On Tue, May 25, 2010 at 9:20 PM, <josef.pktd@gmail.com> wrote:

On Tue, May 25, 2010 at 10:34 PM, Charles R Harris <charlesr.harris@gmail.com> wrote:

Josef,

This is ticket #896 from two years ago. IIRC, there was some more recent discussion on the list of some of these. Do you know what the current state of these distributions is?

I don't have any information on these and I don't remember any discussion (and a quick search didn't find anything). I never looked at the integer overflow problem, besides reading the ticket.

All 3 distributions are used in scipy.stats and tested for some regular values.

(my not very strong opinion: for consistency with the other distributions, I would go with Robert's approach of rejecting overflow samples. I don't know any application where the truncation would have a significant effect. In scipy.stats I switched to returning floats instead of integers for ppf, because we need inf and nans.)

BTW: If you are fixing things in np.random, then depreciating and renaming pareto as we discussed recently on the list would help reduce some confusion. I don't think we filed a ticket.

OK, but it would help if you did file a ticket. And if you think truncation is the way to go on the #896 could you post a note there also? Chuck