Spline Estimation for a Class of Time Series Variance Model

Xin-qian Wu (), Wan-cai Yang and Shu-hong Zhang
Additional contact information
Xin-qian Wu: Henan University of Science and Technology
Wan-cai Yang: Henan University of Science and Technology
Shu-hong Zhang: Henan University of Science and Technology

Chapter Chapter 58 in The 19th International Conference on Industrial Engineering and Engineering Management, 2013, pp 613-623 from Springer

Abstract: Abstract A class of nonparametric variance model with weakly stationary linear innovation process is considered in this paper. Based on polynomial spline method, optimal global rate of convergence of the estimator of nonparametric variance function is obtained. The methodology is illustrated by simulation and real data examples.

Keywords: Global convergence; Linear innovation process; Nonparametric variance model; Spline estimation (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-642-37270-4_58

Ordering information: This item can be ordered from
http://www.springer.com/9783642372704

DOI: 10.1007/978-3-642-37270-4_58

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().