zic: Bayesian Inference for Zero-Inflated Count Models
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 |
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 |
Documentation:
Downloads:
Reverse dependencies:
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