SAS操作-时间序列

1、1菜单操作绘制自相关、偏相关和逆函数K先要激活库文件。2、进入“时间序列”窗口solutions=analysis=timeseriesforecastingsystemSolutionsWindowHelpIAnalysis3DVisualAnalysis1DevelopmentandProgrammingAnalystReportingDesignofExperimentsAccessoriesEnterpriseMinerASSISTGeographicInformationSystemDesktopGuidedDataAnalysisEIS/OLAPApplicationBuilder

2、ntsractiveDataAnalysisi1InvestmentAnalysis1iMarketResearchi1ProjeutManagement11QualityImprovement11QueueingSimulation11TimeSeriesForecastingSystem11TimeSeriesViewerTimeSeriesForecasting0Deve1opMode1sFitMode1sAutomatically也ProduceForecastsManageProjects3、指定数据集Browse=4、指定时间DD变量选择t作t时间ID变量5、观察样本自相关、偏相关

3、函数点击图标ViewsSeriseGiahpicaly=指定变量yn点击Grahp”。6、模型估计project计划DescriptDatasetTimeIDIntervalDevelopmodelsFitmodelsautomaticallyProduceforecastsManageprojects2编程Procprintdata=szzs2;/*/、基本SAS语句dataa;/建立名为“a”的临时数据文件法/Inputxt=_n_；cards;(数据)/文件a中的变量为x,为横读/自动生成序号变量t*7/数据开始*/*据略/法数据结束/Procgplotdata=a;Plotx*t;绘图

4、一按文件a作散点图/纵坐标为x,横坐标为t*/symbolc=redi=joinv=star;曲线颜色ured（红八black（黑）、green（绿）、blue（蓝八pink（粉红），观察值图形vst（星八circle（圆）、diamond（菱），连线方式ijoin（线性八spline（光滑）、needle（悬垂）/Procprintdata=szzs2;/*/procarimadata=a;identifyvar=xnlag=18minicp=(0:4);run;estimatep=2method=uls；forecastlead=5id=i;run;分析一对数据集a进行arima分析/八识

5、别一给出5个信息，最优模型识别B工C*/运行*7八模型估计一阶数，方法法/预测一*/运行*7Procprintdata=szzs2;/*/Procprintdata=szzs2;/*/estimatep=l;run;ARCH效应检验和GARCH模型建立程序如下：datasz;/对x取对数，对lx差分/inputx;lx=log(x);dlx=dif(lx);13=lag3(dlx)16=lag6(dlx)/Cards;Procprintdata=szzs2;/*/数，方法*/ARCH检验，*/Procautoregdata=sz;modelsyl=1316/archtest;Procprint

6、data=szzs2;/*/modelsyl=1316garch=(q=l/p=l)dist=t;outputout=szzs2cev=h;modelsyl=1316garch=(q=lzmean=sqrt)dist=t;modelsyl=1316garch=(q=lzmean=log)dist=t;modelsyl=1316garch=(q=l,p=lztype=Gxp);run;run;dataar指令系统，建立一个名为“ar”的临时数据集inputxy输入两个变量“xv”的数据，“昶”为变量类型formatxy指出变量的输出格式cards;开始输入数据procarima对数据集“址”进行

7、“arima”分析procanova对数据集。匕”进行“方差分析”identify对变量“x,y”的性质进行识别，给出5个方面的信息：1、描述统计量；2、样本自相关函数3、样本偏相关函数；4、样本逆自相关函数；5、白噪声检验。identifyVar=xnlag=8minicp=(0;5)q=(0:5)参数估计方法Method=mlMethod=ulsMethod=cls最大似然估计最小二乘估计条件最小二乘估计dif(x)对X作1阶差分：%dif(dif(x)对X作2阶差分：兀difk(x)对x作k步差分：巒方差齐性检验1dataabc;doa=lto4;doi=lto4;InputxOutpu

8、t;end;end;/*自动生成序号变量徉/cards;19232113212427202018191522252722/Procgplotdata=a;/绘图一按文件a作散点图*7PlotX壮；/纵坐标为X,横坐标为procprinta;procanova;classa;modelx=a;meansa/hovtest;run;2、datadO;Inputxt=_n_；cards;588652959397907267395163775757594545803836398594/procprint;vartx;procgplotdmta=d0;plotx*t;symbolc=redi=joinv

9、=star;run;datadl;doa=lto4;doi=lto6;Inputyoutput;end;end;cards;588652959397907267395163775757594545803836398594/procanova;classa;modely=a;meansa/hovtest;procprint;varay;run;datadO;Inputyt=_n_；doa=lto4;doi=lto6;Inputxoutput;end;end;cards;588692959397907267395163775757594545803836398594/procprint;vartx

10、;procgplotdata=d0;plot*壮；symbolc=redi=joinv=star;run;procanova;classa;modelx=a;meansa/hovtest;run;二、模拟随机数程序程序是对的，我认为是系数的问题对数据的模拟有很大的影响是不是数据对系数的选取有要求呢？就是下面的03,0.26,015这三个系数对模型的估计很童要（为什么？）干扰项X是正态分布，从直方图可以看出来，没有问题。模拟ARdataa;al=06;a2=037;a3=012;doi=lto500;e=0+rannor(12);y=02*al+03*a2+04a3+6;a3=a2;a2=al;

11、al=y;output;end;procprint;variy;run;procarimadata=a;identifyvar=ynlag=24minep=(0:5)d=(1:3)q=(0:5);run;estimatep=3;run;procgplotdata=a;symboli=splinec=red;ploty*i;run;procgchartdata=a;vbarx;run;模拟MAdataa;al=06;a2=037;a3=012;doi=lto5000;e=0+rannor(1);y=02*al+03*a2+04a3+e;a3=a2;a2=al;al=e;output;end;pr

