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Statistical Models for Forecasting Tourists’ Arrival in Kenya

机译:预测肯尼亚游客到达的统计模型

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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.
机译:本文尝试使用统计时间序列建模技术(双指数平滑法和自动回归综合移动平均线(ARIMA))来预测游客的到来。众所周知,预测在制定未来决策(例如为库存系统订购补货或增加可用人员的能力,以满足预期的未来服务交付)中非常重要。在第2节中给出了使用的方法,在第3节中给出了结果,讨论和结论。当验证了这些模型的预测后,双指数平滑模型的性能优于ARIMA模型。

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