| varbvs-package | Large-scale Bayesian variable selection using variational methods |
| bayesfactor | Compute numerical estimate of Bayes factor. |
| case.names.varbvs | Accessing Properties of Fitted varbvs Models |
| coef.varbvs | Accessing Properties of Fitted varbvs Models |
| confint.varbvs | Accessing Properties of Fitted varbvs Models |
| cred | Estimate credible interval. |
| cytokine | Cytokine signaling genes SNP annotation. |
| deviance.varbvs | Accessing Properties of Fitted varbvs Models |
| fitted.varbvs | Accessing Properties of Fitted varbvs Models |
| labels.varbvs | Accessing Properties of Fitted varbvs Models |
| leukemia | Expression levels recorded in leukemia patients. |
| nobs.varbvs | Accessing Properties of Fitted varbvs Models |
| normalizelogweights | Compute normalized probabilities. |
| plot.varbvs | Summarize variable selection results in a single plot. |
| predict.varbvs | Make predictions from a model fitted by varbvs. |
| print.summary.varbvs | Summarize a fitted variable selection model. |
| print.varbvs | Summarize a fitted variable selection model. |
| rand | Return matrices of pseudorandom values. |
| randn | Return matrices of pseudorandom values. |
| resid.varbvs | Accessing Properties of Fitted varbvs Models |
| residuals.varbvs | Accessing Properties of Fitted varbvs Models |
| subset.varbvs | Select hyperparameter settings from varbvs analysis. |
| summary.varbvs | Summarize a fitted variable selection model. |
| varbvs | Fit variable selection model using variational approximation methods. |
| varbvs.properties | Accessing Properties of Fitted varbvs Models |
| varbvsbf | Compute numerical estimate of Bayes factor. |
| varbvsindep | Compute posterior statistics, ignoring correlations. |
| varbvsmix | Fit linear regression with mixture-of-normals priors using variational approximation methods. |
| varbvsproxybf | Compute Bayes factors measuring improvement-in-fit along 1 dimension. |
| variable.names.varbvs | Accessing Properties of Fitted varbvs Models |