BMSC: Bayesian Model Selection under Constraints

A Bayesian regression package supporting constrained coefficient estimation and variable selection using Stan. This includes a robust variable selection algorithm by a horseshoe prior (<doi:10.1093/biomet/asq017>) that finds the optimal model considering main effects, interactions as well as powers of given variables under potential parameter constraints.

Version: 0.2.0
Depends: R (≥ 3.4.0), Rcpp (≥ 0.12.0), methods
Imports: dplyr (≥ 0.7.4), ggplot2 (≥ 2.2.1), loo (≥ 2.0.0), rstan (≥ 2.18.1), rstantools (≥ 1.5.1), R.utils (≥ 2.6.0)
LinkingTo: StanHeaders (≥ 2.18.0), rstan (≥ 2.18.2), BH (≥ 1.66.0), Rcpp (≥ 0.12.0), RcppEigen (≥
Suggests: lintr, testthat
Published: 2019-04-16
Author: Marcus Groß [aut, cre], Ricardo Fernandes [aut], Mira Celine Klein [ctb]
Maintainer: Marcus Groß <marcus.gross at>
License: GPL-3
NeedsCompilation: yes
CRAN checks: BMSC results


Reference manual: BMSC.pdf
Package source: BMSC_0.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X binaries: r-release: BMSC_0.2.0.tgz, r-oldrel: BMSC_0.1.1.tgz
Old sources: BMSC archive


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