Controls settings for the autofit process of the MCMC JAGS sampler (specifies termination criteria), and values for the convergence checks.
Usage
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,
max_extend = 10
)
set_convergence_checks(
max_Rhat = 1.05,
min_ESS = 500,
max_error = NULL,
max_SD_error = NULL,
remove_failed = FALSE,
balance_probability = TRUE
)Arguments
- max_Rhat
maximum value of the R-hat diagnostic. Defaults to
1.05.- min_ESS
minimum estimated sample size. Defaults to
500.- max_error
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.- max_SD_error
maximum value of the proportion of MCMC error of the estimated SD of the parameter. Defaults to
NULL.- max_time
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 tolist(time = 60, unit = "mins").- sample_extend
number of samples to extend the fitting process if the criteria are not satisfied. Defaults to
1000.- restarts
number of times new initial values should be generated in case a model fails to initialize. Defaults to
10.- max_extend
number of times after which the automatic fitting function is stopped.
- remove_failed
whether models not satisfying the convergence checks should be removed from the inference. Defaults to
FALSE- only a warning is raised.- balance_probability
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.
Value
set_autofit_control returns a list of autofit control settings
and set_convergence_checks returns a list of convergence checks settings.