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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.)

Bayesian Reference Analysis for the Generalized Normal Linear Regression Model

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Author(s):
Tomazella, Vera Lucia Damasceno [1] ; Jesus, Sandra Rego [2] ; Gazon, Amanda Buosi [1] ; Louzada, Francisco [3] ; Nadarajah, Saralees [4] ; Nascimento, Diego Carvalho [5] ; Rodrigues, Francisco Aparecido [3] ; Ramos, Pedro Luiz [3]
Total Authors: 8
Affiliation:
[1] Univ Fed Sao Carlos, Dept Stat, BR-13565905 Sao Paulo - Brazil
[2] Univ Fed Bahia, Multidisciplinary Hlth Inst, BR-45029094 Vitoria Da Conquista, BA - Brazil
[3] Univ Sao Paulo, Inst Math Sci & Comp, BR-13566590 Sao Carlos - Brazil
[4] Univ Manchester, Sch Math, Manchester M13 9PR, Lancs - England
[5] Univ Atacama, Fac Ingn, Dept Matemat, Copiapo 1530000 - Chile
Total Affiliations: 5
Document type: Journal article
Source: SYMMETRY-BASEL; v. 13, n. 5 MAY 2021.
Web of Science Citations: 0
Abstract

This article proposes the use of the Bayesian reference analysis to estimate the parameters of the generalized normal linear regression model. It is shown that the reference prior led to a proper posterior distribution, while the Jeffreys prior returned an improper one. The inferential purposes were obtained via Markov Chain Monte Carlo (MCMC). Furthermore, diagnostic techniques based on the Kullback-Leibler divergence were used. The proposed method was illustrated using artificial data and real data on the height and diameter of Eucalyptus clones from Brazil. (AU)

FAPESP's process: 20/09174-5 - Recommendation system of interest items for BeeNet users
Grantee:Diego Carvalho do Nascimento
Support Opportunities: Scholarships in Brazil - Technical Training Program - Technical Training
FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 17/25971-0 - Statistical inference of complex systems
Grantee:Pedro Luiz Ramos
Support Opportunities: Scholarships in Brazil - Post-Doctoral