Definition
The problem of model discrimination arises when several models are proposed to describe one and the same process. To identify the best model from the set of rival models, it may be necessary to collect new information about the process, and thus, additional experiments have to be performed.
Optimal experimental design for model discrimination refers to the experimental design methodologies that are used to find the experimental conditions that allow to discriminate among rival models with the least experimental effort.
Characteristics
Model Discrimination
The aim of any modeling exercise is to obtain a mathematical modelthat adequately describes and even predicts the process behavior. However, it is important to realize that lack of insight in the modeled process may result in the proposal of several so-called rival models, each of which represents a certain hypothesis of how the process works. The problem of identifying the best model from a set of rival models is...
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References
Buzzi-Ferraris G, Forzatti P, Emig G, Hofmann H (1984) Sequential experimental design procedure for model discrimination in the case of multiple responses. Chem Eng Sci 39(1):81–85
Donckels BMR, De Pauw DJW, De Baets B, Maertens J, Vanrolleghem PA (2009) An anticipatory approach to optimal experimental design for model discrimination. Chemometr Intell Lab Syst 95(1):53–63
Hunter WG, Reiner AM (1965) Designs for discriminating between two rival models. Technometrics 5:307–323
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Donckels, B.M.R. (2013). Optimal Experimental Design, Model Discrimination. In: Dubitzky, W., Wolkenhauer, O., Cho, KH., Yokota, H. (eds) Encyclopedia of Systems Biology. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-9863-7_1228
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DOI: https://doi.org/10.1007/978-1-4419-9863-7_1228
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