Sentence examples for fitting indicators from inspiring English sources

The obtained results show that the 2-D NNGM best describes the experimental data providing parameters with adequate statistical fitting indicators.

Table 3 Logistic regression coefficients and model fitting indicators Variables Coefficient(B) Standard Error (S.E).

To better understanding the construct validity of SF-36 for migrant population, the CFA results are presented in Fig.  1, the goodness of fitting indicators are: GFI = 0.926, Chi-Square/Df = 2.059, RMSEA = 0.037, CFI = 0.939.

For example, fitting indicators for individual years yielded an estimate of reduction of 36.5% (29.5% to 43.5%) in all casualties within 20 mph zones and 42.0% (33.4% to 50.6%) for killed or seriously injured casualties.

These are now shown to outperform traditional approaches that fit indicator variables with fixed effects across time [ 62].

The model results indicated convergence problems and lower values for model fit indicators as compared to the two-class model.

The uncertainty of measured data included in the goodness-of-fit indicators is a more realistic method to evaluate model performance and data sets.

An advanced global inverse optimization technique is used for the model calibration process, and the uncertainty of the measured data is considered in goodness-of-fit indicators.

Measured retention efficiencies were compared to simulated values using VFSMOD based on goodness-of-fit indicators that take into account uncertainty linked to the measurements.

The proposed approach has been tested based on the results achieved using two goodness of fit indicators, Nash-Sutcliffe efficiency coefficient and median LH value which confirms high potential of designed GRNN for ranking of ground motion prediction equations.

The usefulness of the approach for the evaluation of model performance is illustrated with case studies including those with similar goodness-of-fit indicators but distinct statistical interpretation, and others to analyze the effects of outliers, model bias and repeated data.