Parameter Estimates - Nonlinear Models

In a simple nonlinear model, even with one parameter, the estimation is complicated. In order to remedy this, here there are the more common methods used for estimating parameters in nonlinear cases:

• ·         Linearization (Gauss-Newton) – Implemented in Minitab and SAS
• ·         Steepest Descent – Implemented in SAS (gradient)
• ·         Marquardt’s Compromise – Implemented in Minitab and SAS
• ·         Newton – Implemented in SAS

All techniques employ an iterative process until some minimum convergence has been reached.