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 smu.edu> |
| License: | MPL (== 2.0) |
| URL: | www.cox.smu.edu/web/michaelbraun |
| 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: bayesGDS_0.6.0.zip, r-release: bayesGDS_0.6.0.zip, r-oldrel: bayesGDS_0.6.0.zip |
| 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 |