Johannes, You are doing what many folks call the parametric bootstrap. The bootstrap that resamples the data is the non-parametric bootstrap. Often it is easier to code by hand, as you have done. If you want access to all the helper functions for the bootstrap, you can use boot() in the boot library and specify sim='parametric'. The details of your random uniform distribution go in the function specified in the ran.gen= argument. Once you've generated the bootstrap samples (parametric or nonparametric), there is no difference in subsequent processing.
Best wishes, Philip Dixon _______________________________________________ R-sig-ecology mailing list R-sig-ecology@r-project.org https://stat.ethz.ch/mailman/listinfo/r-sig-ecology
