Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/1085
Type: Artigo de periódico
Title: Inference and local influence assessment in skew-normal null intercept measurement error model
Author: LACHOS, V. H.
MONTENEGRO, L. C.
BOLFARINE, H.
Abstract: In this article, we discuss inferential aspects of the measurement error regression models with null intercepts when the unknown quantity x (latent variable) follows a skew normal distribution. We examine first the maximum-likelihood approach to estimation via the EM algorithm by exploring statistical properties of the model considered. Then, the marginal likelihood, the score function and the observed information matrix of the observed quantities are presented allowing direct inference implementation. In order to discuss some diagnostics techniques in this type of models, we derive the appropriate matrices to assessing the local influence on the parameter estimates under different perturbation schemes. The results and methods developed in this paper are illustrated considering part of a real data set used by Hadgu and Koch [1999, Application of generalized estimating equations to a dental randomized clinical trial. Journal of Biopharmaceutical Statistics, 9, 161-178].
Subject: skew-normal distribution
EM algorithm
skewness
null intercepts model
measurement error
local influence
Country: Inglaterra
Editor: TAYLOR & FRANCIS LTD
Citation: JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION, v.78, n.3, p.395-419, 2008
Rights: fechado
Identifier DOI: 10.1080/10629360600969388
Address: http://dx.doi.org/10.1080/10629360600969388
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Date Issue: 2008
Appears in Collections:IMECC - Artigos e Materiais de Revistas Científicas

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