update.BiBMA
can be used to
add an additional model to an existing
"BiBMA"
object by specifying either a null or alternative prior for each parameter and the prior odds of the model (prior_weights
), see thevignette("CustomEnsembles")
vignette,change the prior odds of fitted models by specifying a vector
prior_weights
of the same length as the fitted models,refitting models that failed to converge with updated settings of control parameters,
or changing the convergence criteria and recalculating the ensemble results by specifying new
control
argument and settingrefit_failed == FALSE
.
Usage
# S3 method for class 'BiBMA'
update(
object,
refit_failed = TRUE,
extend_all = FALSE,
prior_effect = NULL,
prior_heterogeneity = NULL,
prior_baseline = NULL,
prior_weights = NULL,
prior_effect_null = NULL,
prior_heterogeneity_null = NULL,
prior_baseline_null = NULL,
study_names = NULL,
chains = NULL,
adapt = NULL,
burnin = NULL,
sample = NULL,
thin = NULL,
autofit = NULL,
parallel = NULL,
autofit_control = NULL,
convergence_checks = NULL,
save = "all",
seed = NULL,
silent = TRUE,
...
)
Arguments
- object
a fitted BiBMA object
- refit_failed
whether failed models should be refitted. Relevant only if new priors or
prior_weights
are not supplied. Defaults toTRUE
.- extend_all
extend sampling in all fitted models based on
"sample_extend"
argument inset_autofit_control()
function. Defaults toFALSE
.- prior_effect
prior distribution for the effect size (
mu
) parameter that will be treated as belonging to the alternative hypothesis. Defaults toNULL
.- prior_heterogeneity
prior distribution for the heterogeneity
tau
parameter that will be treated as belonging to the alternative hypothesis. Defaults toNULL
.- prior_baseline
prior distribution for the intercepts (
pi
) of each study that will be treated as belonging to the alternative hypothesis. Defaults toNULL
.- prior_weights
either a single value specifying prior model weight of a newly specified model using priors argument, or a vector of the same length as already fitted models to update their prior weights.
- prior_effect_null
prior distribution for the effect size (
mu
) parameter that will be treated as belonging to the null hypothesis. Defaults toNULL
.- prior_heterogeneity_null
prior distribution for the heterogeneity
tau
parameter that will be treated as belonging to the null hypothesis. Defaults toNULL
.- prior_baseline_null
prior distribution for the intercepts (
pi
) of each study that will be treated as belonging to the null hypothesis. Defaults toNULL
.- study_names
an optional argument with the names of the studies
- chains
a number of chains of the MCMC algorithm.
- adapt
a number of adaptation iterations of the MCMC algorithm. Defaults to
500
.- burnin
a number of burnin iterations of the MCMC algorithm. Defaults to
2000
.- sample
a number of sampling iterations of the MCMC algorithm. Defaults to
5000
.- thin
a thinning of the chains of the MCMC algorithm. Defaults to
1
.- autofit
whether the model should be fitted until the convergence criteria (specified in
autofit_control
) are satisfied. Defaults toTRUE
.- parallel
whether the individual models should be fitted in parallel. Defaults to
FALSE
. The implementation is not completely stable and might cause a connection error.- autofit_control
allows to pass autofit control settings with the
set_autofit_control()
function. See?set_autofit_control
for options and default settings.- convergence_checks
automatic convergence checks to assess the fitted models, passed with
set_convergence_checks()
function. See?set_convergence_checks
for options and default settings.- save
whether all models posterior distributions should be kept after obtaining a model-averaged result. Defaults to
"all"
which does not remove anything. Set to"min"
to significantly reduce the size of final object, however, some model diagnostics and further manipulation with the object will not be possible.- seed
a seed to be set before model fitting, marginal likelihood computation, and posterior mixing for reproducibility of results. Defaults to
NULL
- no seed is set.- silent
whether all print messages regarding the fitting process should be suppressed. Defaults to
TRUE
. Note thatparallel = TRUE
also suppresses all messages.- ...
additional arguments.
Details
See BiBMA()
for more details.