[EMAIL PROTECTED] (akhan) wrote in message news:<[EMAIL PROTECTED]>... > Is there any statistical metod which can be applied to test whether a > non-linear model fit a dataset well or significantly?
Fisher's F-test can be used to quantitatively compare two models of data. The F-test can answer the question "Are these two models significantly different at the X% level?". One model can be constant; i.e. assume that data scatter is entirely random about the dependent variable mean & not dependent on the independent variable(s) at all. Or one can see if adding another parameter to a fitting function makes a significant difference. Or one can find out which of two arbitrary models best fits the data; this is very useful for comparing two theories. As an example, alternate theories for chemical diffusivity D are: (1) D=(K)*exp(-Q/T) (2) D=(K/T)*exp(-Q/T) where K and Q are experimentally determined constants and T is temperature. Given a set of (D,T) data the F-test can be used to see if there is a significant difference between these two models. Any number of models can be compared using the F-test by testing two at a time. . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
