hsstan-package |
Hierarchical shrinkage Stan models for biomarker selection |
bayes_R2 |
Bayesian and LOO-adjusted R-squared |
bayes_R2.hsstan |
Bayesian and LOO-adjusted R-squared |
diabetes |
Diabetes data with interaction terms |
hsstan |
Hierarchical shrinkage models |
kfold |
K-fold cross-validation |
kfold.hsstan |
K-fold cross-validation |
log_lik |
Pointwise log-likelihood |
log_lik.hsstan |
Pointwise log-likelihood |
loo |
Predictive information criteria for Bayesian models |
loo.hsstan |
Predictive information criteria for Bayesian models |
loo_R2 |
Bayesian and LOO-adjusted R-squared |
loo_R2.hsstan |
Bayesian and LOO-adjusted R-squared |
nsamples |
Number of posterior samples |
nsamples.hsstan |
Number of posterior samples |
plot.projsel |
Plot of relative explanatory power of predictors |
posterior_interval |
Posterior uncertainty intervals |
posterior_interval.hsstan |
Posterior uncertainty intervals |
posterior_linpred |
Posterior distribution of the linear predictor |
posterior_linpred.hsstan |
Posterior distribution of the linear predictor |
posterior_performance |
Posterior measures of performance |
posterior_predict |
Posterior predictive distribution |
posterior_predict.hsstan |
Posterior predictive distribution |
posterior_summary |
Posterior summary |
posterior_summary.default |
Posterior summary |
posterior_summary.hsstan |
Posterior summary |
print.hsstan |
Print a summary for the fitted model |
projsel |
Forward selection minimizing KL-divergence in projection |
sampler.stats |
Sampler statistics |
summary.hsstan |
Summary for the fitted model |
waic |
Predictive information criteria for Bayesian models |
waic.hsstan |
Predictive information criteria for Bayesian models |