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Proceedings Paper

Nonparametric density estimation with adaptive varying window size
Author(s): Vladimir Katkovnik; Ilya Shmulevich
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Paper Abstract

We propose a new method of kernel density estimation with a varying adaptive window width. This method is different from traditional ones in two aspects. First, we use symmetric as well as nonsymmetric left and right kernels with discontinuities and show that the fusion of these estimates results in accuracy improvement. Second, we develop estimates with adaptive varying window widths based on the so-called intersection of confidence intervals (ICI) rule. Several examples of the proposed method are given for different types of densities and the quality of the adaptive density estimate is assessed by means of numerical simulations.

Paper Details

Date Published: 19 January 2001
PDF: 10 pages
Proc. SPIE 4170, Image and Signal Processing for Remote Sensing VI, (19 January 2001); doi: 10.1117/12.413890
Show Author Affiliations
Vladimir Katkovnik, Tampere Univ. of Technology (Finland)
Ilya Shmulevich, Tampere Univ. of Technology (Finland)


Published in SPIE Proceedings Vol. 4170:
Image and Signal Processing for Remote Sensing VI
Sebastiano Bruno Serpico, Editor(s)

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