Frontier estimation via kernel regression on high power-transformed data

Stéphane Girard (1) , Pierre Jacob (2)

1 LMC - IMAG - Laboratoire de Modélisation et Calcul
2 I3M - Institut de Mathématiques et de Modélisation de Montpellier

We present a new method for estimating the frontier of a multidimensional sample. The estimator is based on a kernel regression on the power-transformed data. We assume that the exponent of the transformation goes to infinity while the bandwidth of the kernel goes to zero. We give conditions on these two parameters to obtain almost complete convergence and asymptotic normality. The good performance of the estimator is illustrated on some finite sample situations.

Mots clés: frontier estimation; kernel estimator; power-transform; frontier estimation.

Domaines: Statistiques [math.ST]

Stéphane Girard, Pierre Jacob. Frontier estimation via kernel regression on high power-transformed data. 2006. ⟨hal-00077683v1⟩