Objective Bayesian analysis for the Lomax distribution

Paulo H. Ferreira; Eduardo Ramos; Pedro L. Ramos; Jhon Franky Bernedo Gonzales; Vera L.D. Tomazella; Ricardo S. Ehlers; Eveliny B. Silva; Francisco Louzada

doi:10.1016/j.spl.2019.108677

Objective Bayesian analysis for the Lomax distribution

Paulo H. Ferreira, Eduardo Ramos, Pedro L. Ramos, Jhon Franky Bernedo Gonzales, Vera L.D. Tomazella, Ricardo S. Ehlers, Eveliny B. Silva, Francisco Louzada

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

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.

Original language	English
Article number	108677
Journal	Statistics and Probability Letters
Volume	159
DOIs	https://doi.org/10.1016/j.spl.2019.108677
State	Published - Apr 2020

Bibliographical note

Funding Information:
The authors are grateful to the Editor and the two reviewers for their helpful and useful comments that improved the manuscript. Pedro L. Ramos is grateful to the São Paulo State Research Foundation, Brazil (FAPESP Proc. 2017/25971-0 ). Appendix A

Funding Information:
The authors are grateful to the Editor and the two reviewers for their helpful and useful comments that improved the manuscript. Pedro L. Ramos is grateful to the S?o Paulo State Research Foundation, Brazil (FAPESP Proc. 2017/25971-0).

Publisher Copyright:
© 2019 Elsevier B.V.

Keywords

Jeffreys prior
Lomax distribution
Objective Bayesian analysis
Reliability

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10.1016/j.spl.2019.108677

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title = "Objective Bayesian analysis for the Lomax distribution",

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.",

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T1 - Objective Bayesian analysis for the Lomax distribution

AU - Ferreira, Paulo H.

AU - Ramos, Eduardo

AU - Ramos, Pedro L.

AU - Bernedo Gonzales, Jhon Franky

AU - Tomazella, Vera L.D.

AU - Ehlers, Ricardo S.

AU - Silva, Eveliny B.

AU - Louzada, Francisco

PY - 2020/4

Y1 - 2020/4

N2 - 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.

AB - 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.

KW - Jeffreys prior

KW - Lomax distribution

KW - Objective Bayesian analysis

KW - Reliability

UR - http://www.scopus.com/inward/record.url?scp=85076500360&partnerID=8YFLogxK

U2 - 10.1016/j.spl.2019.108677

DO - 10.1016/j.spl.2019.108677

M3 - Artículo

AN - SCOPUS:85076500360

VL - 159

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

M1 - 108677

ER -

Objective Bayesian analysis for the Lomax distribution

Abstract

Bibliographical note

Keywords

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