Testing Lack-of-fit for a Polynomial
Errors-in-variables Model |
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Authors: | Email author" target="_blank">Li-xing?ZhuEmail author Wei-xing?Song Heng-jian?Cui |
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Institution: | (1) Academy of Mathematics and System Sciences, Chinese Academy of Sciences, Beijing, 100080, China;(2) University of Hong Kong, Hong Kong;(3) Beijing Normal University, Beijing, 100875, China |
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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 error-in-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 significance 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. |
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Keywords: | Bias correction lack-of-fit test polynomial errors-in-variables model |
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