| mix_posteriors {BayesTools} | R Documentation |
Model-averages posterior distributions based on a list of models, vector of parameters, and a list of indicators of the null or alternative hypothesis models for each parameter.
mix_posteriors(
model_list,
parameters,
is_null_list,
conditional = FALSE,
seed = NULL,
n_samples = 10000
)
model_list |
list of models, each of which contains marginal
likelihood estimated with bridge sampling |
parameters |
vector of parameters names for which inference should be drawn |
is_null_list |
list with entries for each parameter carrying either logical vector of indicators specifying whether the model corresponds to the null or alternative hypothesis (or an integer vector indexing models corresponding to the null hypothesis) |
conditional |
whether prior and posterior model probabilities should
be returned only for the conditional model. Defaults to |
seed |
integer specifying seed for sampling posteriors for
model averaging. Defaults to |
n_samples |
number of samples to be drawn for the model-averaged posterior distribution |
mix_posteriors returns a named list of mixed posterior
distributions (either a vector of matrix).
ensemble_inference BayesTools_ensemble_tables