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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.
Package details |
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Author | Laurel Stell [aut, cre], Chiara Sabatti [aut] |
Maintainer | Laurel Stell <lstell@stanford.edu> |
License | GPL (>= 2) |
Version | 1.1-5 |
URL | http://web.stanford.edu/~lstell/ptycho/ |
Package repository | View on CRAN |
Installation |
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