U-statistics represent a fundamental class of statistics from modeling quantities of interest
defined by multi-subject responses. U-statistics generalize the empirical mean of a random …

The paper proposes a new nonparametric scheme for multivariate density estimation under
the framework of quasi-interpolation, a classical function approximation scheme in …

High-resolution palmprint recognition is a challenging problem due to deficiencies in
images, such as poor quality, skin distortion, and unallocated images. Considering the …

The nature of the kernel density estimator (KDE) is to find the underlying probability density
function (pdf) for a given dataset. The key to training the KDE is to determine the optimal …

Multiquadric (MQ) quasi-interpolation has been extensively studied in approximation theory
and its applications. However, most of them only focus on the case that the sampling data …

Density estimation of streaming data is a relevant task in numerous domains. In this paper, a
novel non-parametric density estimator called FRONT (forest of normalized trees) is …

When smoothing a function $ f $ via convolution with some kernel, it is often desirable to
adapt the amount of smoothing locally to the variation of $ f $. For this purpose, the constant …

Density estimation is a standard tool for investigating attributes of a continuous distribution
assumed to have generated a finite sample of data. Performing density estimation in a …