Abstract
This article considers linear regression models when neither the response variable nor the covariates can be directly observed, but are measured with both multiplicative and additive distortion measurement errors. We transform the linear regression models via the varying coefficient models, then moment-based estimators are proposed by using the estimated varying coefficient functions. We study the asymptotic results of the proposed estimator, and construct a test statistic to check whether the coefficient in the linear model is zero or not. Lastly, we make some comparisons between the proposed estimators and other existing estimators through the simulation.
Mathematics Subject Classification (2000):
Acknowledgments
The authors thank the editor, the associate editor, and a referee for their constructive suggestions that helped us to improve the early manuscript.