Re: nm7 IMP method question
I've seen on a number of examples (of non-linear differential equations models) the IMP method diverge (by increasing the OF indefinitely, until it hits infinity). In those cases, IMPMAP was more successful.
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Sebastian Ueckert wrote:
> Dear Wu,
>
> it is important to realize that the new estimation methods do not directly maximize the likelihood. The EM algorithm updates the population parameters by averaging the conditional mean/variances of the etas. Therefore, it is not guaranteed that the likelihood increases (OFV decreases). The classical method, opposed to that, are gradient based and only change the population parameters when the OFV decreases.
>
> There are several things you could try if the OFV is continuously increasing when using the IMP method: - make sure that your model is valid for unusual eta samples (prevent e.g. division by zero, logarithm of values smaller than zero, etc.)
>
> - change the initial values
> - use a different estimation methods prior to IMP (e.g. FOCE, ITS)
> - increase the number of individual samples (ISAMPLE)
> - use a different sampling distribution (e.g. DF=1)
> - try using the IMPMAP method instead
>
> It would be interesting to know if other users have additional suggestions.
>
> Best regards,
> Sebastian
>
> Sebastian Ueckert, MSc, PhD student
> -----------------------------------------------
> Pharmacometrics Research Group,
> Department of Pharmaceutical Biosciences,
> Uppsala University
> -----------------------------------------------
> P.O. Box 591
> SE-751 24 Uppsala
> Sweden
> -----------------------------------------------
> [email protected] <mailto:[email protected]>
> -----------------------------------------------
> Work: +46-(0)18-471 4437
>
Quoted reply history
> On Wed, May 12, 2010 at 5:30 PM, Xiao Hu < [email protected] < mailto: [email protected] >> wrote:
>
> *Dear Sebastian and Ethan,*
>
> I have encountered similar situation in the same estimation step. It also occurred using Baysian method. The MCMCOBJ just kept
>
> increasing from approximately -100 to 2000, while CONDITIONAL LAP
> and FOCE converged successfully. I found different methods work for
> different dataset and model structures. Changing initial estimation
> did not help much. Any insight on why OBJ and MCMCOBJ keep
> increasing, and how to prevent it would be helpful. Thanks in advance.
>
> Best regards,
> Shelley
>
> ========================================
> Xiao Hu (Shelley), Ph.D.
> Scientist,
> Development Pharmacokinetics & Disposition
> Biogen Idec, Inc.
> 14 Cambridge Center
> Cambridge, MA 02142
>
> *Sebastian Ueckert <[email protected]
> <mailto:[email protected]>>*
> Sent by: [email protected]
> <mailto:[email protected]>
>
> 12-May-2010 11:08 AM
>
> Message Size: *6.2 KB*
>
> To
> nmusers <[email protected] <mailto:[email protected]>>
> cc
>
> Subject
> Re: [NMusers] nm7 IMP method question
>
> Dear Ethan.
> if you use the IMP method to estimate your parameters, you do not
> have to run a second IMP step. The ESTEP is run for every iteration
> and if the OFV is stable during the last iterations you can just use
> that. However the behavior you are describing is strange. It could
> be related to different settings for both steps. Can you please send
> the code for both $EST lines?
>
> Best regards,
> Sebastian
>
> Sebastian Ueckert, MSc, PhD student
> -----------------------------------------------
> Pharmacometrics Research Group,
> Department of Pharmaceutical Biosciences,
> Uppsala University
> -----------------------------------------------
> P.O. Box 591
> SE-751 24 Uppsala
> Sweden
> -----------------------------------------------_
> [email protected]_
> <mailto:[email protected]>
> -----------------------------------------------
> Work: +46-(0)18-471 4437
>
> On Wed, May 12, 2010 at 4:13 PM, Ethan Wu <[email protected]_
> <mailto:[email protected]>> wrote:
> IACCEPT