GeneralLinear.SumSquaresError Method 

Evaluates the sum of the squares due to error (often referred to as SSE) for the (multi-linear) regression considered.

Return Value

The sum of the squares due to error (SSE).

Remarks

Further Details

The SSE is the sum of the squares of the distances in the y-coordinate between the regression function and each of the data points. That is, the SSE is evaluate as follows:

SSE = Sum of (yi - Ri)2,

where yi is the value of the second coordinate of the i-th data point to which the regression function is fitted, and Ri is the value of regression function evaluated at the i-th data point.

Remarks:

1. This notion of SSE is closely related to that of Chi-Squared (see GetChiSquare()) however here we do not take into account any measurement errors.
2. The sum of the squares due to error (SSE) is always less than the Total Sum of Squares (SST) evaluated using TotalSumSquares() since the regression function is chosen in a way that minimizes the variability.

Preconditions

Please note that before this method is called you must have already performed the following tasks:

1. Set the Fitting Function using SetFunctionBasis
2. Fit the function using SetGeneralFit

See Also

GeneralLinear Class | WebCab.COM.Statistics.CurveFitting Namespace