RE: NM7 Importance Sampling: Objective function goes to zero, but results look reasonable

-----Original Message----- From: Navin Goyal [mailto:[email protected]] Sent: Monday, 10 October 2011 16:37 To: De Ridder, Filip [JRDBE] Subject: Re: [NMusers] NM7 Importance Sampling: Objective function goes to zero, but results look reasonable Hi Filip, Not sure if this will help, but try using IMPMAP instead of IMP after SAEM. Issues have been reported after using IMP with NM7.1 I had similar issues alongwith something else as well...where the IMP estimation OBFV would keep on decreasing (the higher runs I had the more the number kept going down) Dont remeber exactly the details, but I remember switching to IMPMAP. There was a discussion as well on NMUSERS about it. Hope this is of some help Best wishes Navin On Mon, Oct 10, 2011 at 4:40 AM, De Ridder, Filip [JRDBE] <[email protected]> wrote: > Dear NMUsers, > > > > When using SAEM/IMP in NM7.1., I get a peculiar results from IMP. After a > successful SAEM-run resulting in reasonable point estimates, the objective > function is first declared as 0.00000 and later as "NaN" at the final > iteration. I do get standard-errors and these look reasonable, but I am > not sure how trustworthy they are given the NaN OBJ. > > This is the $EST call: > > > > $EST METHOD=SAEM LAPLACE LIKE NBURN=1000 NITER=2000 PRINT=10 CTYPE=3 > CINTERVAL=10 NOABORT > > $EST METHOD=IMP LIKE NITER=20 CTYPE=3 ISAMPLE=300 NOABORT EONLY=1 > > > > FOCE/Laplace terminates due to rounding errors, but gives reasonable point > estimates close to the SAEM result. > > > > Below is a selection of the search. > > > > Kind regards, > > > > Filip De Ridder > > Janssen Research & Development, Beerse, Belgium. > > > > #METH: Stochastic Approximation Expectation-Maximization > > EM/BAYES SETUP > > THETAS THAT ARE MU MODELED: > > 1 2 3 4 5 6 7 8 9 11 12 > > THETAS THAT ARE SIGMA-LIKE: > > > > MONITORING OF SEARCH: > > > > Stochastic/Burn-in Mode > > iteration -1000 SAEMOBJ= 26003.614680275896 > > iteration -990 SAEMOBJ= -1092.1038437297473 > > ... > > iteration -670 SAEMOBJ= -3257.6199048158469 > > iteration -660 SAEMOBJ= -3454.3544417057101 > > Convergence achieved > > Reduced Stochastic/Accumulation Mode > > iteration 0 SAEMOBJ= -3365.8558463970126 > > iteration 10 SAEMOBJ= -3739.6849187475736 > > ... > > iteration 1960 SAEMOBJ= -3823.2755123680026 > > iteration 1970 SAEMOBJ= -3823.2896277883360 > > iteration 1980 SAEMOBJ= -3823.4174894810230 > > iteration 1990 SAEMOBJ= -3823.3225200406459 > > iteration 2000 SAEMOBJ= -3823.2969976068907 > > Elapsed estimation time in seconds: 2862.05 > > > > #TERM: > > STOCHASTIC PORTION COMPLETED > > REDUCED STOCHASTIC PORTION COMPLETED > > > > > > #METH: Objective Function Evaluation by Importance Sampling > > EM/BAYES SETUP > > THETAS THAT ARE MU MODELED: > > 1 2 3 4 5 6 7 8 9 11 12 > > THETAS THAT ARE SIGMA-LIKE: > > > > MONITORING OF SEARCH: > > > > iteration 0 OBJ= 0.0000000000000000 > > iteration 10 OBJ= NaN > > Elapsed estimation time in seconds: 1472.26 > > iteration 20 OBJ= NaN > > > > #TERM: > > OPTIMIZATION NOT TESTED > > > > > > -- Navin Goyal