On Sep 2, 6:15 pm, Thomas Philips <tkp...@gmail.com> wrote: > I mis-spoke - the variance is infinite when df=2 (the variance is df/ > (df-2),
Yes: the variance is infinite both for df=2 and df=1, and Student's t with df=1 doesn't even have an expectation. I don't see why this would stop you from generating meaningful samples, though. > and you get the Cauchy when df=2. Are you sure about this? All my statistics books are currently hiding in my mother-in-law's attic, several hundred miles away, but wikipedia and mathworld seem to say that df=1 gives you the Cauchy distribution. > I made the mistake because the denominator is equivalent to the > square root of the sample variance of df normal observations, As I'm reading it, the denominator is the square root of the sample variance of *df+1* independent standard normal observations. I agree that the wikipedia description is a bit confusing. It seems that there are uses for Student's t distribution with non-integral degrees of freedom. The Boost library, and the R programming language both allow non-integral degrees of freedom. So (as Robert Kern already suggested), you could drop the test for integrality of df. In fact, you could just drop the tests on df entirely: df <= 0.0 will be picked up in the gammavariate call. -- Mark -- http://mail.python.org/mailman/listinfo/python-list
