Nonlinear regression is a procedure for fitting data to any selected
equation. As with linear regression, nonlinear regression procedures
determine values of the parameters that minimize the sum of the
squares of the distances of the data points to the curve. The general
nonlinear regression model is Y ¼ fðX; βÞþε, for Y ¼ ½Y1; Y2; …; Yn
T ,
X ¼ ½X1; X2; …; Xn
T , β ¼ ½β1; β2; …; βn
T , and ε ¼ ½ε1; …; εn. But in
this paper, owing to the parabolic regression model, we need to use
the equation Y ¼ β0 þβ1Xþβ2X2 þε.
S