Density estimation is a fundamental component in statistical analysis, aiming to infer the probability distribution of a random variable from a finite sample without imposing restrictive parametric ...

The problem of using non-parametric methods to estimate multivariate density functions from incomplete continuous data does not appear to have been considered before. Methods of producing kernel ...

We prove, under mild conditions, the existence of a minimizer of the exact mean integrated square error of a kernel density estimator as a function of the bandwidth ...

In this paper we propose a novel approach to obtain the predictive density of global GDP growth. It hinges upon a bottom-up probabilistic model that estimates and combines single countries’ predictive ...