SPSS时间序列分析案例

页脚内容页脚内容用SPSS软件做时间序列分析，有某公司2002年一季度到2010年二季度的34个税后利润数据，要求预测出该公司2010年三季度和四季度的税后利润。要求：画出序列趋势图绘制出自相关图和偏自相关图确定参数和模型4.给出预测值观测值序列图税麻趙刑12{KKKJ.0CI-IWKJilil.OCI-HfKKm.ao-frtkjua.cici-4M<l{].0C|-2004)0.00-o.oo-~IIIIIIIIIIII税麻趙刑12{KKKJ.0CI-IWKJilil.OCI-HfKKm.ao-frtkjua.cici-4M<l{].0C|-2004)0.00-o.oo-~IIIIIIIIIIIIIIIII~QiQ3Qi03QIQ3QI00Q1Q301Q3QIQ3QI<23QI20022QD220032003200420042D0520052DD62006200?20072d0a200B200920092010日期税后盈利自相关图序列:税后盈利滞后白相关标准误差aBox-Liung统计量值dfSig.b1.306.1643.4821.0622.198.1624.9872.0833.185.1596.3403.0964.542.15718.3424.0015.084.15418.6415.0026.067.15118.8366.0047.094.14919.2397.0078.458.14629.0938.0009.041.14329.1769.00110.016.14029.18910.00111.012.13729.19711.00212.236.13432.30812.00113-.092.13132.80613.00214-.094.12833.34514.00315-.079.12533.74515.00416.106.12134.51016.005假定的基础过程是独立性（白噪音）。基于渐近卡方近似。

方差分析偏自相关序列：税后盈利滞后偏白相关标准误差1.306.1712.115.1713.107.1714.503.1715-.279.1716-.010.1717.046.1718.268.1719-.130.17110-.054.17111-.053.17112-.081.17113-.040.17114-.051.17115-.027.17116-.062.171方差分析3、确定参数和模型时间序列建模程序模型描述模型类型模型ID税后利润模型1ARIMA(0,1,0)(0,1,0)模型摘要SE垠水皆百池5102550759Q95平:他券局方5.SO3E-1?5.5O2E-175.5D2E-1T5.503E-175.503E-1?5502E-175.5D2E-1T5.5D2E-1T5.5O3E-1?55D2E-17尺方.B31J.l.631.B31.031J_.031.631.B31.031RMSE10472.3031D472.3Q3104T2.3Q210472.3031O472.3D310472.30310472.2D31fl+72.30210472.3Q310471303WAPE23.20921.20923.20923.20923.20323.2D923.2D923.2D923.20923.209M3XAPE146.390148.390143.390146.390146.390HB.390■143.390iaa.390146.39014B.3BOMAEZfflQ.Bi575098157509.31575D9.H1575D9.H15F50B.815I：'!■■.1：-!7S09.B157509815M湖E27335.1T727935.17727335.17T27935.17727935.17727B35.11727935.17727335.17727935.1772TB35.177z.^-.l-.门■1Q.B291AS2919.6291站対1BJ291G6M19.62919.6231Q.B291D.B39模型统计量模型预测变量数模型拟合统计量Ljung-BoxQ(18)离群值数平稳的R方统计量DFSig.税后利润-模型105.502E-1717.68818.47602WM0.0Q--juquunN1MOTO.0(?-BODDO.aC^--juquunN1MOTO.0(?-BODDO.aC^-4、给出预测值2010年第三季度139621.02万元2010年第四季度170144.55万元剔除季节成分后，平滑处理及剔除循环波动因素的序列图带列3EASON300—MSUL8C4中税AI带列3EASON300—MSUL8C4中税AI和3&^节性训120000.0(XXM3r-IDOOOO.MODO-60000.(xx)oo-4OOOO.<XXXX^-2DD00.(XXX>£rIIIIIIIIIIIIIIIII□103Q103Q1Q3QflQ3QIQ3Q1Q3Q1Q3Q103Q1

20022(X)220032C032004200420352005200620062007200720032336200920CT2010SEASON、MOD_6、MUL、EQU、4中税后利润的季节性调整序列自相关图序列：SEASON、MOD6、MUL、EQU、4中税后利润的季节性调整序列滞后白相关标准误差aBox-Liung统计量值dfSig.b1.728.16419.6331.0002.450.16227.3832.0003.310.15931.1693.0004.207.15732.9114.0005.219.15434.9415.0006.241.15137.4846.0007.243.14940.1687.0008.226.14642.5718.0009.183.14344.2139.00010.162.14045.55110.00011.093.13746.01211.00012.006.13446.01512.00013-.047.13146.14513.00014-.021.12846.17214.00015-.022.12546.20415.00016-.036.12146.29416.000a.假定的基础过程是独立性（白噪音）。

自相关图序列：SEASON、MOD6、MUL、EQU、4中税后利润的季节性调整序列滞后白相关标准误差aBox-Liung统计量值dfSig.b1.728.16419.6331.0002.450.16227.3832.0003.310.15931.1693.0004.207.15732.9114.0005.219.15434.9415.0006.241.15137.4846.0007.243.14940.1687.0008.226.14642.5718.0009.183.14344.2139.00010.162.14045.55110.00011.093.13746.01211.00012.006.13446.01512.00013-.047.13146.14513.00014-.021.12846.17214.00015-.022.12546.20415.00016-.036.12146.29416.000假定的基础过程是独立性（白噪音）。基于渐近卡方近似。□猱融—置侑上朿——迴悄下限偏自相关序列：SEASON、MOD_6、MUL、EQU、4中税后利润的季节性调整序列滞后偏白相关标准误差1.728.1712-.168.1713.108.1714-.053.1715.206.1716.000.1717.076.1718-.015.1719.014.17110.034.17111-.121.17112-.066.17113-.059.17114.115.17115-.134.17116.019.171□系数—堆信上屜——置悄下限模型描述模型类型模型IDSEASON、MOD_6、MUL、EQU、4模型_1中税后利润的季节性调整序列ARIMA(0,l,0)(0,0,0)1吃SE杲J'f3百分应510255075go95于绘Ejm才■2.551E-16-2.501E-1E-2.591E-16-2.591Bie-2.5DiE-1B-2.591E-16-2.591E-16-2.501E-1E-2.591E-16-2.591E-16R方812：：l-.312B12.812.312Bl2：：l-.312.012RM8E10075096W075.0gEi10075.050100750961DQ75.03610075.09610075D96W075.0gEi10075.05010075096MAFE13.1541S.15418.15418.15415.1541B.15418.15+1S.1541B.15418.154bhuAPE第07255.07255.0725507255.07255.0725507255.07255.07255.072MAE758^.7627584.7027534.7E275B47627534.7027534.7B275B47627584.7027534.76275B47623504154935041.549350^1.64935041.54935041.5^9350^1.54935041.54935041.549350^1.64935041.649ZE去毗刃BC13.5421S.5^218.54218.5421S.5^21B.54218.5421S.5^21B.54218.542模型统计量模型预测变量数模型拟合统计量Liung-BoxQ(18)离群值数平稳的R方统计量DFSig.SEASON、MOD_6、MUL、EQU、4中税后利润的季节性调整序列-模型10-2.5