Nonparametric methods provide a flexible framework for estimating the probability density function of random variables without imposing a strict parametric model. By relying directly on observed data, ...

This is a preview. Log in through your library . Abstract Let x1, ⋯, xn be independent observations on a p-dimensional random variable X = (X1, ⋯, Xp) with absolutely continuous distribution function ...

A database on the rain rate collected with disdrometers at various sites located from the middle to tropical latitudes is used to analyze the variations of the parameters of the probability density ...

Kernel density estimation (KDE) and nonparametric methods form a cornerstone of contemporary statistical analysis. Unlike parametric approaches that assume a specific functional form for the ...