A goodness-of-fit test for a polynomial errors-in-variables model

  • C.-L. Cheng


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.
How to Cite
Cheng, C.-L. “A Goodness-of-Fit Test for a Polynomial Errors-in-Variables Model”. Ukrains’kyi Matematychnyi Zhurnal, Vol. 56, no. 4, Apr. 2004, pp. 527–543, https://umj.imath.kiev.ua/index.php/umj/article/view/3774.
Research articles