Purpose: This study introduces two-dimensional (2D) Kernel Density Estimation (KDE) plots as a novel tool for visualising Training Intensity Distribution (TID) in biathlon. The goal was to assess how ...

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This paper studies nonparametric estimation of parameters of multivariate Hawkes processes. We consider the Bayesian setting and derive posterior concentration rates. First, rates are derived for ...

Consider the problem of finding a predictive density of a new observation drawn independently of observations sampled from a multivariate normal distribution with the same unknown mean vector and the ...

Density estimation methods often involve kernels, but there are advantages to using splines. Especially if the shape of the density is known to be decreasing, or unimodal, or bimodal, or if the ...

ABSTRACT: In real-world applications, datasets frequently contain outliers, which can hinder the generalization ability of machine learning models. Bayesian classifiers, a popular supervised learning ...

Umama Ali is an experienced content writer with a passion for gaming. He has been immersed in video games for as long as he can remember. When he is not playing video games, he can be found playing ...

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation ...