Controls settings for the autofit process of the MCMC JAGS sampler (specifies termination criteria), and values for the convergence checks.
set_autofit_control(
max_Rhat = 1.05,
min_ESS = 500,
max_error = NULL,
max_SD_error = NULL,
max_time = list(time = 60, unit = "mins"),
sample_extend = 1000,
restarts = 10
)
set_convergence_checks(
max_Rhat = 1.05,
min_ESS = 500,
max_error = NULL,
max_SD_error = NULL,
remove_failed = FALSE,
balance_probability = TRUE
)maximum value of the R-hat diagnostic.
Defaults to 1.05.
minimum estimated sample size.
Defaults to 500.
maximum value of the MCMC error.
Defaults to NULL. Be aware that PEESE publication bias
adjustment can have estimates on different scale than the rest of
the output, resulting in relatively large max MCMC error.
maximum value of the proportion of MCMC error
of the estimated SD of the parameter.
Defaults to NULL.
list with the time and unit specifying the maximum
autofitting process per model. Passed to difftime function
(possible units are "secs", "mins", "hours", "days", "weeks", "years").
Defaults to list(time = 60, unit = "mins").
number of samples to extend the fitting process if
the criteria are not satisfied.
Defaults to 1000.
number of times new initial values should be generated in case a
model fails to initialize. Defaults to 10.
whether models not satisfying the convergence checks should
be removed from the inference. Defaults to FALSE - only a warning is raised.
whether prior model probability should be balanced
across the combinations of models with the same H0/H1 for effect / heterogeneity / bias
in the case of non-convergence. Defaults to TRUE.
set_autofit_control returns a list of autofit control settings
and set_convergence_checks returns a list of convergence checks settings.