Abstract: Kernel density estimation (KDE), a flexible nonparametric technique unconstrained by specific data distribution assumptions, is extensively employed in fault modeling. However, its ...
Paying invoices sounds simple enough. A vendor creates an invoice and sends a bill, your team approves it, and the money goes out. In practice, though, invoice payments are where a lot of finance ...
To analyse stroke rate (SR) and stroke length (SL) combinations among elite swimmers to better understand stroke strategies across all race distances of freestyle events. We analysed SR and SL data ...
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 KDE plots ...
Measuring the density of a cell can reveal a great deal about the cell’s state. As cells proliferate, differentiate, or undergo cell death, they may gain or lose water and other molecules, which is ...
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 ...
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 ...
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