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: [email protected], [email protected]

> 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: [email protected]
> Web: www.icondevsolutions.com 
> 
> 
> 
> 
> 
> 
> 
> 
> ________________________________
> 
> From: [email protected] [mailto:owner-
> [email protected]]on Behalf Of [email protected]
> Sent: Saturday, October 24, 2009 8:03 PM
> To: [email protected]
> 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
> 
> 
> 
> 
> 
> 
> 
> 
> 
> 
> ICON plc made the following annotations.
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