Asymptotic normality of conditional density estimation in the single index model for functional time series data
Nengxiang Ling and
Qian Xu
Statistics & Probability Letters, 2012, vol. 82, issue 12, 2235-2243
Abstract:
In this paper, we investigate the estimation of conditional density function based on the single-index model for functional time series data. The asymptotic normality of the conditional density estimator and the conditional mode estimator for the α mixing dependence functional time series data are obtained, respectively. Furthermore, as applications, the asymptotic (1-ζ) confidence interval of the conditional density function and the conditional mode are also presented for 0<ζ<1.
Keywords: Asymptotic normality; α mixing dependence; Single functional index model; Conditional density; Conditional mode (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0167715212003239
Full text for ScienceDirect subscribers only
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:eee:stapro:v:82:y:2012:i:12:p:2235-2243
Ordering information: This journal article can be ordered from
http://www.elsevier.com/wps/find/supportfaq.cws_home/regional
https://shop.elsevie ... _01_ooc_1&version=01
DOI: 10.1016/j.spl.2012.08.018
Access Statistics for this article
Statistics & Probability Letters is currently edited by Somnath Datta and Hira L. Koul
More articles in Statistics & Probability Letters from Elsevier
Bibliographic data for series maintained by Catherine Liu ().