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To compare the function of each model, the chemostat data published by Carnicer et al. (2012) were used to verify the predictive function of the models (see Additional file 4).
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Indeed, the present study showed low predictive ability of the models that employed CFR as a marker for microvascular function.
These results also demonstrate the predictive power of the models.
We evaluated the predictive ability of the models as follows.
Even the predictive ability of the models was rarely reported.
The procedure combined the selection of progressively smaller sets of SNPs and the classification of animals into carriers and non-carriers, thus allowing to assess the predictive ability of the model as a function of the number of SNPs.
By evaluating the predictive performance of the model, we provide a comprehensive quantification of the structure-function relationship based only on local structure similarity.
Furthermore, closed-loop transfer function representation of the model predictive control system facilitates the use of frequency response analysis methods for the nominal control performances of the system.
Despite the satisfactory performance of scaling function predictor several tests indicated that implementing a general linear model might further enhance the predictive power of the model.
Furthermore, closed-form transfer function representation of the model predictive control system enables the application of frequency response analysis tools to the nominal performance of the system.
This method provided the predictive ability of the model.
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