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A practical method for discriminating among mechanistic models
Author(s) -
Hsiang Thomas,
Reilly Park M.
Publication year - 1971
Publication title -
the canadian journal of chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.404
H-Index - 67
eISSN - 1939-019X
pISSN - 0008-4034
DOI - 10.1002/cjce.5450490626
Subject(s) - linearization , set (abstract data type) , computer science , bayesian probability , artificial intelligence , nonlinear system , physics , quantum mechanics , programming language
A method is presented for designing and analysing experiments for choosing the best mechanistic model among a set of more than one to describe a real‐world relationship. The method is a personalistic Bayesian one which does not depend on linearization of the models or on any specific form of the error distributions. Examples illustrating different types of applications of the method are given