Package: bayestestR 0.13.2.2

Dominique Makowski

bayestestR: Understand and Describe Bayesian Models and Posterior Distributions

Provides utilities to describe posterior distributions and Bayesian models. It includes point-estimates such as Maximum A Posteriori (MAP), measures of dispersion (Highest Density Interval - HDI; Kruschke, 2015 <doi:10.1016/C2012-0-00477-2>) and indices used for null-hypothesis testing (such as ROPE percentage, pd and Bayes factors). References: Makowski et al. (2021) <doi:10.21105/joss.01541>.

Authors:Dominique Makowski [aut, cre], Daniel Lüdecke [aut], Mattan S. Ben-Shachar [aut], Indrajeet Patil [aut], Michael D. Wilson [aut], Brenton M. Wiernik [aut], Paul-Christian Bürkner [rev], Tristan Mahr [rev], Henrik Singmann [ctb], Quentin F. Gronau [ctb], Sam Crawley [ctb]

bayestestR_0.13.2.2.tar.gz
bayestestR_0.13.2.2.zip(r-4.5)bayestestR_0.13.2.2.zip(r-4.4)bayestestR_0.13.2.2.zip(r-4.3)
bayestestR_0.13.2.2.tgz(r-4.4-any)bayestestR_0.13.2.2.tgz(r-4.3-any)
bayestestR_0.13.2.2.tar.gz(r-4.5-noble)bayestestR_0.13.2.2.tar.gz(r-4.4-noble)
bayestestR_0.13.2.2.tgz(r-4.4-emscripten)bayestestR_0.13.2.2.tgz(r-4.3-emscripten)
bayestestR.pdf |bayestestR.html
bayestestR/json (API)
NEWS

# Install bayestestR in R:
install.packages('bayestestR', repos = c('https://easystats.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/easystats/bayestestr/issues

Datasets:

On CRAN:

bayes-factorsbayesfactorbayesianbayesian-frameworkcredible-intervaleasystatshacktoberfesthdimapposterior-distributionsrope

93 exports 547 stars 9.03 score 2 dependencies 140 dependents

Last updated 28 days agofrom:894626cc315282365678701c6d8a2f7b66606052

Exports:area_under_curveaucbayesfactorbayesfactor_inclusionbayesfactor_modelsbayesfactor_parametersbayesfactor_pointnullbayesfactor_restrictedbayesfactor_ropebayesian_as_frequentistbcaibcibf_inclusionbf_modelsbf_parametersbf_pointnullbf_restrictedbf_ropebic_to_bfcheck_priorcicontr.bayescontr.equalpriorcontr.equalprior_deviationscontr.equalprior_pairscontr.orthonormconvert_bayesian_as_frequentistconvert_p_to_pdconvert_pd_to_pcwidensity_atdescribe_posteriordescribe_priordiagnostic_drawsdiagnostic_posteriordistributiondistribution_betadistribution_binomdistribution_binomialdistribution_cauchydistribution_chisqdistribution_chisquareddistribution_customdistribution_gammadistribution_gaussiandistribution_mixture_normaldistribution_nbinomdistribution_normaldistribution_poissondistribution_studentdistribution_student_tdistribution_tdistribution_tweediedistribution_uniformeffective_sampleequivalence_testestimate_densityetihdimap_estimatemcsemediationmodel_to_priorsoverlapp_directionp_mapp_pointnullp_ropep_significancep_to_bfp_to_pdpdpd_to_ppoint_estimateprint_htmlprint_mdreshape_drawsreshape_iterationsrnorm_perfectroperope_rangesensitivity_to_priorsexitsexit_thresholdssisimulate_correlationsimulate_differencesimulate_priorsimulate_simpsonsimulate_ttestspiunupdateweighted_posteriors

Dependencies:datawizardinsight

Overview of Vignettes

Rendered fromoverview_of_vignettes.Rmdusingknitr::rmarkdownon May 24 2024.

