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A Goodness of Fit Approach to the Unknown Age (UBACT) Class of Life Distribution

by S.E. Abu-youssef, M.E. Bakr
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 1
Year of Publication: 2014
Authors: S.E. Abu-youssef, M.E. Bakr
10.5120/18037-7131

S.E. Abu-youssef, M.E. Bakr . A Goodness of Fit Approach to the Unknown Age (UBACT) Class of Life Distribution. International Journal of Computer Applications. 103, 1 ( October 2014), 12-17. DOI=10.5120/18037-7131

@article{ 10.5120/18037-7131,
author = { S.E. Abu-youssef, M.E. Bakr },
title = { A Goodness of Fit Approach to the Unknown Age (UBACT) Class of Life Distribution },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 1 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 12-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number1/18037-7131/ },
doi = { 10.5120/18037-7131 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:33:25.080638+05:30
%A S.E. Abu-youssef
%A M.E. Bakr
%T A Goodness of Fit Approach to the Unknown Age (UBACT) Class of Life Distribution
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 1
%P 12-17
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Based on the goodness of fit approach, a new test is presented for testing exponentiality versus used better than aged in convex tail ordering UBACT class of life distribution. The percentiles of this test are tabulated for sample sizes n=1(5)100. It is shown that the proposed test is simple and it has high relative efficiency for some commonly used alternatives. A numerical example in medical science demonstrates practical application of the proposed test.

References
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Index Terms

Computer Science
Information Sciences

Keywords

U-Statistics Goodness of fit approach UBACT class of life distribution Hypothesis testing.

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