Understand and Describe Bayesian Models and Posterior
Distributions
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Documentation for package ‘bayestestR’ version 0.13.2
Help Pages
-- A --
| area_under_curve | Area under the Curve (AUC) |
| as.data.frame.density | Coerce to a Data Frame |
| as.logical.bayesfactor_restricted | Bayes Factors (BF) for Order Restricted Models |
| as.matrix.bayesfactor_models | Bayes Factors (BF) for model comparison |
| as.numeric.map_estimate | Convert to Numeric |
| as.numeric.p_direction | Convert to Numeric |
| as.numeric.p_map | Convert to Numeric |
| as.numeric.p_significance | Convert to Numeric |
| auc | Area under the Curve (AUC) |
-- B --
| bayesfactor | Bayes Factors (BF) |
| bayesfactor_inclusion | Inclusion Bayes Factors for testing predictors across Bayesian models |
| bayesfactor_models | Bayes Factors (BF) for model comparison |
| bayesfactor_models.default | Bayes Factors (BF) for model comparison |
| bayesfactor_parameters | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_parameters.blavaan | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_parameters.brmsfit | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_parameters.data.frame | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_parameters.numeric | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_parameters.stanreg | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_pointnull | Bayes Factors (BF) for a Single Parameter |
| bayesfactor_restricted | Bayes Factors (BF) for Order Restricted Models |
| bayesfactor_restricted.blavaan | Bayes Factors (BF) for Order Restricted Models |
| bayesfactor_restricted.brmsfit | Bayes Factors (BF) for Order Restricted Models |
| bayesfactor_restricted.emmGrid | Bayes Factors (BF) for Order Restricted Models |
| bayesfactor_restricted.stanreg | Bayes Factors (BF) for Order Restricted Models |
| bayesfactor_rope | Bayes Factors (BF) for a Single Parameter |
| bayesian_as_frequentist | Convert (refit) a Bayesian model to frequentist |
| bcai | Bias Corrected and Accelerated Interval (BCa) |
| bci | Bias Corrected and Accelerated Interval (BCa) |
| bci.BFBayesFactor | Bias Corrected and Accelerated Interval (BCa) |
| bci.brmsfit | Bias Corrected and Accelerated Interval (BCa) |
| bci.data.frame | Bias Corrected and Accelerated Interval (BCa) |
| bci.emmGrid | Bias Corrected and Accelerated Interval (BCa) |
| bci.get_predicted | Bias Corrected and Accelerated Interval (BCa) |
| bci.MCMCglmm | Bias Corrected and Accelerated Interval (BCa) |
| bci.numeric | Bias Corrected and Accelerated Interval (BCa) |
| bci.sim | Bias Corrected and Accelerated Interval (BCa) |
| bci.sim.merMod | Bias Corrected and Accelerated Interval (BCa) |
| bci.stanreg | Bias Corrected and Accelerated Interval (BCa) |
| bf_inclusion | Inclusion Bayes Factors for testing predictors across Bayesian models |
| bf_models | Bayes Factors (BF) for model comparison |
| bf_parameters | Bayes Factors (BF) for a Single Parameter |
| bf_pointnull | Bayes Factors (BF) for a Single Parameter |
| bf_restricted | Bayes Factors (BF) for Order Restricted Models |
| bf_rope | Bayes Factors (BF) for a Single Parameter |
| bic_to_bf | Convert BIC indices to Bayes Factors via the BIC-approximation method. |
-- C --
| check_prior | Check if Prior is Informative |
| ci | Confidence/Credible/Compatibility Interval (CI) |
| ci.BFBayesFactor | Confidence/Credible/Compatibility Interval (CI) |
| ci.brmsfit | Confidence/Credible/Compatibility Interval (CI) |
| ci.data.frame | Confidence/Credible/Compatibility Interval (CI) |
| ci.MCMCglmm | Confidence/Credible/Compatibility Interval (CI) |
| ci.numeric | Confidence/Credible/Compatibility Interval (CI) |
| ci.sim | Confidence/Credible/Compatibility Interval (CI) |
| ci.sim.merMod | Confidence/Credible/Compatibility Interval (CI) |
| ci.stanreg | Confidence/Credible/Compatibility Interval (CI) |
| contr.bayes | Contrast Matrices for Equal Marginal Priors in Bayesian Estimation |
| contr.equalprior | Contrast Matrices for Equal Marginal Priors in Bayesian Estimation |
| contr.equalprior_deviations | Contrast Matrices for Equal Marginal Priors in Bayesian Estimation |
| contr.equalprior_pairs | Contrast Matrices for Equal Marginal Priors in Bayesian Estimation |
| contr.orthonorm | Contrast Matrices for Equal Marginal Priors in Bayesian Estimation |
