title: KL-optimal experimental design for discriminating between two growth models applied to a beef farm.
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.
authors.affiliation: Institute of Mathematics Applied to Science and Engineering, University of Castilla-La Mancha, 13071-Ciudad Real, Spain. email:santiagocamposbarreiro@gmail.com.
authors.forename: Santiago
authors.initials: S
authors.lastname: Campos-Barreiro
authors.forename: Jesús
authors.initials: J
authors.lastname: López-Fidalgo
mesh_terms: D000375:Aging / Q000502:physiology*; D000383:Agriculture / Q000379:methods*; D000465:Algorithms; D000818:Animals; D001835:Body Weight / Q000502:physiology*; D002417:Cattle / Q000254:growth & development*; D003198:Computer Simulation; D008954:Models, Biological; D000069466:Red Meat; D015203:Reproducibility of Results; D012107:Research Design; D012680:Sensitivity and Specificity; D013030:Spain