Estimate parameters from a specified model using bootstrap resampling and estimated maximum likelihood
ps_bootstrap(n.boots = 200, progress.bar = TRUE, start = NULL,
method = "BFGS", control = list(), ...)
Number of bootstrap replicates
Logical, if true will display a progress bar in the console
Vector of starting values, if NULL, will come up with starting values
Method to use for optimization, can be "pseudo-score" for categorical S with nonparametric integration, or any of the methods available in optim. Defaults to "BFGS"
List of control parameters for passed to optim
Arguments passed to optim