RE: How to model observed quantity tha is an average over compartments

Thanks, both to Tarjinder and Doug. The identifiability is a well known problem with (single fit) data of that sort, and is mostly solved by making an extreme assumption for one of the coeffs. We hope that the population fit can tweak additional information from the very rich data (some 100 per set, but this needs long time). As a first step, assuming that T2 is the only observed quantity gives an excellent fit, so the mix-in is probably low. Dieter ---- From: [email protected] [mailto:[email protected]] On Behalf Of Eleveld, DJ .. If you only observe the average of two quantities you can never estimate the individual contributions. You must have some additional information to be able to do this. Maybe if the time constants are apriori known to be very different, i.e. fast and slow, then it might be possible but you would need very rich data. Multiple fast and slow changes in concentration. As far as $ERROR is concerned it is quite easy to setup when you use A() $ERROR .... CT1=A(1)/V1 ;conc in tissue 1 CT2=A(2)/V2 ;conc in tissue 2 COBS=(CT1+CT2)/2 ;average in tissues Y=COBS*(1+ERR(1)) ;Just guessing proportional error ... Hope this helps, Doug Eleveld