Skew-normal semiparametric varying coefficient model and score test

Abstract

In this paper, we consider inference aspects of skew-normal semiparametric varying coefficient models which provide a useful extension of the normal regression models. The maximum likelihood estimation based on B-spline is proposed. Further, we discuss the score test for homogeneity of the variance in skew-normal semiparametric varying coefficient models. Their asymptotical properties are investigated. Some simulated examples are used to examine our proposed methods.

Keywords:

• skew-normal
• semiparametric varying coefficient models
• homogeneity
• score test
• B-spline

AMS Subject Classification::

• 62G05
• 62G10

Acknowledgements

The authors would like to thank the editor and the two referees for helpful comments, which lead to improvement of an earlier version of this paper. This work was supported by grants from the National Natural Science Foundation of China (11271039 and 11101015); Funding Project of Science and Technology Research Plan of Beijing Education Committee (JC006790201001); and the Fund from the Government of Beijing (2011D005015000007).