Abstract
Polynomial regression models with errors in variables are considered. A goodness-of-fit test is constructed, which is based on an adjusted least-squares estimator and modifies the test introduced by Zhu et al. for a linear structural model with normal distributions. In the present paper, the distributions of errors are not necessarily normal. The proposed test is based on residuals, and it is asymptotically chi-squared under null hypothesis. We discuss the power of the test and the choice of an exponent in the exponential weight function involved in test statistics.
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Published in Ukrains’kyi Matematychnyi Zhurnal, Vol. 56, No. 4, pp. 527–543, April, 2004.
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Cheng, CL., Kukush, A.G. A goodness-of-fit test for a polynomial errors-in-variables model. Ukr Math J 56, 641–661 (2004). https://doi.org/10.1007/s11253-005-0009-x
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DOI: https://doi.org/10.1007/s11253-005-0009-x