Posterior Description

describe_posterior()

Describe Posterior Distributions

describe_prior()

Describe Priors

sexit()

Sequential Effect eXistence and sIgnificance Testing (SEXIT)

Centrality and Uncertainty

point_estimate()

Point-estimates of posterior distributions

map_estimate()

Maximum A Posteriori probability estimate (MAP)

eti()

Equal-Tailed Interval (ETI)

hdi()

Highest Density Interval (HDI)

ci()

Confidence/Credible/Compatibility Interval (CI)

reshape_ci()

Reshape CI between wide/long formats

Effect Existence and Significance

Functions for Bayesian Inference

Posterior Based Methods

mhdior()

Maximum HDI level inside/outside ROPE (MHDIOR)

p_direction() pd()

Probability of Direction (pd)

p_rope()

Probability of being in the ROPE

p_map() p_pointnull()

Bayesian p-value based on the density at the Maximum A Posteriori (MAP)

p_significance()

Practical Significance (ps)

rope()

Region of Practical Equivalence (ROPE)

rope_range()

Find Default Equivalence (ROPE) Region Bounds

equivalence_test()

Test for Practical Equivalence

pd_to_p() p_to_pd() convert_p_to_pd() convert_pd_to_p()

Convert between Probability of Direction (pd) and p-value.

Bayes factors

bayesfactor()

Bayes Factors (BF)

bayesfactor_parameters() bayesfactor_pointull() bayesfactor_rope() bf_parameters() bf_pointull() bf_rope()

Bayes Factors (BF) for a Single Parameter

bayesfactor_models() bf_models()

Bayes Factors (BF) for model comparison

bayesfactor_inclusion() bf_inclusion()

Inclusion Bayes Factors for testing predictors across Bayesian models

bayesfactor_restricted() bf_restricted()

Bayes Factors (BF) for Order Restricted Models

si()

Compute Support Intervals

weighted_posteriors()

Generate posterior distributions weighted across models

Model Diagnostics

diagnostic_posterior()

Posteriors Sampling Diagnostic

sensitivity_to_prior()

Sensitivity to Prior

check_prior()

Check if Prior is Informative

simulate_prior()

Returns Priors of a Model as Empirical Distributions

unupdate()

Un-update Bayesian models to their prior-to-data state

effective_sample()

Effective Sample Size (ESS)

mcse()

Monte-Carlo Standard Error (MCSE)

Density Estimation

estimate_density()

Density Estimation

density_at()

Density Probability at a Given Value

area_under_curve() auc()

Area under the Curve (AUC)

overlap()

Overlap Coefficient

Distributions

distribution() distribution_custom() distribution_beta() distribution_binomial() distribution_binom() distribution_cauchy() distribution_chisquared() distribution_chisq() distribution_gamma() distribution_mixture_normal() distribution_normal() distribution_gaussian() distribution_nbinom() distribution_poisson() distribution_student() distribution_t() distribution_student_t() distribution_tweedie() distribution_uniform() rnorm_perfect()

Empirical Distributions

Utilities

simulate_correlation() simulate_ttest() simulate_difference()

Data Simulation

mediation()

Summary of Bayesian multivariate-response mediation-models

convert_bayesian_as_frequentist() bayesian_as_frequentist()

Convert (refit) a Bayesian model to frequentist

contr.bayes()

Orthonormal Contrast Matrices for Bayesian Estimation

as.numeric(<map_estimate>) as.numeric(<mhdior>) as.numeric(<p_direction>) as.numeric(<p_map>) as.numeric(<p_significance>)

Convert to Numeric

as.data.frame(<density>)

Coerce to a Data Frame

update(<bayesfactor_models>) as.matrix(<bayesfactor_models>)

Methods for bayesfactor_models

sexit_thresholds()

Find Effect Size Thresholds