minimum objective function

4 messages 4 people Latest: Dec 03, 1998

minimum objective function

From: Ian J. Gowrie Date: December 02, 1998 technical
From: "Ian J. Gowrie" <i.j.gowrie@city.ac.uk> Subject: minimum objective function Date: Wed, 02 Dec 1998 17:19:24 +0000 Dear all, I've a simple(?) question concerning the Minimum Objective Function. Say I have some models and during model building I get the following results: THETA(1) only, objective function = OF1 THETA(2) only, objective function = OF2 THETA(1) and THETA(2). objective function = OF3 Must the following statements be true? OF3 < OF2 OF3 < OF1 I ask this, naturally, because I have a situation where one of these is not true, and I am interested in what the causes may be. Thanks for your time Ian J Gowrie *************************************** Centre for Measurement in Medicine City University London

Re: minimum objective function

From: Kenneth G. Kowalski Date: December 02, 1998 technical
From: KENNETH.G.KOWALSKI@monsanto.com Subject: Re: minimum objective function Date: 02 Dec 1998 14:25:47 -0600 Ian, I'm assuming that you checked your models and that the models are hierarchical. That is, for the model with both THETA(1) and THETA(2) you can set either to some null value (typically 0 or 1) such that it reduces to the THETA(1) or THETA(2) alone model. If that is the case then it should be that OF3<OF1 and OF3<OF2. If this is not being met, then you may not have achieved the global optimum (minimum objective function) for the model with both THETA(1) and THETA(2) in the model. Perhaps your model is overparameterized making it difficult to achieve the optimum. Let's suppose that you found OF2<OF3 yet they're supposed to be hierachical. You should be able to use final estimates obtained from the THETA(2) alone model and set THETA(1) to its null value for absence in the model with both THETA(1) and THETA(2) and have the same objective function value (OF2). You might start from there with perhaps only slightly changing the starting value for THETA(1) from its null value and see if you can get it to iterate and converge such that OF3<OF2. Of course if that happens, there is still no guarantee that you have achieved the absolute minimum. Good luck! Ken

minimum objective function

From: Lewis B. Sheiner Date: December 02, 1998 technical
From: Lewis Sheiner <76135.526@compuserve.com> Subject: minimum objective function Date: Wed, 2 Dec 1998 16:38:25 -0500 I assume you mean that you have a model & data that are fixed, and that OF1 is the min OF when theta(2) is fixed to 0 but all other parameters are free; OF2 is the min OF when theta(1) is fixed to zero but all other parameters are free; and OF3 is the min OF when all parameters are free. If that is so, then indeed it must be the case that OF3 is less than either OF1 or OF2. If you think that this been violated, look carefully to be sure there is no abnormal termination, or that constrants on parameters have not also changed, or in the OF3 case, one of either theta(1) or theta(2) is going towards zero, and is bounded at zero, or some such situation that makes the model/data change from case to case other than just through fixing certain parameters. LBS.

RE: minimum objective function

From: Vladimir Piotrovskij Date: December 03, 1998 technical
From: "Piotrovskij, Vladimir [JanBe]" <VPIOTROV@janbe.jnj.com> Subject: RE: minimum objective function Date: Thu, 3 Dec 1998 08:29:30 +0100 Dear Ian, Everything depends on your data and your model. If there is a high intraindividual variability and your model is complex (both are typical in case of PD data) you may observe very strange behavior of NONMEM. Best regards Vladimir