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RE: RE: RE: method=ITS, OPTIMIZATION NOT TESTED (?!)

From: Bauer, Robert <Robert.Bauer>
Date: Fri, 30 Oct 2009 11:25:17 -0400

Pavel:
I'm glad it worked out for you. Sometimes what also works, is keeping
ISAMPLE at 300 but setting METHOD to IMPMAP. The preference depends on
which computes faster.
 

Robert J. Bauer, Ph.D.
Vice President, Pharmacometrics
ICON Development Solutions

Tel: (215) 616-6428
Mob: (925) 286-0769
Email: Robert.Bauer
Web: www.icondevsolutions.com

 

 

 

________________________________

From: nonmem
Sent: Friday, October 30, 2009 11:03 AM
To: Bauer, Robert
Cc: nmusers
Subject: Re: RE: RE: [NMusers] method=ITS, OPTIMIZATION NOT TESTED =
(?!)


Hello Robert,
 
It seems like having ISAMPLE=1000 fixed it. There are occasional
increases in the objective function, but they are not very large.
Although the final objective function is not the lowest one, it is very
close to the lowest one and looks meaningful. Thanks!
 
Pavel
 
 

----- Original Message -----
From: Bauer, Robert
Date: Tuesday, October 27, 2009 11:58 am
Subject: RE: RE: [NMusers] method=ITS, OPTIMIZATION NOT TESTED (?!)
To: nonmem
Cc: nmusers

