Dear Josef,

Thank you for the excellent suggestion! Using fisk.rvs fixed the problem.

Best wishes, Thank you for the excellent suggestion! Using fisk.rvs fixed the problem.

Liz

On Mon, Jun 16, 2014 at 1:05 PM, <josef.pktd@gmail.com> wrote:

You or someone can add new distribution for numpy.random.On Mon, Jun 16, 2014 at 1:38 PM, Liz VanWormer <evanwormer@ucdavis.edu> wrote:

> Dear all,

>

> I'm a novice Python user, and I need to draw random variables from a

> loglogistic distribution. I've used the numpy.random command in the past to

> select variables from supported distributions (beta, normal, lognormal,

> etc). Is there a way to add in a distribution to be used with the

> numpy.random command?

However, scipy has the fisk distribution which according to wikipedia

is the same as log-logistic.

fisk is implemented as a special case of burr and has an explicit

inverse cdf (ppf)

So using fisk.rvs should be reasonably fast for vectorized calls,

since the overhead is much larger than for numpy.random functions.

http://en.wikipedia.org/wiki/Log-logistic_distribution

to make distribution names more fun:

Wikipedia:"generalized log-logistic distribution" "These include the

Burr Type XII distribution (also known as the Singh-Maddala

distribution) "

Josef

> _______________________________________________

>

> Thank you for your insight,

> Liz

>

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