Regress+ has this capability because it must be able to assess the goodness-of-fit of an empirical dataset to a putative parent population. It performs that test by means of a parametric bootstrap, a kind of Monte Carlo simulation. It should be apparent that the synthetic sample (histogram) is a very good fit to the theoretical model (solid line).
where Gam (.) is the complete Gamma function.
The curve shown in the figure is the theoretical model. When this dataset is considered to be a Gamma sample with unknown parameters, the maximum-likelihood parameters are found to be as follows:
The differences, from (1, 2, 3), are due to the natural variation inherent in drawing a sample of size 10,000 from this specific parent population.
** Gamma variates are generated using a rejection algorithm. For this example, execution time (on a 266-MHz G3 PowerMac) was about 2.5 seconds, most of which was disk I/O.