zic: Bayesian Inference for Zero-Inflated Count Models (original) (raw)
Provides MCMC algorithms for the analysis of zero-inflated count models. The case of stochastic search variable selection (SVS) is also considered. All MCMC samplers are coded in C++ for improved efficiency. A data set considering the demand for health care is provided.
| Version: | 0.9.1 |
|---|---|
| Depends: | R (≥ 3.0.2) |
| Imports: | Rcpp (≥ 0.11.0), coda (≥ 0.14-2) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2017-08-22 |
| DOI: | 10.32614/CRAN.package.zic |
| Author: | Markus Jochmann |
| Maintainer: | Markus Jochmann <markus.jochmann at ncl.ac.uk> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| In views: | Bayesian |
| CRAN checks: | zic results |
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