User`s guide

2 Importing, Viewing, and Preprocessing Data

2-40

Additional Preprocessing Steps

Additional preprocessing steps not available through the Curve Fitting

Toolbox GUIs include

• Transforming the response data

• Removing

Infs, NaNs, and outliers

Transforming the Response Data

In some circumstances, you might want to transform the response data.

Common transformations include the logarithm ln(y), and power functions

such as y

1/2

, y

-1

, and so on. Using these transformations, you can linearize a

nonlinear model, contract response data that spans one or more orders of

magnitude, or simplify a model so that it involves fewer coefficients.

Note You must transform variables at the MATLAB command line, and then

import those variables into the Curve Fitting Toolbox. You cannot transform

variables using any of the graphical user interfaces.

For example, suppose you want to use the following model to fit your data.

If you decide to use the power transform y

-1

, then the transformed model is

given by

As another example, the equation

becomes linear if you take the log transform of both sides.

You can now use linear least squares fitting procedures.

bx c++

-------------------------------=

1–

bx c++=

yae

y()ln a() bx+ln=