Tools for Bayesian Analyses

Documentation for package ‘BayesTools’ version 0.4.0

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A B C D E F G H I J K L M P Q R S T U V W

BayesTools

-- A --

add_column	Adds column to BayesTools table
allocation_ref	Random-effect prior specification
as.data.frame.BayesTools_hypothesis_BF	Hypothesis Bayes Factors
as.mcmc.BayesTools_draws_view	JAGS draw geometry and deterministic materialization
as.mcmc.list.BayesTools_draws_view	JAGS draw geometry and deterministic materialization
as_marginal_inference	Model-average marginal posterior distributions and marginal Bayes factors based on BayesTools JAGS model via 'marginal_inference'
as_mixed_posteriors	Export BayesTools JAGS model posterior distribution as model-average posterior distributions via 'mix_posteriors'

-- B --

BayesTools	BayesTools
BayesTools_ensemble_tables	Create BayesTools ensemble summary tables
BayesTools_load_JAGS_module	Load the BayesTools JAGS module
BayesTools_model_tables	Create BayesTools model tables
BF_carrier_drop	Remove the carrier attributes of a Bayes factor
bridgesampling_object	Create a BayesTools marginal-likelihood object

-- C --

ccdf	Creates generics for common statistical functions
ccdf.prior	Elementary prior related functions
cdf	Creates generics for common statistical functions
cdf.prior	Elementary prior related functions
check_bool	Check input
check_char	Check input
check_input	Check input
check_int	Check input
check_list	Check input
check_real	Check input
check_selection_model	Specifies source conditioning in a selection model
compute_inference	Compute posterior probabilities and inclusion Bayes factors
contr.BayesTools	BayesTools Contrast Matrices
contr.independent	BayesTools Contrast Matrices
contr.meandif	BayesTools Contrast Matrices
contr.ordered_cumulative	BayesTools Contrast Matrices
contr.ordered_cumulative_levels	BayesTools Contrast Matrices
contr.orthonormal	BayesTools Contrast Matrices

-- D --

density.prior	Prior density
dmpoint	Multivariate point mass distribution
dpoint	Point mass distribution

-- E --

ensemble_diagnostics_empty_table	Create BayesTools ensemble summary tables
ensemble_diagnostics_table	Create BayesTools ensemble summary tables
ensemble_estimates_empty_table	Create BayesTools ensemble summary tables
ensemble_estimates_table	Create BayesTools ensemble summary tables
ensemble_inference	Compute posterior probabilities and inclusion Bayes factors
ensemble_inference_empty_table	Create BayesTools ensemble summary tables
ensemble_inference_table	Create BayesTools ensemble summary tables
ensemble_summary_empty_table	Create BayesTools ensemble summary tables
ensemble_summary_table	Create BayesTools ensemble summary tables

-- F --

fit_backend_fingerprint	Fingerprint the loaded BayesTools fitting backend
format_BF	Format Bayes factor
format_BF_from_log	Format Bayes factors from natural-log values
format_parameter_names	JAGS parameter-name helpers
formula_add_intercept	Add an Intercept to a Formula

-- G --

geom_prior	Add prior object to a ggplot
geom_prior_list	Add list of prior objects to a plot

-- H --

harrell_davis_quantile	Harrell-Davis quantiles of posterior draws
hypothesis_alias_label	Helpers of hypothesis tables
hypothesis_ast	Versioned hypothesis syntax trees
hypothesis_ast_schema	Versioned hypothesis syntax trees
hypothesis_BF	Hypothesis Bayes Factors
hypothesis_BF.BayesTools_fit	Hypothesis Bayes Factors
hypothesis_BF.default	Hypothesis Bayes Factors
hypothesis_BF_model	Hypothesis Bayes factors of a fitted model
hypothesis_cache_clear	Drop the caches of the hypothesis engine
hypothesis_density_backend	Density backends of fit-level hypothesis Bayes factors
hypothesis_density_backends	Density backends of fit-level hypothesis Bayes factors
hypothesis_linear_target	Compile a hypothesis linear in the levels of one parameter
hypothesis_linear_target_side	Linear form of one side of a hypothesis statement
hypothesis_normalize_level_references	Hypothesis parser helpers
hypothesis_parse	Versioned hypothesis syntax trees
hypothesis_parse_level_reference	Hypothesis parser helpers
hypothesis_parse_point_reference	Hypothesis parser helpers
hypothesis_provider	Hypothesis provider of a fitted model
hypothesis_provider.BayesTools_fit	Hypothesis provider of a fitted model
hypothesis_provider.default	Hypothesis provider of a fitted model
hypothesis_quantities	Available Hypothesis Quantities
hypothesis_quantities.BayesTools_fit	Available Hypothesis Quantities
hypothesis_quantities.default	Available Hypothesis Quantities
hypothesis_render	Versioned hypothesis syntax trees
hypothesis_resolve	Versioned hypothesis syntax trees
hypothesis_rewrite	Versioned hypothesis syntax trees
hypothesis_stop	Stop with a refusal of a hypothesis
hypothesis_symbols	Versioned hypothesis syntax trees
hypothesis_unique_named_warnings	Helpers of hypothesis tables

