Journal of Statistical Theory and Applications

Volume 15, Issue 2, June 2016, Pages 125 - 141

The Additive Weibull-Geometric Distribution: Theory and Applications

Authors
I. Elbatal, M.M. Mansour, Mohammad Ahsanullah
Corresponding Author
I. Elbatal
Received 27 March 2014, Accepted 21 June 2015, Available Online 1 June 2016.
DOI
10.2991/jsta.2016.15.2.3How to use a DOI?
Keywords
Additive Weibull distribution, Geometric distribution, Moments, Maximum likelihood.
Abstract

In this paper, we introduce a new class of lifetime distributions which is called the additive Weibull geometric (AWG) distribution. This distribution obtained by compounding the additive Weibull and geometric distributions. The new distribution has a number of well-known lifetime special sub-models such as modified Weibull geometric, Weibull geometric, exponential geometric, among several others. Some structural properties of the proposed new distribution are discussed. 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.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Journal
Journal of Statistical Theory and Applications
Volume-Issue
15 - 2
Pages
125 - 141
Publication Date
2016/06/01
ISSN (Online)
2214-1766
ISSN (Print)
1538-7887
DOI
10.2991/jsta.2016.15.2.3How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - JOUR
AU  - I. Elbatal
AU  - M.M. Mansour
AU  - Mohammad Ahsanullah
PY  - 2016
DA  - 2016/06/01
TI  - The Additive Weibull-Geometric Distribution: Theory and Applications
JO  - Journal of Statistical Theory and Applications
SP  - 125
EP  - 141
VL  - 15
IS  - 2
SN  - 2214-1766
UR  - https://doi.org/10.2991/jsta.2016.15.2.3
DO  - 10.2991/jsta.2016.15.2.3
ID  - Elbatal2016
ER  -