| convert_bayesian_as_frequentist | Convert (refit) a Bayesian model to frequentist |
| convert_pd_to_p | Convert between Probability of Direction (pd) and p-value. |
| convert_p_to_pd | Convert between Probability of Direction (pd) and p-value. |
| cwi | Curvewise Intervals (CWI) |
| cwi.data.frame | Curvewise Intervals (CWI) |
-- D --
| density_at | Density Probability at a Given Value |
| describe_posterior | Describe Posterior Distributions |
| describe_posterior.brmsfit | Describe Posterior Distributions |
| describe_posterior.numeric | Describe Posterior Distributions |
| describe_posterior.stanreg | Describe Posterior Distributions |
| describe_prior | Describe Priors |
| describe_prior.brmsfit | Describe Priors |
| diagnostic_draws | Diagnostic values for each iteration |
| diagnostic_posterior | Posteriors Sampling Diagnostic |
| diagnostic_posterior.brmsfit | Posteriors Sampling Diagnostic |
| diagnostic_posterior.default | Posteriors Sampling Diagnostic |
| diagnostic_posterior.stanreg | Posteriors Sampling Diagnostic |
| disgust | Moral Disgust Judgment |
| distribution | Empirical Distributions |
| distribution_beta | Empirical Distributions |
| distribution_binom | Empirical Distributions |
| distribution_binomial | Empirical Distributions |
| distribution_cauchy | Empirical Distributions |
| distribution_chisq | Empirical Distributions |
| distribution_chisquared | Empirical Distributions |
| distribution_custom | Empirical Distributions |
| distribution_gamma | Empirical Distributions |
| distribution_gaussian | Empirical Distributions |
| distribution_mixture_normal | Empirical Distributions |
| distribution_nbinom | Empirical Distributions |
| distribution_normal | Empirical Distributions |
| distribution_poisson | Empirical Distributions |
| distribution_student | Empirical Distributions |
| distribution_student_t | Empirical Distributions |
| distribution_t | Empirical Distributions |
| distribution_tweedie | Empirical Distributions |
| distribution_uniform | Empirical Distributions |
-- E --
| effective_sample | Effective Sample Size (ESS) |
| effective_sample.brmsfit | Effective Sample Size (ESS) |
| effective_sample.stanreg | Effective Sample Size (ESS) |
| equivalence_test | Test for Practical Equivalence |
| equivalence_test.brmsfit | Test for Practical Equivalence |
| equivalence_test.data.frame | Test for Practical Equivalence |
| equivalence_test.default | Test for Practical Equivalence |
| equivalence_test.stanreg | Test for Practical Equivalence |
| estimate_density | Density Estimation |
| estimate_density.data.frame | Density Estimation |
| eti | Equal-Tailed Interval (ETI) |
| eti.brmsfit | Equal-Tailed Interval (ETI) |
| eti.get_predicted | Equal-Tailed Interval (ETI) |
| eti.numeric | Equal-Tailed Interval (ETI) |
| eti.stanreg | Equal-Tailed Interval (ETI) |
-- H --
| hdi | Highest Density Interval (HDI) |
| hdi.brmsfit | Highest Density Interval (HDI) |
| hdi.data.frame | Highest Density Interval (HDI) |
| hdi.get_predicted | Highest Density Interval (HDI) |
| hdi.numeric | Highest Density Interval (HDI) |
| hdi.stanreg | Highest Density Interval (HDI) |
-- M --
| map_estimate | Maximum A Posteriori probability estimate (MAP) |
| map_estimate.brmsfit | Maximum A Posteriori probability estimate (MAP) |
| map_estimate.data.frame | Maximum A Posteriori probability estimate (MAP) |
| map_estimate.get_predicted | Maximum A Posteriori probability estimate (MAP) |
| map_estimate.numeric | Maximum A Posteriori probability estimate (MAP) |
| map_estimate.stanreg | Maximum A Posteriori probability estimate (MAP) |
| mcse | Monte-Carlo Standard Error (MCSE) |
| mcse.stanreg | Monte-Carlo Standard Error (MCSE) |
| mediation | Summary of Bayesian multivariate-response mediation-models |
| mediation.brmsfit | Summary of Bayesian multivariate-response mediation-models |
| mediation.stanmvreg | Summary of Bayesian multivariate-response mediation-models |
| model_to_priors | Convert model's posteriors to priors (EXPERIMENTAL) |
-- O --
| overlap | Overlap Coefficient |
-- P --
| pd | Probability of Direction (pd) |
| pd_to_p | Convert between Probability of Direction (pd) and p-value. |
| point_estimate | Point-estimates of posterior distributions |
| point_estimate.BFBayesFactor | Point-estimates of posterior distributions |
| point_estimate.brmsfit | Point-estimates of posterior distributions |
