Title: Vectors in Partitioning
Description: Non-parametric clustering of joint pattern multi-genetic/epigenetic factors. The goal of this package is to cluster subjects based on gene features including single nucleotide polymorphisms (SNPs), DNA methylation (CPG), and gene expression (GE). The novel concept follows the general K-means (Hartigan and Wong (1979) <doi:10.2307/2346830> framework but uses weighted Euclidean distances across the gene features to cluster subjects. This approach is unique in that it attempts to capture all pairwise interactions in an effort to cluster based on their complex biological interactions.
Author: Joseph Handwerker [aut, cre],
Lauren Sobral [ctb],
Meredith Ray [aut, ctb]
Maintainer: Joseph Handwerker <jkhndwrk@memphis.edu>
Diff between RHclust versions 1.0.0 dated 2021-05-06 and 1.1.0 dated 2022-06-16
DESCRIPTION | 6 MD5 | 18 - NAMESPACE | 10 R/BinaryClass.R | 166 +++++------ R/SimData.R | 501 ++++++++++++++++----------------- R/VIP.R | 793 ++++++++++++++++++++++++++--------------------------- R/VIPnoCPG.R | 687 +++++++++++++++++++++++---------------------- R/VIPnoSNP.R | 683 ++++++++++++++++++++++----------------------- man/BinaryClass.Rd | 136 ++++----- man/SimData.Rd | 158 +++++----- 10 files changed, 1586 insertions(+), 1572 deletions(-)
Title: Compute Cluster Robust Standard Errors with Degrees of Freedom
Adjustments
Description: Estimate different types of cluster robust standard errors (CR0, CR1, CR2) with degrees of freedom adjustments. Standard errors are computed based on 'Liang and Zeger' (1986) <doi:10.1093/biomet/73.1.13> and Bell and 'McCaffrey' <https://www150.statcan.gc.ca/n1/en/pub/12-001-x/2002002/article/9058-eng.pdf?st=NxMjN1YZ>. Functions used in Huang and Li <doi:10.3758/s13428-021-01627-0>, Huang, 'Wiedermann', and 'Zhang' <doi:10.1080/00273171.2022.2077290>, and Huang, 'Zhang', and Li (forthcoming: Journal of Research on Educational Effectiveness).
Author: Francis Huang [aut, cre] ,
Bixi Zhang [aut]
Maintainer: Francis Huang <flhuang2000@yahoo.com>
Diff between CR2 versions 0.1.0 dated 2022-05-21 and 0.1.1 dated 2022-06-16
DESCRIPTION | 10 +++++----- MD5 | 13 ++++++++----- R/clustSE.R | 38 ++++++++++---------------------------- R/crct.R |only build/partial.rdb |binary data/crct.rda |only inst/CITATION | 10 +++++----- man/clustSE.Rd | 2 +- man/crct.Rd |only 9 files changed, 29 insertions(+), 44 deletions(-)
Title: Board Game Graphics
Description: Functions to make board game graphics with the 'ggplot2', 'grid', 'rayrender', 'rayvertex', and 'rgl' packages. Specializes in game diagrams, animations, and "Print & Play" layouts for the 'piecepack' <https://www.ludism.org/ppwiki> but can make graphics for other board game systems. Includes configurations for several public domain game systems such as checkers, (double-18) dominoes, go, 'piecepack', playing cards, etc.
Author: Trevor L Davis [aut, cre],
Linux Foundation [dtc] ,
Delapouite <https://delapouite.com/> [ill] ,
Creative Commons [ill] ` uses "license badges"
from Creative Commons to describe the generated print-and-play
file's license)
Maintainer: Trevor L Davis <trevor.l.davis@gmail.com>
Diff between piecepackr versions 1.10.3 dated 2022-03-22 and 1.11.1 dated 2022-06-16
piecepackr-1.10.3/piecepackr/R/utils-pnp-letter.R |only piecepackr-1.11.1/piecepackr/DESCRIPTION | 10 piecepackr-1.11.1/piecepackr/MD5 | 161 +-- piecepackr-1.11.1/piecepackr/NAMESPACE | 28 piecepackr-1.11.1/piecepackr/NEWS.md | 135 ++ piecepackr-1.11.1/piecepackr/R/animate_piece.R | 11 piecepackr-1.11.1/piecepackr/R/basicPieceGrob.R | 106 +- piecepackr-1.11.1/piecepackr/R/cropmarkGrob.R |only piecepackr-1.11.1/piecepackr/R/game_systems.R | 24 piecepackr-1.11.1/piecepackr/R/piece-rayrender.R | 2 piecepackr-1.11.1/piecepackr/R/piece3d-rgl.R | 4 piecepackr-1.11.1/piecepackr/R/pieceGrob-grid.R | 193 ++- piecepackr-1.11.1/piecepackr/R/piece_mesh-rayvertex.R | 2 piecepackr-1.11.1/piecepackr/R/piecepackr-package.R | 1 piecepackr-1.11.1/piecepackr/R/pmap_piece.R | 4 piecepackr-1.11.1/piecepackr/R/pp_cfg.R | 126 +- piecepackr-1.11.1/piecepackr/R/pp_shape.R | 20 piecepackr-1.11.1/piecepackr/R/render_piece.R | 4 piecepackr-1.11.1/piecepackr/R/save_piece_images.R | 7 piecepackr-1.11.1/piecepackr/R/save_piece_obj.R | 111 +- piecepackr-1.11.1/piecepackr/R/save_print_and_play.R | 47 piecepackr-1.11.1/piecepackr/R/sysdata.rda |binary piecepackr-1.11.1/piecepackr/R/utils-bleed-grobs.R | 84 + piecepackr-1.11.1/piecepackr/R/utils-boards.R | 163 ++- piecepackr-1.11.1/piecepackr/R/utils-composite.R | 25 piecepackr-1.11.1/piecepackr/R/utils-d6.R |only piecepackr-1.11.1/piecepackr/R/utils-fudge.R |only piecepackr-1.11.1/piecepackr/R/utils-geometry.R | 33 piecepackr-1.11.1/piecepackr/R/utils-grid.R |only piecepackr-1.11.1/piecepackr/R/utils-grobCoords.R | 24 piecepackr-1.11.1/piecepackr/R/utils-misc.R | 5 piecepackr-1.11.1/piecepackr/R/utils-op-grobs.R | 484 +++++++--- piecepackr-1.11.1/piecepackr/R/utils-pips.R | 244 +++-- piecepackr-1.11.1/piecepackr/R/utils-pnp-4x6.R | 5 piecepackr-1.11.1/piecepackr/R/utils-pnp-letter-bleed.R |only piecepackr-1.11.1/piecepackr/R/utils-pnp-letter-both.R |only piecepackr-1.11.1/piecepackr/R/utils-pnp-letter-compact.R |only piecepackr-1.11.1/piecepackr/R/utils-token.R | 160 ++- piecepackr-1.11.1/piecepackr/R/utils-transformation.R |only piecepackr-1.11.1/piecepackr/R/utils-xyz.R |only piecepackr-1.11.1/piecepackr/R/zzz.R | 5 piecepackr-1.11.1/piecepackr/README.md | 17 piecepackr-1.11.1/piecepackr/data/spdx_license_list.rda |binary piecepackr-1.11.1/piecepackr/man/basicPieceGrobs.Rd | 6 piecepackr-1.11.1/piecepackr/man/figures/README-dominoes-1.png |binary piecepackr-1.11.1/piecepackr/man/figures/README-proj-1.png |binary piecepackr-1.11.1/piecepackr/man/figures/README-rayvertex-1.png |binary piecepackr-1.11.1/piecepackr/man/figures/README-relativity.gif |binary piecepackr-1.11.1/piecepackr/man/game_systems.Rd | 6 piecepackr-1.11.1/piecepackr/man/grid.cropmark.Rd |only piecepackr-1.11.1/piecepackr/man/grid.piece.Rd | 92 + piecepackr-1.11.1/piecepackr/man/obj_fns.Rd | 4 piecepackr-1.11.1/piecepackr/man/piece.Rd | 6 piecepackr-1.11.1/piecepackr/man/piece3d.Rd | 8 piecepackr-1.11.1/piecepackr/man/piece_mesh.Rd | 6 piecepackr-1.11.1/piecepackr/man/piecepackr-package.Rd | 1 piecepackr-1.11.1/piecepackr/man/pp_cfg.Rd | 4 piecepackr-1.11.1/piecepackr/man/save_piece_images.Rd | 3 piecepackr-1.11.1/piecepackr/man/save_piece_obj.Rd | 12 piecepackr-1.11.1/piecepackr/man/save_print_and_play.Rd | 24 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/crop_marks |only piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/alpha-and-scale-op.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/diagram-op-ppgf.svg | 7 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/diagram-op.svg | 7 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/die-face-op.svg | 7 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/pyramid-face-op.svg | 4 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/pyramid-top-op.svg | 6 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/pyramid-top-s4-r3.svg | 24 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/draw_component/tile-back.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/game_systems/checkers.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/game_systems/dice-d6.svg | 42 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/game_systems/fudge.svg |only piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/game_systems/go.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/game_systems/reversi.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/op_transform/oblique-pyramids.svg | 74 - piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/op_transform/op-transform-225.svg | 18 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/op_transform/pyramid-tops-larger-on-top.svg | 48 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/op_transform/pyramid-tops-smaller-on-top.svg | 48 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/pp_shape/circle.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/pp_shape/polyclip-circle.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/_snaps/render_piece/render-piece-algebraic.svg | 2 piecepackr-1.11.1/piecepackr/tests/testthat/test-crop_marks.R |only piecepackr-1.11.1/piecepackr/tests/testthat/test-draw_component.R | 94 + piecepackr-1.11.1/piecepackr/tests/testthat/test-game_systems.R | 10 piecepackr-1.11.1/piecepackr/tests/testthat/test-obj.R | 12 piecepackr-1.11.1/piecepackr/tests/testthat/test-op_transform.R | 15 piecepackr-1.11.1/piecepackr/tests/testthat/test-options.R | 3 piecepackr-1.11.1/piecepackr/tests/testthat/test-render_piece.R | 1 88 files changed, 1914 insertions(+), 939 deletions(-)
Title: Logit Models w/Preference & WTP Space Utility Parameterizations
Description: Fast estimation of multinomial (MNL) and mixed logit (MXL) models in R. Models can be estimated using "Preference" space or "Willingness-to-pay" (WTP) space utility parameterizations. Weighted models can also be estimated. An option is available to run a parallelized multistart optimization loop with random starting points in each iteration, which is useful for non-convex problems like MXL models or models with WTP space utility parameterizations. The main optimization loop uses the 'nloptr' package to minimize the negative log-likelihood function. Additional functions are available for computing and comparing WTP from both preference space and WTP space models and for predicting expected choices and choice probabilities for sets of alternatives based on an estimated model. Mixed logit models can include uncorrelated or correlated heterogeneity covariances and are estimated using maximum simulated likelihood based on the algorithms in Train (2009) "Discrete Choice Methods with Simulation, 2nd Edition" <doi:10.1017/CBO9780511805271>.
