时间序列作业arma模型--

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1、时间序列ARMA模型作业一案例分析的目的本案例选取2001年1月，到2013年我国铁路运输客运量月度数据来构建ARMA模型，并利用该模型进行外推预测分析。二、实验数据数据来自中经网统计数据库15/15时间序列ARMA模型作业时间数量（亿）2001-010.932001-020.852001-030.812001-040.812001-050.872001-060.752001-070.912001-080.952001-090.812001-100.852001-110.722001-120.722

2、002-010.782002-020.932002-030.872002-040.802002-050.852002-060.732002-070.912002-080.962002-090.832002-100.862002-110.732002-120.742003-010.902003-020.962003-030.832003-040.712003-050.332003-060.532003-070.832003-080.952003-090.842003-100.882003-110.78

3、2003-120.762004-011.052004-020.952004-030.832004-040.832004-050.912004-060.822004-071.002004-081.032004-090.852004-100.902004-110.772004-120.782005-010.932005-021.062005-030.932005-040.912005-050.972005-060.862005-071.082005-081.122005-090.942005-101.0

4、02005-110.862005-120.852006-011.072006-021.132006-030.992006-040.992006-051.072006-060.962006-071.202006-081.222006-091.022006-101.102006-110.932006-120.932007-010.992007-021.112007-031.202007-041.032007-051.142007-061.022007-071.312007-081.352007-091.

5、142007-101.212007-111.032007-121.072008-011.192008-021.292008-031.192008-041.162008-051.172008-061.152008-071.382008-081.4115/15时间序列ARMA模型作业2008-091.252008-101.262008-111.082008-121.032009-011.332009-021.362009-031.182009-041.252009-051.292009-061.1520

6、09-071.422009-081.502009-091.222009-101.362009-111.112009-121.092010-011.272010-021.422010-031.412010-041.332010-051.382010-061.342010-071.602010-081.622010-091.382010-101.532010-111.232010-121.222011-011.522011-021.572011-031.412011-041.552011-051.532

7、011-061.512011-071.822011-081.792011-091.612011-101.632011-111.342011-121.312012-011.652012-021.562012-031.452012-041.652012-051.492012-061.622012-071.802012-081.852012-091.692012-101.512012-111.422012-121.482013-011.882013-021.402013-031.692013-041.75

8、2013-051.622013-061.802013-071.992013-082.032013-091.922013-101.6415/15时间序列ARMA模型作业数据来源：中经网数据库三、ARMA模型的平稳性首先绘制出N的折线图，如图从图中可以看出，N序列具有较强的非线性趋势性，因此从图形可以初步判断该序列是非平15/15时间序列ARMA模型作业稳的。此外，N在每年同期出现相同的变动方式，表明N还存在季节性特征。下面对N的平稳性和季节季节性进行进一步检验。四、单位