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arXiv · 1112.2093

Green's function based unparameterised multi-dimensional kernel density and likelihood ratio estimator

Peter Kovesarki·Ian C. Brock·A. Elizabeth Nuncio Quiroz
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Abstract

This paper introduces a probability density estimator based on Green's function identities. A density model is constructed under the sole assumption that the probability density is differentiable. The method is implemented as a binary likelihood estimator for classification purposes, so issues such as mis-modeling and overtraining are also discussed. The identity behind the density estimator can be interpreted as a real-valued, non-scalar kernel method which is able to reconstruct differentiable density functions.

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Peter Kovesarki, Ian C. Brock, A. Elizabeth Nuncio Quiroz. 2012-04-18. Green's function based unparameterised multi-dimensional kernel density and likelihood ratio estimator. https://doi.org/10.1088/1742-6596%2F368%2F1%2F012041

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