AKDE provides an accurate, adaptive kernel density estimator based on the Gaussian Mixture Model for multidimensional data. This Python implementation includes automatic grid construction for ...

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 ...

Abstract: This article investigates a novel robust Kalman filter (RKF) by incorporating kernel density estimation (KDE) in the Kalman filtering framework to address the disturbance of measurement ...

Erratum: Measurement of Completeness and Timeliness of Linked Electronic Health Record Pharmacy Data for Early Detection of Nonadherence to Breast Cancer Adjuvant Endocrine Therapy The article by ...

ABSTRACT: The Negative Binomial Multiple Change Point Algorithm is a hybrid change detection and estimation approach that works well for overdispersed and equidispersed count data. This simulation ...

We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using ...

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 ...

A wolverine walks across the snow in 2018 near the Toolik Field Station on Alaska's North Slope. Wolverines are elusive and need a lot of space, so they are hard to count, but a new study gives an ...

Abstract: This paper proposes a data-driven robust scheduling method for power systems incorporating variable energy. Robust kernel density estimation (RKDE) is combined with distributionally robust ...