Obj. function is infinite (error=136)
From: "Justin Wilkins"
Subject: [NMusers] Obj. function is infinite (error=136)
Date:Mon, 2 Jun 2003 10:49:46 +0200
Hi all,
I'm having a great deal of trouble getting FOCE to work with my
rifampicin data - I've settled on a one-compartment first-order model
for my healthy volunteers, and it minimizes beautifully with believable
parameter estimates using the FO default. However, with METHOD=1, the
following error crops up, rain or shine:
MINIMIZATION TERMINATED
DUE TO PROXIMITY OF LAST ITERATION EST. TO A VALUE
AT WHICH THE OBJ. FUNC. IS INFINITE (ERROR=136)
AT THE LAST COMPUTED INFINITE VALUE OF THE OBJ. FUNCT.:
ERROR IN NCONTR WITH INDIVIDUAL 63 ID=0.66000000E+02
NUMERICAL HESSIAN OF OBJ. FUNC. FOR COMPUTING CONDITIONAL ESTIMATE
IS NON POSITIVE DEFINITE
THETA=
4.39E-01 2.01E+00 5.24E+00 4.89E-01 -1.92E-01 3.41E-01
I've tried a number of solutions, suggested by past NMusers threads:
1) MATRIX=S: Error=136. Estimates hopeless.
2) Assumed related ETAs for KA and TLAG, as below:
$PK
TVKA = THETA(1) ; KA
KA = TVKA * EXP(ETA(1))
TALG = THETA(2) ; ALAG1
ALAG1 = TALG * EXP(THETA(3) + ETA(1))
TVCL = THETA(4) ; CL
CL = TVCL * EXP(ETA(2))
TVV = THETA(5) ; V
V = TVV * EXP(ETA(3))
MINIMIZATION SUCCESSFUL
R MATRIX ALGORITHMICALLY SINGULAR
COVARIANCE MATRIX UNOBTAINABLE
S MATRIX ALGORITHMICALLY SINGULAR
Estimates good, but terrible OBJ compared to FO.
3) Similarly, assumed related ETAs for CL and V - error 136.
4) Tried BAND structures for OMEGA, with no luck either.
The only estimates that approached looking credible were for the
successful minimization where ALAG and KA were assumed similar, but OBJ
was approximately double that obtained using FO.
So I guess the question is, is FO sufficient under such circumstances?
Should I keep trying?
It's worth pointing out that using LOG(DV) failed in both the FO and
FOCE approaches, I'm still not sure why - error structure below, using
pre-transformed data:
$ERROR
IPRED=F
W=SQRT(THETA(5)**2+THETA(6)**2/F**2)
IRES=DV-IPRED
IWRES=IRES/W
Y=LOG(IPRED)+W*EPS(1)
Sorry about the length - trying to cover all my bases! This is all
simple structural stuff, no covariates in the mix yet. Does anyone have
any advice?
Best regards
Justin
---