Empirical likelihood based diagnostics for heteroscedasticity in semiparametric varying-coefficient partially linear errors-in-variables models

ABSTRACT

In this paper, we propose an empirical likelihood based diagnostic technique for heteroscedasticity in the semiparametric varying-coefficient partially linear errors-in-variables models. Under mild conditions, a nonparametric version of Wilk’s theorem is derived. Simulation results reveal that our test performs well in both size and power.

KEYWORDS:

• Errors-in-variables
• Empirical likelihood ratio
• Heteroscedasticity
• Semiparametric varying-coefficient partial linear models.

Acknowledgments

The work of the first author was supported by the National Science Foundation of China (Grant No. 11471060) and the Key Project of Statistical Science of China (Grant No. 2017LZ27).