The paper introduces a n-consistent estimator of the probability density function of the response variable in a nonparametric regression model. The proposed estimator is shown to have a (uniform) asymptotic normal distribution, and it is computationally very simple to calculate. A Monte Carlo...

In this paper we provide a method for estimating multivariate distributions defined through hierarchical Archimedean copulas. In general, the true structure of the hierarchy is unknown, but we develop a computationally efficient technique to determine it from the data. For this purpose we...

We propose a semi-parametric mode regression estimator for the case in which the dependent variable has a continuous conditional density with a well-defined global mode. The estimator is semi-parametric in that the conditional mode is specified as a parametric function, but only mild assumptions...