2]: coefficient of determination; DSD: degree of spatial dependence; SSR: Sum of squared residuals
0] denote the panel sum of squared residuals
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).