应用时间序列分析 -

1/1应用时间序列分析-姓名：葛国峰学号：1122307851编号：33习题2.3

2.解：

datab;

inputy@@;

time=intnx('month','1jan1975'd,_n_-1);

formattimedata;

cards;

330.45330.97331.64332.87333.61333.55

331.90330.05328.58328.31329.41330.63

331.63332.46333.36334.45334.82334.32

333.05330.87329.24328.87330.18331.50

332.81333.23334.55335.82336.44335.99

334.65332.41331.32330.73332.05333.53

334.66335.07336.33337.39337.65337.57

336.25334.39332.44332.25333.59334.76

335.89336.44337.63338.54339.06338.95

337.41335.71333.68333.69335.05336.53

337.81338.16339.88340.57341.19340.87

339.25337.19335.49336.63337.74338.36

;

run;

procgplot;

ploty*time;

symbol1v=doti=joinc=blackw=3;

procarimadata=b;

identifyvar=ynlag=24;

run;

（1）序列图：

判断：由图形可知：该序列不平稳。

（2）

TheSASSystem10：20Tuesday,September20,20131

TheARIMAProcedure

WARNING:ThevalueofNLAGislargerthan25%oftheserieslength.Theasymptoticapproximationsusedforcorrelationbasedstatisticsandconfidenceintervalsmaybepoor.

NameofVariable=y

MeanofWorkingSeries334.5044

StandardDeviation3.151627

NumberofObservations72

Autocorrelations

LagCovarianceCorrelation-198765432101234567891StdError

09.9327521.00000||********************|0

19.0140500.90751|.|******************|0.117851

27.1686040.72171|.|**************|0.191744

35.0907160.51252|.|**********|0.226350

43.4747000.34982|.|*******.|0.241932

52.4523610.24690|.|*****.|0.248858

62.0172850.20309|.|****.|0.252237

72.0879440.21021|.|****.|0.254498

82.6251080.26429|.|*****.|0.256898

93.6188210.36433|.|*******.|0.260647

104.8145710.48472|.|**********.|0.267627

115.8063060.58456|.|************|0.279554

125.9793080.60198|.|************|0.296045

135.1492640.51841|.|**********.|0.312584

143.6608440.36856|.|*******.|0.324305

152.0532200.20671|.|****.|0.330072

160.8083340.08138|.|**.|0.331865

170.0134550.00135|.|.|0.332142

18-0.322607-.03248|.*|.|0.332142

19-0.269167-.02710|.*|.|0.332186

200.1116040.01124|.|.|0.332217

210.8219160.08275|.|**.|0.332222

221.6896320.17011|.|***.|0.332508

232.4156310.24320|.|*****.|0.333715

242.5082480.25252|.|*****.|0.336167

"."markstwostandarderrors

（3）TheSASSystem10：20Tuesday,September20,20132

TheARIMAProcedure

InverseAutocorrelations

LagCorrelation-198765432101234567891

1-0.5808

2|************|.|

2-0.02712|.*|.|

30.20008|.|****.|

4-0.12866|.***|.|

50.07658|.|**.|

6-0.0619

7|.*|.|

70.03185|.|*.|

80.02403|.|.|

9-0.10454|.**|.|

100.17130|.|***.|

11-0.12291|.**|.|

12-0.00765|.|.|

130.04289|.|*.|

14-0.05806|.*|.|

150.11307|.|**.|

16-0.10786|.**|.|

170.02081|.|.|

180.06299|.|*.|

19-0.06869|.*|.|

200.02879|.|*.|

21-0.03841|.*|.|

220.09736|.|**.|

23-0.09477|.**|.|

240.03281|.|*.|

PartialAutocorrelations

LagCorrelation-198765432101234567891

10.90751|.|******************|

2-0.57732|************|.|

30.02855|.|*.|

40.23812|.|*****|

5-0.03355|.*|.|

60.06915|.|*.|

70.15640|.|***.|

80.17931|.|****.|

90.25748|.|*****|

100.10993|.|**.|

110.00617|.|.|

12-0.25943|*****|.|

13-0.17679|.****|.|

140.02902|.|*.|

15-0.03960|.*|.|

160.01081|.|.|

17-0.09768|.**|.|

18-0.02402|.|.|

TheSASSystem10：20Tuesday,September20,20133

TheARIMAProcedure

PartialAutocorrelations

LagCorrelation-198765432101234567891

190.00630|.|.|

20-0.08454|.**|.|

210.06247|.|*.|

220.01467|.|.|

230.02958|.|*.|

24-0.10605|.**|

.|AutocorrelationCheckforWhiteNoise

ToChi-Pr>

LagSquareDFChiSqAutocorrelations

6139.506

LagSquareDFChiSqAutocorrelations

66.5660.36340.052-0.048-0