KL-optimal experimental design for discriminating between two growth models applied to a beef farm

Santiago  Campos-Barreiro; Jesús  López-Fidalgo

doi:10.3934/mbe.2016.13.67

Article Contents

2016, Volume 13, Issue 1: 67-82. Doi: 10.3934/mbe.2016.13.67

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KL-optimal experimental design for discriminating between two growth models applied to a beef farm

Santiago Campos-Barreiro^1, and
Jesús López-Fidalgo^1,

1.
Institute of Mathematics Applied to Science and Engineering, University of Castilla-La Mancha, 13071-Ciudad Real

Received: February 28, 2015

Revised: May 31, 2015

Published: September 2015

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Abstract

The body mass growth of organisms is usually represented in terms of what is known as ontogenetic growth models, which represent the relation of dependence between the mass of the body and time. The paper is concerned with a problem of finding an optimal experimental design for discriminating between two competing mass growth models applied to a beef farm. T-optimality was first introduced for discrimination between models but in this paper, KL-optimality based on the Kullback-Leibler distance is used to deal with correlated obsevations since, in this case, observations on a particular animal are not independent.

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Mathematics Subject Classification: 62k05.

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