> Pavel:
> There is not a way to select the lowest objective function. Your
> variations in the objective function are quite large during IMP,
> and it
> suggests one of two things:
> 1) You may need to increase ISAMPLE to 1000
> 2) You may not be linear mu modeling all of the theta parameters
> 3) Just to make sure, are you using the release version of
> 7.1.0, rather
> than the beta version
>
> If you wish you may want to send me your control stream file.
>
>
> Robert J. Bauer, Ph.D.
> Vice President, Pharmacometrics
> ICON Development Solutions
>
> Tel: (215) 616-6428
> Mob: (925) 286-0769
> Email: Robert.Bauer
> Web: www.icondevsolutions.com
>
>
>
>
>
>
>
>
> ________________________________
>
> From: nonmem
> Sent: Tuesday, October 27, 2009 9:23 AM
> To: Bauer, Robert
> Cc: nmusers
> Subject: Re: RE: [NMusers] method=ITS, OPTIMIZATION NOT TESTED (?!)
>
>
> Hello Robert,
>
> As you suggested, I changed the options. The job converged much
> faster,but the objective function was "quasioptimal", i.e. the
> final objective
> function was equal to 10264.899631336189 (see below) while a lower
> objective function of 10222.499515685291 was observed during the
> interations when the default options were applied. I used the
> parameters resulting in the objective function of
> 10222.499515685291 as
> a starting point and run method=1 with interaction. The starting
> objective function was equal to 10226.5427056802. I find method=imp
> very useful for validation of the results. Is there a way to
> force it
> to select the best parameters and the objective function?
>
> Importance Sampling
> MONITORING OF SEARCH:
> iteration 0 OBJ= 10231.982923426112
> iteration 1 OBJ= 10299.863138426574
> iteration 2 OBJ= 10364.772068665749
> iteration 3 OBJ= 10308.739048014546
> iteration 4 OBJ= 10257.381411982740
> iteration 5 OBJ= 10265.245304914670
> iteration 6 OBJ= 10251.006105651519
> iteration 7 OBJ= 10236.430245954567
> iteration 8 OBJ= 10234.353761873708
> iteration 9 OBJ= 10242.798081619065
> iteration 10 OBJ= 10235.389009976587
> iteration 11 OBJ= 10229.486328373108
> iteration 12 OBJ= 10226.968499926681
> iteration 13 OBJ= 10227.283866001104
> iteration 14 OBJ= 10229.010908067567
> iteration 15 OBJ= 10229.094607380130
> iteration 16 OBJ= 10230.010670330952
> iteration 17 OBJ= 10230.204979821499
> iteration 18 OBJ= 10264.365519362043
> iteration 19 OBJ= 10298.266732255344
> Convergence achieved: ending mode
> Elapsed estimation time in seconds: 13157.00
> Evaluating one more iteration for Variance assessment:
> iteration 19 OBJ= 10264.899631336189
> OPTIMIZATION COMPLETED
> Elapsed covariance time in seconds: 15766.53
>
> Thank you,
> Pavel
>
>
> ----- Original Message -----
> From: "Bauer, Robert"
> Date: Sunday, October 25, 2009 11:56 pm
> Subject: RE: [NMusers] method=ITS, OPTIMIZATION NOT TESTED (?!)
> To: nonmem
>
> > Pavel:
> > The objective function progress looks good. You should expect some
> > Monte Carlo fluctuations. You should also run more iterations
> > (perhapsNITER=200), and set CTYPE=3, which turns on the
> > termination tester. To
> > resume where you left off, rename your new control stream
> file,
> > and put
> > in the following lines.
> >
> > $EST METHOD=CHAIN NSAMPLE=0 ISAMPLE=50
> > FILE=my_old_control_stream_file.ext
> > $EST METHOD=IMP NITER=200 CTYPE=3
> FILE=my_new_control_stream_file.ext>
> > Make sure you are linear MU referencing to get the greatest
> > efficiency.
> >
> >
> > Robert J. Bauer, Ph.D.
> > Vice President, Pharmacometrics
> > ICON Development Solutions
> >
> > Tel: (215) 616-6428
> > Mob: (925) 286-0769
> > Email: Robert.Bauer
> > Web: www.icondevsolutions.com
> >
> >
> >
> >
> >
> >
> >
> >
> > ________________________________
> >
> > From: owner-nmusers
> > nmusers
> > Sent: Saturday, October 24, 2009 8:03 PM
> > To: nmusers
> > Subject: [NMusers] method=ITS, OPTIMIZATION NOT TESTED (?!)
> >
> >
> >
> > Hello NONMEM Team,
> >
> > I found method=imp useful when there are local maxima.
> > Nevertheless, at
> > the end of optimization it prints a message, which makes me feel
> > somewhat uncomfortable: OPTIMIZATION NOT TESTED. Also, the final
> > objective function is not always the lowest one. An example is
> below.> How do we interpret the results in this case?
> >
> > THETAS THAT ARE SIGMA-LIKE:
> > MONITORING OF SEARCH:
> >
> > iteration 0 OBJ= 10625.663135214874
> > iteration 1 OBJ= 10601.188754983375
> > iteration 2 OBJ= 10537.895114114934
> > iteration 3 OBJ= 10471.674625518765
> > iteration 4 OBJ= 10430.297437731866
> > iteration 5 OBJ= 10461.973668565577
> > iteration 6 OBJ= 10462.638834406265
> > iteration 7 OBJ= 10423.464983371641
> > iteration 8 OBJ= 10417.959956991735
> > iteration 9 OBJ= 10417.594007447198
> > iteration 10 OBJ= 10414.708468642830
> > iteration 11 OBJ= 10427.810693855947
> > iteration 12 OBJ= 10412.889081059604
> > iteration 13 OBJ= 10411.980622268416
> > iteration 14 OBJ= 10424.501127174915
> > iteration 15 OBJ= 10416.332869468861
> > iteration 16 OBJ= 10416.622580251338
> > iteration 17 OBJ= 10412.401585537709
> > iteration 18 OBJ= 10415.117257355550
> > iteration 19 OBJ= 10415.302370961055
> > iteration 20 OBJ= 10409.066188189252
> > iteration 21 OBJ= 10413.780620468329
> > iteration 22 OBJ= 10410.787496174480
> > iteration 23 OBJ= 10410.633582415931
> > iteration 24 OBJ= 10409.970257443048
> > iteration 25 OBJ= 10409.702420124611
> > iteration 26 OBJ= 10409.213115058612
> > iteration 27 OBJ= 10409.690639357370
> > iteration 28 OBJ= 10410.016047785200
> > iteration 29 OBJ= 10408.157468814226
> > iteration 30 OBJ= 10407.779614704938
> > iteration 31 OBJ= 10410.164563157052
> > iteration 32 OBJ= 10408.364552302961
> > iteration 33 OBJ= 10407.431920727997
> > iteration 34 OBJ= 10408.286189641487
> > iteration 35 OBJ= 10407.907347050501
> > iteration 36 OBJ= 10407.451608770069
> > iteration 37 OBJ= 10407.189482360372
> > iteration 38 OBJ= 10406.484357336147
> > iteration 39 OBJ= 10409.167125968375
> > iteration 40 OBJ= 10406.840873883246
> > iteration 41 OBJ= 10407.679485561714
> > iteration 42 OBJ= 10405.341101045238
> > iteration 43 OBJ= 10404.704382334516
> > iteration 44 OBJ= 10405.348023082915
> > iteration 45 OBJ= 10405.347406984720
> > iteration 46 OBJ= 10401.873473651774
> > iteration 47 OBJ= 10404.036204419035
> > iteration 48 OBJ= 10405.072916975221
> > iteration 49 OBJ= 10402.976628923887
> > Elapsed estimation time in seconds: 30420.73
> > iteration 50 OBJ= 10403.285958168881
> >
> > #TERM:
> > OPTIMIZATION NOT TESTED
> >
> > Thanks,
> >
> > Pavel
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
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Received on Fri Oct 30 2009 - 11:25:17 EDT

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