Sentence examples for sum of absolute errors from inspiring English sources
The sum of absolute errors is expressed by the equation: {text{SAE}} = sumlimits_{i = 1}^{n} {left| {q_{{{text{e}}({text{cal}})}} - q_{{{text{e}}(exp )}} } right|}.
The complete error analysis using six non-linear error functions: Chi-square (χ2); sum of square errors (SSE); composite fractional error function (HYBRD); derivative of Marquardt's percent standard deviation (MPSD); average relative error (ARE); sum of absolute errors (EABS) were calculated.
The method of least squares was used for obtaining the isotherm constants, and error analysis using the following functions [37] confirmed the model of best fit: sum of squares of errors (SSE), sum of absolute errors (EABS), average relative error (ARE) and nonlinear Chi-test as shown in Table 4.
For each randomly selected object (o_{j'}), one of the original (k) centers, say (o_{j}), will be replaced with it and its new sum (E') of absolute errors will be calculated.
Eilers and Menezes [ 7] perform a quantile smoothing method based on the minimization of the sum of absolute errors to create sharper boundaries between segments.
This improvement in performance is further reflected by the smaller sum of absolute errors across dye spot locations for the SPLASSO, 8.6 as compared to the the LASSO, 16.
The best models that described the adsorption data were determined by looking at the values of the R2 and two error functions which are the sum of absolute error (EABS) and Chi-square test (χ2) as shown in Eqs.
Mean absolute error (MAE): mean of absolute errors between estimated prediction error degrees and their true degrees.
Validation showed that average of absolute errors was 0.029.
The resulting mean of absolute errors was 2.0 kcal/mol.
To confirm the best model for the adsorption system, it is necessary to analyze the data using errors analysis like sum of the absolute errors (SAE) combined with the values of determined correlation coefficient r 2. The results of these analyses are tabulated in Table 2.
