Parameter estimation for Exponential distribution based on doubly type II censoring from imprecise data
In the real world, the data sometimes cannot be recorded or collected precisely due to human errors or some unexpected situations. Therefore, the conventional procedures used for estimating the parameters of lifetime distributions under doubly type-II censoring scheme will have to be adopted to the new situation. In this paper, we propose different procedures for estimating the unknown parameter of Exponential distribution on the basis of doubly type-II censoring scheme when the lifetime observations are imprecise quantities. We consider the classical and Bayesian approaches. In the Bayesian setting, we obtain the estimate of the unknown parameter by using the approximation form of Lindley under the assumption of independent gamma prior. The estimation procedures are discussed in detail, and compared via Monte Carlo simulations in terms of their average values and mean squared errors.
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