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Diagnostics for skew-normal nonlinear regression models with AR(1) errors

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Author Info
Xie, Feng-Chang
Lin, Jin-Guan
Wei, Bo-Cheng
Abstract

In this article, we consider some diagnostics for skew-normal nonlinear regression models with AR(1) errors which provide a useful extension of the normal regression models. The estimation of the parameters in the models is studied based on the EM algorithm. Meanwhile, several score tests are presented for testing the homogeneity of the scale parameter and/or significance of autocorrelation in skew-normal nonlinear regression models. The properties of score tests are investigated through Monte Carlo simulations. The test methods are illustrated with two numerical examples.

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File URL: http://www.sciencedirect.com/science/article/B6V8V-4WM0J59-1/2/6cb017572bf0ad87647eeea61d5bb632
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Publisher Info
Article provided by Elsevier in its journal Computational Statistics & Data Analysis.

Volume (Year): 53 (2009)
Issue (Month): 12 (October)
Pages: 4403-4416
Download reference. The following formats are available: HTML (with abstract), plain text (with abstract), BibTeX, RIS (EndNote, RefMan, ProCite), ReDIF
Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4403-4416

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Web page: http://www.elsevier.com/locate/csda

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This page was last updated on 2009-12-3.


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