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 ...
This is a preview. Log in through your library . Abstract A method is proposed for creating a smooth kernel density estimate from a sample of binned data. Simulations indicate that this method ...
The `curse of dimensionality' has been interpreted as suggesting that kernel methods have limited applicability in more than several dimensions. In this note, qualitative and quantitative performance ...
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