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http://repositorio.unicamp.br/jspui/handle/REPOSIP/348327
Type: | Artigo |
Title: | Robust linear mixed models with skew-normal independent distributions from a bayesian perspective |
Author: | Lachos, Victor H. Dey, Dipak K. Cancho, Vicente G. |
Abstract: | Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally, the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study |
Subject: | Distribuição normal assimétrica |
Country: | Países Baixos |
Editor: | Elsevier |
Rights: | Fechado |
Identifier DOI: | 10.1016/j.jspi.2009.05.040 |
Address: | https://www.sciencedirect.com/science/article/pii/S0378375809001669 |
Date Issue: | 2009 |
Appears in Collections: | IMECC - Artigos e Outros Documentos |
Files in This Item:
File | Description | Size | Format | |
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000270316000013.pdf | 511.68 kB | Adobe PDF | View/Open |
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