ptycho (1.1-2)

Bayesian Variable Selection with Hierarchical Priors.

Bayesian variable selection for linear regression models using hierarchical priors. There is a prior that combines information across responses and one that combines information across covariates, as well as a standard spike and slab prior for comparison. An MCMC samples from the marginal posterior distribution for the 0-1 variables indicating if each covariate belongs to the model for each response.

Maintainer: Laurel Stell
Author(s): Laurel Stell and Chiara Sabatti

License: GPL (>= 2)

Uses: coda, doMC, doRNG, foreach, plyr, reshape2

Released about 4 years ago.