RE: BAYES Estimation: OBJECTIVE FUNCTION IS INFINITE
Hi Xinting,
I frequently use METH=BAYES and have had the same observation at various
occasions. First let me say that BAYES a wonderful estimation engine that has
helped me to model PK, PKPD and odd-type data in cases where FOCE failed, even
where SAEM and IMP(MAP) failed (recently shown at PAGE). In all situations of
infinite OFV I managed to get it to run by making sure the search would not
lead to extremely large or extremely small ( positive ) numbers. For example if
you are looking for a power estimate and you have some idea about it going to
be in the order of 1, then ensure that your safety valves in the code prevent
it from going close to zero or larger than e.g. 3 (arbitrary number). While the
estimate at extreme values may not be problematic per se, one could think that
in combination with the other parameters (I believe BAYES considers all
parameters ‘completely free to choose’ within the initial estimate bounds
during estimation) completely weird predictions could lead to the OFV being
blown up. If I read about your problem being high-dimensional, there may be
many relationships in your model at large to make the OFV go poof. One argument
against directing the parameters in a certain direction is that it may
introduce bias, so it comes at a certain cost. Furthermore I can recommend to
look into the bayes.ext file you’re writing to disk and you may see at what
parameter combinations OFV goes bazurk; that may inform you further on extreme
values.
Apparently BAYES is more flexible in the search which provides combinations of
parameters that will send the OFV into the wild. Perhaps Bob Bauer can add some
insights here – I know too little about what happens under the hood.
By the way, why are you considering BAYES when you get SAEM and IMP to run just
fine? Why not use SAEM results and run IMP with EONLY=1 afterwards?
Hope this helps,
Klaas Prins
________________________________________
Klaas Prins, PhD
Vice President EU
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Quoted reply history
From: [email protected] [mailto:[email protected]] On
Behalf Of Xinting Wang
Sent: Friday, June 12, 2015 4:06 AM
To: [email protected]
Subject: [NMusers] BAYES Estimation: OBJECTIVE FUNCTION IS INFINITE
Dear All,
I am using a cascade of the EM estimation methods implemented in Nonmem 7.2 to
solve a high-dimension PK/PD problem. The estimation chain is coded as below:
$EST MET=SAEM INTER NBURN=2000 NITER=1000 PRINT=5 NOABORT NOPRIOR=0 ISAMPLE=10
SIGL=6 CTYPE=3 IACCEPT=0.4 CONSTRAIN=1 SEED=145612 FILE=Saem.ext
$EST MET=IMP INTER NITER=2000 ISAMPLE=1000 PRINT=5 SEED=581987 SIGL=6, CTYPE=3
MAPITER=0 FILE=Imp.ext
$EST MET=BAYES INTER NBURN=3000 NITER=25000 PRINT=10 NOABORT NOPRIOR=0 FNLETA=0
ISAMPLE_M1=2 ISAMPLE_M2=2 ISAMPLE_M3=2 IACCEPT=0.4 SEED=231457 FILE=Bayes.ext
The first two estimation methods run successfuly with a convergence, but when
it comes to BAYES, an error message always occurs:
OBJECTIVE FUNCTION IS INFINITE. PROBLEM ENDED
1THERE ARE ERROR MESSAGES IN FILE PRDERR
I put safety brakes in the code to prevent 0**power or square root of
negative values, but the problem still occured. Setting lower and upper bound
of the initial estimation, but it did not help either.
I am wondering if anyone here encountered this issue previously? It seems quite
strange to me that SAEM and IMP could succeed, but BAYES fails. Could you
please let me know of the possible reasons behind this? Thanks very much.
Best Regards
--
Xinting