The function MC3() searches for log-linear models with the highest posterior probability. The function gibbsSampler() is a blocked Gibbs sampler for sampling from the posterior distribution of the log-linear parameters. The functions findPostMean() and findPostCov() compute the posterior mean and covariance matrix for decomposable models which, for these models, is available in closed form.
| Version: | 1.0.1 |
| Depends: | igraph |
| Published: | 2016-12-27 |
| Author: | Matthew Friedlander |
| Maintainer: | Matthew Friedlander <friedla at yorku.ca> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| CRAN checks: | bayesloglin results |
| Reference manual: | bayesloglin.pdf |
| Vignettes: |
bayesloglin-R-package |
| Package source: | bayesloglin_1.0.1.tar.gz |
| Windows binaries: | r-devel: bayesloglin_1.0.1.zip, r-release: bayesloglin_1.0.1.zip, r-oldrel: bayesloglin_1.0.1.zip |
| macOS binaries: | r-release: bayesloglin_1.0.1.tgz, r-oldrel: bayesloglin_1.0.1.tgz |
| Old sources: | bayesloglin archive |
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