Author: John Helveston [aut, cre, cph]
,
Connor Forsythe [ctb]
Maintainer: John Helveston <john.helveston@gmail.com>
Diff between logitr versions 0.6.1 dated 2022-06-12 and 0.7.0 dated 2022-06-16
DESCRIPTION | 9 MD5 | 111 +++++------ NEWS.md | 10 R/data.R | 46 +++- R/draws.R | 8 R/encoding.R | 3 R/inputChecks.R | 83 ++------ R/logit.R | 26 +- R/logitr.R | 85 +++++--- R/methods.R | 8 R/modelInputs.R | 119 +++++++---- R/optimLoop.R | 12 - R/predict.R | 42 ++-- R/wtp.R | 79 ++++--- README.md | 12 - build/partial.rdb |binary build/vignette.rds |binary data/runtimes.rda |only inst/CITATION | 4 inst/doc/basic_usage.R | 54 ++--- inst/doc/basic_usage.Rmd | 92 ++++----- inst/doc/basic_usage.html | 351 +++++++++++++++++------------------ inst/doc/benchmark.R |only inst/doc/benchmark.Rmd |only inst/doc/benchmark.html |only inst/doc/data_formatting.html | 22 +- inst/doc/interactions.html | 20 - inst/doc/mnl_models.R | 7 inst/doc/mnl_models.Rmd | 7 inst/doc/mnl_models.html | 85 ++++---- inst/doc/mnl_models_weighted.R | 10 inst/doc/mnl_models_weighted.Rmd | 10 inst/doc/mnl_models_weighted.html | 247 ++++++++++++------------ inst/doc/mxl_models.R | 7 inst/doc/mxl_models.Rmd | 7 inst/doc/mxl_models.html | 328 ++++++++++++++++---------------- inst/doc/predict.R | 16 - inst/doc/predict.Rmd | 18 - inst/doc/predict.html | 75 +++---- inst/example/examples.R | 3 inst/extdata/mxl_pref.Rds |binary inst/extdata/mxl_pref_cor.Rds |binary inst/extdata/mxl_wtp.Rds |binary man/logitr.Rd | 48 +++- man/predict.logitr.Rd | 5 man/recodeData.Rd | 3 man/runtimes.Rd |only man/wtp.Rd | 13 - man/wtp.logitr.Rd | 15 - man/wtpCompare.Rd | 30 +- tests/testthat/test_gradients_pref.R | 12 - tests/testthat/test_gradients_wtp.R | 166 ++++++++-------- tests/testthat/test_startPars.R | 12 - vignettes/basic_usage.Rmd | 92 ++++----- vignettes/benchmark.Rmd |only vignettes/benchmark.png |only vignettes/mnl_models.Rmd | 7 vignettes/mnl_models_weighted.Rmd | 10 vignettes/mxl_models.Rmd | 7 vignettes/predict.Rmd | 18 - 60 files changed, 1260 insertions(+), 1194 deletions(-)
Title: Retrieve Data using the 'IsoMemo' API
Description: API wrapper that contains functions to retrieve data from the 'IsoMemo' partnership databases. Web services for API: <https://isomemodb.com/api/v1/iso-data>.
Author: Jianyin Roachell [cre],
Andreas Neudecker [aut],
Ricardo Fernandes [aut]
Maintainer: Jianyin Roachell <jianyin.roachell@inwt-statistics.de>
Diff between IsoMemo versions 1.0.5 dated 2022-06-03 and 1.0.6 dated 2022-06-16
DESCRIPTION | 10 +-- MD5 | 8 +- NEWS.md | 31 ++++++--- R/01-getData.R | 185 ++++++++++++++++++++++++++++----------------------------- man/getData.Rd | 6 - 5 files changed, 126 insertions(+), 114 deletions(-)
Title: Bindings for Bayesian TidyModels
Description: Fit Bayesian models using 'brms'/'Stan' with 'parsnip'/'tidymodels'
via 'bayesian' <doi:10.5281/zenodo.6654386>. 'tidymodels' is a collection of
packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>).
The technical details of 'brms' and 'Stan' are described in Bürkner (2017)
<doi:10.18637/jss.v080.i01>, Bürkner (2018) <doi:10.32614/RJ-2018-017>,
and Carpenter et al. (2017) <doi:10.18637/jss.v076.i01>.
Author: Hamada S. Badr [aut, cre] ,
Paul-Christian Buerkner [aut]
Maintainer: Hamada S. Badr <badr@jhu.edu>
Diff between bayesian versions 0.0.8 dated 2022-01-20 and 0.0.9 dated 2022-06-16
DESCRIPTION | 12 +++---- MD5 | 30 ++++++++--------- NEWS.md | 10 +++++ R/bayesian.R | 58 +++++++++------------------------- R/bayesian_make.R | 24 ++++++++------ README.md | 35 +++++++------------- inst/CITATION | 2 - inst/WORDLIST | 2 - inst/doc/BugReports.html | 4 +- inst/doc/GetStarted.R | 30 ++++++++--------- inst/doc/GetStarted.Rmd | 30 ++++++++--------- inst/doc/GetStarted.html | 52 +++++++++++++++--------------- man/bayesian.Rd | 69 ++++++++++++++++++++++------------------- man/rmd/bayesian-engine.Rmd | 4 +- tests/testthat/test-bayesian.R | 4 +- vignettes/GetStarted.Rmd | 30 ++++++++--------- 16 files changed, 191 insertions(+), 205 deletions(-)
Title: Bindings for Additive TidyModels
Description: Fit Generalized Additive Models (GAM) using 'mgcv' with 'parsnip'/'tidymodels'
via 'additive' <doi:10.5281/zenodo.6654298>. 'tidymodels' is a collection of
packages for machine learning; see Kuhn and Wickham (2020) <https://www.tidymodels.org>).
The technical details of 'mgcv' are described in Wood (2017)
<doi:10.1201/9781315370279>.
Author: Hamada S. Badr [aut, cre]
Maintainer: Hamada S. Badr <badr@jhu.edu>
Diff between additive versions 0.0.4 dated 2022-01-20 and 0.0.5 dated 2022-06-16
DESCRIPTION | 12 ++++----- MD5 | 30 ++++++++++++------------ NEWS.md | 9 +++++++ R/additive.R | 50 ++++++++--------------------------------- R/additive_make.R | 28 +++++++++------------- README.md | 39 ++++++++++++------------------- build/vignette.rds |binary inst/CITATION | 2 - inst/doc/BugReports.html | 4 +-- inst/doc/GetStarted.R | 28 +++++++++++----------- inst/doc/GetStarted.Rmd | 28 +++++++++++----------- inst/doc/GetStarted.html | 45 +++++++++++++++++++++--------------- man/additive.Rd | 26 +++++++++------------ man/rmd/additive-engine.Rmd | 4 +-- tests/testthat/test-additive.R | 20 ++++++++-------- vignettes/GetStarted.Rmd | 28 +++++++++++----------- 16 files changed, 162 insertions(+), 191 deletions(-)
Title: Implementing Methods for Spatial Fuzzy Unsupervised
Classification
Description: Provides functions to apply spatial fuzzy unsupervised classification, visualize and interpret results. This method is well suited when the user wants to analyze data with a fuzzy clustering algorithm and to account for the spatial dimension of the dataset. In addition, indexes for estimating the spatial consistency and classification quality are proposed.
The methods were originally proposed in the field of brain imagery (seed Cai and al. 2007 <doi:10.1016/j.patcog.2006.07.011> and Zaho and al. 2013 <doi:10.1016/j.dsp.2012.09.016>) and recently applied in geography (see Gelb and Apparicio <doi:10.4000/cybergeo.36414>).
Author: Jeremy Gelb [aut, cre],
Philippe Apparicio [ctb]
Maintainer: Jeremy Gelb <jeremy.gelb@ucs.inrs.ca>
Diff between geocmeans versions 0.2.0 dated 2021-08-23 and 0.2.2 dated 2022-06-16
geocmeans-0.2.0/geocmeans/man/Elsa_categorical_matrix.Rd |only geocmeans-0.2.0/geocmeans/man/moranI_matrix.Rd |only geocmeans-0.2.2/geocmeans/DESCRIPTION | 21 geocmeans-0.2.2/geocmeans/MD5 | 274 +-- geocmeans-0.2.2/geocmeans/NAMESPACE | 2 geocmeans-0.2.2/geocmeans/NEWS.md | 12 geocmeans-0.2.2/geocmeans/R/FCM.R | 22 geocmeans-0.2.2/geocmeans/R/FCMclass.R | 29 geocmeans-0.2.2/geocmeans/R/GFCM.R | 22 geocmeans-0.2.2/geocmeans/R/RcppExports.R | 26 geocmeans-0.2.2/geocmeans/R/assembling.R | 21 geocmeans-0.2.2/geocmeans/R/boostrap_clust_validation.R | 4 geocmeans-0.2.2/geocmeans/R/clustering_evaluation.R | 27 geocmeans-0.2.2/geocmeans/R/raster_support.R | 8 geocmeans-0.2.2/geocmeans/R/shinyapp.R | 13 geocmeans-0.2.2/geocmeans/R/side_functions.R | 60 geocmeans-0.2.2/geocmeans/R/spatial_indices.R | 78 - geocmeans-0.2.2/geocmeans/README.md | 9 geocmeans-0.2.2/geocmeans/build/partial.rdb |binary geocmeans-0.2.2/geocmeans/build/vignette.rds |binary geocmeans-0.2.2/geocmeans/data/Arcachon.rda |binary geocmeans-0.2.2/geocmeans/inst/doc/FCMres.html | 245 +++ geocmeans-0.2.2/geocmeans/inst/doc/adjustinconsistency.R | 7 geocmeans-0.2.2/geocmeans/inst/doc/adjustinconsistency.Rmd | 7 geocmeans-0.2.2/geocmeans/inst/doc/adjustinconsistency.html | 325 +++- geocmeans-0.2.2/geocmeans/inst/doc/introduction.R | 2 geocmeans-0.2.2/geocmeans/inst/doc/introduction.Rmd | 2 geocmeans-0.2.2/geocmeans/inst/doc/introduction.html | 738 +++++++--- geocmeans-0.2.2/geocmeans/inst/doc/rasters.R | 4 geocmeans-0.2.2/geocmeans/inst/doc/rasters.Rmd | 4 geocmeans-0.2.2/geocmeans/inst/doc/rasters.html | 379 ++++- geocmeans-0.2.2/geocmeans/inst/extdata/results_vignette_intro.rda |binary geocmeans-0.2.2/geocmeans/inst/extdata/results_vignette_raster.rda |binary geocmeans-0.2.2/geocmeans/man/Arcachon.Rd | 60 geocmeans-0.2.2/geocmeans/man/Elsa_categorical_matrix_window.Rd | 44 geocmeans-0.2.2/geocmeans/man/Elsa_fuzzy_matrix_window.Rd | 44 geocmeans-0.2.2/geocmeans/man/FCMres.Rd | 96 - geocmeans-0.2.2/geocmeans/man/GCMeans.Rd | 160 +- geocmeans-0.2.2/geocmeans/man/LyonIris.Rd | 78 - geocmeans-0.2.2/geocmeans/man/SGFCMeans.Rd | 254 +-- geocmeans-0.2.2/geocmeans/man/add_matrices_bycol.Rd | 40 geocmeans-0.2.2/geocmeans/man/adj_spconsist_arr_window_globstd.Rd | 44 geocmeans-0.2.2/geocmeans/man/adjustSpatialWeights.Rd | 67 geocmeans-0.2.2/geocmeans/man/barPlots.Rd | 66 geocmeans-0.2.2/geocmeans/man/belongsFCM.Rd | 44 geocmeans-0.2.2/geocmeans/man/belongsGFCM.Rd | 44 geocmeans-0.2.2/geocmeans/man/belongsSFCM.Rd | 44 geocmeans-0.2.2/geocmeans/man/belongsSGFCM.Rd | 44 geocmeans-0.2.2/geocmeans/man/boot_group_validation.Rd | 172 +- geocmeans-0.2.2/geocmeans/man/boot_group_validation.mc.Rd | 150 +- geocmeans-0.2.2/geocmeans/man/boot_worker.Rd | 70 geocmeans-0.2.2/geocmeans/man/calcCalinskiHarabasz.Rd | 76 - geocmeans-0.2.2/geocmeans/man/calcCentroids.Rd | 44 geocmeans-0.2.2/geocmeans/man/calcDaviesBouldin.Rd | 104 - geocmeans-0.2.2/geocmeans/man/calcELSA.Rd | 102 - geocmeans-0.2.2/geocmeans/man/calcEuclideanDistance.Rd | 50 geocmeans-0.2.2/geocmeans/man/calcEuclideanDistance2.Rd | 40 geocmeans-0.2.2/geocmeans/man/calcEuclideanDistance3.Rd | 40 geocmeans-0.2.2/geocmeans/man/calcFGCMBelongMatrix.Rd | 56 geocmeans-0.2.2/geocmeans/man/calcFukuyamaSugeno.Rd | 88 - geocmeans-0.2.2/geocmeans/man/calcFuzzyELSA.Rd | 98 - geocmeans-0.2.2/geocmeans/man/calcFuzzyElsa_raster.Rd | 56 geocmeans-0.2.2/geocmeans/man/calcGD43.Rd | 108 - geocmeans-0.2.2/geocmeans/man/calcGD53.Rd | 112 - geocmeans-0.2.2/geocmeans/man/calcLaggedData.Rd | 52 geocmeans-0.2.2/geocmeans/man/calcNegentropyI.Rd | 102 - geocmeans-0.2.2/geocmeans/man/calcQualIdx.Rd | 46 geocmeans-0.2.2/geocmeans/man/calcSFGCMBelongMatrix.Rd | 66 geocmeans-0.2.2/geocmeans/man/calcSilhouetteIdx.Rd | 48 geocmeans-0.2.2/geocmeans/man/calcUncertaintyIndex.Rd | 92 - geocmeans-0.2.2/geocmeans/man/calcWdataRaster.Rd | 52 geocmeans-0.2.2/geocmeans/man/calc_jaccard_idx.Rd | 40 geocmeans-0.2.2/geocmeans/man/calc_jaccard_mat.Rd | 42 geocmeans-0.2.2/geocmeans/man/calc_local_moran_raster.Rd | 50 geocmeans-0.2.2/geocmeans/man/calc_moran_raster.Rd | 50 geocmeans-0.2.2/geocmeans/man/calc_raster_spinconsistency.Rd | 56 geocmeans-0.2.2/geocmeans/man/cat_to_belongings.Rd | 41 geocmeans-0.2.2/geocmeans/man/centersFCM.Rd | 48 geocmeans-0.2.2/geocmeans/man/centersGFCM.Rd | 48 geocmeans-0.2.2/geocmeans/man/centersSFCM.Rd | 48 geocmeans-0.2.2/geocmeans/man/centersSGFCM.Rd | 48 geocmeans-0.2.2/geocmeans/man/check_matdist.Rd | 36 geocmeans-0.2.2/geocmeans/man/check_raters_dims.Rd | 36 geocmeans-0.2.2/geocmeans/man/check_window.Rd | 36 geocmeans-0.2.2/geocmeans/man/circular_window.Rd | 62 geocmeans-0.2.2/geocmeans/man/div_matrices_bycol.Rd | 40 geocmeans-0.2.2/geocmeans/man/elsa_fuzzy_vector.Rd | 52 geocmeans-0.2.2/geocmeans/man/elsa_raster.Rd | 54 geocmeans-0.2.2/geocmeans/man/elsa_vector.Rd | 52 geocmeans-0.2.2/geocmeans/man/evaluateMatrices.Rd | 60 geocmeans-0.2.2/geocmeans/man/focal_adj_mean_arr_window.Rd | 40 geocmeans-0.2.2/geocmeans/man/focal_euclidean.Rd | 44 geocmeans-0.2.2/geocmeans/man/focal_euclidean_arr_window.Rd | 42 geocmeans-0.2.2/geocmeans/man/focal_euclidean_mat_window.Rd | 42 geocmeans-0.2.2/geocmeans/man/force_sp_sample.Rd | 54 geocmeans-0.2.2/geocmeans/man/geocmeans.Rd | 48 geocmeans-0.2.2/geocmeans/man/geocmeans_env.Rd | 32 geocmeans-0.2.2/geocmeans/man/groups_matching.Rd | 94 - geocmeans-0.2.2/geocmeans/man/input_raster_data.Rd | 56 geocmeans-0.2.2/geocmeans/man/is.FCMres.Rd | 56 geocmeans-0.2.2/geocmeans/man/kppCenters.Rd | 48 geocmeans-0.2.2/geocmeans/man/local_moranI_matrix_window.Rd | 40 geocmeans-0.2.2/geocmeans/man/main_worker.Rd | 58 geocmeans-0.2.2/geocmeans/man/mapLines.Rd | 66 geocmeans-0.2.2/geocmeans/man/mapPoints.Rd | 66 geocmeans-0.2.2/geocmeans/man/mapPolygons.Rd | 66 geocmeans-0.2.2/geocmeans/man/mapRasters.Rd | 60 geocmeans-0.2.2/geocmeans/man/max_mat.Rd | 36 geocmeans-0.2.2/geocmeans/man/moranI_matrix_window.Rd | 40 geocmeans-0.2.2/geocmeans/man/output_raster_data.Rd | 50 geocmeans-0.2.2/geocmeans/man/plot.FCMres.Rd | 92 - geocmeans-0.2.2/geocmeans/man/pow_matrices_bycol.Rd | 42 geocmeans-0.2.2/geocmeans/man/power_mat.Rd | 40 geocmeans-0.2.2/geocmeans/man/predict.FCMres.Rd | 134 - geocmeans-0.2.2/geocmeans/man/print.FCMres.Rd | 56 geocmeans-0.2.2/geocmeans/man/prod_matrices_bycol.Rd | 40 geocmeans-0.2.2/geocmeans/man/rowmins_mat.Rd | 36 geocmeans-0.2.2/geocmeans/man/sanity_check.Rd | 46 geocmeans-0.2.2/geocmeans/man/select_parameters.mc.Rd | 4 geocmeans-0.2.2/geocmeans/man/spConsistency.Rd | 1 geocmeans-0.2.2/geocmeans/man/spiderPlots.Rd | 76 - geocmeans-0.2.2/geocmeans/man/sqrt_matrix_bycol.Rd | 36 geocmeans-0.2.2/geocmeans/man/sub_matrices_bycol.Rd | 40 geocmeans-0.2.2/geocmeans/man/summary.FCMres.Rd | 88 - geocmeans-0.2.2/geocmeans/man/test_inferior_mat.Rd | 40 geocmeans-0.2.2/geocmeans/man/uncertaintyMap.Rd | 116 - geocmeans-0.2.2/geocmeans/man/vecmin.Rd | 50 geocmeans-0.2.2/geocmeans/man/vector_out_prod.Rd | 36 geocmeans-0.2.2/geocmeans/man/violinPlots.Rd | 64 geocmeans-0.2.2/geocmeans/src/RcppExports.cpp | 32 geocmeans-0.2.2/geocmeans/src/moran_for_rasters.cpp | 302 ++-- geocmeans-0.2.2/geocmeans/tests/testthat/test_FCMresclass.R |only geocmeans-0.2.2/geocmeans/tests/testthat/test_basic_functions.R | 70 geocmeans-0.2.2/geocmeans/tests/testthat/test_belongingmatrices.R | 4 geocmeans-0.2.2/geocmeans/tests/testthat/test_focal_functions.R |only geocmeans-0.2.2/geocmeans/tests/testthat/test_group_checking.R |only geocmeans-0.2.2/geocmeans/tests/testthat/test_parameter_evaluation.R |only geocmeans-0.2.2/geocmeans/tests/testthat/test_spatial_functions.R | 178 ++ geocmeans-0.2.2/geocmeans/vignettes/adjustinconsistency.Rmd | 7 geocmeans-0.2.2/geocmeans/vignettes/introduction.Rmd | 2 geocmeans-0.2.2/geocmeans/vignettes/rasters.Rmd | 4 141 files changed, 5140 insertions(+), 3727 deletions(-)
Title: Forest Inventory Estimation and Analysis
Description: A research estimation tool for analysts that work with sample-based
inventory data from the U.S. Department of Agriculture, Forest Service,
Forest Inventory and Analysis (FIA) Program.
Author: Tracey Frescino [aut],
Gretchen Moisen [aut],
Paul Patterson [aut],
Chris Toney [aut],
Grayson White [aut, cre]
Maintainer: Grayson White <graysonwhite13@gmail.com>
Diff between FIESTA versions 3.4.0 dated 2022-05-19 and 3.4.1 dated 2022-06-16
DESCRIPTION | 10 MD5 | 94 - NEWS.md | 19 R/DBgetCSV.R | 35 R/DBgetEvalid.R | 9 R/DBgetPlots.R | 14 R/DBgetStrata.R | 63 R/DBgetXY.R | 13 R/FIESTA-package.R | 35 R/IDBinternal.R |only R/ISAinternal.R | 95 - R/check.auxiliary.R | 17 R/check.pltcnt.R | 7 R/check.popdata.R | 248 +++ R/datSumCond.R | 36 R/datSumTree.R | 123 + R/datSumTreeDom.R | 49 R/modGBpop.R | 20 R/modMAarea.R | 4 R/modMApop.R | 2 R/modSAarea.R | 72 - R/modSAtree.R | 67 R/popTables.R | 16 R/spGetAuxiliary.R | 18 R/spGetEstUnit.R | 8 R/spGetPlots.R | 50 R/spGetSAdoms.R | 67 R/spGetStrata.R | 11 R/spGetXY.R | 23 R/spMakeSpatialPoints.R | 6 R/spUnionPoly.R | 5 data/ref_plt.rda |binary inst/doc/FIESTA_tutorial_GB.R | 89 + inst/doc/FIESTA_tutorial_GB.Rmd | 139 +- inst/doc/FIESTA_tutorial_GB.html | 2614 ++++++++++++++++++++------------------ inst/doc/FIESTA_tutorial_MA.html | 152 +- inst/doc/FIESTA_tutorial_PB.html | 2 inst/doc/FIESTA_tutorial_SA.html | 27 inst/doc/FIESTA_tutorial_dat.html | 141 +- inst/extdata/FIA_data |only man/DBgetStrata.Rd | 7 man/FIESTA-package.Rd | 31 man/datSumCond.Rd | 7 man/datSumTree.Rd | 9 man/datSumTreeDom.Rd | 9 man/popTables.Rd | 11 man/spGetPlots.Rd | 3 man/spGetSAdoms.Rd | 11 vignettes/FIESTA_tutorial_GB.Rmd | 139 +- 49 files changed, 2916 insertions(+), 1711 deletions(-)
Title: Construct PGx PRS
Description: Construct pharmacogenomics (PGx) polygenic risk score (PRS) with PRS-PGx-Unadj (unadjusted), PRS-PGx-CT (clumping and thresholding), PRS-PGx-L, -GL, -SGL (penalized regression), PRS-PGx-Bayes (Bayesian regression). Package is based on ''Pharmacogenomics Polyenic Risk Score for Drug Response Prediction Using PRS-PGx Methods'' by Zhai, S., Zhang, H., Mehrotra, D.V., and Shen, J., 2021 (submitted).
Author: Song Zhai [aut, cre]
Maintainer: Song Zhai <zsviolet1993@gmail.com>
Diff between PRSPGx versions 0.1.0 dated 2021-12-15 and 0.2.0 dated 2022-06-16
DESCRIPTION | 11 ++++++----- MD5 | 16 ++++++++-------- NAMESPACE | 3 +++ R/PRS_PGx_Bayes.R | 12 ++++++------ R/import_pkgs.R | 2 ++ build/vignette.rds |binary inst/doc/README.Rmd | 10 ++++++---- inst/doc/README.html | 48 +++++++++++++++++++++++++++++++++++++++--------- vignettes/README.Rmd | 10 ++++++---- 9 files changed, 76 insertions(+), 36 deletions(-)
Title: Bayesian and Classical Audit Sampling
Description: Provides statistical audit sampling methods as implemented in JASP for Audit (Derks et al., 2021 <doi:10.21105/joss.02733>). The package makes it easy for an auditor to plan a statistical sample, select the sample from the population, and evaluate the misstatement in the sample compliant with the International Standards on Auditing. Next to classical audit sampling methodology, the package implements Bayesian equivalents of these methods whose statistical underpinnings are described in Derks et al. (2021) <doi:10.1111/ijau.12240>, Derks et al. (2021) <doi:10.31234/osf.io/kzqp5>, and Derks et al. (2022) <doi:10.31234/osf.io/8nf3e>.
