Skip to main content

Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study

Abstract

The plug-in method enables optimization of the bandwidth of the kernel density estimator in order to estimate probability density functions (pdfs). Here, a faster procedure than that of the common plug-in method is proposed. The mean integrated square error (MISE) depends directly upon which is linked to the second-order derivative of the pdf. As we intend to introduce an analytical approximation of , the pdf is estimated only once, at the end of iterations. These two kinds of algorithm are tested on different random variables having distributions known for their difficult estimation. Finally, they are applied to genetic data in order to provide a better characterisation in the mean of neutrality of Tunisian Berber populations.

Publisher note

To access the full article, please see PDF.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Samir Saoudi.

Rights and permissions

Open Access This article is distributed under the terms of the Creative Commons Attribution 2.0 International License ( https://creativecommons.org/licenses/by/2.0 ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Troudi, M., Alimi, A.M. & Saoudi, S. Analytical Plug-In Method for Kernel Density Estimator Applied to Genetic Neutrality Study. EURASIP J. Adv. Signal Process. 2008, 739082 (2008). https://doi.org/10.1155/2008/739082

Download citation

Keywords

  • Information Technology
  • Quantum Information
  • Kernel Density
  • Density Estimator
  • Full Article