NEWS.md
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
argumentdummy
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 transformationsplot_posterior
function can now handle factor transformationsrunjags_estimates_table()
function via the remove_parameters
argumentrunjags_estimates_table()
function can now remove factor spike prior distributionsplot_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
functioninclusion_BF
to deal with over/underflow (Issue #9)ensemble_inference_table()
(Issue #11)ensemble_summary_table
(Issue #7)plot_posterior
fails with only mu & PET samples (Issue #5)