Author: Koen Derks [aut, cre]
Maintainer: Koen Derks <k.derks@nyenrode.nl>
Diff between jfa versions 0.6.3 dated 2022-02-21 and 0.6.4 dated 2022-06-16
DESCRIPTION | 14 MD5 | 40 + NEWS.md | 7 R/evaluation.R | 17 R/planning.R | 6 R/report.R | 2 R/selection.R | 2 README.md | 8 build/vignette.rds |binary inst/CITATION | 4 inst/doc/jfa.html | 436 +++++++++++++++++++-- inst/doc/v1_sampling_workflow.html | 353 +++++++++++++++-- inst/doc/v2_bayesian_sampling_workflow.html | 406 +++++++++++++++++-- inst/doc/v3_prior_distributions.html | 450 ++++++++++++++++++---- inst/doc/v4_selection_methodology.html | 412 ++++++++++++++++++-- inst/doc/v5_estimating_misstatement.html | 263 ++++++++++++ inst/doc/v6_testing_misstatement.html | 301 +++++++++++++- inst/doc/v7_bayes_factors_summary_statistics.html | 334 +++++++++++++++- man/jfa.Rd | 2 tests/testthat/test-validation-audit-sampler.R | 2 tests/testthat/test-validation-ezquant.R |only tests/testthat/test-validation-samplingbook.R |only 22 files changed, 2736 insertions(+), 323 deletions(-)
Title: Tests for Detecting Irregular Digit Patterns
Description: Provides statistical tests and support functions for detecting irregular digit patterns in numerical data. The package includes tools for extracting digits at various locations in a number, tests for repeated values, and (Bayesian) tests of digit distributions.
Author: Koen Derks [aut, cre]
Maintainer: Koen Derks <k.derks@nyenrode.nl>
Diff between digitTests versions 0.1.1 dated 2021-11-09 and 0.1.2 dated 2022-06-16
DESCRIPTION | 14 +- MD5 | 26 ++-- NEWS.md | 6 + R/digitTests-methods.R | 15 ++ R/distr.btest.R | 17 ++- R/distr.test.R | 15 ++ R/extract_digits.R | 15 ++ R/rv.test.R | 17 ++- README.md | 7 - build/vignette.rds |binary inst/CITATION | 6 - inst/doc/digitTests.html | 260 ++++++++++++++++++++++++++++++++++++++++++++--- man/digitTests.Rd | 2 man/distr.btest.Rd | 2 14 files changed, 356 insertions(+), 46 deletions(-)
Title: Discrete Goodness-of-Fit Tests
Description: A revision to the stats::ks.test() function and the associated
ks.test.Rd help page. With one minor exception, it does not change the
existing behavior of ks.test(), and it adds features necessary
for doing one-sample tests with hypothesized discrete
distributions. The package also contains cvm.test(), for doing
one-sample Cramer-von Mises goodness-of-fit tests.
Author: Taylor B. Arnold, John W. Emerson, R Core Team and contributors
worldwide
Maintainer: Taylor B. Arnold <taylor.b.arnold@gmail.com>
Diff between dgof versions 1.2 dated 2013-10-25 and 1.4 dated 2022-06-16
DESCRIPTION | 17 ++++++++--------- MD5 | 17 +++++++++-------- NAMESPACE | 4 +++- R/cvm.test.R | 9 ++++----- R/ks.test.R | 26 +++++++++++++------------- inst/CITATION | 6 +++--- man/ks.test.Rd | 6 +++--- src/ctest.h | 23 +++-------------------- src/init.c |only src/ks.c | 22 +++++++++++----------- 10 files changed, 57 insertions(+), 73 deletions(-)
Title: Generalization of the Convex Hull of a Sample of Points in the
Plane
Description: Computation of the alpha-shape and alpha-convex
hull of a given sample of points in the plane. The concepts of
alpha-shape and alpha-convex hull generalize the definition of
the convex hull of a finite set of points. The programming is
based on the duality between the Voronoi diagram and Delaunay
triangulation. The package also includes a function that
returns the Delaunay mesh of a given sample of points and its
dual Voronoi diagram in one single object.
Author: Beatriz Pateiro-Lopez [aut, cre], Alberto Rodriguez-Casal, [aut].
Maintainer: Beatriz Pateiro-Lopez <beatriz.pateiro@usc.es>
Diff between alphahull versions 2.4 dated 2022-03-16 and 2.5 dated 2022-06-16
DESCRIPTION | 12 +- MD5 | 30 +++--- NAMESPACE | 14 +-- R/areaahulleval.R | 2 R/plot.ahull.R | 2 R/plot.ashape.R | 2 R/plot.delvor.R | 2 build/vignette.rds |binary inst/doc/alphahull.R | 50 +++++------ inst/doc/alphahull.pdf |binary inst/doc/alphahull.rnw | 42 +-------- man/alphahull-package.Rd | 6 - man/delvor.Rd | 9 -- man/dummycoor.Rd | 2 vignettes/alphahull.rnw | 42 +-------- vignettes/biblioJSS.bib | 203 ++++++++++++----------------------------------- 16 files changed, 127 insertions(+), 291 deletions(-)
Title: Solving Mixed Model Equations in R
Description: Structural multivariate-univariate linear mixed model solver for estimation of multiple random effects with unknown variance-covariance structures (e.g., heterogeneous and unstructured) and known covariance among levels of random effects (e.g., pedigree and genomic relationship matrices) (Covarrubias-Pazaran, 2016 <doi:10.1371/journal.pone.0156744>; Maier et al., 2015 <doi:10.1016/j.ajhg.2014.12.006>). REML estimates can be obtained using the Direct-Inversion Newton-Raphson and Direct-Inversion Average Information algorithms for the problems r x r (r being the number f records) or using the mixed-model-equations-based average information algorithm for the problem c x c (c being the number of coefficients to estimate). Spatial models can also be fitted using the two-dimensional spline functionality available in sommer.
Author: Giovanny Covarrubias-Pazaran
Maintainer: Giovanny Covarrubias-Pazaran <cova_ruber@live.com.mx>
Diff between sommer versions 4.1.6 dated 2022-04-17 and 4.1.7 dated 2022-06-16
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Title: Phylogenetic Reconstruction and Analysis
Description: Allows for estimation of phylogenetic trees and networks
using Maximum Likelihood, Maximum Parsimony, distance methods and
Hadamard conjugation (Schliep 2011). Offers methods for tree comparison,
model selection and visualization of phylogenetic networks as described in
Schliep et al. (2017).
Author: Klaus Schliep [aut, cre] ,
Emmanuel Paradis [aut] ,
Leonardo de Oliveira Martins [aut]
,
Alastair Potts [aut],
Tim W. White [aut],
Cyrill Stachniss [ctb],
Michelle Kendall [ctb],
Keren Halabi [ctb],
Richel Bilderbeek [ctb],
Kristin Winchell [ctb],
Li [...truncated...]
Maintainer: Klaus Schliep <klaus.schliep@gmail.com>
Diff between phangorn versions 2.8.1 dated 2021-12-14 and 2.9.0 dated 2022-06-16
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Title: Simple Imputation
Description: Easy to use interfaces to a number of imputation methods
that fit in the not-a-pipe operator of the 'magrittr' package.
Author: Mark van der Loo [aut, cre]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>
Diff between simputation versions 0.2.7 dated 2021-09-16 and 0.2.8 dated 2022-06-16
DESCRIPTION | 15 ++-- MD5 | 24 +++---- NEWS | 7 ++ R/hotdeck.R | 4 - R/utils.R | 107 ++++++++++++++++---------------- build/vignette.rds |binary inst/doc/intro.R | 12 +-- inst/doc/intro.Rmd | 30 ++------- inst/doc/intro.html | 133 +++++++++++++++++++--------------------- inst/tinytest/test_utils.R | 2 man/glimpse_na.Rd | 96 ++++++++++++++-------------- man/simputation_capabilities.Rd | 6 - vignettes/intro.Rmd | 30 ++------- 13 files changed, 224 insertions(+), 242 deletions(-)
Title: Initialization Algorithms for Partitioning Cluster Analysis
Description: Partitioning clustering algorithms divide data sets into k subsets or partitions so-called clusters. They require some initialization procedures for starting the algorithms. Initialization of cluster prototypes is one of such kind of procedures for most of the partitioning algorithms. Cluster prototypes are the centers of clusters, i.e. centroids or medoids, representing the clusters in a data set. In order to initialize cluster prototypes, the package 'inaparc' contains a set of the functions that are the implementations of several linear time-complexity and loglinear time-complexity methods in addition to some novel techniques. Initialization of fuzzy membership degrees matrices is another important task for starting the probabilistic and possibilistic partitioning algorithms. In order to initialize membership degrees matrices required by these algorithms, a number of functions based on some traditional and novel initialization techniques are also available in the package 'inaparc'.
Author: Zeynel Cebeci [aut, cre],
Cagatay Cebeci [aut]
Maintainer: Zeynel Cebeci <zcebeci@cukurova.edu.tr>
Diff between inaparc versions 1.1.0 dated 2020-02-08 and 1.2.0 dated 2022-06-16
DESCRIPTION | 9 ++++----- MD5 | 25 +++++++++++++------------ build |only inst/NEWS.Rd | 5 +++++ man/aldaoud.Rd | 2 +- man/inaparc-package.Rd | 12 ++++++------ man/inofrep.Rd | 2 +- man/inscsf.Rd | 2 +- man/insdev.Rd | 2 +- man/kkz.Rd | 2 +- man/lhsmaximin.Rd | 2 +- man/lhsrandom.Rd | 2 +- man/maximin.Rd | 4 ++-- man/spaeth.Rd | 2 +- 14 files changed, 38 insertions(+), 33 deletions(-)
Title: Manipulation of Linear Systems of (in)Equalities
Description: Variable elimination (Gaussian elimination, Fourier-Motzkin elimination),
Moore-Penrose pseudoinverse, reduction to reduced row echelon form, value substitution,
projecting a vector on the convex polytope described by a system of (in)equations,
simplify systems by removing spurious columns and rows and collapse implied equalities,
test if a matrix is totally unimodular, compute variable ranges implied by linear
(in)equalities.
Author: Mark van der Loo [aut, cre],
Edwin de Jonge [aut]
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>
Diff between lintools versions 0.1.5 dated 2021-04-29 and 0.1.6 dated 2022-06-16
DESCRIPTION | 9 ++++----- MD5 | 16 ++++++++-------- NEWS | 4 ++++ R/substval.R | 6 ++++-- build/vignette.rds |binary inst/doc/project.html | 16 ++++++++++++---- inst/tinytest/test_compact.R | 6 ++++++ inst/tinytest/test_substitute.R | 33 ++++++++++++++++++++------------- man/subst_value.Rd | 5 ++++- 9 files changed, 62 insertions(+), 33 deletions(-)
Title: Adapt Numerical Records to Fit (in)Equality Restrictions
Description: Minimally adjust the values of numerical records in a data.frame, such
that each record satisfies a predefined set of equality and/or inequality
constraints. The constraints can be defined using the 'validate' package.
The core algorithms have recently been moved to the 'lintools' package,
refer to 'lintools' for a more basic interface and access to a version
of the algorithm that works with sparse matrices.
Author: Mark van der Loo
Maintainer: Mark van der Loo <mark.vanderloo@gmail.com>
Diff between rspa versions 0.2.6 dated 2022-05-24 and 0.2.7 dated 2022-06-16
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- NEWS | 6 ++++++ R/match_restrictions.R | 13 +++++++++---- inst/tinytest/test_match_restrictions.R | 9 +++++++++ man/match_restrictions.Rd | 2 +- 6 files changed, 33 insertions(+), 13 deletions(-)
Title: Robust Data-Driven Statistical Inference in
Regression-Discontinuity Designs
Description: Regression-discontinuity (RD) designs are quasi-experimental research designs popular in social, behavioral and natural sciences. The RD design is usually employed to study the (local) causal effect of a treatment, intervention or policy. This package provides tools for data-driven graphical and analytical statistical inference in RD designs: rdrobust() to construct local-polynomial point estimators and robust confidence intervals for average treatment effects at the cutoff in Sharp, Fuzzy and Kink RD settings, rdbwselect() to perform bandwidth selection for the different procedures implemented, and rdplot() to conduct exploratory data analysis (RD plots).
