Sentence examples for model statistical quality from inspiring English sources

Model statistical quality measures (R2, NSE and KGE) achieved during calibration and validation ranged between 0.6 and 0.9 for total discharge, soil moisture, and groundwater level, indicating a good agreement between observed and simulated variables.

The best partial least squares (PLS) model outperforms the previously reported multiple linear regression (MLR) model in statistical quality and predictive ability (R2 = 0.955, Q2 = 0.917, Rpred2= 0.848).

The best CoMSIA model gave significant statistical quality.

The present model showed high statistical quality as confirmed by its robust predictive potential and satisfactory descriptive capability.

It could be concluded that 3D kernel approach is a robust and highly accurate classification technique that can be successfully applied to derive statistical models with statistical qualities and predictive capabilities for the protein location and function.

It has been shown that a simple molecular descriptor χox can efficiently encode cytotoxicity of metal oxides leading to models with high statistical quality as well as interpretability.

The best ETA model (Q2=0.938; R2pred=0.923) could outperform in statistical quality and predictive ability the models developed with non-ETA (Q2=0.910; R2pred=0.885) and combined set (ETA and non-ETA) of descriptors (Q2=0.926; R2pred=0.915).

With stepwise regression 23 descriptors were selected and a simple ''break point'' technique was used to control the model expansion in the improvement of the statistical quality of the model, by analyzing the plot of the number of descriptors involved in the obtained models versus squared correlation coefficient values corresponding to those models (Figure 2).

From the results, it is clear that the best ETA model shows reliable prediction of the logCMC values and the statistical quality of the model is comparable with the corresponding non-ETA model.

Pressures within health care systems are driving a need for robust clinical risk-prediction models to inform care provision, but, to be useful, these models must be of high statistical quality and be clinically relevant.

Statistical quality of QSAR models developed from all splits was very good and fulfilled the criteria.