Package index • shrinkr

All functions

as.data.frame(<shrinkr_fit>): Convert shrinkr_fit to data.frame
as.data.frame(<shrinkr_mixture>): Convert mixture fit to data frame
as.data.frame(<shrinkr_prior_pred>): Convert prior predictive samples to data frame
as_draws_df(<shrinkr_fit>): Convert shrinkr_fit to draws_df
extract_mu_tau(): Extract mu and tau parameters
extract_theta(): Extract theta (group-level effect) parameters
fit_mixture(): Fit Gaussian mixture models to posterior samples
plot(<shrinkr_fit>): Plot shrinkage fit
plot(<shrinkr_mixture>): Plot fitted marginal densities or QQ plots for mixture models
plot(<shrinkr_prior_contrasts>): Plot prior predictive pairwise differences
plot(<shrinkr_prior_pred>): Plot prior predictive samples
print(<shrinkr_fit>): Print method for shrinkr_fit
print(<shrinkr_mixture>): Print method for mixture fits
print(<shrinkr_prior_contrasts>): Print method for prior pairwise contrasts
print(<shrinkr_prior_pred>): Print method for prior predictive samples
print(<summary.shrinkr_mixture>): Print summary of mixture fit
print(<summary.shrinkr_prior_pred>): Print summary of prior predictive samples
prior_mixture(): Create a mixture prior
prior_pairwise_differences(): Compute prior predictive pairwise differences |theta_i - theta_j|
prior_spike_slab(): Spike-and-slab prior for testing homogeneity
sample_prior_predictive(): Sample from prior predictive distribution
shrink(): Bayesian Hierarchical Shrinkage Model
shrinkr-imports: Imports from stats
shrinkr-package shrinkr: shrinkr: Modular Bayesian Hierarchical Shrinkage Models
summarise_mu_tau() summarize_mu_tau(): Summarize mu and tau hyperparameters
summarise_theta() summarize_theta(): Summarize theta parameters by group
summary(<shrinkr_fit>): Summary method for shrinkr_fit
summary(<shrinkr_mixture>): Summary statistics for mixture fits
summary(<shrinkr_prior_pred>): Summary statistics for prior predictive samples
theta_contrasts(): Linear combinations of theta