NONMEM Users Network Archive

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Re: count simulations

From: Nick Holford <n.holford>
Date: Fri, 07 Aug 2009 07:47:49 +1200

Mats,

Thanks for pointing out that R and 1-R are equivalent when R is a
uniform 0-1 random deviate.

There is an NM-TRAN example using 1-R in this paper:

Frame B, Miller R, Lalonde RL. Evaluation of Mixture Modeling with Count
Data
using NONMEM. Journal of Pharmacokinetics and Pharmacodynamics.
2003;30(3):167-83.

I have to admit to having cut and pasted this example and used it to
show others how to simulate count data so it may have propogated that
way too.

Do you know of a clear explanation of why this simple algorithm produces
Poisson distribution samples?


Nick


Mats Karlsson wrote:
>
> Dear both,
>
> You have both simulated count data using the code below (or very
> similar). My question is why do you use LOG(1-R) rather than the
> simpler LOG(R)? If you’ve done it because you inherited the code,
> where did you get the code.
>
> *IF (ICALL.EQ.4) THEN*
>
> * T=0*
>
> * N=0*
>
> * DO WHILE (T.LT.1)*
>
> * CALL RANDOM (2,R)*
>
> * T=T-LOG(1-R)/LAMB*
>
> * IF (T.LT.1) N=N+1*
>
> * END DO*
>
> * DV=N*
>
> *ENDIF*
>
> Best regards,
>
> Mats
>
> Mats Karlsson, PhD
>
> Professor of Pharmacometrics
>
> Dept of Pharmaceutical Biosciences
>
> Uppsala University
>
> Box 591
>
> 751 24 Uppsala Sweden
>
> phone: +46 18 4714105
>
> fax: +46 18 471 4003
>

--
Nick Holford, Professor Clinical Pharmacology
Dept Pharmacology & Clinical Pharmacology
University of Auckland, 85 Park Rd, Private Bag 92019, Auckland, New Zealand
n.holford
mobile: +64 21 46 23 53
http://www.fmhs.auckland.ac.nz/sms/pharmacology/holford
Received on Thu Aug 06 2009 - 15:47:49 EDT

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