Simultaneous Inference of the Mean of Functional Time Series

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Simultaneous Inference of the Mean of Functional Time Series

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Title: Simultaneous Inference of the Mean of Functional Time Series
Author(s):
Chen, Ming (UT Dallas);
Song, Qiongxia (UT Dallas)
Item Type: article
Keywords: Show Keywords
Abstract: For functional time series with physical dependence, we construct confidence bands for its mean function. The physical dependence is a general dependence framework, and it slightly relaxes the conditions of m-approximable dependence.We estimate functional time series mean functions via a spline smoothing technique. Confidence bands have been constructed based on a long-run variance and a strong approximation theorem, which is satisfied with mild regularity conditions. Simulation experiments provide strong evidence that corroborates the asymptotic theories. Additionally, an application to S&P500 index data demonstrates a non-constant volatility mean function at a certain significance level. © 2015, Institute of Mathematical Statistics. All rights reserved.
Publisher: Institute of Mathematical Statistics
ISSN: 1935-7524
Persistent Link: http://dx.doi.org/10.1214/15-EJS1052
http://hdl.handle.net/10735.1/5330
Bibliographic Citation: Chen, M., and Q. Song. 2015. "Simultaneous inference of the mean of functional time series." Electronic Journal of Statistics 9(2), doi:10.1214/15-EJS1052
Terms of Use: CC BY 2.5 (Attribution) License
©2015 Institute of Mathematical Statistics. All rights reserved.

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