Discrete Weighted Exponential Distribution of the Second Type: Properties and Applications

Mahdi Rasekhi, Omid Chatrabgoun, Alireza Daneshkhah

Research output: Contribution to journalArticle

6 Downloads (Pure)

Abstract

In this paper, we propose a new lifetime model as a discrete version of the continuous weighted exponential distribution which is called discrete weighted exponential distribution (DWED). This model is a generalization of the discrete exponential distribution which is originally introduced by Chakraborty (2015). We present various statistical indices/properties of this distribution including reliability indices, moment generating function, probability generating function, survival and hazard rate functions, index of dispersion, and stress-strength parameter. We rst present a numerical method to compute the maximum likelihood estima-tions (MLEs) of the models parameters, and then conduct a simulation study to further analyze these estimations. The advantages of the DWED are shown in practice by applying it on two real world applications and compare it with some other well-known lifetime distributions.
Original languageEnglish
Article number6262
Pages (from-to)3043–3056
Number of pages14
JournalFILOMAT
Volume32
Issue number8
Publication statusPublished - 2018

Bibliographical note

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Fingerprint Dive into the research topics of 'Discrete Weighted Exponential Distribution of the Second Type: Properties and Applications'. Together they form a unique fingerprint.

Cite this