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Simulations have been used to study the application of model discrimination methods to the problem of discriminating between the terminal and penultimate copolymerization models on the basis of composition and rate data.
Both models are reviewed and the three model discrimination methods chosen for study are explained.
To determine the most plausible model candidate is the objective of model selection or model discrimination methods.
Differences between the three model discrimination methods are discussed along with differences between the three copolymer measurements that have been studied.
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These findings highlight the possibility of distinguishing between mechanisms that implement a given biological function using simple models, empowered by model-discrimination methods such as those presented in this work.
Some methods change model discrimination and calibration, whereas others only modify model calibration [ 43].
An optimal experimental design method for model discrimination for polynomial uncertain systems is presented that can be used to discriminate models based on dissimilarity of the probability densities of the model outputs.
Comparison of the model to other models for fluid solid reactions is presented together with the method for model discrimination.
Agreement between calculated and experimentally determined eigenfunctions testifies to the validity of the present method of model discrimination.
Model discrimination was assessed using several complementary methods.
We highlight this point by developing, in our specific modelling framework, the frame discrimination method initially proposed in [26].
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