Sentence examples for sum of squared data from inspiring English sources

The slip distribution, which minimizes the sum of squared data misfit and the sum of the smoothness terms with a hyper-parameter, is the optimum solution.

Indeed, the relative contribution of a penalty function for smoothing [Eq. (4)] to the sum of squared data misfit, which was determined by ABIC, was very large.

It is shown in [22, Chapter 5] that solving the instantaneous problem obtained from drift-plus-penalty policy in the case of infinite buffer capacities (i.e., when the constraints C3 and C6 are not imposed) provides a utility (4a) that has a gap of (frac {D}{V}) from its optimal value, where D is a constant related to sum of the squared data arrivals and squared transmission rates.

The estimates from the Logistic model were used because this model best fitted the experimental data, as attested by the lowest residual sums of squares (data not shown).

The deviation of the model from experimental data was calculated from the sum of squared deviations between data and prediction (SS) provided by COPASI and from absolute deviations between fitted and experimental values.

Moreover, the sum of squared deviations between data and prediction was not significantly affected when a single k parameter was used for all three phosphatases.

Rather than minimize the sum of squared residuals for all data points included in ordinary least squares regression, LTS minimizes the sum of squared residuals for a subset of data points that minimizes the sum of squared residuals to remove the influence of outliers from the regression.

Following simulation of the model with the random values, the overall relative sum of squared deviations from the experimental data was calculated as well as the relative deviation at each experimental time point.

Experimental results reveal that model curves gained by this proposed method are in good agreement with the measured data with smaller sum of squared error.

θ is determined by searching the minimum sum of squared residuals between the estimated and observed data among all basis functions.

Since the original data showed daily frequency of onset only, we fitted the cumulative distribution of the incubation period to the observed data, minimising the sum of squared errors.