Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach

Christina Beneki; Bruno Eeckels; Costas Leon

doi:10.1002/for.1220

journal article Mar 09, 2011

Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach

Christina Beneki Bruno Eeckels Costas Leon

Journal of Forecasting Vol. 31 No. 5 pp. 391-400 · Wiley

View at Publisher Save 10.1002/for.1220

Abstract

ABSTRACTWe present and apply singular spectrum analysis (SSA), a relatively new, non‐parametric and data‐driven method for signal extraction (trends, seasonal and business cycle components) and forecasting of UK tourism income. Our results show that SSA slightly outperforms SARIMA and time‐varying‐parameter state space models in terms of root mean square error, mean absolute error and mean absolute percentage error forecasting criteria. Copyright © 2011 John Wiley & Sons, Ltd.

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Metrics

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Citations

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References

Details

Published: Mar 09, 2011
Vol/Issue: 31(5)
Pages: 391-400
License: View

Authors

C

Christina Beneki

Department of Business Administration Technological Educational Institution of Ionian Islands Kefallinia Greece

B

Bruno Eeckels

Les Roches‐Gruyère University of Applied Sciences Switzerland

C

Costas Leon

DCT University Centre Vitznau Switzerland

Cite This Article

Christina Beneki, Bruno Eeckels, Costas Leon (2011). Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach. Journal of Forecasting, 31(5), 391-400. https://doi.org/10.1002/for.1220

Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach

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