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Combination of long term and short term forecasts, with application to tourism demand forecasting

机译：长期和短期预测相结合，应用于旅游需求预测

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摘要

Forecast combination is a well-established and well-tested approach for improving the forecasting accuracy. One beneficial strategy is to use constituent forecasts that have diverse information. In this paper we consider the idea of diversity being accomplished by using different time aggregations. For example, we could create a yearly time series from a monthly time series and produce forecasts for both, then combine the forecasts. These forecasts would each be tracking the dynamics of different time scales, and would therefore add diverse types of information. A comparison of several forecast combination methods, performed in the context of this setup, shows that this is indeed a beneficial strategy and generally provides a forecasting performance that is better than the performances of the individual forecasts that are combined. As a case study, we consider the problem of forecasting monthly tourism numbers for inbound tourism to Egypt. Specifically, we consider 33 individual source countries, as well as the aggregate. The novel combination strategy also produces a generally improved forecasting accuracy.
机译：预测组合是一种完善且经过测试的方法，可以提高预测准确性。一种有益的策略是使用具有多种信息的成分预测。在本文中，我们考虑通过使用不同的时间聚合来实现分集的想法。例如，我们可以从每月的时间序列中创建一个年度时间序列，并为这两个时间序列生成预测，然后合并这些预测。这些预测将各自跟踪不同时间尺度的动态，因此将添加各种类型的信息。在此设置的上下文中执行的几种预测组合方法的比较表明，这确实是一种有益的策略，并且通常提供的预测性能要好于组合的各个预测的性能。作为案例研究，我们考虑了预测前往埃及的入境旅游的每月旅游人数的问题。具体来说，我们考虑了33个单独的来源国，以及总数。新颖的组合策略还可以产生总体上提高的预测准确性。

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