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.
|Author||Laurel Stell and Chiara Sabatti|
|Date of publication||2015-11-12 19:09:21|
|Maintainer||Laurel Stell <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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