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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Objective Bayesian analysis for the Lomax distribution

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Author(s):
Ferreira, Paulo H. [1] ; Ramos, Eduardo [2] ; Ramos, Pedro L. [2] ; Gonzales, Jhon F. B. [3] ; Tomazella, Vera L. D. [4] ; Ehlers, Ricardo S. [2] ; Silva, Eveliny B. [5] ; Louzada, Francisco [2]
Total Authors: 8
Affiliation:
[1] Univ Fed Bahia, Salvador, BA - Brazil
[2] Univ Sao Paulo, Inst Math & Comp Sci, Sao Carlos, SP - Brazil
[3] Univ Nacl San Agustin, Arequipa - Peru
[4] Univ Fed Sao Carlos, Sao Carlos, SP - Brazil
[5] Univ Fed Mato Grosso, Cuiaba, MG - Brazil
Total Affiliations: 5
Document type: Journal article
Source: Statistics & Probability Letters; v. 159, APR 2020.
Web of Science Citations: 0
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. (C) 2019 Elsevier B.V. All rights reserved. (AU)

FAPESP's process: 17/25971-0 - Statistical inference of complex systems
Grantee:Pedro Luiz Ramos
Support type: Scholarships in Brazil - Post-Doctorate