2012Unpublished venueRequires access

Minimax estimation of parameter of inverse exponential distribution

Zhou Guoping

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Abstract

Bayes estimators of the parameter of the inverse exponential distribution are obtained for the well known weighted square error loss, square log error loss and Modified linear Exponential (MLINEX) loss functions. Further minimax estimators are derived by using Lehmann's Theorem. Comparision of these estimators are also studied by numerical examples.

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What this paper is about

Bayes estimators of the parameter of the inverse exponential distribution are obtained for the well known weighted square error loss, square log error loss and Modified linear Exponential (MLINEX) loss functions. Further minimax estimators are derived by using Lehmann's Theorem. Comparision of these estimators are also studied by numerical examples.

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Available abstract

Bayes estimators of the parameter of the inverse exponential distribution are obtained for the well known weighted square error loss, square log error loss and Modified linear Exponential (MLINEX) loss functions. Further minimax estimators are derived by using Lehmann's Theorem. Comparision of these estimators are also studied by numerical examples.

Key concepts: Minimax, Estimator, Mathematics, Applied mathematics, Exponential function, Mean squared error, Minimax estimator, Inverse

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