Prediction of Euclidean distances with discrete and continuous outcomes

Mortier Frédéric, Robin S., Lassalvy Stéphane, Baril C.P., Bar-Hen Avner. 2006. Prediction of Euclidean distances with discrete and continuous outcomes. Journal of Multivariate Analysis, 97 : 1799-1814.

https://doi.org/10.1016/j.jmva.2005.06.010

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Liste HCERES des revues (en SHS) : oui

Thème(s) HCERES des revues (en SHS) : Economie-gestion; Psychologie-éthologie-ergonomie

Résumé : The objective of this paper is first to predict generalized Euclidean distances in the context of discrete and quantitative variables and then to derive their statistical properties. We first consider the simultaneous modelling of discrete and continuous random variables with covariates and obtain the likelihood. We derive an important property useful for its practical maximization. We then study the prediction of any Euclidean distances and its statistical proprieties, especially for the Mahalanobis distance. The quality of distance estimation is analyzed through simulations. This results are applied to our motivating example: the official distinction procedure of rapeseed varieties. © 2005 Elsevier Inc. All rights reserved.

Mots-clés Agrovoc : modèle mathématique, analyse quantitative, méthode statistique

Classification Agris : U10 - Informatique, mathématiques et statistiques
K10 - Production forestière

Champ stratégique Cirad : Hors axes (2005-2013)

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