A convenient wrapper function (
simulate) to simulate data (and process error) from the likelihood function.
simulate(object, ...) # S4 method for Assessment simulate( object, nsim = 1, seed = NULL, process_error = FALSE, refit = FALSE, cores = 1, ... ) # S4 method for RCModel simulate( object, nsim = 1, seed = NULL, process_error = FALSE, refit = FALSE, cores = 1, ... )
An object of class Assessment or RCModel containing the fitted model.
Number of simulations
Used for the random number generator
Logical, indicates if process error is re-sampled in the simulation.
Logical, whether to re-fit the model for each simulated dataset.
The number of CPUs for parallel processing for model re-fitting if
refit = TRUE.
A sim-class object returning the original data, simulated data, original parameters, parameters estimated from simulated data, and process error used to simulate data. then a nested list of model output (`opt`, `SD`, and `report`).
Process error, e.g., recruitment deviations, will be re-sampled in the simulation.