On the asymptotic distribution of Matusita's overlapping measure

Moh'D Taleb Suleiman Alodat, Moh'D Taleb Suleiman Alodat*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this paper, we study the asymptotic distribution of the plug-in kernel density estimator of the Matusita's overlapping measure. By utilizing the convergence of functional of stochastic processes, we show, under certain conditions, that the asymptotic distribution of the plug-in kernel density estimator (KDE) of Matusita's overlapping measure is normal distribution. Also, a small simulation study is conducted to support the theoretical finding of this paper. Furthermore, we apply our finding to a breast cancer data.
Original languageEnglish
JournalCommunications in Statistics - Theory and Methods
Publication statusPublished - 2021

Keywords

  • Asymptotic distribution
  • kernel density estimation
  • limiting distribution
  • Matusita's overlapping measure
  • breast cancer

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