主成分分析作业解析

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1、主成分分析作业解答没有人看得懂SAS的输出。所以实验报告明确写出实验的结果：方程、向量、统计量是多少，不要写SAS的输出。namex1x2x3x4x5x6x7x81(冶金)9034252455101091192728216.11974350.1722(电力)4903197320351031334.27.15920770.0033(煤炭)6735211393767178036.18.27263960.0034(化学)4945436241815572250498.125.93482260.9855(机械)13919020350

2、52158981060993.212.61395720.6286(建材)122151621910351638262.58.71458180.0667(森工)23726572810312329184.422.2209210.1528(食品)11062230785493523804370.441654860.2639(纺织)17111239075210821796221.521.5638060.27610(缝纫)12063930612615586330.429.518400.43711(皮革)21505704620010870

3、184.21289130.27412(造纸)525161551038316875146.427.5787960.15113(文教艺术用品)1434113203193961469194.617.863541.574练习一、书p292，7-11题。用主成分分析确定信息损失不超过15%应取几个主成分，并解释这几个主成分的涵意。datadata711;inputname:$18.x1-x8;cards;1(冶金)90342524551010911927282.00016.1001974350.1722(电力)49031973203

4、51031334.2007.1005920770.0033(煤炭)6735211393767178036.1008.2007263960.0034(化学)4945436241815572250498.10025.9003482260.9855(机械)1391902035052158981060993.20012.6001395720.6286(建材)122151621910351638262.5008.7001458180.0667(森工)23726572810312329184.40022.200209210.1528(

5、食品)11062230785493523804370.40041.000654860.2639(纺织)17111239075210821796221.50021.500638060.27610(缝纫)12063930612615586330.40029.50018400.43711(皮革)21505704620010870184.20012.00089130.27412(造纸)525161551038316875146.40027.500787960.15113(文教艺术用品)1434113203193961469194.

6、60017.80063541.574;procprincompdata=data711prefix=zout=o711;varx1-x8;run;procmeansdata=data711;varx1-x8;run;means过程可以不必要。因为用它来计算均值和标准差，但princomp过程自己就会计算均值和标准差。EigenvaluesoftheCorrelationMatrixEigenvalueDifferenceProportionCumulative13.104912520.207470900.38810.388

7、122.897441621.967226080.36220.750330.930215550.288093290.11630.866640.642122260.338038130.08030.946850.304084130.217486370.03800.984860.086597760.054413380.01080.995770.032184380.029742610.00400.999780.002441780.00031.0000相关系数矩阵的特征根（可以看出各主成分的贡献率和累积贡献率）：TheSASSyste

8、m16:26Tuesday,May27,20082ThePRINCOMPProcedureEigenvectorsz1z2z3z4z5z6z7z8x10.4766500.2959910.1041900.045303-.184219-.0658540.7576190.245000x20.4728080.2