Analysis of Gamma and Weibull lifetime data under a general censoring scheme and in the presence of covariates

Nathan Bennett, Srikanth K. Iyer and S. Rao Jammalamadaka

Communications in Statistics - Theory and Methods, 2017, vol. 46, issue 5, 2277-2289

Abstract: We consider the problem of estimating the lifetime distributions of survival times subject to a general censoring scheme called “middle censoring”. The lifetimes are assumed to follow a parametric family of distributions, such as the Gamma or Weibull distributions, and is applied to cases when the lifetimes come with covariates affecting them. For any individual in the sample, there is an independent, random, censoring interval. We will observe the actual lifetime if the lifetime falls outside of this censoring interval, otherwise we only observe the interval of censoring. This censoring mechanism, which includes both right- and left-censoring, has been called “middle censoring” (see Jammalamadaka and Mangalam, 2003). Maximum-likelihood estimation of the parameters as well as their large-sample properties are studied under this censoring scheme, including the case when covariates are available. We conclude with an application to a dataset from Environmental Economics dealing with ContingentValuation of natural resources.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2015.1041981 (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:5:p:2277-2289

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2015.1041981

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 ().