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Notes
- 1.
In order to achieve stationarity in sample’s variance.
- 2.
Box-Cox transformation: \(X_t = \left\{ {\begin{array}{*{20}c} {\frac{{Y_t^\lambda - 1}}{\lambda },\lambda \ne 0} \\ {\ln \left( {Y_t } \right),\lambda = 0} \\\end{array}} \right.\)
- 3.
H0: Coefficient = 0 e H1: Coefficient ≠ 0
- 4.
H0: ρ 1 = ρ 2 = … = ρ n = 0 e H1: There is at least one ρ i ≠ 0
- 5.
\(\nabla X_t = X_t - X_{t - 1} = (1 - B)X_t \)
- 6.
\(\nabla _{12} X_t = X_t - X_{t - 12} = (1 - B^{12} )X_t\)
- 7.
Total overnights forecasts based on segmented data sample given by he sum of the forecasts using the most accurate forecasting method for each one of the tourists’ eight countries of origin.
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Santos, C., Couto, G., Pimentel, P.M. (2009). Forecasting Hotel Overnights in the Autonomous Region of the Azores. In: Matias, Á., Nijkamp, P., Sarmento, M. (eds) Advances in Tourism Economics. Physica-Verlag HD. https://doi.org/10.1007/978-3-7908-2124-6_11
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