多元分析上机实验修改

多元分析上机实验修改第一页，共二十一页，2022年，8月28日2023/1/292第二页，共二十一页，2022年，8月28日2023/1/293Model:MODEL1DependentVariable:YAnalysisofVariance

SumofMeanSourceDFSquaresSquareFValueProb>FModel114141.7405214141.74052140.9920.0001Error6601.80823100.30137CTotal714743.54875RootMSE10.01506R-square0.9592DepMean43.51250AdjR-sq0.9524C.V.23.01651为校正后的决定系数.第三页，共二十一页，2022年，8月28日2023/1/294

ParameterEstimatesParameterStandardTforH0:VariableDFEstimateErrorParameter=0Prob>|T|INTERCEP15.9223664.749695801.2470.2589X12.0768030.1749030211.8740.0001ModelCrossproductsX'XX'YY'YX'XINTERCEPXYINTERCEP8144.8348.1X144.85899.6613109.99Y348.113109.9929890.25X'XInverse,ParameterEstimates,andSSEINTERCEPXYINTERCEP0.2249182623-0.0055203465.9223664747X-0.0055203460.00030499152.0768029572Y5.92236647472.0768029572601.80822932第四页，共二十一页，2022年，8月28日2023/1/295Model:MODEL1DependentVariable:YAnalysisofVariance

SumofMeanSourceDFSquaresSquareFValueProb>FModel114141.7405214141.74052140.9920.0001Error6601.80823100.30137CTotal714743.54875RootMSE10.01506R-square0.9592DepMean43.51250AdjR-sq0.9524C.V.23.01651为校正后的决定系数.第五页，共二十一页，2022年，8月28日2023/1/296

ParameterEstimatesParameterStandardTforH0:VariableDFEstimateErrorParameter=0Prob>|T|INTERCEP15.9223664.749695801.2470.2589X12.0768030.1749030211.8740.0001ModelCrossproductsX'XX'YY'YX'XINTERCEPXYINTERCEP8144.8348.1X144.85899.6613109.99Y348.113109.9929890.25X'XInverse,ParameterEstimates,andSSEINTERCEPXYINTERCEP0.2249182623-0.0055203465.9223664747X-0.0055203460.00030499152.0768029572Y5.92236647472.0768029572601.80822932第六页，共二十一页，2022年，8月28日2023/1/297

DepVarPredictStdErrLower95%Upper95%ObsYValuePredictPredictPredictResidual146.300035.62063.6039.577361.664010.6794230.700034.99763.6138.945961.0493-4.29763144.6149.89.630115.8183.8-5.2448469.200053.06583.63126.998879.132716.1342516.000021.08304.013-5.317247.4833-5.0830612.300022.53683.957-3.812748.8863-10.236872.70008.62224.601-18.346435.5908-5.9222826.300022.32913.965-4.027448.68563.97099.47.45843.55621.453273.4636.SumofResiduals0SumofSquaredResiduals601.8082PredictedResidSS(Press)5610.2160第七页，共二十一页，2022年，8月28日2023/1/298OBSXYPRESIDI114.346.312.2667214.030.7-4.9405369.3144.6-69.4832422.769.218.576157.316.0-6.055468.012.3-12.130571.32.7-7.506787.926.34.7089是第个观测值的预测残差,而是删去第i个观测值后,根据剩下的n－1组观测值建立线性回归方程并将xi代入此回归方程所得到的第i个观测值的预测值.第八页，共二十一页，2022年，8月28日2023/1/299多元线性回归上机实验2.

例1.2P25datalreg07;inputx1x2y@@;cards;1.379.084.9311.341.891.869.673.062.330.7610.25.7817.670.050.0615.910.730.4315.741.030.875.416.253.865.46.3.;symboli=rlv=star;/*（symbol为绘图设置语句*//*

i=rl要求画回归直线*//*v=star要求用星号表示点）*/第九页，共二十一页，2022年，8月28日2023/1/2910procgplot;ploty*x1;/*（要求画回归直线及点x1,y）*/procreg;modely=x1/xpxi;run;/*（要求建立一元线性回归方程并作检验）*/

procgplot;ploty*x2;procreg;modely=x2;run;procreg;modely=x1x2/alpha=0.01cli;run;/*（要求建立二元线性回归方程并作检验及回报与预报）*/第十页，共二十一页，2022年，8月28日2023/1/2911第十一页，共二十一页，2022年，8月28日2023/1/2912Y=5.621170-0.319113*X1;F=494.064;Prob>F为0.0001;R-square=0.9880;Y=0.363778+0.532975*X2;F=279.602;Prob>F为0.0001;R-square=0.9790;Y=3.610506-0.198281*X1+0.206755*X2;F=392.516;Prob>F为0.0001;R-square=0.9937;第十二页，共二十一页，2022年，8月28日2023/1/2913ModelCrossproductsX'XX'YY'YX'XINTERCEPX1X2YINTERCEP877.8732.2920.12X177.871066.931733.736997.2483X232.29133.736940.0809139.7036Y20.1297.2483139.703682.4468

