Non-parametric smoothing and prediction for nonlinear circular time series

Di Marzio, M, Panzera, A and Taylor, CC (2012) Non-parametric smoothing and prediction for nonlinear circular time series. Journal of Time Series Analysis, 33 (4). 620 - 630 . ISSN 0143-9782

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Abstract

Not much research has been done in the field of circular time-series analysis. We propose a non-parametric theory for smoothing and prediction in the time domain for circular time-series data. Our model is based on local constant and local linear fitting estimates of a minimizer of an angular risk function. Both asymptotic arguments and empirical examples are used to describe the accuracy of our methods.

Item Type:	Article
Copyright, Publisher and Additional Information:	© 2012,Blackwell Pubishing. This is the pre-peer reviewed version of the following article: Di Marzio, M, Panzera, A and Taylor, CC (2012) Non-parametric smoothing and prediction for nonlinear circular time series, Journal of Time Series Analysis, 33 (4). 620 - 630, which has been published in final form at http://dx.doi.org/10.1111/j.1467-9892.2012.00794.x Uploaded in accordance with the publisher's self-archiving policy.
Academic Units:	The University of Leeds > Faculty of Maths and Physical Sciences (Leeds) > School of Mathematics (Leeds) > Statistics (Leeds)
Depositing User:	Symplectic Publications
Date Deposited:	01 Nov 2012 15:19
Last Modified:	08 Feb 2013 17:40
Published Version:	http://dx.doi.org/10.1111/j.1467-9892.2012.00794.x
Status:	Published
Publisher:	Blackwell Pubishing
Identification Number:	10.1111/j.1467-9892.2012.00794.x
URI:	http://eprints.whiterose.ac.uk/id/eprint/74708

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