SAS程序范例2文档格式.docx

1、d&i;proc cancorr data=&i out=a&i;var &c&with &b&run;proc print data=a&i（keep=v1 w1 v2 w2）;%let plotitop=gopts=cback=blue, color=white, cframe=yellow;%end;%mend;%cancorr; 表5.13.1 d1的典型相关系数及显著性检验The CANCORR ProcedureCanonical Correlation AnalysisAdjusted Approximate Squared Canonical Canonical Standar

2、d Canonical Correlation Correlation Error Correlation1 0.894618 0.889469 0.039156 0.8003412 0.009496 . 0.196098 0.000090Test of H0: The canonical correlations in theEigenvalues of Inv（E）*H current row and all that follow are zero= CanRsq/（1-CanRsq）Likelihood ApproximateEigenvalue Difference Proporti

3、on Cumulative Ratio F Value Num DF Den DF Pr F1 4.0085 4.0084 1.0000 1.0000 0.19964137 14.24 4 46 Wilks Lambda 0.19964137 14.24 4 46 Pillais Trace 0.80043080 8.01 4 48 Hotelling-Lawley Trace 4.00862032 22.76 4 26.595 Roys Greatest Root 4.00853014 48.10 2 24 1 37.4028 19.8272 0.6502 0.6502 0.00028519

4、 57.10 16 67.849 2 17.5756 15.7910 0.3055 0.9557 0.01095221 33.62 9 56.127 3 1.7846 1.0194 0.0310 0.9867 0.20344374 14.60 4 48 Lambda 0.00028519 57.10 16 67.849 s Trace 2.99449995 18.61 16 100 Hotelling-Lawley Trace 57.52815537 75.87 16 38.364 s Greatest Root 37.40278297 233.77 4 25 表5.14.2 d1的典型相关分

5、析 V1 V2 V3 V4x1 0.0176483864 -0.018438494 -0.072065034 -0.036908372x2 -0.004138819 -0.016483463 0.0392402698 0.0378485365x3 -0.044067571 0.0168780218 -0.067099874 -0.010344513x4 0.0314882969 0.0085774763 0.0490970681 -0.003744316 W1 W2 W3 W4y1 0.0268298418 -0.023770114 -0.069220296 -0.124811032y.025

6、*y4 0.0416134733 0.0090148585 0.0866163355 0.0026487349x1 2.0275 -2.1182 -8.2789 -4.2401x2 -0.8954 -3.5660 8.4893 8.1882x3 -9.6032 3.6781 -14.6224 -2.2543x4 8.9950 2.4503 14.0252 -1.0696W1 W2 W3 W4y1 1.0219 -0.9054 -2.6365 -4.7539y2 -0.5954 -1.1608 1.4504 6.1246y3 -3.6022 1.5443 -7.6390 -1.4531y4 3.

7、9799 0.8622 8.2840 0.2533x1 0.5810 0.3565 -0.3876 0.6206x2 0.4981 0.3942 -0.3352 0.6958x3 0.4661 0.5182 -0.3414 0.6306x4 0.5274 0.5121 -0.3105 0.6026y1 0.8738 0.0805 -0.4344 0.2031y2 0.8100 0.1712 -0.4184 0.3736y3 0.6899 0.5452 -0.3963 0.2642y4 0.7725 0.4984 -0.3097 0.2429x1 0.5734 0.3468 -0.3103 0.

8、4086x2 0.4916 0.3834 -0.2684 0.4581x3 0.4600 0.5040 -0.2733 0.4152x4 0.5205 0.4981 -0.2486 0.3968y1 0.8624 0.0783 -0.3478 0.1337y2 0.7994 0.1665 -0.3349 0.2459y3 0.6808 0.5303 -0.3172 0.1740y4 0.7623 0.4848 -0.2479 0.1599表5.14.3 d1的典型相关分析结果Obs D V1 V2 W1 W21 Beijing 3.50032 -2.80389 3.45586 -2.82174

9、2 Tianjin -0.76879 0.22625 -0.95963 0.318673 Hebei -0.04681 -0.18632 0.00253 -0.215394 Shanxi -0.28237 -0.12460 -0.39521 -0.291935 Inner Mongolia 0.30510 0.01303 0.56018 -0.035816 Liaoning -0.57683 0.57580 -0.67997 0.707347 Jilin -0.48922 -0.19005 -0.45423 -0.314098 Heilongjiang -0.98150 0.24046 -1.

10、18846 0.349499 Shanghai 2.25688 1.75375 2.27277 2.1256210 Jiangsu -0.25188 2.15720 0.05209 2.1024811 Zhejiang 0.70449 2.15860 0.70351 1.8158312 Anhui -0.29929 -0.05501 -0.31896 -0.1086613 Fujian -0.98139 -0.49088 -0.70698 -0.1137914 Jiangxi -0.52130 -0.04863 -0.57200 -0.2668215 Shandong 0.07078 0.14

11、063 -0.00864 0.4245116 Henan 0.07757 -0.40429 -0.30917 -0.3814417 Hubei -0.32718 -0.20418 -0.43890 -0.1548418 Hunan 0.42951 -0.51119 0.41897 -0.1503319 Guangdong 1.72151 2.23704 1.60625 2.0817920 Guangxi 0.30715 -0.86204 0.54000 -0.6031321 Hainan -0.77586 -0.74224 -0.73227 -0.0937222 Sichuan 0.76562

12、 -0.03533 0.58319 -0.1765523 Guizhou -0.20683 -0.39726 -0.39349 -0.4969124 Yunnan -1.06109 -0.28876 -0.94736 -0.4579025 Tibet -0.62581 -0.37420 -0.57004 -0.5324526 Shaanxi 0.19275 -0.68828 0.47605 -1.1033027 Gansu -0.39091 -0.31438 -0.43389 -0.4480528 Qinghai -0.73687 -0.19395 -0.69015 -0.3161329 Ningxia -0.74773 -0.17897 -0.69357 -0.3044130 Xinjiang -0.26001 -0.40831 -0.17848 -0.53832图5.14.1 d1的（D，V1）图（标号地区）图5.14.2 d1的（D，W1）图（标号地区）图5.14.3 d1的（D，V2）图（标号地区）图5.19.4 d1的（D，W2）图（标号地区）