Asymptotic properties of nonparametric M-estimation for mixing functional data
Date
2008
Authors
Chen, J.
Zhang, L.
Editors
Advisors
Journal Title
Journal ISSN
Volume Title
Type:
Journal article
Citation
Journal of Statistical Planning and Inference, 2008; 139(2):533-546
Statement of Responsibility
Jia Chen and Lixin Zhang
Conference Name
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.