Author: Sebastian Calonico <sebastian.calonico@columbia.edu>, Matias D. Cattaneo <cattaneo@princeton.edu>, Max H. Farrell <max.farrell@chicagobooth.edu>, Rocio Titiunik <titiunik@princeton.edu>
Maintainer: Sebastian Calonico <sebastian.calonico@columbia.edu>
Diff between rdrobust versions 2.0.1 dated 2022-06-07 and 2.0.2 dated 2022-06-16
DESCRIPTION | 8 - MD5 | 10 - R/functions.R | 12 -- R/rdbwselect.R | 18 +-- R/rdrobust.R | 285 ++++++++++++++++++++++++------------------------ man/rdrobust-package.Rd | 4 6 files changed, 168 insertions(+), 169 deletions(-)
Title: A Common API to Modeling and Analysis Functions
Description: A common interface is provided to allow users to specify a
model without having to remember the different argument names across
different functions or computational engines (e.g. 'R', 'Spark',
'Stan', etc).
Author: Max Kuhn [aut, cre],
Davis Vaughan [aut],
Emil Hvitfeldt [ctb],
RStudio [cph, fnd]
Maintainer: Max Kuhn <max@rstudio.com>
Diff between parsnip versions 0.2.1 dated 2022-03-17 and 1.0.0 dated 2022-06-16
parsnip-0.2.1/parsnip/R/decision_tree_party.R |only parsnip-0.2.1/parsnip/R/rand_forest_party.R |only parsnip-0.2.1/parsnip/man/details_decision_tree_party.Rd |only parsnip-0.2.1/parsnip/man/details_rand_forest_party.Rd |only parsnip-0.2.1/parsnip/man/rmd/decision_tree_party.Rmd |only parsnip-0.2.1/parsnip/man/rmd/decision_tree_party.md |only parsnip-0.2.1/parsnip/man/rmd/logistic-reg.Rmd |only parsnip-0.2.1/parsnip/man/rmd/logistic-reg.md |only parsnip-0.2.1/parsnip/man/rmd/nearest-neighbor.Rmd |only parsnip-0.2.1/parsnip/man/rmd/rand_forest_party.Rmd |only parsnip-0.2.1/parsnip/man/rmd/rand_forest_party.md |only parsnip-0.2.1/parsnip/tests/testthat/test_svm_liquidsvm.R |only parsnip-1.0.0/parsnip/DESCRIPTION | 23 parsnip-1.0.0/parsnip/MD5 | 817 +++++----- parsnip-1.0.0/parsnip/NAMESPACE | 50 parsnip-1.0.0/parsnip/NEWS.md | 42 parsnip-1.0.0/parsnip/R/aaa_models.R | 30 parsnip-1.0.0/parsnip/R/arguments.R | 50 parsnip-1.0.0/parsnip/R/bag_mars.R | 42 parsnip-1.0.0/parsnip/R/bag_tree.R | 50 parsnip-1.0.0/parsnip/R/bart.R | 47 parsnip-1.0.0/parsnip/R/boost_tree.R | 123 - parsnip-1.0.0/parsnip/R/boost_tree_data.R | 24 parsnip-1.0.0/parsnip/R/boost_tree_h2o.R |only parsnip-1.0.0/parsnip/R/boost_tree_lightgbm.R |only parsnip-1.0.0/parsnip/R/c5_rules.R | 44 parsnip-1.0.0/parsnip/R/case_weights.R |only parsnip-1.0.0/parsnip/R/convert_data.R | 6 parsnip-1.0.0/parsnip/R/cubist_rules.R | 48 parsnip-1.0.0/parsnip/R/decision_tree.R | 46 parsnip-1.0.0/parsnip/R/decision_tree_partykit.R |only parsnip-1.0.0/parsnip/R/descriptors.R | 12 parsnip-1.0.0/parsnip/R/discrim_flexible.R | 39 parsnip-1.0.0/parsnip/R/discrim_linear.R | 39 parsnip-1.0.0/parsnip/R/discrim_quad.R | 39 parsnip-1.0.0/parsnip/R/discrim_regularized.R | 39 parsnip-1.0.0/parsnip/R/engine_docs.R | 23 parsnip-1.0.0/parsnip/R/engines.R | 6 parsnip-1.0.0/parsnip/R/fit.R | 40 parsnip-1.0.0/parsnip/R/fit_helpers.R | 13 parsnip-1.0.0/parsnip/R/gen_additive_mod.R | 45 parsnip-1.0.0/parsnip/R/gen_additive_mod_data.R | 7 parsnip-1.0.0/parsnip/R/grouped_binomial.R |only parsnip-1.0.0/parsnip/R/linear_reg.R | 60 parsnip-1.0.0/parsnip/R/linear_reg_data.R | 4 parsnip-1.0.0/parsnip/R/linear_reg_gls.R | 2 parsnip-1.0.0/parsnip/R/linear_reg_h2o.R |only parsnip-1.0.0/parsnip/R/logistic_reg.R | 61 parsnip-1.0.0/parsnip/R/logistic_reg_data.R | 6 parsnip-1.0.0/parsnip/R/logistic_reg_h2o.R |only parsnip-1.0.0/parsnip/R/mars.R | 47 parsnip-1.0.0/parsnip/R/misc.R | 182 +- parsnip-1.0.0/parsnip/R/mlp.R | 50 parsnip-1.0.0/parsnip/R/mlp_data.R | 4 parsnip-1.0.0/parsnip/R/mlp_h2o.R |only parsnip-1.0.0/parsnip/R/multinom_reg.R | 59 parsnip-1.0.0/parsnip/R/multinom_reg_data.R | 6 parsnip-1.0.0/parsnip/R/multinom_reg_h2o.R |only parsnip-1.0.0/parsnip/R/naive_Bayes.R | 41 parsnip-1.0.0/parsnip/R/naive_Bayes_h2o.R |only parsnip-1.0.0/parsnip/R/nearest_neighbor.R | 47 parsnip-1.0.0/parsnip/R/nullmodel_data.R | 4 parsnip-1.0.0/parsnip/R/parsnip-package.R | 5 parsnip-1.0.0/parsnip/R/partykit.R |only parsnip-1.0.0/parsnip/R/pls.R | 43 parsnip-1.0.0/parsnip/R/poisson_reg.R | 56 parsnip-1.0.0/parsnip/R/poisson_reg_h2o.R |only parsnip-1.0.0/parsnip/R/predict.R | 27 parsnip-1.0.0/parsnip/R/predict_classprob.R | 15 parsnip-1.0.0/parsnip/R/print.R |only parsnip-1.0.0/parsnip/R/proportional_hazards.R | 47 parsnip-1.0.0/parsnip/R/rand_forest.R | 57 parsnip-1.0.0/parsnip/R/rand_forest_data.R | 6 parsnip-1.0.0/parsnip/R/rand_forest_h2o.R |only parsnip-1.0.0/parsnip/R/rand_forest_partykit.R |only parsnip-1.0.0/parsnip/R/reexports.R | 9 parsnip-1.0.0/parsnip/R/rule_fit.R | 47 parsnip-1.0.0/parsnip/R/rule_fit_h2o.R |only parsnip-1.0.0/parsnip/R/surv_reg.R | 48 parsnip-1.0.0/parsnip/R/survival_reg.R | 48 parsnip-1.0.0/parsnip/R/svm_linear.R | 47 parsnip-1.0.0/parsnip/R/svm_linear_data.R | 5 parsnip-1.0.0/parsnip/R/svm_poly.R | 47 parsnip-1.0.0/parsnip/R/svm_rbf.R | 47 parsnip-1.0.0/parsnip/R/translate.R | 73 parsnip-1.0.0/parsnip/R/tunable.R | 29 parsnip-1.0.0/parsnip/R/tune_args.R | 2 parsnip-1.0.0/parsnip/R/update.R | 41 parsnip-1.0.0/parsnip/R/zzz.R | 85 - parsnip-1.0.0/parsnip/build/parsnip.pdf |binary parsnip-1.0.0/parsnip/build/vignette.rds |binary parsnip-1.0.0/parsnip/inst/doc/parsnip.html | 291 +++ parsnip-1.0.0/parsnip/inst/models.tsv | 23 parsnip-1.0.0/parsnip/man/add_on_exports.Rd | 21 parsnip-1.0.0/parsnip/man/boost_tree.Rd | 3 parsnip-1.0.0/parsnip/man/case_weights.Rd |only parsnip-1.0.0/parsnip/man/contr_one_hot.Rd | 48 parsnip-1.0.0/parsnip/man/ctree_train.Rd |only parsnip-1.0.0/parsnip/man/details_C5_rules_C5.0.Rd | 23 parsnip-1.0.0/parsnip/man/details_bag_mars_earth.Rd | 34 parsnip-1.0.0/parsnip/man/details_bag_tree_C5.0.Rd | 20 parsnip-1.0.0/parsnip/man/details_bag_tree_rpart.Rd | 49 parsnip-1.0.0/parsnip/man/details_bart_dbarts.Rd | 24 parsnip-1.0.0/parsnip/man/details_boost_tree_C5.0.Rd | 20 parsnip-1.0.0/parsnip/man/details_boost_tree_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_boost_tree_lightgbm.Rd |only parsnip-1.0.0/parsnip/man/details_boost_tree_mboost.Rd | 17 parsnip-1.0.0/parsnip/man/details_boost_tree_spark.Rd | 33 parsnip-1.0.0/parsnip/man/details_boost_tree_xgboost.Rd | 81 parsnip-1.0.0/parsnip/man/details_cubist_rules_Cubist.Rd | 10 parsnip-1.0.0/parsnip/man/details_decision_tree_C5.0.Rd | 20 parsnip-1.0.0/parsnip/man/details_decision_tree_partykit.Rd |only parsnip-1.0.0/parsnip/man/details_decision_tree_rpart.Rd | 49 parsnip-1.0.0/parsnip/man/details_decision_tree_spark.Rd | 33 parsnip-1.0.0/parsnip/man/details_discrim_flexible_earth.Rd | 29 parsnip-1.0.0/parsnip/man/details_discrim_linear_MASS.Rd | 19 parsnip-1.0.0/parsnip/man/details_discrim_linear_mda.Rd | 28 parsnip-1.0.0/parsnip/man/details_discrim_linear_sda.Rd | 19 parsnip-1.0.0/parsnip/man/details_discrim_linear_sparsediscrim.Rd | 19 parsnip-1.0.0/parsnip/man/details_discrim_quad_MASS.Rd | 19 parsnip-1.0.0/parsnip/man/details_discrim_quad_sparsediscrim.Rd | 19 parsnip-1.0.0/parsnip/man/details_discrim_regularized_klaR.Rd | 19 parsnip-1.0.0/parsnip/man/details_gen_additive_mod_mgcv.Rd | 52 parsnip-1.0.0/parsnip/man/details_linear_reg_brulee.Rd | 19 parsnip-1.0.0/parsnip/man/details_linear_reg_gee.Rd | 27 parsnip-1.0.0/parsnip/man/details_linear_reg_glm.Rd | 44 parsnip-1.0.0/parsnip/man/details_linear_reg_glmnet.Rd | 24 parsnip-1.0.0/parsnip/man/details_linear_reg_gls.Rd | 93 - parsnip-1.0.0/parsnip/man/details_linear_reg_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_linear_reg_keras.Rd | 19 parsnip-1.0.0/parsnip/man/details_linear_reg_lm.Rd | 41 parsnip-1.0.0/parsnip/man/details_linear_reg_lme.Rd | 23 parsnip-1.0.0/parsnip/man/details_linear_reg_lmer.Rd | 30 parsnip-1.0.0/parsnip/man/details_linear_reg_spark.Rd | 45 parsnip-1.0.0/parsnip/man/details_linear_reg_stan.Rd | 24 parsnip-1.0.0/parsnip/man/details_linear_reg_stan_glmer.Rd | 28 parsnip-1.0.0/parsnip/man/details_logistic_reg_LiblineaR.Rd | 18 parsnip-1.0.0/parsnip/man/details_logistic_reg_brulee.Rd | 19 parsnip-1.0.0/parsnip/man/details_logistic_reg_gee.Rd | 27 parsnip-1.0.0/parsnip/man/details_logistic_reg_glm.Rd | 44 parsnip-1.0.0/parsnip/man/details_logistic_reg_glmer.Rd | 31 parsnip-1.0.0/parsnip/man/details_logistic_reg_glmnet.Rd | 35 parsnip-1.0.0/parsnip/man/details_logistic_reg_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_logistic_reg_keras.Rd | 19 parsnip-1.0.0/parsnip/man/details_logistic_reg_spark.Rd | 47 parsnip-1.0.0/parsnip/man/details_logistic_reg_stan.Rd | 24 parsnip-1.0.0/parsnip/man/details_logistic_reg_stan_glmer.Rd | 28 parsnip-1.0.0/parsnip/man/details_mars_earth.Rd | 34 parsnip-1.0.0/parsnip/man/details_mlp_brulee.Rd | 31 parsnip-1.0.0/parsnip/man/details_mlp_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_mlp_keras.Rd | 29 parsnip-1.0.0/parsnip/man/details_mlp_nnet.Rd | 39 parsnip-1.0.0/parsnip/man/details_multinom_reg_brulee.Rd | 19 parsnip-1.0.0/parsnip/man/details_multinom_reg_glmnet.Rd | 35 parsnip-1.0.0/parsnip/man/details_multinom_reg_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_multinom_reg_keras.Rd | 19 parsnip-1.0.0/parsnip/man/details_multinom_reg_nnet.Rd | 21 parsnip-1.0.0/parsnip/man/details_multinom_reg_spark.Rd | 47 parsnip-1.0.0/parsnip/man/details_naive_Bayes_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_naive_Bayes_klaR.Rd | 18 parsnip-1.0.0/parsnip/man/details_naive_Bayes_naivebayes.Rd | 18 parsnip-1.0.0/parsnip/man/details_nearest_neighbor_kknn.Rd | 29 parsnip-1.0.0/parsnip/man/details_pls_mixOmics.Rd | 36 parsnip-1.0.0/parsnip/man/details_poisson_reg_gee.Rd | 29 parsnip-1.0.0/parsnip/man/details_poisson_reg_glm.Rd | 48 parsnip-1.0.0/parsnip/man/details_poisson_reg_glmer.Rd | 31 parsnip-1.0.0/parsnip/man/details_poisson_reg_glmnet.Rd | 35 parsnip-1.0.0/parsnip/man/details_poisson_reg_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_poisson_reg_hurdle.Rd | 44 parsnip-1.0.0/parsnip/man/details_poisson_reg_stan.Rd | 24 parsnip-1.0.0/parsnip/man/details_poisson_reg_stan_glmer.Rd | 28 parsnip-1.0.0/parsnip/man/details_poisson_reg_zeroinfl.Rd | 44 parsnip-1.0.0/parsnip/man/details_proportional_hazards_glmnet.Rd | 55 parsnip-1.0.0/parsnip/man/details_proportional_hazards_survival.Rd | 42 parsnip-1.0.0/parsnip/man/details_rand_forest_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_rand_forest_partykit.Rd |only parsnip-1.0.0/parsnip/man/details_rand_forest_randomForest.Rd | 20 parsnip-1.0.0/parsnip/man/details_rand_forest_ranger.Rd | 34 parsnip-1.0.0/parsnip/man/details_rand_forest_spark.Rd | 33 parsnip-1.0.0/parsnip/man/details_rule_fit_h2o.Rd |only parsnip-1.0.0/parsnip/man/details_rule_fit_xrf.Rd | 100 + parsnip-1.0.0/parsnip/man/details_surv_reg_flexsurv.Rd | 10 parsnip-1.0.0/parsnip/man/details_surv_reg_survival.Rd | 20 parsnip-1.0.0/parsnip/man/details_survival_reg_flexsurv.Rd | 12 parsnip-1.0.0/parsnip/man/details_survival_reg_survival.Rd | 30 parsnip-1.0.0/parsnip/man/details_svm_linear_LiblineaR.Rd | 37 parsnip-1.0.0/parsnip/man/details_svm_linear_kernlab.Rd | 29 parsnip-1.0.0/parsnip/man/details_svm_poly_kernlab.Rd | 29 parsnip-1.0.0/parsnip/man/details_svm_rbf_kernlab.Rd | 29 parsnip-1.0.0/parsnip/man/dot-model_param_name_key.Rd |only parsnip-1.0.0/parsnip/man/extract-parsnip.Rd | 8 parsnip-1.0.0/parsnip/man/fit.Rd | 16 parsnip-1.0.0/parsnip/man/format-internals.Rd |only parsnip-1.0.0/parsnip/man/glm_grouped.Rd |only parsnip-1.0.0/parsnip/man/glmnet-details.Rd | 88 - parsnip-1.0.0/parsnip/man/linear_reg.Rd | 13 parsnip-1.0.0/parsnip/man/logistic_reg.Rd | 15 parsnip-1.0.0/parsnip/man/max_mtry_formula.Rd |only parsnip-1.0.0/parsnip/man/mlp.Rd | 3 parsnip-1.0.0/parsnip/man/model_printer.Rd | 2 parsnip-1.0.0/parsnip/man/multinom_reg.Rd | 13 parsnip-1.0.0/parsnip/man/null_model.Rd | 22 parsnip-1.0.0/parsnip/man/parsnip_update.Rd | 20 parsnip-1.0.0/parsnip/man/poisson_reg.Rd | 13 parsnip-1.0.0/parsnip/man/proportional_hazards.Rd | 13 parsnip-1.0.0/parsnip/man/reexports.Rd | 4 parsnip-1.0.0/parsnip/man/rmd/C5_rules_C5.0.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/C5_rules_C5.0.md | 11 parsnip-1.0.0/parsnip/man/rmd/bag_mars_earth.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/bag_mars_earth.md | 7 parsnip-1.0.0/parsnip/man/rmd/bag_tree_C5.0.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/bag_tree_C5.0.md | 7 parsnip-1.0.0/parsnip/man/rmd/bag_tree_rpart.Rmd | 10 parsnip-1.0.0/parsnip/man/rmd/bag_tree_rpart.md | 16 parsnip-1.0.0/parsnip/man/rmd/boost_tree_C5.0.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/boost_tree_C5.0.md | 7 parsnip-1.0.0/parsnip/man/rmd/boost_tree_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/boost_tree_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/boost_tree_lightgbm.Rmd |only parsnip-1.0.0/parsnip/man/rmd/boost_tree_lightgbm.md |only parsnip-1.0.0/parsnip/man/rmd/boost_tree_mboost.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/boost_tree_mboost.md | 8 parsnip-1.0.0/parsnip/man/rmd/boost_tree_spark.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/boost_tree_spark.md | 9 parsnip-1.0.0/parsnip/man/rmd/boost_tree_xgboost.Rmd | 12 parsnip-1.0.0/parsnip/man/rmd/boost_tree_xgboost.md | 34 parsnip-1.0.0/parsnip/man/rmd/decision_tree_C5.0.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/decision_tree_C5.0.md | 7 parsnip-1.0.0/parsnip/man/rmd/decision_tree_partykit.Rmd |only parsnip-1.0.0/parsnip/man/rmd/decision_tree_partykit.md |only parsnip-1.0.0/parsnip/man/rmd/decision_tree_rpart.Rmd | 10 parsnip-1.0.0/parsnip/man/rmd/decision_tree_rpart.md | 17 parsnip-1.0.0/parsnip/man/rmd/decision_tree_spark.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/decision_tree_spark.md | 9 parsnip-1.0.0/parsnip/man/rmd/discrim_flexible_earth.Rmd | 4 parsnip-1.0.0/parsnip/man/rmd/discrim_flexible_earth.md | 11 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_MASS.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_MASS.md | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_mda.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_mda.md | 11 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_sda.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_sda.md | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_sparsediscrim.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_linear_sparsediscrim.md | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_quad_MASS.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_quad_MASS.md | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_quad_sparsediscrim.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_quad_sparsediscrim.md | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_regularized_klaR.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/discrim_regularized_klaR.md | 5 parsnip-1.0.0/parsnip/man/rmd/gen_additive_mod_mgcv.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/gen_additive_mod_mgcv.md | 19 parsnip-1.0.0/parsnip/man/rmd/linear_reg_brulee.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_brulee.md | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_gee.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_gee.md | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_glm.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/linear_reg_glm.md | 9 parsnip-1.0.0/parsnip/man/rmd/linear_reg_glmnet.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_glmnet.md | 7 parsnip-1.0.0/parsnip/man/rmd/linear_reg_gls.Rmd | 3 parsnip-1.0.0/parsnip/man/rmd/linear_reg_gls.md | 11 parsnip-1.0.0/parsnip/man/rmd/linear_reg_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/linear_reg_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/linear_reg_keras.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_keras.md | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_lm.Rmd | 9 parsnip-1.0.0/parsnip/man/rmd/linear_reg_lm.md | 11 parsnip-1.0.0/parsnip/man/rmd/linear_reg_lme.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_lme.md | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_lmer.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_lmer.md | 9 parsnip-1.0.0/parsnip/man/rmd/linear_reg_spark.Rmd | 15 parsnip-1.0.0/parsnip/man/rmd/linear_reg_spark.md | 19 parsnip-1.0.0/parsnip/man/rmd/linear_reg_stan.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_stan.md | 7 parsnip-1.0.0/parsnip/man/rmd/linear_reg_stan_glmer.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/linear_reg_stan_glmer.md | 7 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_LiblineaR.md | 4 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_brulee.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_brulee.md | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_gee.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_gee.md | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_glm.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_glm.md | 9 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_glmer.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_glmer.md | 10 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_glmnet.Rmd | 11 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_glmnet.md | 13 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/logistic_reg_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/logistic_reg_keras.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_keras.md | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_spark.Rmd | 14 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_spark.md | 18 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_stan.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_stan.md | 7 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_stan_glmer.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/logistic_reg_stan_glmer.md | 7 parsnip-1.0.0/parsnip/man/rmd/mars_earth.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/mars_earth.md | 7 parsnip-1.0.0/parsnip/man/rmd/mlp_brulee.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/mlp_brulee.md | 13 parsnip-1.0.0/parsnip/man/rmd/mlp_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/mlp_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/mlp_keras.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/mlp_keras.md | 9 parsnip-1.0.0/parsnip/man/rmd/mlp_nnet.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/mlp_nnet.md | 19 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_brulee.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_brulee.md | 5 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_glmnet.Rmd | 11 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_glmnet.md | 13 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/multinom_reg_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/multinom_reg_keras.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_keras.md | 5 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_nnet.Rmd | 6 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_nnet.md | 8 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_spark.Rmd | 15 parsnip-1.0.0/parsnip/man/rmd/multinom_reg_spark.md | 19 parsnip-1.0.0/parsnip/man/rmd/naive_Bayes_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/naive_Bayes_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/naive_Bayes_klaR.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/naive_Bayes_klaR.md | 7 parsnip-1.0.0/parsnip/man/rmd/naive_Bayes_naivebayes.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/naive_Bayes_naivebayes.md | 7 parsnip-1.0.0/parsnip/man/rmd/nearest_neighbor_kknn.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/nearest_neighbor_kknn.md | 5 parsnip-1.0.0/parsnip/man/rmd/null-model.md | 8 parsnip-1.0.0/parsnip/man/rmd/pls_mixOmics.Rmd | 9 parsnip-1.0.0/parsnip/man/rmd/pls_mixOmics.md | 9 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_gee.Rmd | 7 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_gee.md | 7 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_glm.Rmd | 16 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_glm.md | 20 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_glmer.