典型相关分析的过程和程序

1、典型相关程序：proc cancorr data=work.xing vprefix=u wprefix=v;var x1-x2;with y1-y2;run;结果：(典型相关系数及检验)Canonical Correlation AnalysisAdjusted ApproximateSquaredCanonicalCanonicalStandardCanonicalCorrelation CorrelationErrorCorrelation0.7885080.7746980.0772110.6217450.053740.0.2035350.002888此结果可知，第 对典型变量之间的典型

2、相关系数为0.788508，它比0.053740大，说明正确。12Eigenvalues of Inv(E)*H=CanRsq/(1-CanRsq)Eigenvalue Difference ProportionCumulative1.64371.64080.99820.99820.00290.00181.0000下面为用似然比法检验典型相关系数与0的差别是否显著。Test of H0: The canonical correlations in the current row and all that follow are zeroLikelihoodRatioApproximateF Va

3、lueNum DFDen DFPr F10.377162886.604420.000320.997112040.061220.8031由于0.00030.05，所以说明第二对典型相 关系数不显著。所以只取一对典型变量。The CANCORR Procedure（原始的典型系数）Canonical Correlation AnalysisRaw Canonical Coefficients for the VAR Variablesu1u2X1X10.0565661954-0.139971093X2X20.07073683130.1869496027Raw Canonical Coefficie

4、nts for the WITH Variablesv1v2y1y10.0502425983-0.176147939y2y20.08022239880.2620835635用原指标来线性表达第一对典型变量的系数：U1=0.0565661954x1+0.0707368313x2V1=0.0502425983 y1+0.0802223988y2Canonical Correlation Analysis（标准化的典型系数）Standardized Canonical Coefficients for the VAR Variablesu1u2X1X10.5522-1.3664X2X20.52151

5、.3784Standardized Canonical Coefficients for the WITH Vriablesv1v2y1y10.5044-1.7686y2y20.53831.7586用标准化指标来线性表达第一对典型变量的系数，即：U1=0.5522x1+ 0.5215x2V1=0.5044y1+0.5383y2第一典型变量在x1和x2上的系数几乎一样大。同理。The CANCORR Procedure（典型结构）Canonical StructureCorrelations Between the VAR Variables and Their Canonical Variab

6、lesu1u2X1X10.9353-0.3539X2 X2 0.92720.3747X1在典型变量u1上的系数和它跟典型变量u1的相关系数符号相同，都是正的。所以x1 对u1有正的影响。同理x2对u1也有正的影响。 TOC o 1-5 h z Correlations Between the WITH Variables and Their Canonical Variables v1v2y1y10.9562-0.2927y2y20.96160.2743Correlations Between the VAR Variables and the Canonical Variables of the WITH Variables v1v2X1X10.7375-0.0190X2X20.73110.0201Correlations Between the WI