RE: $COV UNCONDITIONAL PRINT=E
Sam, Many years ago Stuart scolded me for using the Unconditional option, saying that a model that didn't converge had no chance of a successful covariance step (I didn't ask why he put the option in if he didn't want people using it). But, I have had put a couple of models that appeared to be "hung" into the development environment and found that they were not, in fact hung. Almost invariably, the "hung" part is in the call to OBETA (I assume you're using FOCE?), OBETA is a minimization in itself, and while the main NONMEM minimization has a limit (MAXEVAL) OBETA doesn't seem to. So, if the minimization (in OBETA) is difficult it will just keep running. Options are to beleive those who claim covariance doesn't mean anything, or wait for the parallel version of NONMEM. Mark Mark Sale MD Next Level Solutions, LLC www.NextLevelSolns.com 919-846-9185
Quoted reply history
-------- Original Message --------
Subject: [NMusers] $COV UNCONDITIONAL PRINT=E
From: "Sam Liao" < [email protected] >
Date: Mon, October 26, 2009 11:36 am
To: < [email protected] >, < [email protected] >
Dear NONMEM team: I have two nm7 questions. I have a PKPD model using ADVAN13 to solve the ODE. It took 12 hours to complete the $EST step with rounding error. But it’s been over 15 hours running the $COV step with UNCONDITIONAL option. This is much longer time than I expected. Could this be an infinitive loop? Should I interrupt the run and try smaller SIGL in $COV? I tried the CTL-K or CTL-E to exit, but it did not work for me. The second question related to BAYES method in $EST step. The model run successfully using FOCE method. But when I tried the BAYES method with NOABORT option, it terminated with ‘OBJECTIVE FUNCTION IS INFINITE’ in Burn-in mode after 10 iterations. The statement used as below. How can I get around this problem? ======================= $SUBROUTINES ADVAN13 TOL=6 $EST METHOD=BAYES NBURN=100 NSAMPLE=3000 SIGL=6 NOABORT FILE=RUN136.TXT Best regards, Sam From: [email protected] [ mailto: [email protected] ] On Behalf Of Bauer, Robert Sent: Sunday, October 25, 2009 11:29 PM To: [email protected] ; [email protected] Subject: RE: [NMusers] method=ITS, OPTIMIZATION NOT TESTED (?!) Pavel: The objective function progress looks good. You should expect some Monte Carlo fluctuations. You should also run more iterations (perhaps NITER=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: [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