Exact Bayesian Model Selection Methods for the Sparse Normal Sequence Model
Compute marginal posterior estimates for beta-spike-and-slab prior
Compute marginal posterior estimates
Fast Exact Bayesian Inference for the Sparse Normal Means Model
Compute marginal posterior probabilities (slab probabilities) that dat...
Given a prior Lambda on the alpha-parameter in the spike-and-slab mode...
Given prior Lambda=Beta(kappa,lambda) on the alpha-parameter in the sp...
Compute marginal posterior probabilities (slab probabilities) that dat...
Compute marginal posterior probabilities (slab probabilities) that dat...
Calculate log of phi and psi marginal densities for Cauchy(gamma) slab
Calculate log of phi and psi marginal densities for Laplace(lambda) sl...
Creates a vector of uniformly spaced grid points in the beta parametri...
Compute posterior means of data points for the Cauchy(gamma) slab
Compute posterior means of data points for the Laplace(lambda) slab
Contains fast functions to calculate the exact Bayes posterior for the Sparse Normal Sequence Model, implementing the algorithms described in Van Erven and Szabo (2021, <doi:10.1214/20-BA1227>). For general hierarchical priors, sample sizes up to 10,000 are feasible within half an hour on a standard laptop. For beta-binomial spike-and-slab priors, a faster algorithm is provided, which can handle sample sizes of 100,000 in half an hour. In the implementation, special care has been taken to assure numerical stability of the methods even for such large sample sizes.