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The GMM Problem as One of the Estimation Methods of a Probability Density Function

  • Kiyoshi Tsukagoshi
  • Kenichi Ida
  • Takao Yokota
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8210)

Abstract

In data analysis, we must be conscious of the probability density function of population distribution. Then it is a problem why the probability density function is expressed.

The estimation of a probability density function based on a sample of independent identically distributed observations is essential in a wide range of applications. The estimation method of probability density function – (1)a parametric method (2)a nonparametric method and (3)a semi-parametric method etc. – it is. In this paper, GMM problem is taken up as a semi-parametric method and We use a wavelet method as a powerful new technique. Compactly supported wavelets are particularly interesting because of their natural ability to represent data with intrinsically local properties.

Keywords

GMM wavelet probability density function Compactly supported kernel 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Kiyoshi Tsukagoshi
    • 1
  • Kenichi Ida
    • 2
  • Takao Yokota
    • 1
  1. 1.Faculty of EngineeringAshikaga Institute of TechnologyAshikaga CityJapan
  2. 2.Faculty of EngineeringMaebashi Institute of TechnologyMaebashi CityJapan

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