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.

Version: 1.0.1
Imports: Rcpp (≥ 0.12.9), glmnet (≥ 4.0.0), scales (≥ 1.1.1), methods, caret, truncnorm, progress, MASS
LinkingTo: Rcpp, RcppArmadillo
Published: 2022-10-29
Author: Antonio R. Linero [aut, cre]
Maintainer: Antonio R. Linero <antonio.linero at austin.utexas.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
Citation: SoftBart citation info
Materials: NEWS
CRAN checks: SoftBart results

Documentation:

Reference manual: SoftBart.pdf
Vignettes: SoftBartUsage

Downloads:

Package source: SoftBart_1.0.1.tar.gz
Windows binaries: r-devel: SoftBart_1.0.1.zip, r-release: SoftBart_1.0.1.zip, r-oldrel: SoftBart_1.0.1.zip
macOS binaries: r-release (arm64): SoftBart_1.0.1.tgz, r-oldrel (arm64): SoftBart_1.0.1.tgz, r-release (x86_64): SoftBart_1.0.1.tgz
Old sources: SoftBart archive

Linking:

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