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Research Article Open access CC BY 4.0

Bayesian Analysis of Weibull-Lindley Distribution Using Different Loss Functions

Innocent Boyle Eraikhuemen, Olateju Alao Bamigbala, Umar Alhaji Magaji, Bassa Shiwaye Yakura, Kabiru Ahmed Manju

Asian Journal of Advanced Research and Reports · pp. 28–41 · Published 7 Mar 2020

10.9734/ajarr/2020/v8i430205

Abstract

In the present paper, a three-parameter Weibull-Lindley distribution is considered for Bayesian analysis. The estimation of a shape parameter of Weibull-Lindley distribution is obtained with the help of both the classical and Bayesian methods. Bayesian estimators are obtained by using Jeffrey’s prior, uniform prior and Gamma prior under square error loss function, quadratic loss function and Precautionary loss function. Estimation by the method of Maximum likelihood is also discussed. These methods are compared by using mean square error through simulation study with varying parameter values and sample sizes.

Weibull-Lindley distribution Bayesian method priors loss functions MLE simulation MSE.

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