ptycho (1.1-4)

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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, plyr, reshape2, foreach, doRNG

Released almost 4 years ago.

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