sbgcop: Semiparametric Bayesian Gaussian copula estimation and imputation
Version 0.975

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.

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AuthorPeter Hoff
Date of publication2012-10-29 08:59:38
MaintainerPeter Hoff <hoff@stat.washington.edu>
LicenseGPL (>= 2)
Version0.975
URL http://www.stat.washington.edu/hoff
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("sbgcop")

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

Functions

ldmvnorm Man page
plot.psgc Man page
plotci.sA Man page
print.sum.psgc Man page
qM.sM Man page
rwish Man page
sR.sC Man page
sbgcop Man page
sbgcop-package Man page
sbgcop.mcmc Man page
summary.psgc Man page

Files

NAMESPACE
man
man/plotci.sA.Rd
man/sbgcop.mcmc.Rd
man/ldmvnorm.Rd
man/sR.sC.Rd
man/rwish.Rd
man/sbgcop.package.Rd
man/qM.sM.Rd
DESCRIPTION
MD5
R
R/print.sum.psgc.R
R/ldmvnorm.R
R/summary.psgc.R
R/plotci.sA.R
R/qM.sM.R
R/sR.sC.R
R/plot.psgc.R
R/sbgcop.mcmc.R
R/rwish.R
sbgcop documentation built on May 20, 2017, 2:07 a.m.