Functions for implementing the Braun and Damien (2015) rejection sampling algorithm for Bayesian hierarchical models. The algorithm generates posterior samples in parallel, and is scalable when the individual units are conditionally independent.
NEWS file for bayesGDS package
Added devtools infrastructure.
Documentation now created using roxygen2
All new vignettes
New CITATION information
This is a complete reworking of the package, with new function names and arguments. The function for the rejection sampling phase is now sample.GDS. Function arguments have changed. Altogether, the sample.GDS phase should run much more efficiently than previous versions.
The dependency to Rmfpr has been removed.
An updated version of Braun and Damien (2013) is available in the /doc folder of the package.