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Reseach Article

Quasi Lindley Geometric Distribution

by L. S. Diab, Hiba Z. Muhammed
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 95 - Number 13
Year of Publication: 2014
Authors: L. S. Diab, Hiba Z. Muhammed
10.5120/16652-6628

L. S. Diab, Hiba Z. Muhammed . Quasi Lindley Geometric Distribution. International Journal of Computer Applications. 95, 13 ( June 2014), 9-16. DOI=10.5120/16652-6628

@article{ 10.5120/16652-6628,
author = { L. S. Diab, Hiba Z. Muhammed },
title = { Quasi Lindley Geometric Distribution },
journal = { International Journal of Computer Applications },
issue_date = { June 2014 },
volume = { 95 },
number = { 13 },
month = { June },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume95/number13/16652-6628/ },
doi = { 10.5120/16652-6628 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:19:20.616047+05:30
%A L. S. Diab
%A Hiba Z. Muhammed
%T Quasi Lindley Geometric Distribution
%J International Journal of Computer Applications
%@ 0975-8887
%V 95
%N 13
%P 9-16
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, we introduce a new class of lifetime distributions which is called the Quasi Lindley Geometric (QLG) distribution. This distribution obtained by compounding the Quasi Lindley and geometric distributions. Some structural properties of the proposed new distribution are discussed, including probability density function and explicit algebraic formulas for its survival and hazard functions, moment , moment generating function and mean deviations. We propose the method of maximum likelihood for estimating the model parameters and obtain the observed information matrix. A real data set is used to illustrate the importance and flexibility of the new distribution.

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Index Terms

Computer Science
Information Sciences

Keywords

Quasi Lindley distribution Geometric distribution Moments Maximum likelihood.