Abstract:

The products are supposed to fail with competing risks, and each risk conforms to the Lindley distribution.The competing risks fail data include incomplete data and censoring data.The maximum likelihood procedure is used to derive point estimation of the unknown parameters, and their asymptotic confidence interval estimation and Bootstrap confidence interval estimation are discussed.The relative risks due to each cause of failure are investigated. The theoretical results obtained on a set of real data are applied.Also, hypothesis tests are studied to investigate whether the real data set can be fitted well by the Lindley distribution. The results show that the Lindley distribution fits best compared with the exponential distribution and Weibull distribution.