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_glmer.md | 10 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_glmnet.Rmd | 11 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_glmnet.md | 13 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/poisson_reg_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/poisson_reg_hurdle.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_hurdle.md | 7 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_stan.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_stan.md | 7 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_stan_glmer.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_stan_glmer.md | 7 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_zeroinfl.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/poisson_reg_zeroinfl.md | 7 parsnip-1.0.0/parsnip/man/rmd/proportional_hazards_glmnet.Rmd | 17 parsnip-1.0.0/parsnip/man/rmd/proportional_hazards_glmnet.md | 22 parsnip-1.0.0/parsnip/man/rmd/proportional_hazards_survival.Rmd | 10 parsnip-1.0.0/parsnip/man/rmd/proportional_hazards_survival.md | 15 parsnip-1.0.0/parsnip/man/rmd/rand_forest_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/rand_forest_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/rand_forest_partykit.Rmd |only parsnip-1.0.0/parsnip/man/rmd/rand_forest_partykit.md |only parsnip-1.0.0/parsnip/man/rmd/rand_forest_ranger.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/rand_forest_ranger.md | 11 parsnip-1.0.0/parsnip/man/rmd/rand_forest_spark.Rmd | 8 parsnip-1.0.0/parsnip/man/rmd/rand_forest_spark.md | 10 parsnip-1.0.0/parsnip/man/rmd/rule_fit_h2o.Rmd |only parsnip-1.0.0/parsnip/man/rmd/rule_fit_h2o.md |only parsnip-1.0.0/parsnip/man/rmd/rule_fit_xrf.Rmd | 21 parsnip-1.0.0/parsnip/man/rmd/rule_fit_xrf.md | 47 parsnip-1.0.0/parsnip/man/rmd/survival_reg_flexsurv.Rmd | 3 parsnip-1.0.0/parsnip/man/rmd/survival_reg_flexsurv.md | 4 parsnip-1.0.0/parsnip/man/rmd/survival_reg_survival.Rmd | 8 parsnip-1.0.0/parsnip/man/rmd/survival_reg_survival.md | 11 parsnip-1.0.0/parsnip/man/rmd/svm_linear_LiblineaR.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/svm_linear_LiblineaR.md | 17 parsnip-1.0.0/parsnip/man/rmd/svm_linear_kernlab.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/svm_linear_kernlab.md | 9 parsnip-1.0.0/parsnip/man/rmd/svm_poly_kernlab.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/svm_poly_kernlab.md | 9 parsnip-1.0.0/parsnip/man/rmd/svm_rbf_kernlab.Rmd | 5 parsnip-1.0.0/parsnip/man/rmd/svm_rbf_kernlab.md | 9 parsnip-1.0.0/parsnip/man/rmd/template-early-stopping.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-h2o-glm-penalty.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-h2o-init.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-mtry-prop.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-no-case-weights.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-survival-mean.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-survival-median.Rmd |only parsnip-1.0.0/parsnip/man/rmd/template-uses-case-weights.Rmd |only parsnip-1.0.0/parsnip/man/rule_fit.Rd | 7 parsnip-1.0.0/parsnip/man/set_engine.Rd | 3 parsnip-1.0.0/parsnip/man/xgb_train.Rd | 12 parsnip-1.0.0/parsnip/tests/testthat/_snaps |only parsnip-1.0.0/parsnip/tests/testthat/helpers.R | 9 parsnip-1.0.0/parsnip/tests/testthat/test-case-weights.R |only parsnip-1.0.0/parsnip/tests/testthat/test_aaaa.R | 3 parsnip-1.0.0/parsnip/tests/testthat/test_adds.R | 7 parsnip-1.0.0/parsnip/tests/testthat/test_args_and_modes.R | 27 parsnip-1.0.0/parsnip/tests/testthat/test_augment.R | 5 parsnip-1.0.0/parsnip/tests/testthat/test_boost_tree.R | 137 - parsnip-1.0.0/parsnip/tests/testthat/test_boost_tree_C50.R | 29 parsnip-1.0.0/parsnip/tests/testthat/test_boost_tree_xgboost.R | 186 +- parsnip-1.0.0/parsnip/tests/testthat/test_convert_data.R | 81 parsnip-1.0.0/parsnip/tests/testthat/test_decision_tree.R | 127 - parsnip-1.0.0/parsnip/tests/testthat/test_default_engines.R | 18 parsnip-1.0.0/parsnip/tests/testthat/test_descriptors.R | 16 parsnip-1.0.0/parsnip/tests/testthat/test_extract.R | 19 parsnip-1.0.0/parsnip/tests/testthat/test_failed_models.R | 14 parsnip-1.0.0/parsnip/tests/testthat/test_fit_interfaces.R | 14 parsnip-1.0.0/parsnip/tests/testthat/test_gen_additive_model.R | 28 parsnip-1.0.0/parsnip/tests/testthat/test_grouped_glm.R |only parsnip-1.0.0/parsnip/tests/testthat/test_linear_reg.R | 234 -- parsnip-1.0.0/parsnip/tests/testthat/test_linear_reg_keras.R | 20 parsnip-1.0.0/parsnip/tests/testthat/test_logistic_reg.R | 300 --- parsnip-1.0.0/parsnip/tests/testthat/test_logistic_reg_keras.R | 25 parsnip-1.0.0/parsnip/tests/testthat/test_mars.R | 122 - parsnip-1.0.0/parsnip/tests/testthat/test_misc.R | 69 parsnip-1.0.0/parsnip/tests/testthat/test_mlp.R | 167 -- parsnip-1.0.0/parsnip/tests/testthat/test_mlp_keras.R | 24 parsnip-1.0.0/parsnip/tests/testthat/test_mlp_nnet.R | 20 parsnip-1.0.0/parsnip/tests/testthat/test_model_basics.R |only parsnip-1.0.0/parsnip/tests/testthat/test_multinom_reg.R | 121 - parsnip-1.0.0/parsnip/tests/testthat/test_multinom_reg_keras.R | 31 parsnip-1.0.0/parsnip/tests/testthat/test_multinom_reg_nnet.R | 22 parsnip-1.0.0/parsnip/tests/testthat/test_nearest_neighbor.R | 122 - parsnip-1.0.0/parsnip/tests/testthat/test_nearest_neighbor_kknn.R | 30 parsnip-1.0.0/parsnip/tests/testthat/test_nullmodel.R | 45 parsnip-1.0.0/parsnip/tests/testthat/test_packages.R | 1 parsnip-1.0.0/parsnip/tests/testthat/test_partykit.R |only parsnip-1.0.0/parsnip/tests/testthat/test_predict_formats.R | 41 parsnip-1.0.0/parsnip/tests/testthat/test_print.R |only parsnip-1.0.0/parsnip/tests/testthat/test_proportional_hazards.R | 69 parsnip-1.0.0/parsnip/tests/testthat/test_rand_forest.R | 194 -- parsnip-1.0.0/parsnip/tests/testthat/test_rand_forest_ranger.R | 116 - parsnip-1.0.0/parsnip/tests/testthat/test_registration.R | 47 parsnip-1.0.0/parsnip/tests/testthat/test_surv_reg.R | 82 - parsnip-1.0.0/parsnip/tests/testthat/test_surv_reg_flexsurv.R | 22 parsnip-1.0.0/parsnip/tests/testthat/test_surv_reg_survreg.R | 29 parsnip-1.0.0/parsnip/tests/testthat/test_survival_reg.R | 48 parsnip-1.0.0/parsnip/tests/testthat/test_svm_linear.R | 115 - parsnip-1.0.0/parsnip/tests/testthat/test_svm_poly.R | 112 - parsnip-1.0.0/parsnip/tests/testthat/test_svm_rbf.R | 85 - parsnip-1.0.0/parsnip/tests/testthat/test_translate.R |only parsnip-1.0.0/parsnip/tests/testthat/test_update.R |only parsnip-1.0.0/parsnip/tests/testthat/test_varying.R | 7 442 files changed, 5385 insertions(+), 5136 deletions(-)
Title: R Interface to RESTful Web Services
Description: Models a RESTful service as if it were a nested R list.
Author: Michael Lawrence
Maintainer: Michael Lawrence <michafla@gene.com>
Diff between restfulr versions 0.0.14 dated 2022-06-05 and 0.0.15 dated 2022-06-16
DESCRIPTION | 6 +++--- MD5 | 10 +++++----- NAMESPACE | 7 +++---- R/HTTP-class.R | 50 +++++++++++++++++++++++++++++++++++++++----------- R/RestUri-class.R | 23 +++++------------------ man/RestUri-class.Rd | 8 ++++---- 6 files changed, 59 insertions(+), 45 deletions(-)
Title: Point Forecast Reconciliation
Description: Classical (bottom-up and top-down), optimal and heuristic combination forecast
reconciliation procedures for cross-sectional, temporal, and cross-temporal linearly
constrained time series (Di Fonzo and Girolimetto, 2021) <doi:10.1016/j.ijforecast.2021.08.004>.
Author: Daniele Girolimetto [aut, cre, fnd],
Tommaso Di Fonzo [aut, fnd]
Maintainer: Daniele Girolimetto <daniele.girolimetto@phd.unipd.it>
Diff between FoReco versions 0.2.2 dated 2022-02-17 and 0.2.4 dated 2022-06-16
DESCRIPTION | 10 - MD5 | 98 +++++------ NAMESPACE | 1 NEWS.md | 17 +- R/FoReco-package.R | 9 - R/FoReco_data.R | 22 +- R/commat.R | 4 R/cstrec.R | 6 R/ctbu.R | 8 R/ctf_tools.R | 8 R/htsrec.R | 40 ++-- R/iterec.R | 10 - R/lccrec.R | 11 - R/lcmat.R |only R/octrec.R | 214 +++++++++++++------------ R/reco.R | 121 +++++++++++++- R/score_index.R | 25 +- R/tcsrec.R | 6 R/tdrec.R | 2 R/thf_tools.R | 22 +- R/thfrec.R | 224 +++++++++++++------------- README.md | 5 build/FoReco.pdf |binary build/vignette.rds |binary inst/CITATION | 6 inst/doc/FoReco_package.Rmd | 3 inst/doc/FoReco_package.html | 323 +++++++++++++++++++++++++++++++++----- inst/doc/accuracy_indices.Rmd | 2 inst/doc/accuracy_indices.html | 348 +++++++++++++++++++++++++++++++++++------ man/Cmatrix.Rd | 1 man/FoReco-package.Rd | 9 - man/FoReco2ts.Rd | 1 man/FoReco_data.Rd | 21 +- man/commat.Rd | 5 man/cstrec.Rd | 6 man/ctbu.Rd | 6 man/ctf_tools.Rd | 3 man/hts_tools.Rd | 1 man/htsrec.Rd | 11 - man/iterec.Rd | 6 man/lccrec.Rd | 9 - man/lcmat.Rd |only man/oct_bounds.Rd | 1 man/octrec.Rd | 29 ++- man/score_index.Rd | 7 man/shrink_estim.Rd | 1 man/tcsrec.Rd | 6 man/thf_tools.Rd | 22 +- man/thfrec.Rd | 11 - vignettes/FoReco_package.Rmd | 3 vignettes/accuracy_indices.Rmd | 2 51 files changed, 1207 insertions(+), 499 deletions(-)
Title: Small Area Estimation using Hierarchical Bayesian under Zero
Inflated Negative Binomial Distribution
Description: We designed this package to provide a function for area level of small area estimation using Hierarchical Bayesian (HB) method under Zero Inflated Negative Binomial Distribution. This package provides model using Univariate Zero Inflated Negative Binomial Distribution for variable of interest. This package also provides a dataset produced by a data generation. The 'rjags' package is employed to obtain parameter estimates. Model-based estimators involves the HB estimators which include the mean and the variation of mean, and the quantile. For the reference, see Rao,J.N.K & Molina (2015) <doi:10.1002/9781118735855>.