-- I --

inclusion_BF	Compute inclusion Bayes factors
interpret	Interpret ensemble inference and estimates
interpret2	Interpret ensemble inference and estimates
interpret_records	Normalize structured interpretation sources
interpret_tables	Normalize structured interpretation sources
invert_BF_bound_operator	Invert the orientation of Bayes factor bound operators
is.prior	Reports whether x is a a prior object
is.prior.discrete	Reports whether x is a a prior object
is.prior.factor	Reports whether x is a a prior object
is.prior.independent	Reports whether x is a a prior object
is.prior.meandif	Reports whether x is a a prior object
is.prior.mixture	Reports whether x is a a prior object
is.prior.none	Reports whether x is a a prior object
is.prior.ordered	Reports whether x is a a prior object
is.prior.orthonormal	Reports whether x is a a prior object
is.prior.PEESE	Reports whether x is a a prior object
is.prior.PET	Reports whether x is a a prior object
is.prior.point	Reports whether x is a a prior object
is.prior.simple	Reports whether x is a a prior object
is.prior.simplex	Reports whether x is a a prior object
is.prior.spike_and_slab	Reports whether x is a a prior object
is.prior.treatment	Reports whether x is a a prior object
is.prior.vector	Reports whether x is a a prior object
is.prior.weightfunction	Reports whether x is a a prior object
is_prior_bias	Reports whether x is a composed publication-bias prior
is_prior_phacking	Reports whether x is a p-hacking prior

