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: 0.1
Depends: R (≥ 3.4.0), Rcpp (≥ 0.12.0)
Imports: dplyr (≥ 0.7.4), ggplot2 (≥ 2.2.1), loo (≥ 2.0.0), methods (≥ 3.4.4), rstan (≥ 2.17.3), rstantools (≥ 1.5.0), R.utils (≥ 2.6.0)
LinkingTo: StanHeaders (≥ 2.17.1), rstan (≥ 2.17.2), BH (≥ 1.65.0), Rcpp (≥ 0.12.0), RcppEigen (≥ 0.3.3.3.0)
Suggests: lintr, testthat
Published: 2018-08-05
Author: Marcus Groß [aut, cre], Ricardo Fernandes [aut], Mira Celine Klein [ctb]
Maintainer: Marcus Groß <marcus.gross at inwt-statistics.de>
License: GPL-3
NeedsCompilation: yes
CRAN checks: BMSC results

Downloads:

Reference manual: BMSC.pdf
Package source: BMSC_0.1.tar.gz
Windows binaries: r-devel: BMSC_0.1.zip, r-release: BMSC_0.1.zip, r-oldrel: BMSC_0.1.zip
OS X binaries: r-release: BMSC_0.1.tgz, r-oldrel: BMSC_0.1.tgz

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