Package: sbgcop 1.0

sbgcop: Semiparametric Bayesian Gaussian Copula Estimation and Imputation

Estimation and inference for parameters in a Gaussian copula model, treating the univariate marginal distributions as nuisance parameters as described in Hoff (2007) <doi:10.1214/07-AOAS107>. This package also provides a semiparametric imputation procedure for missing multivariate data.

Authors:Peter Hoff

sbgcop_1.0.tar.gz
sbgcop_1.0.zip(r-4.7)sbgcop_1.0.zip(r-4.6)sbgcop_1.0.zip(r-4.5)
sbgcop_1.0.tgz(r-4.6-any)sbgcop_1.0.tgz(r-4.5-any)
sbgcop_1.0.tar.gz(r-4.7-any)sbgcop_1.0.tar.gz(r-4.6-any)
sbgcop_1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
sbgcop/json (API)
NEWS

# Install 'sbgcop' in R:

install.packages('sbgcop', repos = c('https://pdhoff.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/pdhoff/sbgcop/issues

On CRAN:

3.19 score 1 packages 52 scripts 333 downloads 9 exports 0 dependencies

Last updated from:916c56e28b. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	103
source / vignettes	OK	126
linux-release-x86_64	OK	95
macos-release-arm64	OK	67
macos-oldrel-arm64	OK	77
windows-devel	OK	67
windows-release	OK	77
windows-oldrel	OK	66
wasm-release	OK	80

Exports:ldmvnorm plot.psgc plotci.sA print.sum.psgc qM.sM rwish sbgcop.mcmc sR.sC summary.psgc

Dependencies:

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Semiparametric Bayesian Gaussian Copula Estimation and Imputation	sbgcop-package sbgcop
Log Multivariate Normal Density	ldmvnorm
Plot Confidence Bands for Association Parameters	plotci.sA
Matrix Quantiles	qM.sM
Sample from the Wishart Distribution	rwish
Semiparametric Bayesian Gaussian copula estimation and imputation	plot.psgc print.sum.psgc sbgcop.mcmc summary.psgc
Compute Regression Parameters	sR.sC