area_under_curve        Area under the Curve (AUC)
as.data.frame.density   Coerce to a Data Frame
as.numeric.map_estimate
                        Convert to Numeric
bayesfactor             Bayes Factors (BF)
bayesfactor_inclusion   Inclusion Bayes Factors for testing predictors
                        across Bayesian models
bayesfactor_models      Bayes Factors (BF) for model comparison
bayesfactor_parameters
                        Bayes Factors (BF) for a Single Parameter
bayesfactor_restricted
                        Bayes Factors (BF) for Order Restricted Models
bci                     Bias Corrected and Accelerated Interval (BCa)
bic_to_bf               Convert BIC indices to Bayes Factors via the
                        BIC-approximation method.
check_prior             Check if Prior is Informative
ci                      Confidence/Credible/Compatibility Interval (CI)
contr.equalprior        Contrast Matrices for Equal Marginal Priors in
                        Bayesian Estimation
convert_bayesian_as_frequentist
                        Convert (refit) a Bayesian model to frequentist
density_at              Density Probability at a Given Value
describe_posterior      Describe Posterior Distributions
describe_prior          Describe Priors
diagnostic_draws        Diagnostic values for each iteration
diagnostic_posterior    Posteriors Sampling Diagnostic
disgust                 Moral Disgust Judgment
display.describe_posterior
                        Print tables in different output formats
distribution            Empirical Distributions
effective_sample        Effective Sample Size (ESS)
equivalence_test        Test for Practical Equivalence
estimate_density        Density Estimation
eti                     Equal-Tailed Interval (ETI)
hdi                     Highest Density Interval (HDI)
map_estimate            Maximum A Posteriori probability estimate (MAP)
mcse                    Monte-Carlo Standard Error (MCSE)
mediation               Summary of Bayesian multivariate-response
                        mediation-models
model_to_priors         Convert model's posteriors to priors
                        (EXPERIMENTAL)
overlap                 Overlap Coefficient
p_direction             Probability of Direction (pd)
p_map                   Bayesian p-value based on the density at the
                        Maximum A Posteriori (MAP)
p_rope                  Probability of being in the ROPE
p_significance          Practical Significance (ps)
p_to_bf                 Convert p-values to (pseudo) Bayes Factors
pd_to_p                 Convert between Probability of Direction (pd)
                        and p-value.
point_estimate          Point-estimates of posterior distributions
reshape_iterations      Reshape estimations with multiple iterations
                        (draws) to long format
rope                    Region of Practical Equivalence (ROPE)
rope_range              Find Default Equivalence (ROPE) Region Bounds
sensitivity_to_prior    Sensitivity to Prior
sexit                   Sequential Effect eXistence and sIgnificance
                        Testing (SEXIT)
sexit_thresholds        Find Effect Size Thresholds
si                      Compute Support Intervals
simulate_correlation    Data Simulation
simulate_prior          Returns Priors of a Model as Empirical
                        Distributions
simulate_simpson        Simpson's paradox dataset simulation
spi                     Shortest Probability Interval (SPI)
weighted_posteriors     Generate posterior distributions weighted
                        across models
