In many cases, the experimenter is faced with a situation where there are several competing models (only one of which is correct) and he is unable to determine the correct model. The purpose of this article is to introduce optimality criteria for examining and identifying the correct model. In this regard, we will discuss two approaches: Bayesian and non-Bayesian. Although the Bayesian approach has some limitations, it has an advantage over the non-Bayesian approach in that it significantly reduces the dependence of the inferences made on the initial value of the parameters. In this article, in addition to introducing various criteria, we also present an algorithm for each, which is useful in obtaining numerically optimal designs.
Talebi, H. & zadeh Labaf, F. (2012). Optimality criteria for distinguishing the correct model from competing models. Andishe_ye Amari, 16(2), 57-70.
MLA
Talebi, H., & zadeh Labaf, F. "Optimality criteria for distinguishing the correct model from competing models", Andishe_ye Amari, 16, 2, 2012, 57-70.
HARVARD
Talebi H., zadeh Labaf F. (2012). 'Optimality criteria for distinguishing the correct model from competing models', Andishe_ye Amari, 16(2), pp. 57-70.
CHICAGO
H. Talebi & F. zadeh Labaf, "Optimality criteria for distinguishing the correct model from competing models," Andishe_ye Amari, 16 2 (2012): 57-70,
VANCOUVER
Talebi H., zadeh Labaf F. Optimality criteria for distinguishing the correct model from competing models. Andishe_ye Amari. 2012;16(2):57-70 (In Persian).
