Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1149739 | Journal of Statistical Planning and Inference | 2009 | 14 Pages |
Abstract
We investigate the asymptotic behavior of a nonparametric M-estimator of a regression function for stationary dependent processes, where the explanatory variables take values in some abstract functional space. Under some regularity conditions, we give the weak and strong consistency of the estimator as well as its asymptotic normality. We also give two examples of functional processes that satisfy the mixing conditions assumed in this paper. Furthermore, a simulated example is presented to examine the finite sample performance of the proposed estimator.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Jia Chen, Lixin Zhang,