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http://hdl.handle.net/10397/104879
Title: | Can bagging improve the forecasting performance of tourism demand models? | Authors: | Song, H Witt, SF Qiu, RT |
Issue Date: | 2017 | Source: | In Kreinovich, V., Sriboonchitta, S., Huynh, V. N. (Eds. ), Robustness in Econometrics, p. 419–433. Cham: Springer, 2017 | Abstract: | This study examines the forecasting performance of the general-to-specific (GETS) models developed for Hong Kong through the bootstrap aggregating method (known as bagging). Although the literature in other research areas shows that bagging can improve the forecasting performance of GETS models, the empirical analysis in this study does not confirm this conclusion. This study is the first attempt to apply bagging to tourism forecasting, but additional effort is needed to examine the effectiveness of bagging in tourism forecasting by extending the models to cover more destination-source markets related to destinations other than Hong Kong. | Keywords: | Bagging General-to-specific modeling Hong Kong Tourism demand |
Publisher: | Springer | Journal: | Studies in computational intelligence | ISBN: | 978-3-319-50741-5 (Hardcover ISBN) 978-3-319-84480-0 (Softcover ISBN) 978-3-319-50742-2 (eBook ISBN) |
ISSN: | 1860-949X | DOI: | 10.1007/978-3-319-50742-2_25 | Rights: | © Springer International Publishing AG 2017 This version of the book chapter has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use (https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/978-3-319-50742-2_25. |
Appears in Collections: | Book Chapter |
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Song_Can_Bagging_Improve.pdf | Pre-Published version | 645.98 kB | Adobe PDF | View/Open |
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