[SciPy-user] lognormal distribution
Robert Kern
rkern at ucsd.edu
Fri Feb 11 16:28:54 CST 2005
Gary wrote:
> Stephen Walton wrote:
>
>> An application question for a change: I need to produce pseudorandom
>> numbers drawn from a lognormal distribution (see
>> http://www.itl.nist.gov/div898/handbook/eda/section3/eda3669.htm).
>> Does anyone have existing code for this in Numeric or numarray?
>
>
> It is interesting to me to see this question.
>
> If I understand you correctly, I can say that Speakeasy has what you
> want. Actually, Speakeasy can produce random numbers from any
> user-defined distribution, even one that is not analytical. A
> colleague of mine once (in the early '90s) used that capability in
> modeling nuclear scintillation detectors. He took a *measured* pulse
> height distribution from a PMT and used it to generate random numbers
> that he input into a model of a scintillation crystal. His "Monte
> Carlo" simulation was 13 lines long.
> I was intrigued by the usefulness of this feature, so I always have my
> eye open to see if any other software package has that capability. I
> haven't searched exhaustively, but I haven't seen it in Matlab (or
> octave or scilab) or Mathematica or Mathcad. Or any of the usual
> python packages.
Well, it depends on how tricky the function is.
If it's univariate, and you can write out the pdf or cdf as a function,
then I believe you can subclass scipy.stats.rv_continuous, and it's
rvs() method will numerically invert the cdf to generate it's random
numbers.
If the function is highly multivariate, you might need to do
Markov-Chain Monte Carlo which is implemented by PyMC.
If you have a bunch of data points from a continuous distribution, but
no functional description, then you can make a kernel density estimate
and draw random numbers from that. As of last night, that functionality
is in scipy.stats.gaussian_kde.
Resampling from discrete data is pretty trivial to handwrite.
Is there anything else you need?
--
Robert Kern
rkern at ucsd.edu
"In the fields of hell where the grass grows high
Are the graves of dreams allowed to die."
-- Richard Harter
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