Nonlinear Regression: The NLIN Procedure

Introduction to Regression Procedures

Nonlinear Regression: The NLIN Procedure

The NLIN procedure implements iterative methods that attempt to find least-squares estimates for nonlinear models. The default method is Gauss-Newton, although several other methods, such as Gauss or Marquardt, are available. You must specify parameter names, starting values, and expressions for the model. For some iterative methods, you also need to specify expressions for derivatives of the model with respect to the parameters. A grid search is also available to select starting values for the parameters. Since nonlinear models are often difficult to estimate, PROC NLIN may not always find the globally optimal least-squares estimates.

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