-- J --

JAGS_add_priors	Add 'JAGS' prior
JAGS_bridgesampling	Compute marginal likelihood of a 'JAGS' model
JAGS_bridgesampling_posterior	Prepare 'JAGS' posterior for 'bridgesampling'
JAGS_check_and_list	Check and list 'JAGS' fitting settings
JAGS_check_and_list_autofit_settings	Check and list 'JAGS' fitting settings
JAGS_check_and_list_fit_settings	Check and list 'JAGS' fitting settings
JAGS_check_convergence	Assess convergence of a runjags model
JAGS_deterministic_evaluator	Generated deterministic nodes
JAGS_deterministic_nodes	Generated deterministic nodes
JAGS_diagnostics	Plot diagnostics of a 'JAGS' model
JAGS_diagnostics_autocorrelation	Plot diagnostics of a 'JAGS' model
JAGS_diagnostics_density	Plot diagnostics of a 'JAGS' model
JAGS_diagnostics_trace	Plot diagnostics of a 'JAGS' model
JAGS_draw_geometry	JAGS draw geometry and deterministic materialization
JAGS_draw_geometry_schema	JAGS draw geometry and deterministic materialization
JAGS_estimates_empty_table	Create BayesTools model tables
JAGS_estimates_table	Create BayesTools model tables
JAGS_evaluate_deterministic	Generated deterministic nodes
JAGS_evaluate_formula	Evaluate JAGS formula using posterior samples
JAGS_extend	Fits a 'JAGS' model
JAGS_fit	Fits a 'JAGS' model
JAGS_fit_contract	JAGS formula name map and fitted-object contract
JAGS_fit_contract_schema	JAGS formula name map and fitted-object contract
JAGS_formula	Create JAGS formula syntax and data object
JAGS_formula_coefficient_route	Original-scale route of a formula coefficient
JAGS_formula_coefficient_transform	Formula coefficient transformations and induced prior densities
JAGS_formula_coefficient_transform_schema	Formula coefficient transformations and induced prior densities
JAGS_formula_coordinate_dependencies	Fitted-formula coordinate dependencies
JAGS_formula_design	Extract Fitted JAGS Formula Design Metadata
JAGS_formula_draws	Formula designs for draws without a fit
JAGS_formula_internal_coordinate_priors	Formula coefficient transformations and induced prior densities
JAGS_formula_name_map	JAGS formula name map and fitted-object contract
JAGS_formula_point_finalize	Finalize formula designs built outside JAGS_fit()
JAGS_formula_predictor_basis	Exact fitted-formula predictor update basis
JAGS_formula_prior_density	Formula coefficient transformations and induced prior densities
JAGS_formula_random_marginal_covariance	Compile formula random effects as marginal JAGS covariance nodes
JAGS_formula_scale_finalize	Finalize formula designs built outside JAGS_fit()
JAGS_get_inits	Create initial values for 'JAGS' model
JAGS_indexed_parameter_columns	JAGS parameter-name helpers
JAGS_indexed_parameter_matrix	JAGS parameter-name helpers
JAGS_indexed_parameter_vector	JAGS parameter-name helpers
JAGS_inference_empty_table	Create BayesTools model tables
JAGS_inference_table	Create BayesTools model tables
JAGS_lkj_corr_cholesky	Generate a JAGS LKJ-Cholesky correlation module
JAGS_marglik_parameters	Extract parameters for 'JAGS' priors
JAGS_marglik_parameters_formula	Extract parameters for 'JAGS' priors
JAGS_marglik_priors	Compute marginal likelihood for 'JAGS' priors
JAGS_marglik_priors_formula	Compute marginal likelihood for 'JAGS' priors
JAGS_marglik_priors_rows	Compute marginal likelihood for 'JAGS' priors
JAGS_marglik_priors_rows_evaluator	Compute marginal likelihood for 'JAGS' priors
JAGS_materialize_draws	JAGS draw geometry and deterministic materialization
JAGS_ordered_density_kernel	Batched numerical density kernel for ordered primitives
JAGS_ordered_parameter_spec	Fitted ordered parameter specifications
JAGS_package_builds	Build fingerprints of loaded packages
JAGS_parameter_names	JAGS parameter-name helpers
JAGS_predict_formula	Formula prediction with explicit random-effect target
JAGS_regex_escape	JAGS parameter-name helpers
JAGS_runtime_cluster	Worker clusters with the running package builds
JAGS_runtime_cluster_stop	Worker clusters with the running package builds
JAGS_summary_table	Create BayesTools model tables
JAGS_to_monitor	Create list of monitored parameters for 'JAGS' model
JAGS_validate_fit_contract	JAGS formula name map and fitted-object contract
JAGS_with_draws	JAGS draw geometry and deterministic materialization

-- K --

kitchen_rolls

Kitchen Rolls data from Wagenmakers et al. (2015) replication study.

-- L --

lines.prior	Add prior object to a plot
lines_prior_list	Add list of prior objects to a plot
lpdf	Creates generics for common statistical functions
lpdf.prior	Elementary prior related functions

-- M --

marginal_estimates_table	Create BayesTools ensemble summary tables
marginal_inference	Model-average marginal posterior distributions and marginal Bayes factors
marginal_posterior	Model-average marginal posterior distributions
mccdf	Creates generics for common statistical functions
mccdf.prior	Elementary prior related functions
mcdf	Creates generics for common statistical functions
mcdf.prior	Elementary prior related functions
mdone.sided	Weight functions
mdone.sided_fixed	Weight functions
mdtwo.sided	Weight functions
mdtwo.sided_fixed	Weight functions
mean.prior	Prior mean
mix_posteriors	Model-average posterior distributions
mlpdf	Creates generics for common statistical functions
mlpdf.prior	Elementary prior related functions
models_inference	Compute posterior probabilities and inclusion Bayes factors
model_summary_empty_table	Create BayesTools model tables
model_summary_table	Create BayesTools model tables
mpdf	Creates generics for common statistical functions
mpdf.prior	Elementary prior related functions
mpoint	Multivariate point mass distribution
mpone.sided	Weight functions
mpone.sided_fixed	Weight functions
mptwo.sided	Weight functions
mptwo.sided_fixed	Weight functions
mqone.sided	Weight functions
mqone.sided_fixed	Weight functions
mqtwo.sided	Weight functions
mqtwo.sided_fixed	Weight functions
mquant	Creates generics for common statistical functions
mquant.prior	Elementary prior related functions