| point_estimate.get_predicted | Point-estimates of posterior distributions |
| point_estimate.numeric | Point-estimates of posterior distributions |
| point_estimate.stanreg | Point-estimates of posterior distributions |
| p_direction | Probability of Direction (pd) |
| p_direction.BFBayesFactor | Probability of Direction (pd) |
| p_direction.brmsfit | Probability of Direction (pd) |
| p_direction.data.frame | Probability of Direction (pd) |
| p_direction.emmGrid | Probability of Direction (pd) |
| p_direction.get_predicted | Probability of Direction (pd) |
| p_direction.MCMCglmm | Probability of Direction (pd) |
| p_direction.numeric | Probability of Direction (pd) |
| p_direction.stanreg | Probability of Direction (pd) |
| p_map | Bayesian p-value based on the density at the Maximum A Posteriori (MAP) |
| p_map.brmsfit | Bayesian p-value based on the density at the Maximum A Posteriori (MAP) |
| p_map.get_predicted | Bayesian p-value based on the density at the Maximum A Posteriori (MAP) |
| p_map.numeric | Bayesian p-value based on the density at the Maximum A Posteriori (MAP) |
| p_map.stanreg | Bayesian p-value based on the density at the Maximum A Posteriori (MAP) |
| p_pointnull | Bayesian p-value based on the density at the Maximum A Posteriori (MAP) |
| p_rope | Probability of being in the ROPE |
| p_rope.brmsfit | Probability of being in the ROPE |
| p_rope.numeric | Probability of being in the ROPE |
| p_rope.stanreg | Probability of being in the ROPE |
| p_significance | Practical Significance (ps) |
| p_significance.brmsfit | Practical Significance (ps) |
| p_significance.get_predicted | Practical Significance (ps) |
| p_significance.numeric | Practical Significance (ps) |
| p_significance.stanreg | Practical Significance (ps) |
| p_to_bf | Convert p-values to (pseudo) Bayes Factors |
| p_to_bf.default | Convert p-values to (pseudo) Bayes Factors |
| p_to_bf.numeric | Convert p-values to (pseudo) Bayes Factors |
| p_to_pd | Convert between Probability of Direction (pd) and p-value. |
-- R --
| reshape_draws | Reshape estimations with multiple iterations (draws) to long format |
| reshape_iterations | Reshape estimations with multiple iterations (draws) to long format |
| rnorm_perfect | Empirical Distributions |
| rope | Region of Practical Equivalence (ROPE) |
| rope.brmsfit | Region of Practical Equivalence (ROPE) |
| rope.numeric | Region of Practical Equivalence (ROPE) |
| rope.stanreg | Region of Practical Equivalence (ROPE) |
| rope_range | Find Default Equivalence (ROPE) Region Bounds |
| rope_range.default | Find Default Equivalence (ROPE) Region Bounds |
-- S --
| sensitivity_to_prior | Sensitivity to Prior |
| sensitivity_to_prior.stanreg | Sensitivity to Prior |
| sexit | Sequential Effect eXistence and sIgnificance Testing (SEXIT) |
| sexit_thresholds | Find Effect Size Thresholds |
| si | Compute Support Intervals |
| si.blavaan | Compute Support Intervals |
| si.brmsfit | Compute Support Intervals |
| si.data.frame | Compute Support Intervals |
| si.emmGrid | Compute Support Intervals |
| si.get_predicted | Compute Support Intervals |
| si.numeric | Compute Support Intervals |
| si.stanreg | Compute Support Intervals |
| simulate_correlation | Data Simulation |
| simulate_difference | Data Simulation |
| simulate_prior | Returns Priors of a Model as Empirical Distributions |
| simulate_simpson | Simpson's paradox dataset simulation |
| simulate_ttest | Data Simulation |
| spi | Shortest Probability Interval (SPI) |
| spi.brmsfit | Shortest Probability Interval (SPI) |
| spi.get_predicted | Shortest Probability Interval (SPI) |
| spi.numeric | Shortest Probability Interval (SPI) |
| spi.stanreg | Shortest Probability Interval (SPI) |
-- U --
| update.bayesfactor_models | Bayes Factors (BF) for model comparison |
-- W --
| weighted_posteriors | Generate posterior distributions weighted across models |
| weighted_posteriors.BFBayesFactor | Generate posterior distributions weighted across models |
| weighted_posteriors.blavaan | Generate posterior distributions weighted across models |
| weighted_posteriors.brmsfit | Generate posterior distributions weighted across models |
| weighted_posteriors.data.frame | Generate posterior distributions weighted across models |
| weighted_posteriors.stanreg | Generate posterior distributions weighted across models |