zic: Bayesian Inference for Zero-Inflated Count Models
Version 0.9

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.

Browse man pages Browse package API and functions Browse package files

AuthorMarkus Jochmann <markus.jochmann@ncl.ac.uk>
Date of publication2015-09-04 01:07:45
MaintainerMarkus Jochmann <markus.jochmann@ncl.ac.uk>
LicenseGPL (>= 2)
Version0.9
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("zic")

Man pages

docvisits: Demand for Health Care Data
zic: Bayesian Inference for Zero-Inflated Count Models
zic-internal: Internal functions
zic.svs: SVS for Zero-Inflated Count Models

Functions

docvisits Man page
get.scale Man page Source code
is.dummy Man page Source code
zic Man page Source code
zic.svs Man page Source code

Files

src
src/Makevars
src/zicmodel.h
src/spikeslab.h
src/random_R.cc
src/zic_R_interface.cc
src/Makevars.win
src/random_R.h
src/spikeslab.cc
src/zicmodel.cc
NAMESPACE
data
data/docvisits.rda
R
R/zic.R
MD5
DESCRIPTION
man
man/docvisits.Rd
man/zic.Rd
man/zic.svs.Rd
man/zic-internal.Rd
zic documentation built on May 19, 2017, 10:48 p.m.