Forecasting tourist arrivals to Thailand using belief functions

• Main Authors: Min,N., Sirisrisakulchai,J., Sriboonchitta,S.
• Format: Article
• Published: Springer Verlag 2015
• Subjects: Artificial Intelligence
• Online Access: http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=84919360822&origin=inward; http://cmuir.cmu.ac.th/handle/6653943832/39146
• Institution: Chiang Mai University

© Springer International Publishing Switzerland 2015. This paper applies the belief function approach to statistical forecasting of tourist arrivals to Thailand. Seasonal autoregressive integrated moving average (SARIMA) model was applied to forecast the tourists arrivals to Thailand using the time series data during the period of 1997–2013. To quantify the uncertainty of statistical forecasting, we used the method proposed by Kanjanatarakul et al. [5]. We utilized the statistical model, SARIMA to obtain parameter space whichwas constructed from the normalized likelihood given the observed data. Then, we rewrote the forecasting equation as a function of parameters and an auxiliary random variable with known distribution not depending on the parameters in prediction stage. Combining beliefs about parameters and auxiliary random variable gave us a predictive belief function for tourist arrivals. The finding supports the statement that the method can be used with any parametric model such as linear regression and time series models including SARIMA.