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2021•Journal of Mathematical Sciences & Computational MathematicsOpen access

BAYESIAN ESTIMATION OF SHAPE PARAMETER OF POWER LOMAX DISTRIBUTION UNDER DIFFERENT LOSS FUNCTION

Arun Kumar Rao, Himanshu Pandey

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Abstract

In this paper, the power Lomax distribution is considered for Bayesian analysis. The expressions for Bayes estimators of the parameter have been derived under squared error, precautionary, entropy, K-loss, and Al-Bayyati’s loss functions by using quasi and gamma priors.

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What this paper is about

In this paper, the power Lomax distribution is considered for Bayesian analysis. The expressions for Bayes estimators of the parameter have been derived under squared error, precautionary, entropy, K-loss, and Al-Bayyati’s loss functions by using quasi and gamma priors.

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Available abstract

In this paper, the power Lomax distribution is considered for Bayesian analysis. The expressions for Bayes estimators of the parameter have been derived under squared error, precautionary, entropy, K-loss, and Al-Bayyati’s loss functions by using quasi and gamma priors.

Key concepts: Lomax distribution, Prior probability, Bayes estimator, Mathematics, Estimator, Mean squared error, Statistics, Bayes factor

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