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Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach
Author(s) -
Beneki Christina,
Eeckels Bruno,
Leon Costas
Publication year - 2012
Publication title -
journal of forecasting
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.543
H-Index - 59
eISSN - 1099-131X
pISSN - 0277-6693
DOI - 10.1002/for.1220
Subject(s) - singular spectrum analysis , series (stratigraphy) , time series , econometrics , tourism , moving average , mean squared error , statistics , signal (programming language) , forecast error , mathematics , state space , parametric statistics , state space representation , computer science , algorithm , singular value decomposition , geography , paleontology , archaeology , biology , programming language
We 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.