On Bayesian Estimation of Loss and Risk Functions for Exponential Distribution

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Abstract
Loss functions and Risk functions are two very important aspects in Bayesian estimation. In this paper the Bayesian estimation for the loss and risk functions of the unknown parameter θ of exponential distribution has been studied under Rukhin’s loss function for Type II censoring. The inverse Gamma distribution has been assumed as the prior distribution for the unknown parameter θ. On the part of loss functions, the Squared Error Loss Function (SELF) and three different forms of Weighted Squared Error Loss Function (WSELF) namely, the Degroot’s Loss Function, Minimum Expected Loss (MELO) Function and Exponentially Weighted Minimum Expected Loss (EWMELO) Function have been considered.
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