OJS> Vol.5 No.1, February 2015

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Albert Orwa Akuno¹, Michael Oduor Otieno², Charles Wambugu Mwangi¹, Lawrence Areba Bichanga¹

¹Department of Mathematics, Egerton University, Egerton, Kenya.
²Department of Mathematics and Computer Science, Laikipia University, Nyahururu, Kenya.

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.

Exponential Smoothing, ARIMA Model, Tourists’ Arrival Data

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.