RE: Unexpected influence of parameter order on estimation results

-----Original Message----- From: [email protected] [mailto:[email protected]] On Behalf Of [email protected] Sent: Friday, 18 June, 2010 4:05 To: [email protected] Subject: [NMusers] Unexpected influence of parameter order on estimation results Dear NMusers, I always thought that the order in which parameters are declared in the control stream has no impact on the estimation outcomes, but the following results seem to contradict this. The PK of drug X was modeled with a linear 3-compartment model using a proportional residual variability model. Inter-individual variability was estimated on elimination clearance and central volume of distribution. The magnitude of residual variability was estimated using a THETA and a SIGMA fixed to 1 as follows: $ERROR IPRED=F CV=THETA(x) W=CV*IPRED Y=IPRED+W*EPS(1) Two versions of this model were created with slight differences in the order of declaration of the theta parameters: the theta used to estimate the RV was basically moved from the third to the last position and the $PK and the $ERROR blocks were updated accordingly. Both models were run with NONMEM 6.2.0 on opensuse 11.1 (with the gfortran compiler). One of the models converged successfully while the other stopped at an early iteration and returned some estimation warnings and a 'S matrix singular' message. The strange thing is that gradients appears identical until the 10th iteration, at which point the two models take different search paths (see below). I would be very interested to know the opinion of the group on this puzzling result. Thanks Sebastien [] This message and any attachments are solely for the intended recipient. If you are not the intended recipient, disclosure, copying, use or distribution of the information included in this message is prohibited --- Please immediately and permanently delete.