A study of the Gamma-Pareto (IV) distribution and its applications
Ayman Alzaatreh and
Indranil Ghosh
Communications in Statistics - Theory and Methods, 2016, vol. 45, issue 3, 636-654
Abstract:
Pareto distributions and their close relatives and generalizations provide very flexible families of heavy-tailed distributions that may be used to model income distributions as well as a wide variety of other social and economic distributions. On the other hand, gamma distribution has a wide application in various social and economic spheres such as survival analysis, to model aggregate insurance claims, and the amount of rainfall accumulated in a reservoir etc. Combining the above two heavy-tailed distributions, using the technique by Alzaatreh et al. (2012), we define a new distribution, namely Gamma-Pareto (IV) distribution, hereafter called as GPD(IV) distribution. Various properties of the GPD(IV) are investigated such as limiting behavior, moments, mode, and Shannon entropy. Also some characterizations of the GPD(IV) distribution are mentioned in this paper. Maximum likelihood method is proposed for estimating the model parameters. For illustrative purposes, real data sets are considered as applications of the GPD(IV) distribution.
Date: 2016
References: Add references at CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2013.834453 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:45:y:2016:i:3:p:636-654
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2013.834453
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().