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Provides an approximate algorithm for the horseshoe estimator used in Bayesian linear models. By implementing a sampler with high computational cost in the 'Rcpp' package and using an approximate algorithm that reduces matrix calculation complexity, parameter estimation speed for high-dimensional sparse data is faster. The approximate algorithm is described in Johndrow et al. (2020) <https://www.jmlr.org/papers/v21/19-536.html>.
| Version: | 0.1.2 |
| Imports: | stats, Rcpp (≥ 1.0.11) |
| LinkingTo: | Rcpp |
| Suggests: | knitr, rmarkdown, ggplot2, horseshoe |
| Published: | 2023-11-24 |
| Author: | Kang Mingi [aut, cre], Lee Kyoungjae [aut] |
| Maintainer: | Kang Mingi <leehuimin115 at g.skku.edu> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | Mhorseshoe results |
| Reference manual: | Mhorseshoe.pdf |
| Vignettes: |
Mhorseshoe |
| Package source: | Mhorseshoe_0.1.2.tar.gz |
| Windows binaries: | r-devel: Mhorseshoe_0.1.2.zip, r-release: Mhorseshoe_0.1.2.zip, r-oldrel: Mhorseshoe_0.1.2.zip |
| macOS binaries: | r-release (arm64): Mhorseshoe_0.1.2.tgz, r-oldrel (arm64): Mhorseshoe_0.1.2.tgz, r-release (x86_64): Mhorseshoe_0.1.2.tgz, r-oldrel (x86_64): Mhorseshoe_0.1.2.tgz |
| Old sources: | Mhorseshoe archive |
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