Statistical Models for Forecasting Tourists’ Arrival in Kenya

DOI: 10.4236/ojs.2015.51008   PDF   HTML   XML   3,919 Downloads   4,860 Views   Citations


In this paper, an attempt has been made to forecast tourists’ arrival using statistical time series modeling techniques—Double Exponential Smoothing and the Auto-Regressive Integrated Moving Average (ARIMA). It is common knowledge that forecasting is very important in making future decisions such as ordering replenishment for an inventory system or increasing the capacity of the available staff in order to meet expected future service delivery. The methodology used is given in Section 2 and the results, discussion and conclusion are given in Section 3. When the forecasts from these models were validated, Double Exponential Smoothing model performed better than the ARIMA model.

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Akuno, A. , Otieno, M. , Mwangi, C. and Bichanga, L. (2015) Statistical Models for Forecasting Tourists’ Arrival in Kenya. Open Journal of Statistics, 5, 60-65. doi: 10.4236/ojs.2015.51008.

Conflicts of Interest

The authors declare no conflicts of interest.


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