PPC_group_distribution
                        Posterior Predictive Check for Stan model
approx_equal            Approximate equal
cbbPalette              A colorblind-friendly palette (with black)
change_colnames         Change column names of a dataframe
compute_RPS             Compute RPS for a single forecast
compute_calibration     Estimate calibration given forecasts and
                        corresponding outcomes
compute_resolution      Compute resolution of forecasts, normalised by
                        the uncertainty
coverage                Coverage probability
empirical_pval          Compute empirical p-values
extract_ci              Extract confidence intervals from a vector of
                        samples
extract_distribution    Extract a distribution represented by samples
extract_draws           Extract parameters' draws
extract_index_nd        Extract multiple indices inside bracket(s) as a
                        list
extract_parameters_from_draw
                        Extract parameters from a single draw
extract_pdf             Extract probability density function from
                        vector of samples
extract_pmf             Extract probability mass function from vector
                        of samples
factor_to_numeric       Change the type of the column of a dataframe
                        from factor to numeric
illustrate_RPS          Illustration of the Ranked Probability Score
illustrate_forward_chaining
                        Illustration forward chaining
is_scalar               Test whether x is of length 1
is_stanfit              Test whether an object is of class "stanfit"
is_wholenumber          Test whether x is a whole number
logit                   Logit and Inverse logit
post_pred_pval          Posterior Predictive p-value
prior_posterior         Compare prior to posterior
process_replications    Extract posterior predictive distribution
summary_statistics      Extract summary statistics
