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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 |
| Reference manual: | SoftBart.pdf |
| Vignettes: |
SoftBartUsage |
| 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, r-oldrel (x86_64): SoftBart_1.0.1.tgz |
| Old sources: | SoftBart archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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