A more direct approach to compartmental modelling.

By first using some simple linear curve fitting method, (such as spline fitting), on data following a compartmental model, direct application of linear regression can then be made to the system of differential equations describing this data. This allows information about the parameters governing the system to be obtained from tracer and tracee measurements. It simplifies both the process of determining which parameters are estimable from various measurements, as well as the estimation process itself. Since it does not rely on knowledge of a simple closed form of the solution it has the potential to make full use of data measured over very long time periods under nonequilibrium conditions. Essentially it allows introduction of sequential estimation methods of statistics. These results can then be used to predict future substrate concentration from known substrate production, or determine substrate production from concentration measurements. A byproduct of these methods is the ability to estimate parameters in data assumed to be a finite linear combination of exponentials or sinusoids of unknown exponents or frequencies, without use of complicated nonlinear regression methods.