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Article Dans Une Revue Journal of Multivariate Analysis Année : 2006

Prediction of euclidean distances with discrete and continuous outcomes

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.

Dates et versions

hal-01208115 , version 1 (01-10-2015)

Identifiants

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Frédéric Mortier, Stephane Robin, Stéphane Lassalvy, Claire Baril, Avner Bar-Hen. Prediction of euclidean distances with discrete and continuous outcomes. Journal of Multivariate Analysis, 2006, 97 (8), pp.1799-1814. ⟨10.1016/j.jmva.2005.06.010⟩. ⟨hal-01208115⟩
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