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A New Test for Unknown Age Class of Life Distribution based on Laplace Transform Technique

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
S. E. Abu-Youssef, Nahd S. A. Ali, M. E. Bakr
10.5120/ijca2018916833

S E Abu-Youssef, Nahd S A Ali and M E Bakr. A New Test for Unknown Age Class of Life Distribution based on Laplace Transform Technique. International Journal of Computer Applications 180(33):21-27, April 2018. BibTeX

@article{10.5120/ijca2018916833,
	author = {S. E. Abu-Youssef and Nahd S. A. Ali and M. E. Bakr},
	title = {A New Test for Unknown Age Class of Life Distribution based on Laplace Transform Technique},
	journal = {International Journal of Computer Applications},
	issue_date = {April 2018},
	volume = {180},
	number = {33},
	month = {Apr},
	year = {2018},
	issn = {0975-8887},
	pages = {21-27},
	numpages = {7},
	url = {http://www.ijcaonline.org/archives/volume180/number33/29259-2018916833},
	doi = {10.5120/ijca2018916833},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Most of the approaches suggested during the last decades for solving life testing problems are markedly different from those used in the related but wider area of Laplace transform technique. In this paper, it is demonstrated that applying the Laplace transform technique makes sense also for solving life testing problems and that result in simpler procedures that are asymptotically equivalent or better than standard ones. A new test statistics for testing exponentiality against used better than age in the Laplace transform order aging class of life distribution (UBAL) is proposed. Pitman’s asymptotic efficiencies of this test are calculated and compared with other tests. The percentiles of this test statistic are tabulated for censored and non-censored data. Finally, examples in different areas are used as practical applications of the proposed test.

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Keywords

UBA and UBAL classes of life distributions; Testing hypothesis; Right censored data; Makeham, Weibull, Linear failure rate (LFR) distributions.