Package: SoftBart 1.0.1
Antonio R. Linero
SoftBart: Implements the SoftBart Algorithm
Implements the SoftBart model of described by Linero and Yang (2018) <doi:10.1111/rssb.12293>, with the optional use of a sparsity-inducing prior to allow for variable selection. For usability, the package maintains the same style as the 'BayesTree' package.
Authors:
SoftBart_1.0.1.tar.gz
SoftBart_1.0.1.tar.gz(r-4.5-noble)SoftBart_1.0.1.tar.gz(r-4.4-noble)
SoftBart_1.0.1.tgz(r-4.4-emscripten)SoftBart_1.0.1.tgz(r-4.3-emscripten)
SoftBart.pdf |SoftBart.html✨
SoftBart/json (API)
NEWS
# Install 'SoftBart' in R: |
install.packages('SoftBart', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:1bc8a6bb20. Checks:OK: 2. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Dec 13 2024 |
R-4.5-linux-x86_64 | OK | Dec 13 2024 |
Exports:contr.ltfrgsoftbart_regressionHypersMakeForestOptspartial_dependence_probitpartial_dependence_regressionpdsoftbartposterior_probspredict.softbart_probitpredict.softbart_regressionpreprocess_dfquantile_normalize_bartrmsesoftbartsoftbart_probitsoftbart_regressionvc_softbart_regression
Dependencies:caretclasscliclockcodetoolscolorspacecpp11crayondata.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2glmnetglobalsgluegowergtablehardhathmsipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrprettyunitspROCprodlimprogressprogressrproxypurrrR6RColorBrewerRcppRcppArmadilloRcppEigenrecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetruncnormtzdbutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Create a Full Set of Dummy Variables | contr.ltfr |
General SoftBart Regression | gsoftbart_regression |
Create a list of hyperparameter values | Hypers |
Create an Rcpp_Forest Object | MakeForest |
MCMC options for SoftBart | Opts |
Partial Dependence Function for SoftBART Probit Regression | partial_dependence_probit |
Partial Dependence Function for SoftBART Regression | partial_dependence_regression |
Partial dependence plots for SoftBart | pdsoftbart |
BART Posterior Inclusion Probabilities | posterior_probs |
Predict for SoftBart Probit Regression | predict.softbart_probit |
Predict for SoftBart Regression | predict.softbart_regression |
Preprocess a dataset for use with SoftBart | preprocess_df |
Quantile normalization for predictors | quantile_normalize_bart |
Root mean squared error | rmse |
Fits the SoftBart model | softbart |
SoftBart Probit Regression | softbart_probit |
SoftBart Regression | softbart_regression |
SoftBart Varying Coefficient Regression | vc_softbart_regression |