Hierarchical Shrinkage Stan Models for Biomarker Selection

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Documentation for package ‘hsstan’ version 0.8.1

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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