用sas进行灰色预测

dataa1;inputtyearxt@@;yt+xt;/*生成一阶累加序列*/index=1;zt=-(yt+lag(yt))/2;/*为数据矩阵B准备数据*/datalines;119902439521991252863199226901419932733951994278716199528721719962972881997300679199830791101999312841120003371612200134558;prociml;usea1;readallvar{ztindex}intoBwhere(zt^=.);readallvar{xt}intoynwhere(zt^=.);ahat=inv(B`*B)*B`*yn;ahatt=ahat`;na={au};creata2fromahatt[colname=na];appendfromahatt;quit;dataa3;seta2;index=1;dataa4;seta1;if_n_=1;xt0=xt;keepxt0index;dataa5;mergea1a3a4;byindex;if_n_=1thenxp=xt;elsedoyt1=(xt0-u/a)*exp(-a*(t-1))+u/a;yt0=(xt0-u/a)*exp(-a*(t-2))+u/a;xp=yt1-yt0;end;error=xp-xt;rerror=error/xt*100;dropytindexztyt1yt0xt0;procprintdata=a5;run;

运行结果：ObstyearxtAUxperrorrerror11199024395-0.02856924543.3924395.000.0000.0000022199125286-0.02856924543.3925604.33318.3311.2589233199226901-0.02856924543.3926346.36-554.635-2.0617644199327339-0.02856924543.3927109.90-229.097-0.8379855199427871-0.02856924543.3927895.5724.5700.0881666199528721-0.02856924543.3928704.01-16.994-0.0591777199629728-0.02856924543.3929535.87-192.129-0.6462988199730067-0.02856924543.3930391.84324.8431.0804099199830791-0.02856924543.3931272.62481.6231.564171010199931284-0.02856924543.3932178.93894.9292.860661111200033716-0.02856924543.3933111.50-604.501-1.792921212200134558-0.02856924543.3934071.10-486.903-1.40894

datacai;inputty@@;y1=LOG(y);/*LOG2(argument)LOG10(argument)*/cards;1978548.291979558.361980567.231981577.901982586.971983594.401984600.591985608.391986619.961987629.341988641.721989653.261990669.751991677.031992684.461993691.691994700.011995710.011996715.941997723.901998731.791999740.202000749.192001758.232002768.102003781.192010.2020.;procreg;modely1=t/cli;run;

运行结果：DepVarPredictedStdErrorObsy1ValueMeanPredict95%CLPredictResidual16.30686.31900.0034246.29926.3388-0.012226.32506.33300.0032256.31336.3527-0.00800936.34086.34700.0030316.32756.3666-0.00626046.35946.36100.0028436.34166.3805-0.00163656.37506.37500.0026636.35576.3944-0.00007566.38766.38910.0024926.36986.4083-0.00150776.39796.40310.0023316.38396.4222-0.00515986.41086.41710.0021856.39806.4362-0.00626796.42976.43110.0020556.41216.4501-0.001440106.44476.44510.0019446.42616.4641-0.000435116.46426.45910.0018576.44026.47810.005034126.48206.47310.0017976.45426.49200.008846136.50696.48710.0017666.46826.50600.0198146.51776.50120.0017666.48236.52000.0166156.52866.51520.0017976.49636.53410.0135166.53916.52920.0018576.51026.54810.009962176.55116.54320.0019446.52426.56220.007907186.56536.55720.0020556.53826.57620.008080196.57366.57120.0021856.55216.59030.002385206.58476.58520.0023316.56616.6044-0.000570216.59556.59920.0024926.58006.6185-0.003741226.60696.61320.0026636.59396.6326-0.006326236.61906.62730.0028436.60786.6467-0.008265246.63106.64130.0030316.62176.6608-0.0103256.64396.65530.0032256.63566.6750-0.011426