Nonlinear Regression Parameter Constraints

A constraint is a restriction on the allowable values for a parameter during the iterative search for a solution. Linear expressions are evaluated before a step is taken, so you can use linear constraints to prevent steps that might result in overflows. Nonlinear expressions are evaluated after a step is taken.

Each equation or inequality requires the following elements:

• An expression involving at least one parameter in the model. Type the expression or use the keypad, which allows you to paste numbers, operators, or parentheses into the expression. You can either type in the required parameter(s) along with the rest of the expression or paste from the Parameters list at the left. You cannot use ordinary variables in a constraint.
• One of the three logical operators <=, =, or >=.
• A numeric constant, to which the expression is compared using the logical operator. Type the constant. Numeric constants must be typed in American format, with the dot as a decimal delimiter.

Specifying Nonlinear Regression Parameter Constraints

This feature requires the Regression option.

1. From the menus choose:

   Analyze > Regression > Nonlinear…

2. In the Nonlinear Regression dialog box, click Constraints.
3. For each constraint, define the following elements:
   • An expression involving at least one parameter in the model. Type the expression or use the keypad, which allows you to paste numbers, operators, or parentheses into the expression. You can either type in the required parameter(s) along with the rest of the expression or paste from the Parameters list at the left. You cannot use ordinary variables in a constraint.
   • One of the three logical operators <=, =, or >=.
   • A numeric constant, to which the expression is compared using the logical operator. Type the constant. Numeric constants must be typed in American format, with the dot as a decimal delimiter.
4. After defining each constraint, click Add to add it to the constraint list.