Statistical inference for α-series process with gamma distribution
Mahmut Kara,
Halil Aydoğdu and
Birdal Şenoğlu
Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 13, 6727-6736
Abstract:
The explicit estimators of the parameters α, μ and σ2 are obtained by using the methodology known as modified maximum likelihood (MML) when the distribution of the first occurrence time of an event is assumed to be Weibull in series process. The efficiencies of the MML estimators are compared with the corresponding nonparametric (NP) estimators and it is shown that the proposed estimators have higher efficiencies than the NP estimators. In this study, we extend these results to the case, where the distribution of the first occurrence time is Gamma. It is another widely used and well-known distribution in reliability analysis. A real data set taken from the literature is analyzed at the end of the study for better understanding the methodology presented in this paper.
Date: 2017
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2015.1134571 (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:46:y:2017:i:13:p:6727-6736
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2015.1134571
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 ().