Nonlinear Regression Loss Function
The loss function in nonlinear regression is the function that is minimized by the algorithm. Select either Sum of squared residuals to minimize the sum of the squared residuals or User-defined loss function to minimize a different function.
If you select User-defined loss function, you must define the loss function whose sum (across all cases) should be minimized by the choice of parameter values.
- Most loss functions involve the special variable RESID_, which represents the residual. (The default Sum of squared residuals loss function could be entered explicitly as RESID_**2.) If you need to use the predicted value in your loss function, it is equal to the dependent variable minus the residual.
- It is possible to specify a conditional loss function using conditional logic.
You can either type an expression in the User-defined loss function field or paste components of the expression into the field. String constants must be enclosed in quotation marks or apostrophes, and numeric constants must be typed in American format, with the dot as a decimal delimiter.
Defining a Loss Function
This feature requires the Regression option.
- From the menus choose:
- In the Nonlinear Regression dialog box, select one or more parameters and click Loss.
- You can either type an expression in the User-defined loss function field or paste components of the expression into the field.