RE: R MATRIX ALGORITHMICALLY SINGULAR

From: Jeroen Elassaiss-Schaap Date: September 10, 2009 technical Source: cognigen.com
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: owner-nmusers On Behalf Of wangx826 Sent: Thursday, 10 September, 2009 5:01 To: Hudachek,Susan Cc: nmusers 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: Susan.Hudachek > This message and any attachments are solely for the intended recipient. If you are not the intended recipient, disclosure, copying, use or distribution of the information included in this message is prohibited --- Please immediately and permanently delete.
Sep 09, 2009 Susan Hudachek R MATRIX ALGORITHMICALLY SINGULAR
Sep 09, 2009 Wangx826 Re: R MATRIX ALGORITHMICALLY SINGULAR
Sep 10, 2009 Susan Hudachek R MATRIX ALGORITHMICALLY SINGULAR
Sep 10, 2009 Jeroen Elassaiss-Schaap RE: R MATRIX ALGORITHMICALLY SINGULAR
Sep 10, 2009 Wangx826 Re: R MATRIX ALGORITHMICALLY SINGULAR
Sep 10, 2009 Joachim Grevel RE: R MATRIX ALGORITHMICALLY SINGULAR
Sep 10, 2009 Jeroen Elassaiss-Schaap RE: R MATRIX ALGORITHMICALLY SINGULAR