create_new_trial_data   Data on new trial in target population
create_posterior_data   Creates posterior distributions for a range of
                        weights on the informative component of the
                        robust MAP prior
create_prior_data       Creates input data frame for construction of
                        MAP prior
create_tipmap_data      Create data frame ready to use for tipping
                        point analysis
default_quantiles       Default quantiles
default_weights         Default weights
draw_beta_mixture_1sample
                        Draw a single sample from a mixture of beta
                        distributions
draw_beta_mixture_nsamples
                        Draw n samples from a mixture of beta
                        distributions
fit_beta_1exp           Fit beta distribution for one expert
fit_beta_mult_exp       Fit beta distributions for multiple experts
get_cum_probs_1exp      Get cumulative probabilities from distribution
                        of chips of one expert
get_model_input_1exp    Transform cumulative probabilities to fit beta
                        distributions
get_posterior_by_weight
                        Filter posterior by given weights
get_stochast_weight_posterior
                        Computation of posterior distribution using
                        weights sampled from a distribution of weights
get_summary_mult_exp    Summarize expert weights
get_tipping_points      Identify tipping point for a specific quantile.
load_tipmap_data        Load exemplary datasets
tipmap_darkblue         Custom dark blue
tipmap_lightred         Custom light red
tipmap_plot             Visualize tipping point analysis
