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bayescopulareg: Bayesian Copula Regression

Tools for Bayesian copula generalized linear models (GLMs). The sampling scheme is based on Pitt, Chan, and Kohn (2006) <doi:10.1093/biomet/93.3.537>. Regression parameters (including coefficients and dispersion parameters) are estimated via the adaptive random walk Metropolis approach developed by Haario, Saksman, and Tamminen (1999) <doi:10.1007/s001800050022>. The prior for the correlation matrix is based on Hoff (2007) <doi:10.1214/07-AOAS107>.

Version: 0.1.3
Depends: R (≥ 3.6.0)
Imports: Rcpp (≥ 1.0.3), stats
LinkingTo: Rcpp, RcppArmadillo, RcppDist, mvtnorm
Published: 2020-11-30
Author: Ethan Alt [aut, cre], Yash Bhosale [aut]
Maintainer: Ethan Alt <ethanalt at live.unc.edu>
BugReports: https://github.com/ethan-alt/bayescopulareg/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/ethan-alt/bayescopulareg
NeedsCompilation: yes
Materials: README NEWS
In views: Bayesian
CRAN checks: bayescopulareg results

Documentation:

Reference manual: bayescopulareg.pdf

Downloads:

Package source: bayescopulareg_0.1.3.tar.gz
Windows binaries: r-devel: bayescopulareg_0.1.3.zip, r-release: bayescopulareg_0.1.3.zip, r-oldrel: bayescopulareg_0.1.3.zip
macOS binaries: r-release (arm64): bayescopulareg_0.1.3.tgz, r-oldrel (arm64): bayescopulareg_0.1.3.tgz, r-release (x86_64): bayescopulareg_0.1.3.tgz, r-oldrel (x86_64): bayescopulareg_0.1.3.tgz
Old sources: bayescopulareg archive

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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