bayesGDS: Functions to implement Generalized Direct Sampling

This package contains functions to help users implement the Generalized Direct Sampling algorithm for Bayesian hierarchical models (Braun and Damien, 2013). GDS is useful for sampling from posterior distributions for which there is a large number of conditionally independent heterogeneous units.

Version: 0.6.0
Depends: R (≥ 3.0.2), Matrix (≥ 1.1.0), compiler
Suggests: sparseHessianFD (≥ 0.1.1), sparseMVN (≥ 0.1.0), mvtnorm, trustOptim (≥ 0.8.3), plyr (≥ 1.8)
Published: 2013-12-14
Author: Michael Braun
Maintainer: Michael Braun <braunm at>
License: MPL (== 2.0)
NeedsCompilation: no
Materials: NEWS
CRAN checks: bayesGDS results


Reference manual: bayesGDS.pdf
Vignettes: Using the bayesGDS package
Package source: bayesGDS_0.6.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
OS X Snow Leopard binaries: r-release: bayesGDS_0.6.0.tgz, r-oldrel: bayesGDS_0.6.0.tgz
OS X Mavericks binaries: r-release: bayesGDS_0.6.0.tgz
Old sources: bayesGDS archive