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Smoothing splines for trend estimation and prediction in time series

โœ Scribed by Richard Morton; Emily L. Kang; Brent L. Henderson


Publisher
John Wiley and Sons
Year
2009
Tongue
English
Weight
302 KB
Volume
20
Category
Article
ISSN
1180-4009

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โœฆ Synopsis


Abstract

We consider the use of generalized additive models with correlated errors for analysing trends in time series. The trend is represented as a smoothing spline so that it can be extrapolated. A method is proposed for choosing the smoothing parameter. It is based on the ability to predict a short term into the future. The choice not only addresses the purpose in hand, but also performs very well, and avoids the tendency to underโ€smooth or to interpolate the data that can occur with other dataโ€driven methods used to choose the smoothing parameter. The method is applied to data from a chemical process and to stream salinity measurements. Copyright ยฉ 2008 John Wiley & Sons, Ltd.


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