-- P --

parameter_catalog	Semantic parameter catalogs and deferred draw extraction
parameter_catalog.BayesTools_fit	Semantic parameter catalogs and deferred draw extraction
parameter_catalog_extend	Semantic parameter catalogs and deferred draw extraction
parameter_catalog_resolve	Semantic parameter catalogs and deferred draw extraction
parameter_catalog_schema	Semantic parameter catalogs and deferred draw extraction
parameter_coordinates	Fitted parameter map and coordinate view
parameter_coordinates.BayesTools_fit	Fitted parameter map and coordinate view
parameter_coordinates_schema	Fitted parameter map and coordinate view
parameter_draws	Semantic parameter catalogs and deferred draw extraction
parameter_draws.BayesTools_fit	Semantic parameter catalogs and deferred draw extraction
parameter_gate_states	Per-draw gate and point states of a catalog quantity
parameter_labels	Parameter labels
parameter_map	Fitted parameter map and coordinate view
parameter_map.BayesTools_fit	Fitted parameter map and coordinate view
parameter_map_cache	Cache a value derived from a fitted parameter map
parameter_map_schema	Fitted parameter map and coordinate view
parameter_mixed_posterior	Mixed posterior of one catalog quantity
parameter_names	JAGS parameter-name helpers
parameter_prior_density	Semantic parameter catalogs and deferred draw extraction
parameter_prior_density.BayesTools_fit	Semantic parameter catalogs and deferred draw extraction
parameter_source	External JAGS parameter source
parameter_transform	Semantic parameter catalogs and deferred draw extraction
parameter_transform_forward	Semantic parameter catalogs and deferred draw extraction
parameter_transform_inverse	Semantic parameter catalogs and deferred draw extraction
parameter_transform_jacobian	Semantic parameter catalogs and deferred draw extraction
pdf	Creates generics for common statistical functions
pdf.prior	Elementary prior related functions
phack_alpha_from_pi_null	P-hacking calibration helpers
phack_backend_constants	P-hacking calibration helpers
phack_pi_null	P-hacking calibration helpers
plot.prior	Plots a prior object
plot.prior_linear_density	Plot a prior linear density
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_transformed_prior	Plot Transformed Prior Densities
pmpoint	Multivariate point mass distribution
point	Point mass distribution
posterior_atoms_free	Whether posterior draws are declared atom-free
posterior_atom_attribute	Declare posterior point-mass metadata
posterior_density_attribute	Posterior density and ordinate attributes
posterior_density_method_match	Posterior density method helpers
posterior_density_method_uses_precomputed	Posterior density method helpers
posterior_fitted_linear_weights	Metadata checks of the linear targets of posterior draws
posterior_formula_measure_check	Metadata checks of the linear targets of posterior draws
posterior_linear_weight_space	Metadata checks of the linear targets of posterior draws
posterior_log_ordinate_attribute	Posterior ordinate attributes from log heights
posterior_measure_check	Check that a measure of posterior draws is available
posterior_metadata	Metadata of BayesTools posterior draws
posterior_metadata<-	Metadata of BayesTools posterior draws
posterior_ordinate_append	Posterior density and ordinate attributes
posterior_ordinate_attribute	Posterior density and ordinate attributes
posterior_ordinate_has_value	Posterior density and ordinate attributes
posterior_ordinate_supports_bf	Posterior density and ordinate attributes
posterior_support_attribute	Posterior support metadata
posterior_transform	Transform posterior draws with their metadata
ppoint	Point mass distribution
print.BayesTools_draws_view	JAGS draw geometry and deterministic materialization
print.BayesTools_table	Print a BayesTools table
print.prior	Prints a prior object
print.selection_model	Specifies source conditioning in a selection model
prior	Creates a prior distribution
prior_bias	Creates a composed publication-bias prior
prior_density_has_provenance	Whether a prior density has deterministic provenance
prior_density_ordinate	Classify a prior-density ordinate
prior_factor	Creates a prior distribution for factors
prior_factor_levels	Levels of a factor prior distribution
prior_functions	Elementary prior related functions
prior_functions_methods	Creates generics for common statistical functions
prior_informed	Creates an informed prior distribution based on research
prior_informed_medicine_names	Names of medical subfields from the Cochrane database of systematic reviews
prior_lkj	Random-effect prior specification
prior_mixture	Creates a mixture of prior distributions
prior_none	Creates a prior distribution
prior_ordered	Creates a prior distribution for ordered factor effects
prior_ordered_total_name	Name of the total node of an ordered prior
prior_ordinate_status	Point-hypothesis eligibility of prior ordinates
prior_PEESE	Creates a prior distribution for PET or PEESE models
prior_PET	Creates a prior distribution for PET or PEESE models
prior_phacking	Creates a prior distribution for a p-hacking selection kernel
prior_PP	Creates a prior distribution for PET or PEESE models
prior_random	Random-effect prior specification
prior_spike_and_slab	Creates a spike and slab prior distribution
prior_weightfunction	Creates a prior distribution for a weight function

