On the asymptotic distribution of Matusita’s overlapping measure

Moh'D Taleb Suleiman Alodat; Moh’d  Al Fayez; Omer Eidous

doi:10.1080/03610926.2020.1869260

On the asymptotic distribution of Matusita’s overlapping measure

Moh'D Taleb Suleiman Alodat, Moh’d Al Fayez, Omer Eidous

Mathematics

Research output: Contribution to journal › Article › peer-review

6 Citations (Scopus)

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 language	English
Article number	20
Pages (from-to)	6963
Number of pages	6977
Journal	Communications in Statistics - Theory and Methods
Volume	51
Issue number	20
DOIs	https://doi.org/10.1080/03610926.2020.1869260
Publication status	Published - 2022

Keywords

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

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title = "On the asymptotic distribution of Matusita{\textquoteright}s overlapping measure",

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.",

keywords = "Asymptotic distribution, kernel density estimation, limiting distribution, Matusita's overlapping measure, breast cancer",

author = "{Taleb Suleiman Alodat}, Moh'D and {Al Fayez}, Moh{\textquoteright}d and Omer Eidous",

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T1 - On the asymptotic distribution of Matusita’s overlapping measure

AU - Taleb Suleiman Alodat, Moh'D

AU - Al Fayez, Moh’d

AU - Eidous, Omer

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Asymptotic distribution

KW - kernel density estimation

KW - limiting distribution

KW - Matusita's overlapping measure

KW - breast cancer

UR - https://doi.org/10.1080/03610926.2020.1869260

U2 - 10.1080/03610926.2020.1869260

DO - 10.1080/03610926.2020.1869260

M3 - Article

SN - 0361-0926

VL - 51

SP - 6963

JO - Communications in Statistics - Theory and Methods

JF - Communications in Statistics - Theory and Methods

IS - 20

M1 - 20

ER -

On the asymptotic distribution of Matusita’s overlapping measure

Abstract

Keywords

UN SDGs

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