# Guillem Hurault Functions' Library

## Documentation for package ‘HuraultMisc’ version 1.2.1

- DESCRIPTION file
- Package NEWS
- Package README

## Help Pages

%~% | Approximate equal
approx_equal | Approximate equal
cbbPalette | A colour blind friendly palette (with black)
check_model_sensitivity | Compare prior to posterior
combine_prior_posterior | Compare prior to posterior
compute_calibration | Estimate calibration given forecasts and corresponding outcomes
compute_coverage | Coverage probability
compute_prior_influence | Compare prior to posterior
compute_resolution | Compute resolution of forecasts, normalised by the uncertainty
compute_RPS | Compute RPS for a single forecast
compute_rsquared | Compute Bayesian R-squared from matrix of posterior replications
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_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
inv_logit | Logit and Inverse logit
is_scalar | Test whether x is of length 1
is_scalar_wholenumber | Test whether x is a whole number
is_stanfit | Test whether an object is of class "stanfit"
is_wholenumber | Test whether x is a whole number
logit | Logit and Inverse logit
plot_coverage | Coverage probability
plot_prior_influence | Compare prior to posterior
plot_prior_posterior | Compare prior to posterior
post_pred_pval | Posterior Predictive p-value
PPC_group_distribution | Posterior Predictive Check for Stan model
prior_posterior | Compare prior to posterior
summary_statistics | Extract summary statistics