Minimax Estimation of the Scale Parameter of the Laplace Distribution under Different Loss Function
Journal Title: International Journal of Emerging Technologies in Computational and Applied Sciences - Year 2015, Vol 14, Issue 1
Abstract
In this paper, we obtained Minimax estimators of the scale parameter θ for the Laplace distribution under different loss function by applying the theorem of Lehmann [1950]. Some Bayes estimators for the unknown scale parameter θ of Laplace distribution have been obtained, using Non-informative prior (Jeffreys) and Informative priors (Gumbel Type II) under different loss function, represented by (Quadratic loss function, Squared – log error loss function, Entropy loss function). According to Monte-Carlo simulation study, the performance of these estimates is compared depending on the mean squared errors (MSE’s).
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