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The foregoing argument leads to the generic procedure of grouped graphical Granger modeling method, exhibited in Figure 1.
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By combining the efficiency of low-fidelity models and the accuracy of high-fidelity models, our method exhibits fast convergence with a limited number of high-fidelity simulations.
A comparison between the thermal properties obtained by the numerical model and the TPS method exhibited a relative error in the range of 2 10%.
We then chose the model with the lowest standard error of residuals (the Huber method exhibited the lowest standard error for the model residuals for all indicators except adjusted hospital readmissions, see Additional File 2 Annex 2).
(The method exhibited less-than-ideal performance in our simulation study, likely due to poor model fit with the simulated error structures).
These results implied that the proposed method exhibited satisfactory reproducibility.
The OG method exhibited less noise than the 4D method.
All miRNAs analyzed by this method exhibited the expected sizes.
In [26], the authors deal with RSSI-based localization in an unknown path loss model and the proposed method exhibits better performance at low signal-to-noise ratio.
While maintaining accuracy, the unconditionally stable FADI-FDTD method exhibits high efficiency in modeling hemoglobin.
Therefore, this method exhibits strong modeling effectiveness and reliability, and can be an efficient alternative method for estimating regional 3D IED models.
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