Nonparametric density estimation with adaptive varying window size

نویسندگان

  • Vladimir Katkovnik
  • Ilya Shmulevich
چکیده

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.

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Kernel density estimation with adaptive varying window size

A new method of kernel density estimation with a varying adaptive window size is proposed. It is based on the socalled 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. 2002 Elsevier Science B.V. All rights reserved.

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تاریخ انتشار 2000