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.

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

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Files in this package

zic
zic/src
zic/src/Makevars
zic/src/zicmodel.h
zic/src/spikeslab.h
zic/src/random_R.cc
zic/src/zic_R_interface.cc
zic/src/Makevars.win
zic/src/random_R.h
zic/src/spikeslab.cc
zic/src/zicmodel.cc
zic/NAMESPACE
zic/data
zic/data/docvisits.rda
zic/R
zic/R/zic.R
zic/MD5
zic/DESCRIPTION
zic/man
zic/man/docvisits.Rd zic/man/zic.Rd zic/man/zic.svs.Rd zic/man/zic-internal.Rd

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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