Objective Bayesian analysis for the Lomax distribution

Paulo H. Ferreira, Eduardo Ramos, Pedro L. Ramos, Jhon F.B. Gonzales, Vera L.D. Tomazella, Ricardo Ehlers (), Eveliny B. Silva and Francisco Louzada

Statistics & Probability Letters, 2020, vol. 159, issue C

Abstract: In this paper, we propose to make Bayesian inferences for the parameters of the Lomax distribution using non-informative priors, namely the (dependent and independent) Jeffreys prior and the reference prior. We assess Bayesian estimation through a Monte Carlo study with 10,000 simulated datasets. In order to evaluate the possible impact of prior specification on estimation, two criteria were considered: the mean relative error and the mean square error. An application on a real dataset illustrates the developed procedures.

Keywords: Jeffreys prior; Lomax distribution; Objective Bayesian analysis; Reliability (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1016/j.spl.2019.108677

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