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Type: Artigo de periódico
Title: Influence Diagnostics For Grubbs's Model With Asymmetric Heavy-tailed Distributions
Author: Zeller C.B.
Lachos V.H.
Labra F.V.
Abstract: Grubbs's model (Grubbs, Encycl Stat Sci 3:42-549, 1983) is used for comparing several measuring devices, and it is common to assume that the random terms have a normal (or symmetric) distribution. In this paper, we discuss the extension of this model to the class of scale mixtures of skew-normal distributions. Our results provide a useful generalization of the symmetric Grubbs's model (Osorio et al., Comput Stat Data Anal, 53:1249-1263, 2009) and the asymmetric skew-normal model (Montenegro et al., Stat Pap 51:701-715, 2010). We discuss the EM algorithm for parameter estimation and the local influence method (Cook, J Royal Stat Soc Ser B, 48:133-169, 1986) for assessing the robustness of these parameter estimates under some usual perturbation schemes. The results and methods developed in this paper are illustrated with a numerical example. © 2013 Springer-Verlag Berlin Heidelberg.
Editor: Springer New York LLC
Rights: fechado
Identifier DOI: 10.1007/s00362-013-0519-9
Date Issue: 2014
Appears in Collections:Unicamp - Artigos e Outros Documentos

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