Analysis of Incomplete, Censored Data in Competing Risks Models With Generalized Exponential Distributions

Author

Sarhan, Ammar M.

Author_Institution

Dept. of Math., Mansoura Univ.

Volume

56

Issue

1

fYear

2007

fDate

3/1/2007 12:00:00 AM

Firstpage

132

Lastpage

138

Abstract

This paper presents estimates of the parameters included in a competing risks model in the presence of incomplete & censored data. We consider the case when the competing risks have generalized exponential distributions. The maximum likelihood procedure is used to derive point, and asymptotic confidence interval estimations of the unknown parameters. The relative risks due to each cause of failure are investigated. A set of real data is used to test the hypothesis that the causes of failure follow exponential distributions against that they follow generalized exponential distributions

Keywords

exponential distribution; failure analysis; maximum likelihood estimation; reliability theory; risk analysis; asymptotic confidence interval estimations; censored data; competing risks model; generalized exponential distributions; incomplete data; maximum likelihood procedure; survival analysis; unknown parameter estimation; Covariance matrix; Distribution functions; Exponential distribution; Failure analysis; Maximum likelihood estimation; Parameter estimation; Probability density function; Risk analysis; Testing; Weibull distribution; Exponential distribution; goodness of fit; maximum-likelihood estimator; variance covariance matrix;

fLanguage

English

Journal_Title

Reliability, IEEE Transactions on

Publisher

ieee

ISSN

0018-9529

Type

jour

DOI

10.1109/TR.2006.890899

Filename

4118449