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Table 4 shows the GOF for the SEM model, measured by χ2, χ2/DF, GFI, CFI, and RMSEA.

The predictive accuracy of the three-factor model measured by sensitivity, specificity, and balanced accuracy is >70% of both the unadjusted and adjusted models (Table 5).

The analysis of the impact of changes to individual parameters on the observation of chaoticity is consistent with our observations with respect to the other properties investigated (similarity to the original model measured by the cost function, similarity to the original model measured by trend changes in the dependence of ISI, IBI, etc. on current injection).

Moreover, the alterations in brain metabolite concentrations in this model measured by in vivo 1H MRS, particularly N-acetylaspartate/Creatine (NAA/Cr), are very similar to those found in people with HAND.

Model's performances of the final model measured by the goodness of fit statistic and the C statistic were assessed.

At each stage, we calculate the improvement in the predictive accuracy of the model, measured by the percentage of explained variation and area under the ROC curve.

Figure 4 Break-in times for UK make-models measured by the "WhatCar?" Security Supertest in 2000 and 2003.

The prediction capabilities of individual QSAR models, measured by q ext 2 for the test set containing 2376 molecules, ranged from 0.572 to 0.659.

Overall, the performance of the models is slightly better with a time-varying price of risk, which, however, goes with a higher complexity of the models, measured by the number of parameters.

Performance of the models measured by the determination coefficient (mathrm{r}^{2}) when restricted to pairs of nodes for which the real flows are above a given threshold value.

As shown in Table 3, the performances of the univariate models measured by AIC and RMSE for the fitting dataset were similar.