Title :
Analysis of Incomplete, Censored Data in Competing Risks Models With Generalized Exponential Distributions
Author :
Sarhan, Ammar M.
Author_Institution :
Dept. of Math., Mansoura Univ.
fDate :
3/1/2007 12:00:00 AM
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;
Journal_Title :
Reliability, IEEE Transactions on
DOI :
10.1109/TR.2006.890899
