Multivariate exponential smoothing for forecasting tourist arrivals

George Athanasopoulos, Ashton James de Silva

Research output: Contribution to journalArticleResearchpeer-review

Abstract

In this article, we propose a new set of multivariate stochastic models that capture time-varying seasonality within the vector innovations structural time-series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend, and damped trend VISTS models with an additive multivariate seasonal component. We evaluate the forecasting accuracy of these models against the forecasting accuracy of univariate alternatives using international tourist arrivals from 11 source countries to Australia and New Zealand. In general, the newly proposed multivariate models improve on forecast accuracy over the univariate alternatives.
Original languageEnglish
Pages (from-to)640 - 652
Number of pages13
JournalJournal of Travel Research
Volume51
Issue number5
DOIs
Publication statusPublished - 2012

Cite this

@article{3f2b1ee3dbb94711a3a91578e6e8fc25,
title = "Multivariate exponential smoothing for forecasting tourist arrivals",
abstract = "In this article, we propose a new set of multivariate stochastic models that capture time-varying seasonality within the vector innovations structural time-series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend, and damped trend VISTS models with an additive multivariate seasonal component. We evaluate the forecasting accuracy of these models against the forecasting accuracy of univariate alternatives using international tourist arrivals from 11 source countries to Australia and New Zealand. In general, the newly proposed multivariate models improve on forecast accuracy over the univariate alternatives.",
author = "George Athanasopoulos and {de Silva}, {Ashton James}",
year = "2012",
doi = "10.1177/0047287511434115",
language = "English",
volume = "51",
pages = "640 -- 652",
journal = "Journal of Travel Research",
issn = "0047-2875",
publisher = "SAGE Publications Ltd",
number = "5",

}

Multivariate exponential smoothing for forecasting tourist arrivals. / Athanasopoulos, George; de Silva, Ashton James.

In: Journal of Travel Research, Vol. 51, No. 5, 2012, p. 640 - 652.

Research output: Contribution to journalArticleResearchpeer-review

TY - JOUR

T1 - Multivariate exponential smoothing for forecasting tourist arrivals

AU - Athanasopoulos, George

AU - de Silva, Ashton James

PY - 2012

Y1 - 2012

N2 - In this article, we propose a new set of multivariate stochastic models that capture time-varying seasonality within the vector innovations structural time-series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend, and damped trend VISTS models with an additive multivariate seasonal component. We evaluate the forecasting accuracy of these models against the forecasting accuracy of univariate alternatives using international tourist arrivals from 11 source countries to Australia and New Zealand. In general, the newly proposed multivariate models improve on forecast accuracy over the univariate alternatives.

AB - In this article, we propose a new set of multivariate stochastic models that capture time-varying seasonality within the vector innovations structural time-series (VISTS) framework. These models encapsulate exponential smoothing methods in a multivariate setting. The models considered are the local level, local trend, and damped trend VISTS models with an additive multivariate seasonal component. We evaluate the forecasting accuracy of these models against the forecasting accuracy of univariate alternatives using international tourist arrivals from 11 source countries to Australia and New Zealand. In general, the newly proposed multivariate models improve on forecast accuracy over the univariate alternatives.

U2 - 10.1177/0047287511434115

DO - 10.1177/0047287511434115

M3 - Article

VL - 51

SP - 640

EP - 652

JO - Journal of Travel Research

JF - Journal of Travel Research

SN - 0047-2875

IS - 5

ER -