Introduction | Data | Reference model | Variable selection | Preliminary cv_varsel() run | Final cv_varsel() run | Predictive performance plot from final cv_varsel() run | Decision for final submodel size | Predictive performance table from final cv_varsel() run | Predictor ranking(s) from final cv_varsel() run and identification of the selected submodel | Post-selection inference | Marginals of the projected posterior | Predictions | Supported types of models | Troubleshooting | Non-convergence of predictive performance | Overfitting | Issues with the traditional projection | Issues with the augmented-data projection | Speed | References

Introduction | General idea | Implementation | Example: Poisson distribution | Data | Reference model | Variable selection using the latent projection | Variable selection using the traditional projection | Conclusion | Example: Negative binomial distribution | Censored observations (survival analysis) | Example: Weibull distribution with right-censored observations | Example: Log-normal distribution with right-censored observations | References