This [EXPERIMENTAL] function combines several sampling tricks to compute a version of an importance sample (based on flat priors) for the parameters.
pop_pred_samp(object, n = 1000, n_imp = n * 10, return_wts = FALSE,
impsamp = FALSE, PDify = FALSE, PDmethod = NULL, tol = 1e-06,
return_all = FALSE, rmvnorm_method = c("mvtnorm", "MASS"),
fix_params = NULL)a fitted mle2 object
number of samples to return
number of total samples from which to draw, if doing importance sampling
return a column giving the weights of the samples, for use in weighted summaries?
subsample values (with replacement) based on their weights?
use Gill and King generalized-inverse procedure to correct non-positive-definite variance-covariance matrix if necessary?
method for fixing non-positive-definite covariance matrices
tolerance for detecting small eigenvalues
return a matrix including all values, and weights (rather than taking a sample)
package to use for generating MVN samples
parameters to fix (in addition to parameters that were fixed during estimation)
Gill, Jeff, and Gary King. "What to Do When Your Hessian Is Not Invertible: Alternatives to Model Respecification in Nonlinear Estimation." Sociological Methods & Research 33, no. 1 (2004): 54-87. Lande, Russ and Steinar Engen and Bernt-Erik Saether, Stochastic Population Dynamics in Ecology and Conservation. Oxford University Press, 2003.