BayesTools0.2.23 package

Tools for Bayesian Analyses

add_column

Adds column to BayesTools table

as_marginal_inference

Model-average marginal posterior distributions and marginal Bayes fact...

as_mixed_posteriors

Export BayesTools JAGS model posterior distribution as model-average p...

BayesTools_ensemble_tables

Create BayesTools ensemble summary tables

BayesTools_model_tables

Create BayesTools model tables

BayesTools

BayesTools

bridgesampling_object

Create a 'bridgesampling' object

check_input

Check input

contr.BayesTools

BayesTools Contrast Matrices

density.prior

Prior density

ensemble_inference

Compute posterior probabilities and inclusion Bayes factors

format_BF

Format Bayes factor

geom_prior_list

Add list of prior objects to a plot

geom_prior

Add prior object to a ggplot

inclusion_BF

Compute inclusion Bayes factors

interpret

Interpret ensemble inference and estimates

is.prior

Reports whether x is a a prior object

JAGS_add_priors

Add 'JAGS' prior

JAGS_bridgesampling_posterior

Prepare 'JAGS' posterior for 'bridgesampling'

JAGS_bridgesampling

Compute marginal likelihood of a 'JAGS' model

JAGS_check_and_list

Check and list 'JAGS' fitting settings

JAGS_check_convergence

Assess convergence of a runjags model

JAGS_diagnostics

Plot diagnostics of a 'JAGS' model

JAGS_evaluate_formula

Evaluate JAGS formula using posterior samples

JAGS_fit

Fits a 'JAGS' model

JAGS_formula

Create JAGS formula syntax and data object

JAGS_get_inits

Create initial values for 'JAGS' model

JAGS_marglik_parameters

Extract parameters for 'JAGS' priors

JAGS_marglik_priors

Compute marginal likelihood for 'JAGS' priors

JAGS_to_monitor

Create list of monitored parameters for 'JAGS' model

lines_prior_list

Add list of prior objects to a plot

lines.prior

Add prior object to a plot

marginal_inference

Model-average marginal posterior distributions and marginal Bayes fact...

marginal_posterior

Model-average marginal posterior distributions

mean.prior

Prior mean

mix_posteriors

Model-average posterior distributions

mpoint

Multivariate point mass distribution

parameter_names

Clean parameter names from JAGS

plot_marginal

Plot samples from the marginal posterior distributions

plot_models

Plot estimates from models

plot_posterior

Plot samples from the mixed posterior distributions

plot_prior_list

Plot a list of prior distributions

plot.prior

Plots a prior object

point

Point mass distribution

print.BayesTools_table

Print a BayesTools table

print.prior

Prints a prior object

prior_factor

Creates a prior distribution for factors

prior_functions_methods

Creates generics for common statistical functions

prior_functions

Elementary prior related functions

prior_informed_medicine_names

Names of medical subfields from the Cochrane database of systematic re...

prior_informed

Creates an informed prior distribution based on research

prior_mixture

Creates a mixture of prior distributions

prior_PP

Creates a prior distribution for PET or PEESE models

prior_spike_and_slab

Creates a spike and slab prior distribution

prior_weightfunction

Creates a prior distribution for a weight function

prior

Creates a prior distribution

range.prior

Prior range

remove_column

Removes column to BayesTools table

Savage_Dickey_BF

Compute Savage-Dickey inclusion Bayes factors

sd.prior

Prior sd

sd

Creates generic for sd function

transform_factor_samples

Transform factor posterior samples into differences from the mean

transform_meandif_samples

Transform meandif posterior samples into differences from the mean

transform_orthonormal_samples

Transform orthonomal posterior samples into differences from the mean

update.BayesTools_table

Updates BayesTools table

var.prior

Prior var

var

Creates generic for var function

weightfunctions_mapping

Create coefficient mapping between multiple weightfunctions

weightfunctions

Weight functions

Provides tools for conducting Bayesian analyses and Bayesian model averaging (Kass and Raftery, 1995, <doi:10.1080/01621459.1995.10476572>, Hoeting et al., 1999, <doi:10.1214/ss/1009212519>). The package contains functions for creating a wide range of prior distribution objects, mixing posterior samples from 'JAGS' and 'Stan' models, plotting posterior distributions, and etc... The tools for working with prior distribution span from visualization, generating 'JAGS' and 'bridgesampling' syntax to basic functions such as rng, quantile, and distribution functions.

  • Maintainer: František Bartoš
  • License: GPL-3
  • Last published: 2025-12-08