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:
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-4.4-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
Last updated 6 years agofrom:8e67c159e8. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-win | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
| R-4.4-win | OK | Nov 16 2024 |
| R-4.4-mac | OK | Nov 16 2024 |
| R-4.3-win | OK | Nov 16 2024 |
| R-4.3-mac | OK | Nov 16 2024 |
Exports:ldmvnormplot.psgcplotci.sAprint.sum.psgcqM.sMrwishsbgcop.mcmcsR.sCsummary.psgc
Dependencies:
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 |
