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:Markus Jochmann <[email protected]>

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'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.00 score 212 downloads 4 exports 4 dependencies

Last updated 7 years agofrom:ce0559a177. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 09 2024
R-4.5-linux-x86_64OKDec 09 2024

Exports:get.scaleis.dummyziczic.svs

Dependencies:codalatticeRcppRcppArmadillo