2]: coefficient of determination; DSD: degree of spatial dependence; SSR:

Sum of squared residuals.

0] denote the panel

sum of squared residuals under [H.

Greene (Greene, 1992) concludes that the nonlinear regression model could be characterized (defined) as being a model for which the so-called normal equations (obtained by annulling the partial derivatives of the

sum of squared residuals with respect to every unknown, when using the least squares method) are nonlinear functions of parameters.

Considering only the range of numerators which did not produce outliers, the

sum of squared residuals (or squared numerical errors) was calculated.

Here RSSE is the

sum of squared residuals on fitting a quadratic equation to the combined sample, USSE is obtained on adding the

sum of squared residuals of the quadratic equations fitted on each sample separately, and [n.

T] is the

sum of squared residuals from the whole sample period.

12]; therefore, a summary statistics using two measures; total absolute bias and

sum of squared residuals are included for this study.

The fitness function is the minimum of the

sum of squared residuals of measured and simulated return temperatures:

Once all potential break points have been considered, the break point associated with the lowest

sum of squared residuals is chosen, which is then associated with the values of the fractional integration parameters.

MAT] be the

sum of squared residuals from the combined data, [S.

Just as we can define the sample mean as the solution to the problem of minimizing a

sum of squared residuals, we can define the median as the solution to the problem of minimizing a sum of absolute residuals (Koenker and Hallock 2001).

However, the

sum of squared residuals can be excessively influenced by observations with unusually large residuals (Huber 1980).