RE: R MATRIX ALGORITHMICALLY SINGULAR
Dear Susan, Tianli,
These kind of problems may be caused by numerical instability of the
covariance step which seems to be unscaled in contrast to the estimation
step. Inspection of the T (or R) matrix helps identifying the associated
parameters: locate the largest number on the diagonal and look up that
parameter. You are likely to find out that that particular parameter is
much smaller than others. Such a parameter can be rescaled in the $PK
block, e.g. by dividing it with a constant (or by exponentiation).
Obviously, a very large parameter would result in the opposite
behaviour.
Other sources of numerical instability, apart from the aforementioned
over-parameterization, are numerous but include: suboptimal choice of
integration procedure (ADVAN and TOL), estimation mode (FOCE INTER is
less stable than FOCE etc.), suboptimal design and outlying observations
or individuals.
Best regards,
Jeroen
Jeroen Elassaiss-Schaap, PhD
Modeling & Simulation Expert
Pharmacokinetics, Pharmacodynamics & Pharmacometrics (P3)
Early Clinical Research and Experimental Medicine
Schering-Plough Research Institute
T: +31 41266 9320
Quoted reply history
-----Original Message-----
From: [email protected] [mailto:[email protected]]
On Behalf Of [email protected]
Sent: Thursday, 10 September, 2009 5:01
To: Hudachek,Susan
Cc: [email protected]
Subject: Re: [NMusers] R MATRIX ALGORITHMICALLY SINGULAR
Hi Susan,
The most common reason is that you got too many parameters. But if there
is someone who could summarize all other possible reasons for this kind
of error, it would be really appreciated.
If your model is not over-parameterized, there's one way to avoid it.
You could try adding "Matrix=S" into $COV block. This would give you a
similar estimate of covariance matrix if your sample size is large
enough.
Hope it helps,
Tianli
****************************************************
Tianli Wang
PhD Candidate
Department of Pharmaceutics
University of Minnesota
On Sep 9 2009, Hudachek,Susan wrote:
> Greetings! I have run several models and the covariance steps have
> been unsuccessful due to the following error:
>
>R MATRIX ALGORITHMICALLY SINGULAR
>COVARIANCE MATRIX UNOBTAINABLE
>R MATRIX IS OUTPUT
>T MATRIX - EQUAL TO RS*R, WHERE S* IS THE INVERSE OF S - IS OUTPUT
>
> Does anyone have an idea as to what this indicates and how to 'fix"
it?
> Thanks in advance for any help/input you can offer!
>Susan
>
>Susan Hudachek, M.S., Ph.D.
>Animal Cancer Center
>Veterinary Teaching Hospital
>Colorado State University
>300 West Drake Road
>Fort Collins, CO 80523-1620
>PHONE: (970) 219-7599
>FAX: (970) 297-1254
>EMAIL: [email protected]
>
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