| Re: Random Numbers [message #81814 is a reply to message #13427] |
Thu, 25 October 2012 08:06   |
John O'Neill
Messages: 2
Registered: October 2012
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Junior Member |
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On Thursday, October 25, 2012 10:37:58 AM UTC-4, David wrote:
> Yngvar Larsen writes:
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>>
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>> On Wednesday, 24 October 2012 23:38:34 UTC+2, John O'Neill wrote:
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>>> Hello Everyone,
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>>>
>
>>> I am trying to create a set of random numbers using an Inverse Gaussian Distribution (Wald distribution) but randomu doesn't seem able to do this. Is there anything more general then randomu, or something where I can define what function I want to use to create random numbers?
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>> Google and Wikipedia are your friends.
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>>
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>> http://en.wikipedia.org/wiki/Inverse_Gaussian_distribution#G enerating_random_variates_from_an_inverse-Gaussian_distribut ion
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>>
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>> IDL> N = 100
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>> IDL> mu = 1d0 & lambda = 1d0
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>> IDL> nu = randomn(seed, N)
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>> IDL> z = randomu(seed, N)
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>> IDL> igvariates = dblarr(N)
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>> IDL> y = nu^2
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>> IDL> x = mu + mu^2*y/(2*lambda) - mu/2/lambda*sqrt(4*mu*lambda*y + mu^2*y^2)
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>> IDL> ind = where(z le mu/(mu+x), complement=cind)
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>> IDL> igvariates[ind] = x[ind]
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>> IDL> igvariates[cind] = mu^2/x[cind]
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>>
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>> Include checking for empty index arrays IND and/or CIND if you use IDL version < 8.0.
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> This code is easy enough to implement that I just wrote
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> a function, cgRandomWald to do it this morning. You can
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> find it here:
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> http://www.idlcoyote.com/programs/cgrandomwald.pro
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> It works very much like the other RandomX functions in IDL.
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> Cheers,
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> David
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>
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> --
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> David Fanning, Ph.D.
>
> Fanning Software Consulting, Inc.
>
> Coyote's Guide to IDL Programming: http://www.dfanning.com/
>
> Sepore ma de ni thue. ("Perhaps thos speakest truth.")
Thank you very much David, Yngvar, and Craig for your help. This is exactly what I was looking for.
John
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