A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample

Robert L. Vogel; Hani M. Samawi

A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample

Georgia Southern University

Research output: Contribution to conference › Presentation

Abstract

In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.

Original language	American English
State	Published - Mar 23 2011
Event	Eastern North American Region International Biometric Society Annual Conference (ENAR) - Duration: Mar 15 2015 → …

Conference

Conference	Eastern North American Region International Biometric Society Annual Conference (ENAR)
Period	03/15/15 → …

Disciplines

Biostatistics
Public Health

Keywords

Nonparametric test of symmetry
Overlapping coeffient
Extreme ranked set sample

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

https://www.enar.org/meetings/meetings2011/2011_preliminary_program.pdf

Cite this

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title = "A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample",

abstract = " In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.",

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author = "Vogel, {Robert L.} and Samawi, {Hani M.}",

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T1 - A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample

AU - Vogel, Robert L.

AU - Samawi, Hani M.

PY - 2011/3/23

Y1 - 2011/3/23

N2 - In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.

AB - In this paper we provide a more efficient nonparametric test of symmetry based on the empirical overlap coefficient using kernel density estimation applied to an extreme order statistics, namely extreme ranked set sampling. Our simulation investigation reveals that our proposed test of symmetry is at least as powerful as currently available tests of symmetry. Intensive simulation is conducted to examine the power of the proposed test. An illustration is provided using cardiac output and body weight of neonates in a neonatal intensive care unit.

KW - Nonparametric test of symmetry

KW - Overlapping coeffient

KW - Extreme ranked set sample

UR - https://digitalcommons.georgiasouthern.edu/biostat-facpres/62

UR - https://www.enar.org/meetings/meetings2011/2011_preliminary_program.pdf

M3 - Presentation

T2 - Eastern North American Region International Biometric Society Annual Conference (ENAR)

Y2 - 15 March 2015

ER -

A More Efficient Nonparametric Test of Symmetry Based on the Overlapping Coefficient Using Extreme Ranked Set Sample

Abstract

Conference

Disciplines

Keywords

UN SDGs

Access to Document

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Cite this