Hi Navin,

Thanks for the hint, but I tried that, to no avail.

Kind regards,

Filip

-----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

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