Package: zic 0.9.1
Markus Jochmann
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.
Authors:
zic_0.9.1.tar.gz
zic_0.9.1.tar.gz(r-4.5-noble)zic_0.9.1.tar.gz(r-4.4-noble)
zic_0.9.1.tgz(r-4.4-emscripten)zic_0.9.1.tgz(r-4.3-emscripten)
zic.pdf |zic.html✨
zic/json (API)
| # Install 'zic' in R: |
| install.packages('zic', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Datasets:
- docvisits - Demand for Health Care Data
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:ce0559a177. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 09 2024 |
| R-4.5-linux-x86_64 | OK | Nov 09 2024 |
Exports:get.scaleis.dummyziczic.svs
Dependencies:codalatticeRcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Demand for Health Care Data | docvisits |
| Bayesian Inference for Zero-Inflated Count Models | zic |
| SVS for Zero-Inflated Count Models | zic.svs |