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 () that finds the optimal model considering main effects, interactions as well as powers of given variables under potential parameter constraints.


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install.packages("BMSC")

0.1.1 by Marcus Groß, 5 months ago


Browse source code at https://github.com/cran/BMSC


Authors: Marcus Groß [aut, cre] , Ricardo Fernandes [aut] , Mira Celine Klein [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports dplyr, ggplot2, loo, rstan, rstantools, R.utils

Depends on Rcpp, methods

Suggests lintr, testthat

Linking to StanHeaders, rstan, BH, Rcpp, RcppEigen


See at CRAN