Statistical Models for Forecasting Tourists’ Arrival in Kenya  

作　　者：Albert Orwa Akuno Michael Oduor Otieno Charles Wambugu Mwangi Lawrence Areba Bichanga 

机构地区：[1]Department of Mathematics, Egerton University, Egerton, Kenya [2]Department of Mathematics and Computer Science, Laikipia University, Nyahururu, Kenya

出　　处：《Open Journal of Statistics》2015年第1期60-65,共6页统计学期刊（英文）

摘　　要：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.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.

关 键 词：EXPONENTIAL SMOOTHING ARIMA Model Tourists’ ARRIVAL DATA 

分 类 号：R73[医药卫生—肿瘤]