  We consider a resampling scheme for parameters estimates in nonlinear
regression models. We provide an estimation procedure which recycles, via
random weighting, the relevant parameters estimates to construct consistent
estimates of the sampling distribution of the various estimates. We establish
the asymptotic normality of the resampled estimates and demonstrate the
applicability of the recycling approach in a small simulation study and via
example.
