prior_mixture()
function for creating a mixture of prior distributionsas_mixed_posteriors()
and as_marginal_inference()
functions for a single JAGS models (with spike and slab or mixture priors) to enabling tables and figures based on the corresponding outputinterpret2()
function for another way of creating textual summaries without the need of inference and samples objectsrunjags_estimates_table()
functionprior_informed()
functionbridge_object()
(fixes: https://github.com/FBartos/BayesTools/issues/28)Na/NaN
tests for check_
functions (fixes: https://github.com/FBartos/BayesTools/issues/26)JAGS_extend()
functionautofit_control
argument in JAGS_fit()
: "restarts"
allows to restart model initialization up to restarts
times in case of failuremodel_summary_table()
in case of prior_none()
contrast = "meandif"
to the prior_factor
function which generates identical prior distributions for difference between the grand mean and each factor levelcontrast = "independent"
to the prior_factor
function which generates independent identical prior distributions for each factor levelremove_column
function for removing columns from BayesTools_table
objects without breaking the attributes etc...remove_parameters
argument to model_summary_table()
point
prior distribution as option to prior_factor
with "meandif"
and "orthonormal"
contrastsmarginal_posterior()
function which creates marginal prior and posterior distributions (according to a model formula specification)Savage_Dickey_BF()
function to compute density ratio Bayes factors based on marginal_posterior
objectsmarginal_inference()
function to combine information from marginal_posterior()
and Savage_Dickey_BF()
marginal_estimates_table()
function to summarize marginal_inference()
objectsplot_marginal()
function to visualize marginal_inference()
objectscontrast = "meandif"
is now the default setting for prior_factor
functiontransform_orthonormal
argument in favor of more general transform_factors
argument dummy
contrast/factor attributes to treatment
for consistency (https://github.com/FBartos/BayesTools/issues/23)check_bool()
, check_char()
, check_real()
, check_int()
, and check_list()
do not throw error if allow_NULL = TRUE
student-t
allowed as a prior distribution name
JAGS_evaluate_formula
runjags_estimates_table()
function can now handle factor transformations plot_posterior
function can now handle factor transformations runjags_estimates_table()
function via the remove_parameters
argumentrunjags_estimates_table()
function can now remove factor spike prior distributionsstan_estimates_summary()
functionJAGS_marglik_parameters_formula
functionrunjags_estimates_table
functionensemble_summary_table
and ensemble_diagnostics_table
function can create table without model componentsJAGS_evaluate_formula
for evaluating formulas based on data and posterior samples (for creating predictions etc) JAGS_parameter_names
for transforming formula names into the JAGS syntaxplot_models
implementation for factor predictorsformat_parameter_names
for cleaning parameter names from JAGSmean
, sd
, and var
functions now return the corresponding values for differences from the mean for the orthonormal prior distributionsrunjags_summary_table
function (previous version crashed under other than default fit_JAGS
settings)runjags_summary_table
functionplot_models
functionadd_column
function for extending BayesTools_table
objects without breaking the attributes etc...BayesTools_table
functions with with formula_prefix
argumentmultiply_by
attribute passed with the prior)plot_posterior
(posterior is now plotted over the prior)inclusion_BF
to deal with over/underflow (Issue #9)ensemble_inference_table()
(Issue #11)ensemble_summary_table
(Issue #7)prior_informed
function for creating informed prior distributions based on the past psychological and medical researchprior.plot
can't plot "spike" with plot_type == "ggplot"
(Issue #6)MCMC error/SD
print names in BayesTools tables (Issue #8)JAGS_bridgesampling_posterior
unable to add a parameter via add_parameters
interpret
function for creating textual summaries based on inference and samples objectsplot_posterior
fails with only mu & PET samples (Issue #5)Add the following code to your website.
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