Some ideas for the probability module:
- hyperparameters - random matrices - stochastic processes (through indexed random variables) On Tuesday, 23 January 2018 12:03:33 UTC+1, Leonid Kovalev wrote: > > There is a discussion at https://github.com/sympy/sympy/pull/13943 but no > separate issue (yet). > > On Jan 23, 2018 5:27 AM, "Shilpa Sangappa" <shilpa....@gmail.com > <javascript:>> wrote: > >> Thanks Leonid, for pointing me to this issue. I will start looking into >> it. >> What is the issue id? >> >> With Regards, >> Shilpa. >> >> P.S.: I didn't get a notification of your reply to my e-mail. Is there >> any settings that I need to do? >> >> On Tuesday, January 23, 2018 at 12:04:50 AM UTC+5:30, Leonid Kovalev >> wrote: >>> >>> Thanks for your interest. An issue that recently came up in the >>> Probability module is sampling from a Poisson distribution >>> <https://en.wikipedia.org/wiki/Poisson_distribution>. It used to not >>> work at all, and now it does but the algorithm is not efficient when the >>> parameter lamda is large. For example: >>> >>> from sympy.stats import * >>> sample(Poisson('x', 1000)) >>> >>> can take a while to return. >>> >>> Usually one can sample by generating a Uniform(0, 1) random number u, >>> and then apply the inverse of the cumulative distribution function (CDF) to >>> u. But there isn't a formula for the inverse of the of a Poisson random >>> variable. The current algorithm >>> <https://github.com/sympy/sympy/blob/master/sympy/stats/drv_types.py#L31> >>> simply >>> goes over all integers looking for the first one where CDF(n) >= u. There >>> ought to be a better way of doing this. >>> >>> The first idea that comes to mind is to make giant steps (in power of 2) >>> until CDF(n) >= u is reached, and then refine by bisection. But perhaps >>> it's better to do research first, there is probably an algorithm out there >>> that we can use. Maybe R has it? https://www.r-project.org/ >>> >>> >>> >>> >> -- >> You received this message because you are subscribed to the Google Groups >> "sympy" group. >> To unsubscribe from this group and stop receiving emails from it, send an >> email to sympy+un...@googlegroups.com <javascript:>. >> To post to this group, send email to sy...@googlegroups.com <javascript:> >> . >> Visit this group at https://groups.google.com/group/sympy. >> To view this discussion on the web visit >> https://groups.google.com/d/msgid/sympy/0cb65d20-5126-4387-8aa4-f2e5ec1b82cc%40googlegroups.com >> >> <https://groups.google.com/d/msgid/sympy/0cb65d20-5126-4387-8aa4-f2e5ec1b82cc%40googlegroups.com?utm_medium=email&utm_source=footer> >> . >> For more options, visit https://groups.google.com/d/optout. >> > -- You received this message because you are subscribed to the Google Groups "sympy" group. To unsubscribe from this group and stop receiving emails from it, send an email to sympy+unsubscr...@googlegroups.com. To post to this group, send email to sympy@googlegroups.com. Visit this group at https://groups.google.com/group/sympy. To view this discussion on the web visit https://groups.google.com/d/msgid/sympy/f50bd982-1652-47e7-96d7-bd753406d567%40googlegroups.com. For more options, visit https://groups.google.com/d/optout.
