Parameter Values p1 and p2

The function of a curve f(x) has two fixed parameter values that define its shape, along with the independent variable x. We call these values p1 and p2.  In order to fit a curve to our data that minimizes the RSS, we need to approximate the parameter values.

In the case of Linear Regression, we can find these values with equations.

The Special Case of Linear Regression

With Nonlinear Regression, the parameter values aren't as easily determinable.  We are forced to rely upon a process of trial and error to discover p1 and p2.  This concept is more easily understood with a visual representation.

Nonlinear Regression: A Graphical Representation