Based on a constructive representation, which distinguishes between a skewing mechanism P and an underlying symmetric distribution F, we introduce two flexible classes of distributions. They are generated by nonparametric ...

In this article, we develop a nonparametric estimator for the Hölder constant of a density function. We consider a simulation study to evaluate the performance of the proposal and construct smooth bootstrap confidence ...

Wood is a material widely used in various sectors of construction, such as in structures and building components. The volume of wood extracted from tropical forests has reached a considerable amount, and this wood is ...

A new methodology for density estimation is proposed. The method- ology, which builds on the one developed in [15], normalizes the data points through the composition of simple maps. The parameters of each map are determined ...

In this paper, we define a n-consistent nonparametric estimator for the marginal density function of an order one stationary process built up from a sample of i.i.d continuous time trajectories. Under mild conditions we ...

Durbin (1980a) proposed a simple method for obtaining asymptotic expansions for the densities of sufficient estimators. The expansion is a series which is effectively in powers of n-1, where n is the sample size, as compare ...

We review some aspects of nonparametric Bayesian data analysis with discrete random probability measures. We focus on the class of species sampling models (SSMs). We critically investigate the common use of the Dirichlet ...