中国快递包裹总量的预测-基于SARIMA模型

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中国快递包裹总量：基于SARIMA模型的预测

shangfr

2015年10月28日

目前，我国快递业务总量已成为全球第一。国家邮政局发布的数据显示，2015年4月底，快递业务量完成15亿件，同比增长50.9%。目前，快递业务量增速已连续50个月超过50%，尤其是网购旺季（双十一、双十二等），我国快递包裹在当月的总量在世界范围内没有任何国家可以相比。 电子商务的兴盛有效带动快递行业的高速发展，反之，快递行业的提升也为电子商务的增长提供配套支撑。不过，快递业在迅猛发展的同时，也让行业“亚健康”的现状越发凸显。业内人士表示，虽然国内快递行业仍在高速增长，但目前运营“压力山大”，比如人员、车辆、场地等问题。 国家统计局网站公布的快递包裹量数据可以看作是标准的时序数据，但与普通时序数据不同的是，它的数值变化存在明显的季节性波动。处理季节性时间序列只用ARMA方法是不够的。描述这类序列的模型之一是季节时间序列模型(Seasona ARIMA Model)，用SARIMA表示。本文旨在通过SARMA模型研究中国快递包裹总量变化情况，并测算合理参数构建模型用于预测，以帮助有关部门提前了解快递量需求，做好相应对策。从国家统计局网站下载2003年1月至2014年12月的快递量-当期值(万件)，首先，通过时间序列图对快递包裹量变化情况作一个直观判断。

library(tseries)#加载时间序列程序包
library(forecast)

## Loading required package: zoo
##
## Attaching package: 'zoo'
##
## The following objects are masked from 'package:base':
##
##     as.Date, as.Date.numeric
##
## Loading required package: timeDate
## This is forecast 6.1

require(graphics)
#快递包裹量（国家统计局数据）
exp=structure(c(1119.7, 986.9, 1319.8, 1436.2, 1402.3, 1572.7, 1435.4,
                    1592, 1678.2, 1425.8, 1575.2, 1695.1, 1277.7, 1410, 1666.9, 1688.5,
                    1600.5, 1796.8, 1656.9, 1871.4, 1772.8, 1543.9, 1707, 1798.4,
                    1549.8, 1369.4, 1822.8, 1903.7, 1826.6, 1988, 1884, 2161.2, 2289.2,
                    1906.4, 2013.5, 2164.1, 1798.7, 1768.4, 2132.4, 2236.2, 2112.9,
                    2373.3, 2655.1, 2637.4, 2601.5, 2159.3, 2213.2, 2315.8, 2235.1,
                    1858.7, 2773.9, 2693.6, 2526.3, 2866.6, 2861, 3274.9, 3116.5,
                    2643.7, 2795.9, 2984.4, 11227.7, 9137, 13350.8, 11220.4, 12187.4,
                    12824.5, 12571.6, 13582.5, 13471.2, 13351.5, 13236.4, 15168.2,
                    10971.8, 11781, 15292.7, 14593.4, 14829.1, 15714.1, 16273.1,
                    16850.4, 17791.9, 14853.5, 17534.8, 19299, 17065.7, 11147.1,
                    19083.3, 18193.8, 18661.1, 19438, 19308.2, 19710.6, 21535.3,
                    20162.9, 23220, 26366.2, 25301.6, 17177.4, 28645.4, 28015, 29113.8,
                    30078.4, 29599, 31235.6, 32462.6, 33414.7, 39393.8, 42873.8,
                    27319.4, 35164.2, 41850.9, 40373.8, 48993.9, 45447.6, 46244.9,
                    46561.8, 51345.3, 52421.3, 67126.6, 65698.4, 68917.7, 35473.1,
                    67043.8, 66249.4, 74178.7, 72154.1, 74802.1, 75266.7, 83637.1,
                    85303.5, 108703.4, 106945.3, 88950, 68886.2, 102528.2, 105417.5,
                    111634.7, 112926.3, 111245.1, 114050.7, 122992, 128997.1, 164616.5,
                    163681.1), .Tsp = c(2003, 2014.91666666667, 12), class = "ts")

ts.plot(exp)#作这个时间序列的图,通过图作一个直观判断

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" title alt width="672" />

从上图可以看出，从2008年开始，我国快递包裹量呈级数增长，并且存在明显的周期性变化，快递行业在此期间飞速发展。这种周期是由于季节性变化（包括季度、月度、周度等变化）或其他一些固有因素引起的。这类序列称为季节性序列。在快递包裹运输领域中，季节性影响是不可避免的。处理季节性时间序列只用ARMA方法是不够的。描述这类序列的模型之一是季节时间序列模型(Seasonal ARIMA Model)，用SARIMA表示。

par(mfrow=c(1,2))
acf(exp)#查看自相关图
pacf(exp)#查看偏相关图

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" title alt width="672" />

经过图形观察，可以初步判断出： 1.我国快递包裹量有明显呈级数增长趁势； 2.包裹量的变化存在季节性因素； 3.通过自相关-偏自相关图可以看出，应该使用MA（）模型来拟合。 接下来使用R软件时间序列包的decompose函数对包括时序数据进行分解，分别为随机、趋势、季节。

x<-decompose(exp)#通过decompose 进行分解：随机、趋势、季节

plot(x)#作图查看

aaarticlea/png;base64,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" title alt width="672" />

通过随机、趋势、季节三张图可以看出，我国快递包裹量呈级数增长；包裹量的变化存在季节性因素；时序随机性变化平稳。

plot(x$seasonal)

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" title alt width="672" />

通过以上分析，选择ARIMA(0,1,1)(0,1,1)[12]模型拟合数据效果最好，下面进行模型定阶检验：

exp.fit <- arima(exp,order=c(0,1,1), seasonal=list(order=c(0,1,2), period=12))
nobs(exp.fit)

## [1] 131

tsdiag(exp.fit)

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" title alt width="672" />

arimafit<-auto.arima(exp)
plot(forecast(arimafit,h=20))

aaarticlea/png;base64,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" title alt width="672" />

模型预测

arimafit<-auto.arima(exp)
plot(forecast(arimafit,h=20))

aaarticlea/png;base64,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" title alt width="672" />

exp.forecast <- forecast(exp,4)#给出80%，95%置信度下的置信区间，向前预测12期，默认情况下24期

plot.forecast(exp.forecast)

aaarticlea/png;base64,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" title alt width="672" />

b=exp.forecast$mean #2015年预测值
a=c(144570.40,81779.50,142537.80,151483.90) #2015年真实值
(b-a)/a#误差

##            Jan       Feb       Mar       Apr
## 2015 0.7768333 1.3146107 0.8487638 0.6584730

除了二月份，其余三个月的预测值可以说非常准。二月份之所以不准，主要原因是赶上春节假期，全国休假，包裹量骤降是必然的。 综上所诉，针对带有季节波动性的时序数据，SARIMA模型明显优于ARIMA模型。通过SARIMA模型的预测结果可以看出，今后几年，我国快递行业将保持持续快速发展态势。全国还有将近一半的乡镇不通快递。在这些乡镇，人们网购还不像北上广等大城市居民那样方便。还有很多农民盼望着快递企业可以帮助他们利用网络打开市场。因此，中国快递市场增长空间仍然十分巨大。

反馈与建议

Author：shangfr

邮箱：shangfr@foxmail.com