12、ocprint;variy;run;procarimadata=a;identifyvar=ynlag=24minep=(0:5)q=(0:5);run;estimateq=3;run;procgplotdata=a;symboli=splinec=red;ploty*i;run;procgchartdata=a;vbarx;run;一、读出和数据指出文件的路径和文件名即可。procprintdata=Td:/SAS90/shuju/exajnp422sas7bdatT;procprintx;run;激活库文件libnamekuTd:/SAS90T;dataku.abc;inputx;card

13、s;167168procprint;run;libnamekuTd:/SAS90/shujuT;dataku.abc;inputcards;frun;“库”三、建立sas数据文件libnamekuTd:/SAS9.O;dataku.ss;inputy;t=_n_;cards;47642371procprint;run;以化学反应数据为例dataa;Inputxt=_n_；cards;fProcgplotdata=a；Plot*壮ime;symbolc=redi=joinv=star;procarimadata=a;identifyvar=xnlag=18minep=(0:5)q=(0:5);e

14、stimatep=2;run;MininumTableValue:BIC(1,0)=4.707681datali;建立临时数据集liinputx;变量x,“为横读，否则为竖读t=nj序号txl=dif(x);变幻=变乂的一阶差分y=x-0.05*t;将序列x-0.05*t值给ycards;procarimadata=li;对数据集temp进行arima分析identifyvar=xnlag=18minicp=(0:5)q=(0：5)；对变进行识别，计算最优BICestimatep=2;估计模型AR(p)的参数forecastlead=5id=t;预测run;procgplotdata=li;对

15、数据集1除图ploty*t;以y为横坐标、t为纵坐标作图symbolc=redi=jionv=star;曲线红色，折线连接，星形点procarimadata=li;对数据集temp进行arima分析identifyvar=ynlag=18minicp=(0:5)q=(0:5);计算最优BICestimatep=2;forecastlead=5id=t;自相关和偏相关都截尾怎么办?拖尾与載尾的用处dataar;i=0;seed=O;x=0;dowhile(i200);i=i+l;x=05*x+normal(seed);output;dropseed;end;run;procprint;run;/

16、i=0;seed=0;x=0;dov/hile(i=Tljan57Td;plotx*dateforecast*date195*dateu95*date/overlayvaxis=axislhaxis=axis2-0g294-0O586-08292一：L.26520.7591-037360667318955-020570.8985043360.608903252一：L.26780.6705href=T31dec60symbol1symbolZsymbolssymbol4axisllabel=(TPassenger1)order=(250to800by50);axis2label=(TMonthT

17、)order=(Tljan57TdtoTljan62Tdbyyear);formattitleltitle2title3title4i=joini=joini=joini=joinv=Cv=F1=11=1h=l51=1font=swissbc=red;h=21=1font=swissbc=blue;font=s,wissbc=green;font=s,wissbc=green;datemonyy.;TForecastChartT;TC-xT;TF-forecastT;TNone-u95and195T;run;AR数据0.5000-0.964011116-06413-04349-0.4415-0

18、252307283-0.58380.308611659一:L.31930.544909W710.3545-31748-0605108261-0.9684-079610.59390.5534-0.0302-0.0289-07470-0.0328-0.58280162509951-0.33330.58050.4829-031580.3884-0.00050.3899-06701-0.39953.3149一：L.9040-065941.2795-0.9665-0.8482一0.516103235-0.07820.2717036350.0294-07355一：L.25002.109900416一：L3

19、878083351.4192一:L.1132一:L.6165-0491W一0.9178-000900.1583-06740-0.009506113-0.08610.3869一：L.3408-04734-0732600064一：L.2432一三.21942.5102一024200.0129-0.9886-04340一0.56210.6022-0647115653一三09601.2718dataa;/建立名为的临时数据文件*7Inputx/文件a中的变量为x,为横读/t=_n_;/*自动生成序号变量徉/cards;/法数据开始/TOC o 1-5 h z1121181321291211351481

20、481361191041181151261411351251491701701581331141401451501781631721781991991841621461661711801931811832182302422091911721941961962362352292432642722372111802012041882352272342643022932592292032292422332672692703153643473122742372782842773173133183744134053553062713063153013563483554224654674043473053

21、36340318362348363435491505404359310337360342406396420472548559463407362405417391419461472535622606408461390432Procgplotdata=a;Plotx*t;symbolc=redi=joinv=star;procarimadata=a;identifyvar=xnlag=18minicp=(0:4);/数据结束*7/按文件a作散点图法/纵坐标为x,横坐标为t*/设定图中线和的颜色.类型等*/八对数据集a进行arima分析舟/统计童，散点图，白噪声检验，计算最优的BIC*/run;/运

22、行/procreg;运行*7modely=c;run;datatest;inputxlog=log(x);xl=dif(x);x2=difl2(xl);dmte=intnx(TmonthTrTljanl949Tdz_n_-l);formatdatemonyy.;cards;1121181321291211351481481361191041181151261411351251491701701581331141401451501781631721781991991841621461661711801931811832182302422091911721941961962362352292432

23、64272237211180201204188235227234264302293259229203229242233267269270315364347312274237278284277317313318374413405355306271306315301356348355422465467404347305336340318362348363435491505404359310337360342406396420472548559463407362405417391419461472535622606508461390432procgplotest;plotx*date=l/haxis=11jan49TdtoTljan61Tdbyyear;plotxlog*date=l/hax