Statistical inference of Marshall-Olkin bivariate Weibull distribution with three shocks based on progressive interval censored data

COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION(2019)

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Abstract
There are several failure modes may cause system failed in reliability and survival analysis. It is usually assumed that the causes of failure modes are independent each other, though this assumption does not always hold. Dependent competing risks modes from Marshall-Olkin bivariate Weibull distribution under Type-I progressive interval censoring scheme are considered in this paper. We derive the maximum likelihood function, the maximum likelihood estimates, the 95% Bootstrap confidence intervals and the 95% coverage percentages of the parameters when shape parameter is known, and EM algorithm is applied when shape parameter is unknown. The Monte-Carlo simulation is given to illustrate the theoretical analysis and the effects of parameters estimates under different sample sizes. Finally, a data set has been analyzed for illustrative purposes.
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Key words
Dependent competing risks,Marshall-Olkin bivariate Weibull (MOBW) distribution,progressive interval censoring,EM algorithm,Bootstrap confidence intervals (CIs)
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