| Texto completo | |
| Autor(es): |
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]
Número total de Autores: 8
|
| Afiliação do(s) autor(es): | [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
Número total de Afiliações: 5
|
| Tipo de documento: | Artigo Científico |
| Fonte: | Statistics & Probability Letters; v. 159, APR 2020. |
| Citações Web of Science: | 0 |
| Resumo | |
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) | |
| Processo FAPESP: | 17/25971-0 - Inferência estatística de sistemas complexos |
| Beneficiário: | Pedro Luiz Ramos |
| Modalidade de apoio: | Bolsas no Brasil - Pós-Doutorado |