Signal Extraction and Forecasting of the UK Tourism Income Time Series: A Singular Spectrum Analysis Approach
We present and apply the Singular Spectrum Analysis (SSA), a relatively new, non-parametric and data-driven method used for signal extraction (trends, seasonal and business cycle components) and forecasting of the UK tourism income. Our results show that SSA outperforms slightly SARIMA and time-varying parameter State Space Models in terms of RMSE, MAE and MAPE forecasting criteria.
(This abstract was borrowed from another version of this item.)
To our knowledge, this item is not available for
download. To find whether it is available, there are three
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Volume (Year): 31 (2012)
Issue (Month): 5 (08)
|Contact details of provider:|| Web page: http://www3.interscience.wiley.com/cgi-bin/jhome/2966|
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Hassani, Hossein, 2007. "Singular Spectrum Analysis: Methodology and Comparison," MPRA Paper 4991, University Library of Munich, Germany.
- Leon, Costas & Eeckels, Bruno, 2009. "A Dynamic Correlation Approach of the Swiss Tourism Income," MPRA Paper 15215, University Library of Munich, Germany.
When requesting a correction, please mention this item's handle: RePEc:wly:jforec:v:31:y:2012:i:5:p:391-400. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.