Last update: 2022-04-20
Started: 2022-04-20

Readme and manuals

Help Manual

Help pageTopics
Area under the Curve (AUC)area_under_curve auc
Coerce to a Data Frameas.data.frame.density
Convert to Numericas.numeric.map_estimate as.numeric.p_direction as.numeric.p_map as.numeric.p_significance
Bayes Factors (BF)bayesfactor
Inclusion Bayes Factors for testing predictors across Bayesian modelsbayesfactor_inclusion bf_inclusion
Bayes Factors (BF) for model comparisonas.matrix.bayesfactor_models bayesfactor_models bayesfactor_models.default bf_models update.bayesfactor_models
Bayes Factors (BF) for a Single Parameterbayesfactor_parameters bayesfactor_parameters.blavaan bayesfactor_parameters.brmsfit bayesfactor_parameters.data.frame bayesfactor_parameters.numeric bayesfactor_parameters.stanreg bayesfactor_pointnull bayesfactor_rope bf_parameters bf_pointnull bf_rope
Bayes Factors (BF) for Order Restricted Modelsas.logical.bayesfactor_restricted bayesfactor_restricted bayesfactor_restricted.blavaan bayesfactor_restricted.brmsfit bayesfactor_restricted.emmGrid bayesfactor_restricted.stanreg bf_restricted
Bias Corrected and Accelerated Interval (BCa)bcai bci bci.BFBayesFactor bci.brmsfit bci.data.frame bci.emmGrid bci.get_predicted bci.MCMCglmm bci.numeric bci.sim bci.sim.merMod bci.stanreg
Convert BIC indices to Bayes Factors via the BIC-approximation method.bic_to_bf
Check if Prior is Informativecheck_prior
Confidence/Credible/Compatibility Interval (CI)ci ci.BFBayesFactor ci.brmsfit ci.data.frame ci.MCMCglmm ci.numeric ci.sim ci.sim.merMod ci.stanreg
Contrast Matrices for Equal Marginal Priors in Bayesian Estimationcontr.bayes contr.equalprior contr.equalprior_deviations contr.equalprior_pairs contr.orthonorm
Convert (refit) a Bayesian model to frequentistbayesian_as_frequentist convert_bayesian_as_frequentist
Curvewise Intervals (CWI)cwi cwi.data.frame
Density Probability at a Given Valuedensity_at
Describe Posterior Distributionsdescribe_posterior describe_posterior.brmsfit describe_posterior.numeric describe_posterior.stanreg
Describe Priorsdescribe_prior describe_prior.brmsfit
Diagnostic values for each iterationdiagnostic_draws
Posteriors Sampling Diagnosticdiagnostic_posterior diagnostic_posterior.brmsfit diagnostic_posterior.default diagnostic_posterior.stanreg
Moral Disgust Judgmentdisgust
Empirical Distributionsdistribution distribution_beta distribution_binom distribution_binomial distribution_cauchy distribution_chisq distribution_chisquared distribution_custom distribution_gamma distribution_gaussian distribution_mixture_normal distribution_nbinom distribution_normal distribution_poisson distribution_student distribution_student_t distribution_t distribution_tweedie distribution_uniform rnorm_perfect
Effective Sample Size (ESS)effective_sample effective_sample.brmsfit effective_sample.stanreg
Test for Practical Equivalenceequivalence_test equivalence_test.brmsfit equivalence_test.data.frame equivalence_test.default equivalence_test.stanreg
Density Estimationestimate_density estimate_density.data.frame
Equal-Tailed Interval (ETI)eti eti.brmsfit eti.get_predicted eti.numeric eti.stanreg
Highest Density Interval (HDI)hdi hdi.brmsfit hdi.data.frame hdi.get_predicted hdi.numeric hdi.stanreg
Maximum A Posteriori probability estimate (MAP)map_estimate map_estimate.brmsfit map_estimate.data.frame map_estimate.get_predicted map_estimate.numeric map_estimate.stanreg
Monte-Carlo Standard Error (MCSE)mcse mcse.stanreg
Summary of Bayesian multivariate-response mediation-modelsmediation mediation.brmsfit mediation.stanmvreg
Convert model's posteriors to priors (EXPERIMENTAL)model_to_priors
Overlap Coefficientoverlap
Probability of Direction (pd)pd p_direction p_direction.BFBayesFactor p_direction.brmsfit p_direction.data.frame p_direction.emmGrid p_direction.get_predicted p_direction.MCMCglmm p_direction.numeric p_direction.stanreg
Bayesian p-value based on the density at the Maximum A Posteriori (MAP)p_map p_map.brmsfit p_map.get_predicted p_map.numeric p_map.stanreg p_pointnull
Probability of being in the ROPEp_rope p_rope.brmsfit p_rope.numeric p_rope.stanreg
Practical Significance (ps)p_significance p_significance.brmsfit p_significance.get_predicted p_significance.numeric p_significance.stanreg
Convert p-values to (pseudo) Bayes Factorsp_to_bf p_to_bf.default p_to_bf.numeric
Convert between Probability of Direction (pd) and p-value.convert_pd_to_p convert_p_to_pd pd_to_p p_to_pd
Point-estimates of posterior distributionspoint_estimate point_estimate.BFBayesFactor point_estimate.brmsfit point_estimate.get_predicted point_estimate.numeric point_estimate.stanreg
Reshape estimations with multiple iterations (draws) to long formatreshape_draws reshape_iterations
Region of Practical Equivalence (ROPE)rope rope.brmsfit rope.numeric rope.stanreg
Find Default Equivalence (ROPE) Region Boundsrope_range rope_range.default
Sensitivity to Priorsensitivity_to_prior sensitivity_to_prior.stanreg
Sequential Effect eXistence and sIgnificance Testing (SEXIT)sexit
Find Effect Size Thresholdssexit_thresholds
Compute Support Intervalssi si.blavaan si.brmsfit si.data.frame si.emmGrid si.get_predicted si.numeric si.stanreg
Data Simulationsimulate_correlation simulate_difference simulate_ttest
Returns Priors of a Model as Empirical Distributionssimulate_prior
Simpson's paradox dataset simulationsimulate_simpson
Shortest Probability Interval (SPI)spi spi.brmsfit spi.get_predicted spi.numeric spi.stanreg
Generate posterior distributions weighted across modelsweighted_posteriors weighted_posteriors.BFBayesFactor weighted_posteriors.blavaan weighted_posteriors.brmsfit weighted_posteriors.data.frame weighted_posteriors.stanreg