-- Q --

qmpoint	Multivariate point mass distribution
qpoint	Point mass distribution
quant	Creates generics for common statistical functions
quant.prior	Elementary prior related functions

-- R --

random_block	Random-effect prior specification
random_covariance	Random-effect prior specification
random_effects_compile	Random-effect compilation policy
random_effects_correlation_draws	Scalar-structured random-effect correlation draws
random_effects_dependency_matrix	Structural row dependencies of formula random effects
random_effects_formula	Normalize random-effect formula input
random_effects_level_roles	Grouping-level roles of formula random effects
random_effects_marginal_diagonal_factor	Diagonal-plus-factor random-effect marginal representation
random_effects_marginal_factor_diagonal	Random-effect marginal covariance diagonals from factor states
random_effects_marginal_factor_product	Multiply random-effect marginal covariance factors by row vectors
random_effects_marginal_factor_states	Random-effect marginal covariance factor states
random_effects_marginal_factor_vcov	Materialize random-effect marginal covariance factors
random_effects_marginal_update_grid	Random-effect marginal covariance update grid
random_effects_marginal_update_plan	Random-effect marginal covariance update plan
random_effects_marginal_variance_factors	Random-effect marginal variance factors
random_effects_marginal_vcov	Random-effect marginal variance-covariance samples
random_effects_source_roles	Structural source roles of formula random effects
random_effects_summary_posterior	Extract random-effect summary posterior distributions
random_group_component_names	Grouping variables and group keys of a compiled random-effect term
random_group_covariance	Known group covariance for random effects
random_group_prediction_keys	Grouping variables and group keys of a compiled random-effect term
random_monitor	Random-effect prior specification
random_new_levels	Random-effect prior specification
random_sd_source	External JAGS parameter source
random_variance_allocation	Random-effect prior specification
range.prior	Prior range
register_hypothesis_density_backend	Density backends of fit-level hypothesis Bayes factors
remove_column	Removes column to BayesTools table
rmpoint	Multivariate point mass distribution
rng	Creates generics for common statistical functions
rng.prior	Elementary prior related functions
rone.sided	Weight functions
rone.sided_fixed	Weight functions
rpoint	Point mass distribution
rtwo.sided	Weight functions
rtwo.sided_fixed	Weight functions
runjags_estimates_empty_table	Create BayesTools model tables
runjags_estimates_table	Create BayesTools model tables
runjags_inference_empty_table	Create BayesTools model tables
runjags_inference_table	Create BayesTools model tables

-- S --

Savage_Dickey_BF	Compute Savage-Dickey inclusion Bayes factors
sd	Creates generic for sd function
sd.prior	Prior sd
selection_backend_spec	Compile selection priors for backend consumers
selection_context_subset_observations	Selection context helpers
selection_context_subset_rows	Selection context helpers
selection_context_validate	Selection context helpers
selection_event_support	Check Gaussian selection-event support
selection_model	Specifies source conditioning in a selection model
selection_model_spec	Specifies source conditioning in a selection model
selection_native_kernel_args	Selection context helpers
selection_native_static_args	Selection context helpers
selection_qmc_design	Fixed randomized quasi-Monte Carlo design
selection_row_arg	Selection context helpers
simplify_as_mixed_posterior_bias	Scalar PET, PEESE or omega posterior from a bias mixed posterior
stan_estimates_table	Create BayesTools model tables

-- T --

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
transform_prior_samples	Transform prior samples to original scale
transform_scale_samples	Transform standardized posterior samples back to original scale

-- U --

unregister_hypothesis_density_backend	Density backends of fit-level hypothesis Bayes factors
update.BayesTools_table	Updates BayesTools table

-- V --

var	Creates generic for var function
var.prior	Prior var

-- W --

weightfunctions	Weight functions
weightfunctions_mapping	Create coefficient mapping between multiple weightfunctions
wf_cumulative	Creates a prior distribution for a weight function
wf_fixed	Creates a prior distribution for a weight function
wf_independent	Creates a prior distribution for a weight function