.Rd | 2 CVXR-1.9.1/CVXR/man/sum_entries.Rd | 2 CVXR-1.9.1/CVXR/man/sum_largest.Rd | 8 CVXR-1.9.1/CVXR/man/sum_signs.Rd | 2 CVXR-1.9.1/CVXR/man/sum_smallest.Rd | 8 CVXR-1.9.1/CVXR/man/sum_squares.Rd | 2 CVXR-1.9.1/CVXR/man/supports_quad_obj.Rd | 2 CVXR-1.9.1/CVXR/man/to_latex.Rd | 2 CVXR-1.9.1/CVXR/man/total_variation.Rd | 2 CVXR-1.9.1/CVXR/man/tr_inv.Rd | 2 CVXR-1.9.1/CVXR/man/tree_copy.Rd | 2 CVXR-1.9.1/CVXR/man/tv.Rd | 2 CVXR-1.9.1/CVXR/man/unpack_results.Rd | 2 CVXR-1.9.1/CVXR/man/update_parameters.Rd | 2 CVXR-1.9.1/CVXR/man/upper_tri.Rd | 2 CVXR-1.9.1/CVXR/man/validate_arguments.Rd | 2 CVXR-1.9.1/CVXR/man/value-set.Rd | 2 CVXR-1.9.1/CVXR/man/value.Rd | 2 CVXR-1.9.1/CVXR/man/var_dict.Rd |only CVXR-1.9.1/CVXR/man/variables.Rd | 2 CVXR-1.9.1/CVXR/man/vdot.Rd | 2 CVXR-1.9.1/CVXR/man/vec.Rd | 2 CVXR-1.9.1/CVXR/man/vec_to_upper_tri.Rd | 2 CVXR-1.9.1/CVXR/man/violation.Rd | 2 CVXR-1.9.1/CVXR/man/visualize.Rd | 2 CVXR-1.9.1/CVXR/man/vstack.Rd | 2 CVXR-1.9.1/CVXR/man/with_dpp_scope.Rd | 2 CVXR-1.9.1/CVXR/man/with_quad_form_dpp_scope.Rd |only CVXR-1.9.1/CVXR/man/xexp.Rd | 2 CVXR-1.9.1/CVXR/tests/testthat/helper-solver-test-problems.R | 103 CVXR-1.9.1/CVXR/tests/testthat/helper-solvers.R | 9 CVXR-1.9.1/CVXR/tests/testthat/test-complex-parity.R |only CVXR-1.9.1/CVXR/tests/testthat/test-cran-solver-matrix.R | 39 CVXR-1.9.1/CVXR/tests/testthat/test-cvxpy-3180-parity-v19.R |only CVXR-1.9.1/CVXR/tests/testthat/test-cvxpy-atoms-parity.R |only CVXR-1.9.1/CVXR/tests/testthat/test-dgp-parity.R |only CVXR-1.9.1/CVXR/tests/testthat/test-dpp-parity.R |only CVXR-1.9.1/CVXR/vignettes/cvxr_intro.Rmd | 31 CVXR-1.9.1/CVXR/vignettes/whats_new.Rmd | 492 ++-- 883 files changed, 2462 insertions(+), 2028 deletions(-)
Title: Congruence Class Models for Networks
Description: Provides an implementation of Congruence Class Models (CCMs) for
generating networks. For additional details on CCMs see Goyal, Blitzstein,
and De Gruttola (2014) <doi:10.1017/nws.2014.2> and
Goyal, De Gruttola, Martin, Rennert, and Onnela <doi:10.48550/arXiv.2603.02467>.
'ccmnet' facilitates sampling networks based on specific topological properties
and attribute mixing patterns using a Markov Chain Monte Carlo framework.
The implementation builds upon code from the 'ergm' package;
see Handcock, Hunter, Butts, Goodreau, and Morris (2008) <doi:10.18637/jss.v024.i01>.
Author: Ravi Goyal [aut, cre],
Statnet Development Team [ctb, cph]
Maintainer: Ravi Goyal <ravi.j.goyal@gmail.com>
Diff between CCMnet versions 1.1.1 dated 2026-06-05 and 1.1.2 dated 2026-06-09
DESCRIPTION | 6 +++--- MD5 | 8 ++++---- R/CCMnet_Sample.R | 8 ++++---- man/sample_ccm.Rd | 24 ++++++++++++------------ src/MCMC_prob.c | 2 -- 5 files changed, 23 insertions(+), 25 deletions(-)