An Iterative Plug-In Algorithm for Nonparametric Modelling of Seasonal Time Series

Yuanhua Feng

No 02/04, CoFE Discussion Papers from University of Konstanz, Center of Finance and Econometrics (CoFE)

Abstract: This paper focuses on developing a new data-driven procedure for decomposing seasonal time series based on local regression. Formula of the asymptotic optimal bandwidth hA in the current context is given. Methods for estimating the unknowns in hA are investigated. A data-driven algorithm for decomposing seasonal time series is proposed based on the iterative plug-in idea introduced by Gasser et al. (1991). Asymptotic behaviour of this algorithm is investigated. Some computational aspects are discussed in detail. Practical performance of the proposed algorithm is illustrated by simulated and data examples. The results here also provide some insights into the iterative plug-in idea.

Keywords: Time series decomposition; Local regression; Iterative plug-in; Bandwidth selection (search for similar items in EconPapers)
Date: 2002
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://www.econstor.eu/bitstream/10419/85178/1/dp02-04.pdf (application/pdf)

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:zbw:cofedp:0204

Access Statistics for this paper

More papers in CoFE Discussion Papers from University of Konstanz, Center of Finance and Econometrics (CoFE) Contact information at EDIRC.
Bibliographic data for series maintained by ZBW - Leibniz Information Centre for Economics (econstor@zbw-workspace.eu).