Quotation Ledolter, Johannes. 2008. Smoothing Time Series with Local Polynomial Regression on Time. Communications in Statistics. Theory and Methods 37 (6): 959-971.


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Abstract

Time series smoothers estimate the level of a time series at time t as its conditional expectation given present, past and future observations, with the smoothed value depending on the estimated time series model. Alternatively, local polynomial regressions on time can be used to estimate the level, with the implied smoothed value depending on the weight function and the bandwidth in the local linear least squares fit. In this article we compare the two smoothing approaches and describe their similarities. Through simulations, we assess the increase in the mean square error that results when approximating the estimated optimal time series smoother with the local regression estimate of the level.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Communications in Statistics. Theory and Methods
Citation Index SCI
Language English
Title Smoothing Time Series with Local Polynomial Regression on Time
Volume 37
Number 6
Year 2008
Page from 959
Page to 971
Reviewed? Y
URL http://www.informaworld.com/smpp/content~db=all~content=a790490148

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Ledolter, Johannes (Former researcher)
Organization
Institute for Statistics and Mathematics IN (Details)
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