Objective Bayesian analysis for the Lomax distribution
| Autor: | Paulo H. Ferreira, Ricardo S. Ehlers, Eduardo Ramos, Jhon Franky Bernedo Gonzales, Francisco Louzada, Eveliny Barroso da Silva, Pedro Luiz Ramos, Vera Tomazella |
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| Rok vydání: | 2020 |
| Předmět: |
Statistics and Probability
Bayes estimator Mean squared error 010102 general mathematics Bayesian probability Monte Carlo method TESTES DE VIDA (PESQUISA OPERACIONAL) 01 natural sciences 010104 statistics & probability Approximation error Prior probability Statistics Lomax distribution 0101 mathematics Statistics Probability and Uncertainty Jeffreys prior Mathematics |
| Zdroj: | Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP |
| ISSN: | 0167-7152 |
| DOI: | 10.1016/j.spl.2019.108677 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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