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Estimation of Dynamic Cumulative Past Entropy for Power Function Distribution under Type II Right Censored sample
Abstract
In the present work, we introduced the maximum likelihood and Bayesian estimators of the dynamic cumulative past entropy of power function distribution in the context of Type II right censoring. We also provided the asymtotic and bootstrap confidence intervals for the estimators. For deriving the Bayesian estimators we used the approximation procedure proposed by Lindley and importance sampling procedure. In order to study the performance of the proposed estimators we use simulated and real data approaches.
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