SPSS时间序列分析案例

1、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：1 .画出序列趋势图2 .绘制出自相关图和偏自相关图3 .确定参数和模型4 .给出预测值观测值序列图W-1CKHKI0dQ-税后照利40000.00-20000.00-0.00-1-I-III-1-1-1-I-1-I-1-Q103O103Q10301030103O103Q103Q103Q1200220022003200320M200420D5200520062006200720072008200B200Q谢2010II期税后盈利自相关图序列：税

2、后盈利滞后自相关标准误差aBox-Ljung统计量值dfbSig.1.306.1643.4821.0622.198.1624.9872.0833.185.1596.3403.0964.542.15718.3424.0015.084.15418.6415.0026.067.15118.8366.0047.094.14919.2397.0078.458.14629.0938.0009.041.14329.1769.00110.016.14029.18910.00111.012.13729.19711.00212.236.13432.30812.00113-.092.13132.80613.0021

3、4-.094.12833.34514.00315-.079.12533.74515.00416.106.12134.51016.005a.假定的基础过程是独立性（白噪音）b.基于渐近卡方近似。税后猛利1234567S9W111213141516偏自相关序列：税后盈利滞后偏自相关标准误差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

4、.171税后锐利系数一曾信上限改令下限12345678910111213141516延迟数目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ARIMA(0,1,0)(0,1,0)模型摘要植酣拉舍拉宫战计量均值SE量小渔«±ffi百分自5102550759095平幅的R方S.S02E-17S.S02E-1755412E-175.501E-1I?5.502E-17凯5诬1F5.502E-175.M2E-175.502E-175.502E-17R方,631,831.B31.831,631.831.6318J1.B31RMSE10472.3031D4723U3

5、1D472.3DI310472.30110472J0310472.3D31072.30310472.3D31Q472.3Q31D472.3OJMAPE23.209盟二。923.209'23.20923JU23.20923.20923.20923.20933.209MaPE148.3901圾理。H6.390148.3901地甄14S.39Q148.390146.390148.390149J90MAE7509.S13泻的旬15750S.B157509.611S75D&.615?5O9.B1$片g.白H7506.6137509.6157MW5MR小27935JTT打9节17737S3

6、5.17737935,1?27835,17737935,177271935.17737935.1TT27935.177打9节17了正双比的日心16,63919«291Q6年19,6291&&J91302919.S3B19,62919629模型统计量k.，qulnNItXXJOT.CKTDODOO.QQT一瓦刎叩敏於tfi%测?QQ2?QQ?2Da3?二中1MC47口齿2CM5MD5?jfl?KK7M77QC72CGS200B?DDf2Q-q7羽口？0*Q日期税后利涧模居1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

7、润-模型05.502E-1717.68818.47604、给由预测值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12MOOOOOOO-10WOOQOGOO-fifldDOmak40000000002000000000-BDOOOO.OOCXKrSEASON芸口口2MULE0U4中税后利SES'f'q性调ai2002IIIIIIIIIIIIIIIQI03QIQ3Qi03Q-03Q103QIQ3QIQ3QI2003MD4加E7口口不?QOS2OQ62006pnn71M国2D0R2C1Ck门。701

8、门II期SEASONMOD_6MULEQU4中税后利润的季节性调整序列自相关图序列:SEASONMOD_6MULEQU4中税后利润的季节性调整序列滞后自相关标准误差aBox-Ljung统计量值dfSig.b1.728.16419.6331.0002.450.16227.3832.0003.310.15931.1693.0004.207.15732.9114.0005.219.15434.9415.0006.241.15137.4846.0007.243.14940.1687.0008.226.14642.5718.0009.183.14344.2139.00010.162.14045.5511

9、0.00011.093.13746.01211.00012.006.13446.01512.00013-.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:SEASONMOD_6MULEQU4中税后利润的季节性调整序列滞后自相关标准误差aBox-Ljung统计量值dfbSig.1.728.16419.6331.0002.450.16227.3832.0003.310.15931.1693.0004.207.15732.9

10、114.0005.219.15434.9415.0006.241.15137.4846.0007.243.14940.1687.0008.226.14642.5718.0009.183.14344.2139.00010.162.14045.55110.00011.093.13746.01211.00012.006.13446.01512.00013-.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）b.基于渐近卡方近似。SEASON

11、.MOD_6,MUL.EQU，4中税后利涧的季节性调整序列123456789W111213141516延迟数II偏自相关序歹SEASONMOD_6MULEQU4中税后利润的季节性调整序列SEASON.MOD6.MUL.EQU>4中脱片利润的季¥性调塾存列布数一世情上限置存TF取滞后偏自相关标准误差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-.13

12、4.17116.019.171延迟数目模型描述模型类型模型IDSEASONMOD_6MULEQU4模型_1中税后利润的季节性调整序列ARIMA(0,1,0)(0,0,0)器型拟合撞台铿计员SE最小值最文值百分便510255076q。95工巷的R方-2.591E-1B-2.591E-15-2.561E-162.691E-15-3.691E-16-2.591E-162.691E-16-2.691E-162.591E-1&-2.691E-16同方812.812812.812912812.812812,812.812RMSE10Q75.09610075.0961007509810075.096

13、10075.0961007509010075.09610075.096100750961i0075,096MATE18,15413.1541B15418,15413.1541B.15418.16418.1541S,154M*APE55.07255.07255.07256.07256.0725SJ7255.07265.07255,07255.072MAE75647627584.76275847627584.7627684.762758476275847627584.76275847627584.703MME35041.64935041.6493504164935041.64935041.6493504164935041.64935041S493504164935041649正S优的BIC18.51213.5121B542IS.5218.5121B.542118.54218.542IB.54213.542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.SEASONMOD_6MULEQU4中税后利润的季节性调整序列-模型0-2.591E-168.517