A quantile-copula approach to conditional density estimation.

Olivier P. Faugeras (1)

1 LSTA - Laboratoire de Statistique Théorique et Appliquée

We present a new non-parametric estimator of the conditional density of the kernel type. It is based on an efficient transformation of the data by quantile transform. By use of the copula representation, it turns out to have a remarkable product form. We study its asymptotic properties and compare its bias and variance to competitors based on nonparametric regression.

Mots clés: conditional density; copula; nonparametric estimation; quantile transform; regression.; regression

Domaines: Méthodologie [stat.ME]; Théorie [stat.TH]; Statistiques [math.ST]

Olivier P. Faugeras. A quantile-copula approach to conditional density estimation.. 2007. ⟨hal-00172589v4⟩