The MLAB Applications Manual begins with a discussion of how curve fitting minimizes the weighted sums of squares. A model and a function are not the same thing. A model is a combination of functions that describes some natural phenomenon, whether physical or biological. A linear model may be composed from both linear and nonlinear functions as long as the composition is in the form of a linear combination of terms. The advantage of linear models is that one can solve the equations with one or two iterations.
Many programs can perform linear regression analysis with ease.
Many models in biology are nonlinear and the parameters cannot be found by linear regression analysis. One cannot find the parameters by linear regression analysis without linearization of the equation. Where programming for linear regression analysis was relatively easy, programming for nonlinear regression analysis is not. MLAB was specifically designed to perform nonlinear regression analysis efficiently and accurately. In biological problems, one often turns to nonlinear models because linear models are insufficient models for studying the binding of ligands to large molecules, as occurs with immunoassays and receptor studies.