X'XInverse,ParameterEstimates,andSSEINTERCEPX1X2YINTERCEP22.8232-1.37712.30253.6105X1-1.37710.08410.1384-0.1983X2-2.30250.13840.23680.2068Y3.6105-0.19830.20680.2015第十三页，共二十一页，2022年，8月28日2023/1/2914AnalysisofVarianceSumofMeanSourceDFSquaresSquareFValueProb>FModel231.6434615.82173392.5160.0001Error50.201540.04031CTotal731.84500RootMSE0.20077R-square0.9937DepMean2.51500AdjR-sq0.9911C.V.7.98289第十四页，共二十一页，2022年，8月28日2023/1/2915

DepVarPredictStdErrLower95%Upper95%ObsYValuePredictPredictPredictResidual14.93005.21620.1204.61505.8174-0.286221.86001.75280.1391.12522.38030.107232.33002.32580.1221.72212.92950.0042045.78005.56870.1544.91886.21860.211350.06000.11720.132-0.49980.7343-0.057260.43000.60680.1040.02511.1884-0.176870.87000.70250.1100.11371.29140.167583.86003.83000.0923.26264.39740.03009.3.84230.0903.27634.4084.

观测值预测值标准误95%置信下限与上限残差（剩余）第十五页，共二十一页，2022年，8月28日2023/1/2916例1.4逐步回归dataex;inputx1-x4y@@;cards;9.22.731.471.141.169.13.731.820.831.158.64.881.832.131.8410.233.971.591.351.365.63.731.841.820.865.374.241.871.350.96.133.151.991.650.128.24.651.624.570.98.84.381.542.071.937.63.861.62.421.19.74.381.691.521.48.375.11.812.281.7612.174.91.731.581.6410.273.731.611.21.478.94.471.880.80.928.235.281.73.071.5;procreg;modely=x1-x4/selection=rsquareb;modely=x1-x4/selection=rsquareadjrsqcpAICMSESSEcollinoint;run;procreg;modely=x1-x4/selection=stepwisesle=0.3sls=0.2;run;/*slsisthelevelspcifiedbyuser*/SLS=0.2定义剔除时的概率水平为0.2，SLE=0.3定义选入时的概率水平为0.3第十六页，共二十一页，2022年，8月28日2023/1/2917例1.4共线性诊断dataex;inputx1-x4y@@;x5=int((x2+x3+x4)*90)/90;cards;9.22.731.471.141.169.13.731.820.831.158.64.881.832.131.8410.233.971.591.351.365.63.731.841.820.865.374.241.871.350.96.133.151.991.650.128.24.651.624.570.98.84.381.542.071.937.63.861.62.421.19.74.381.691.521.48.375.11.812.281.7612.174.91.731.581.6410.273.731.611.21.478.94.471.880.80.928.235.281.73.071.5;procregdata=ex;modely=x1-x5/vifcollinoint;run;第十七页，共二十一页，2022年，8月28日2023/1/2918AnalysisofVarianceSumofMeanSourceDFSquaresSquareFValuePr>FModel52.554970.510998.030.0028Error100.636720.06367CorrectedTotal153.19169RootMSE0.25233R-Square0.8005DependentMean1.25063AdjR-Sq0.7008CoeffVar20.17663ParameterEstimatesParameterStandardVarianceVariableDFEstimateErrortValuePr>|t|InflationIntercept12.825101.339942.110.06120x110.026930.062210.430.67432.85303x21-27.0002325.70336-1.050.318276421x31-29.7323625.68616-1.160.27403263.98863x41-27.8153725.68282-1.080.3042137920x5127.5845725.695861.070.3083308366第十八页，共二十一页，2022年，8月28日2023/1/2919CollinearityDiagnostics(interceptadjusted)ConditionNumberEigenvalueIndex

12.455881.00000

21.484511.28621