Package: sbgcop 0.980

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_0.980.tar.gz
sbgcop_0.980.zip(r-4.5)sbgcop_0.980.zip(r-4.4)sbgcop_0.980.zip(r-4.3)
sbgcop_0.980.tgz(r-4.5-any)sbgcop_0.980.tgz(r-4.4-any)sbgcop_0.980.tgz(r-4.3-any)
sbgcop_0.980.tar.gz(r-4.5-noble)sbgcop_0.980.tar.gz(r-4.4-noble)
sbgcop_0.980.tgz(r-4.4-emscripten)sbgcop_0.980.tgz(r-4.3-emscripten)
sbgcop.pdf |sbgcop.html✨
sbgcop/json (API)

# 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:

3.13 score 1 packages 45 scripts 273 downloads 9 exports 0 dependencies

Last updated 7 years agofrom:8e67c159e8. Checks:8 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKFeb 14 2025
R-4.5-winOKFeb 14 2025
R-4.5-macOKFeb 14 2025
R-4.5-linuxOKFeb 14 2025
R-4.4-winOKFeb 14 2025
R-4.4-macOKFeb 14 2025
R-4.3-winOKFeb 14 2025
R-4.3-macOKFeb 14 2025

Exports:ldmvnormplot.psgcplotci.sAprint.sum.psgcqM.sMrwishsbgcop.mcmcsR.sCsummary.psgc

Dependencies: