Acta Mathematicae Applicatae Sinica, English Series

, Volume 19, Issue 3, pp 353–362 | Cite as

Testing Lack-of-fit for a Polynomial Errors-in-variables Model

Original papers

Abstract

When a regression model is applied as an approximation of underlying model of data, the model checking is important and relevant. In this paper, we investigate the lack-of-fit test for a polynomial errorin-variables model. As the ordinary residuals are biased when there exist measurement errors in covariables, we correct them and then construct a residual-based test of score type. The constructed test is asymptotically chi-squared under null hypotheses. Simulation study shows that the test can maintain the signi.cance level well. The choice of weight functions involved in the test statistic and the related power study are also investigated. The application to two examples is illustrated. The approach can be readily extended to handle more general models.

Keywords

Bias correction lack-of-fit test polynomial errors-in-variables model 

2000 MR Subject Classification

62G10 62G20 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  1. 1.Academy of Mathematics and System SciencesChinese Academy of SciencesBeijingChina
  2. 2.University of Hong KongHong Kong
  3. 3.Beijing Normal UniversityBeijingChina

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