sbgcop: Semiparametric Bayesian Gaussian copula estimation and imputation

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This package estimates parameters of a Gaussian copula, treating the univariate marginal distributions as nuisance parameters as described in Hoff(2007). It also provides a semiparametric imputation procedure for missing multivariate data.

Author
Peter Hoff
Date of publication
2012-10-29 08:59:38
Maintainer
Peter Hoff <hoff@stat.washington.edu>
License
GPL (>= 2)
Version
0.975
URLs

View on CRAN

Man pages

ldmvnorm
Log Multivariate Normal Density
plotci.sA
Plot Confidence Bands for Association Parameters
qM.sM
Matrix Quantiles
rwish
Sample from the Wishart Distribution
sbgcop.mcmc
Semiparametric Bayesian Gaussian copula estimation and...
sbgcop.package
Semiparametric Bayesian Gaussian copula estimation and...
sR.sC
Compute Regression Parameters

Files in this package

sbgcop
sbgcop/NAMESPACE
sbgcop/man
sbgcop/man/plotci.sA.Rd
sbgcop/man/sbgcop.mcmc.Rd
sbgcop/man/ldmvnorm.Rd
sbgcop/man/sR.sC.Rd
sbgcop/man/rwish.Rd
sbgcop/man/sbgcop.package.Rd
sbgcop/man/qM.sM.Rd
sbgcop/DESCRIPTION
sbgcop/MD5
sbgcop/R
sbgcop/R/print.sum.psgc.R
sbgcop/R/ldmvnorm.R
sbgcop/R/summary.psgc.R
sbgcop/R/plotci.sA.R
sbgcop/R/qM.sM.R
sbgcop/R/sR.sC.R
sbgcop/R/plot.psgc.R
sbgcop/R/sbgcop.mcmc.R
sbgcop/R/rwish.R