A practical method for discriminating among mechanistic models

Abstract

Abstract 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