快递是交通运输行业中的新兴子行业,其发展具有长趋势性和短周期性.对全球跨国快递业务量进行分析和预测.数据来源是四大快递公司的季度跨国快递包裹量,跨度为2001年1季度至2010年4季度,考虑到原始数据为非平稳时间序列,运用时间序列分析方法中的ARIMA模型,对原始序列进行差分处理,根据自相关和偏相关函数的特性,确定模型中的各项参数,最终可以选择ARIMA(1,1,1)(1,1,1)4作为模型,该模型可以得到较为理想的结果.%Express, a newly rising sub-industry in transportation industry, has both long term trend and short cyclical trend of development. This article is to analyze and forecast global transnational express business volume. Data sources are the four major international express company's quarterly transnational package volume,ranging from 2001Q1 to 2010Q4. Considering the original data series are non-stationary time series,this article uses the ARIMA model in time series analysis method to conduct differential treatment and determine parameters in the model according to autocorrelation and partial autocorrelation function of the characteristics. Eventually ARIMA (1,1,1) is chosen as model which has a satisfactory result.
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