Author: Azka Ubaidillah [aut], Hayun [aut, cre]
Maintainer: Hayun <221810327@stis.ac.id>
Diff between saeHB.zinb versions 0.1.0 dated 2022-03-03 and 0.1.1 dated 2022-06-16
DESCRIPTION | 8 - MD5 | 24 +-- R/ZinbHB.R | 254 +++++++++++++++++-------------- R/dataZINB.R | 8 - R/dataZINBNS.R | 2 build/vignette.rds |binary inst/doc/saeHB_zinb.R | 13 + inst/doc/saeHB_zinb.Rmd | 27 +++ inst/doc/saeHB_zinb.html | 375 ++++++++++++++++++++++++++++++++++++++++++++++- man/ZinbHB.Rd | 32 ++-- man/dataZINB.Rd | 8 - man/dataZINBNS.Rd | 2 vignettes/saeHB_zinb.Rmd | 27 +++ 13 files changed, 617 insertions(+), 163 deletions(-)
Title: Reduced-Rank Regression
Description: Multivariate regression methodologies including
classical reduced-rank regression (RRR)
studied by Anderson (1951) <doi:10.1214/aoms/1177729580> and
Reinsel and Velu (1998) <doi:10.1007/978-1-4757-2853-8>,
reduced-rank regression via adaptive nuclear norm penalization
proposed by Chen et al. (2013) <doi:10.1093/biomet/ast036> and
Mukherjee et al. (2015) <doi:10.1093/biomet/asx080>,
robust reduced-rank regression (R4) proposed by
She and Chen (2017) <doi:10.1093/biomet/asx032>,
generalized/mixed-response reduced-rank regression (mRRR) proposed by
Luo et al. (2018) <doi:10.1016/j.jmva.2018.04.011>,
row-sparse reduced-rank regression (SRRR) proposed by
Chen and Huang (2012) <doi:10.1080/01621459.2012.734178>,
reduced-rank regression with a sparse singular value decomposition (RSSVD)
proposed by Chen et al. (2012) <doi:10.1111/j.1467-9868.2011.01002.x>
and sparse and orthogonal factor regression (SOFAR) proposed by
Uematsu et al. (2019) <doi:10.1109/TIT.2019.2909889>.
Author: Kun Chen [aut, cre] ,
Wenjie Wang [aut] ,
Jun Yan [ctb]
Maintainer: Kun Chen <kun.chen@uconn.edu>
Diff between rrpack versions 0.1-12 dated 2022-04-06 and 0.1-13 dated 2022-06-16
rrpack-0.1-12/rrpack/man/coef.Rd |only rrpack-0.1-12/rrpack/src/Makevars.win |only rrpack-0.1-13/rrpack/DESCRIPTION | 12 ++-- rrpack-0.1-13/rrpack/MD5 | 68 +++++++++++------------ rrpack-0.1-13/rrpack/NAMESPACE | 2 rrpack-0.1-13/rrpack/R/coef.R | 20 +++--- rrpack-0.1-13/rrpack/R/mrrr.R | 13 ---- rrpack-0.1-13/rrpack/R/r4.R | 6 -- rrpack-0.1-13/rrpack/R/rrpack.R |only rrpack-0.1-13/rrpack/R/rrr.R | 13 ---- rrpack-0.1-13/rrpack/R/sim.R | 22 ------- rrpack-0.1-13/rrpack/R/sofar.R | 13 ---- rrpack-0.1-13/rrpack/R/srrr.R | 6 -- rrpack-0.1-13/rrpack/R/ssvd.R | 4 - rrpack-0.1-13/rrpack/inst |only rrpack-0.1-13/rrpack/man/cv.mrrr.Rd | 22 +++++-- rrpack-0.1-13/rrpack/man/cv.rrr.Rd | 10 ++- rrpack-0.1-13/rrpack/man/cv.sofar.Rd | 14 ++++ rrpack-0.1-13/rrpack/man/mrrr.Rd | 17 ++++- rrpack-0.1-13/rrpack/man/r4.Rd | 14 +++- rrpack-0.1-13/rrpack/man/rrpack-coef.Rd |only rrpack-0.1-13/rrpack/man/rrr.Rd | 14 +++- rrpack-0.1-13/rrpack/man/rrr.sim1.Rd | 12 +++- rrpack-0.1-13/rrpack/man/rrr.sim2.Rd | 14 ++++ rrpack-0.1-13/rrpack/man/rrr.sim3.Rd | 10 ++- rrpack-0.1-13/rrpack/man/rrr.sim4.Rd | 20 +++++- rrpack-0.1-13/rrpack/man/rrr.sim5.Rd | 21 ++++++- rrpack-0.1-13/rrpack/man/rssvd.Rd | 11 +++ rrpack-0.1-13/rrpack/man/sofar.Rd | 14 +++- rrpack-0.1-13/rrpack/man/srrr.Rd | 16 ++++- rrpack-0.1-13/rrpack/src/Makevars | 5 + rrpack-0.1-13/rrpack/src/RcppExports.cpp | 1 rrpack-0.1-13/rrpack/src/lasso_shooting.cpp | 82 +--------------------------- rrpack-0.1-13/rrpack/src/rrpack_init.c | 5 - rrpack-0.1-13/rrpack/src/sofar.cpp | 5 - rrpack-0.1-13/rrpack/src/srrr.cpp | 12 +--- rrpack-0.1-13/rrpack/src/surr_fit.cpp | 32 +++++----- 37 files changed, 251 insertions(+), 279 deletions(-)
Title: Simulation Methods for Legislative Redistricting
Description: Enables researchers to sample redistricting plans from a pre-specified
target distribution using Sequential Monte Carlo and Markov Chain Monte Carlo
algorithms. The package allows for the implementation of various constraints in
the redistricting process such as geographic compactness and population parity
requirements. Tools for analysis such as computation of various summary statistics
and plotting functionality are also included. The package implements methods
described in Fifield, Higgins, Imai and Tarr (2020) <doi:10.1080/10618600.2020.1739532>,
Fifield, Imai, Kawahara, and Kenny (2020) <doi:10.1080/2330443X.2020.1791773>,
and McCartan and Imai (2020) <arXiv:2008.06131>.
Author: Christopher T. Kenny [aut, cre],
Cory McCartan [aut],
Ben Fifield [aut],
Kosuke Imai [aut],
Jun Kawahara [ctb],
Alexander Tarr [ctb],
Michael Higgins [ctb]
Maintainer: Christopher T. Kenny <christopherkenny@fas.harvard.edu>
Diff between redist versions 3.1.5 dated 2021-10-05 and 4.0.1 dated 2022-06-16
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Title: Generalised Management Strategy Evaluation Simulator
Description: Integrates game theory and ecological theory to construct
social-ecological models that simulate the management of populations and
stakeholder actions. These models build off of a previously developed
management strategy evaluation (MSE) framework to simulate all aspects of
management: population dynamics, manager observation of populations, manager
decision making, and stakeholder responses to management decisions. The
newly developed generalised management strategy evaluation (GMSE)
framework uses genetic algorithms to mimic the decision-making process of
managers and stakeholders under conditions of change, uncertainty, and
conflict. Simulations can be run using gmse(), gmse_apply(), and
gmse_gui() functions.
Author: A. Bradley Duthie [aut, cre] ,
Adrian Bach [aut],
Jeremy Cusack [ctb] ,
Isabel Jones [ctb] ,
Jeroen Minderman [aut] ,
Erlend Nilsen [ctb] ,
Ochoa Gabriela [aut] ,
Rocio Pozo [ctb] ,
Sarobidy Rakotonarivo [ctb] ,
Bram Van Moorter [ctb] ,
Nils Bunnefel [...truncated...]
Maintainer: A. Bradley Duthie <brad.duthie@gmail.com>
Diff between GMSE versions 1.0.0.1 dated 2022-05-25 and 1.0.0.2 dated 2022-06-16
DESCRIPTION | 16 ++++++++-------- MD5 | 6 +++--- README.md | 3 +++ tests/testthat/test-make_utilities.R | 3 +++ 4 files changed, 17 insertions(+), 11 deletions(-)
Title: Assessing and Visualizing Fragility of Clinical Results with
Binary Outcomes
Description: A collection of user-friendly functions for assessing and visualizing fragility of individual studies (Walsh et al., 2014 <doi:10.1016/j.jclinepi.2013.10.019>; Lin, 2021 <doi:10.1111/jep.13428>), conventional pairwise meta-analyses (Atal et al., 2019 <doi:10.1016/j.jclinepi.2019.03.012>), and network meta-analyses of multiple treatments with binary outcomes (Xing et al., 2020 <doi:10.1016/j.jclinepi.2020.07.003>). The included functions are designed to: 1) calculate the fragility index (i.e., the minimal event status modifications that can alter the significance or non-significance of the original result) and fragility quotient (i.e., fragility index divided by sample size) at a specific significance level; 2) give the cases of event status modifications for altering the result's significance or non-significance and visualize these cases; 3) visualize the trend of statistical significance as event status is modified; 4) efficiently derive fragility indexes and fragility quotients at multiple significance levels, and visualize the relationship between these fragility measures against the significance levels; and 5) calculate fragility indexes and fragility quotients of multiple datasets (e.g., a collection of clinical trials or meta-analyses) and produce plots of their overall distributions. The outputs from these functions may inform the robustness of clinical results in terms of statistical significance and aid the interpretation of fragility measures. The usage of this package is detailed in Lin and Chu (2022 <doi:10.1371/journal.pone.0268754>).
Author: Lifeng Lin [aut, cre] ,
Haitao Chu [aut]
Maintainer: Lifeng Lin <linl@stat.fsu.edu>
Diff between fragility versions 1.2 dated 2022-04-19 and 1.3 dated 2022-06-16
DESCRIPTION | 10 +++++----- MD5 | 34 +++++++++++++++++----------------- R/frag.nma.R | 8 ++++---- R/frag.nma.alpha.R | 8 ++++---- build/partial.rdb |binary man/frag.ma.Rd | 2 ++ man/frag.ma.alpha.Rd | 2 ++ man/frag.mas.Rd | 2 ++ man/frag.nma.Rd | 2 ++ man/frag.nma.alpha.Rd | 2 ++ man/frag.studies.Rd | 2 ++ man/frag.study.Rd | 2 ++ man/frag.study.alpha.Rd | 2 ++ man/plot.frag.alpha.Rd | 2 ++ man/plot.frag.ma.Rd | 6 +++--- man/plot.frag.multi.Rd | 2 ++ man/plot.frag.nma.Rd | 6 +++--- man/plot.frag.study.all.Rd | 2 ++ 18 files changed, 58 insertions(+), 36 deletions(-)
Title: An R Autograding Extension for Otter-Grader
Description: An R autograding extension for Otter-Grader (<https://otter-grader.readthedocs.io>). It supports
grading R scripts, RMarkdown documents, and R Jupyter Notebooks.
Author: Christopher Pyles [aut, cre] ,
UC Berkeley Data Science Education Program [cph]
Maintainer: Christopher Pyles <cpyles@berkeley.edu>
Diff between ottr versions 1.1.4 dated 2022-03-25 and 1.1.5 dated 2022-06-16
DESCRIPTION | 10 ++++---- MD5 | 18 +++++++------- NAMESPACE | 2 + R/ottr.r | 2 + man/TestCase.Rd | 24 +++++++++---------- man/TestCaseResult.Rd | 36 ++++++++++++++--------------- man/TestFileResult.Rd | 60 ++++++++++++++++++++++++------------------------- man/export.Rd | 5 ++++ man/results_to_list.Rd | 4 +-- man/run_autograder.Rd | 5 ++++ 10 files changed, 90 insertions(+), 76 deletions(-)