Frontier estimation with local polynomials and high power-transformed data

Stephane Girard 1 Pierre Jacob 2
1 MISTIS - Modelling and Inference of Complex and Structured Stochastic Systems
Inria Grenoble - Rhône-Alpes, LJK - Laboratoire Jean Kuntzmann, INPG - Institut National Polytechnique de Grenoble
Abstract : We present a new method for estimating the frontier of a sample. The estimator is based on a local polynomial regression on the power-transformed data. We assume that the exponent of the transformation goes to infinity while the bandwidth goes to zero. We give conditions on these two parameters for obtaining almost complete convergence. The asymptotic conditional bias and variance of the estimator are provided and its good performance is illustrated for some finite sample situations.
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Article dans une revue
Journal of Multivariate Analysis, Elsevier, 2009, 100 (8), pp.1691-1705. 〈10.1016/j.jmva.2009.01.011〉
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https://hal.archives-ouvertes.fr/hal-00384731
Contributeur : Stephane Girard <>
Soumis le : vendredi 15 mai 2009 - 17:17:59
Dernière modification le : mercredi 11 avril 2018 - 01:59:08

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Stephane Girard, Pierre Jacob. Frontier estimation with local polynomials and high power-transformed data. Journal of Multivariate Analysis, Elsevier, 2009, 100 (8), pp.1691-1705. 〈10.1016/j.jmva.2009.01.011〉. 〈hal-00384731〉

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