多元分析SAS上機(jī)實驗修改ppt課件

1、Y0102030405060708090100110120130140150X010203040506070Model: MODEL1Dependent Variable: YAnalysis of Variance Sum of MeanSource DF Squares Square F Value ProbFModel 1 14141.74052 14141.74052 140.992 0.0001Error 6 601.80823 100.30C Total 7 14743.54875 Root MSE 10.01506 R-square 0.9592 Dep Mean 43.5125

2、0 Adj R-sq 0.9524C.V. 23.016511)1(222 pnRpRRjdA為校正后的決議系數(shù)為校正后的決議系數(shù). Parameter Estimates Parameter Standard T for H0:Variable DF Estimate Error Parameter=0 Prob |T|INTERCEP 1 5.922366 4.74969580 1.247 0.2589 X 1 2.076803 0.17490302 11.874 0.0001Model Crossproducts XX XY YYXX INTERCEP X YINTERCEP 8 144

3、.8 348.1X 144.8 5899.66 13109.99Y 348.1 13109.99 29890.25XX Inverse, Parameter Estimates, and SSE INTERCEP X YINTERCEP 0.2249182623 -0.005520346 5.9223664747 X -0.005520346 0.0003049915 2.0768029572 Y 5.9223664747 2.0768029572 601.80822932Model: MODEL1Dependent Variable: YAnalysis of Variance Sum of

4、 MeanSource DF Squares Square F Value ProbFModel 1 14141.74052 14141.74052 140.992 0.0001Error 6 601.80823 100.30C Total 7 14743.54875 Root MSE 10.01506 R-square 0.9592 Dep Mean 43.51250 Adj R-sq 0.9524C.V. 23.016511)1(222 pnRpRRjdA為校正后的決議系數(shù)為校正后的決議系數(shù). Parameter Estimates Parameter Standard T for H0:

5、Variable DF Estimate Error Parameter=0 Prob |T|INTERCEP 1 5.922366 4.74969580 1.247 0.2589 X 1 2.076803 0.17490302 11.874 0.0001Model Crossproducts XX XY YYXX INTERCEP X YINTERCEP 8 144.8 348.1X 144.8 5899.66 13109.99Y 348.1 13109.99 29890.25XX Inverse, Parameter Estimates, and SSE INTERCEP X YINTER

6、CEP 0.2249182623 -0.005520346 5.9223664747 X -0.005520346 0.0003049915 2.0768029572 Y 5.9223664747 2.0768029572 601.80822932 Dep Var Predict Std Err Lower95% Upper95%Obs Y Value Predict Predict Predict Residual 1 46.3000 35.6206 3.603 9.5773 61.6640 10.6794 2 30.7000 34.9976 3.613 8.9459 61.0493 -4.

7、2976 3 144.6 149.8 9.630 115.8 183.8 -5.2448 4 69.2000 53.0658 3.631 26.9988 79.1327 16.1342 5 16.0000 21.0830 4.013 -5.3172 47.4833 -5.0830 6 12.3000 22.5368 3.957 -3.8127 48.8863 -10.2368 7 2.7000 8.6222 4.601 -18.3464 35.5908 -5.9222 8 26.3000 22.3291 3.965 -4.0274 48.6856 3.9709 9 . 47.4584 3.55

8、6 21.4532 73.4636 . Sum of Residuals 0 Sum of Squared Residuals 601.8082 Predicted Resid SS (Press) 5610.2160OBS X Y PRESIDI 1 14.3 46.3 12.2667 2 14.0 30.7 -4.9405 3 69.3 144.6 -69.4832 4 22.7 69.2 18.5761 5 7.3 16.0 -6.0554 6 8.0 12.3 -12.1305 7 1.3 2.7 -7.5067 8 7.9 26.3 4.7089)(iyyPRESIDiii 是第個觀

9、測值的預(yù)測殘差是第個觀測值的預(yù)測殘差,而而 )(iyi是刪去第是刪去第i個觀測值后個觀測值后,根據(jù)剩下的根據(jù)剩下的n1組觀測值建立線組觀測值建立線性回歸方程并將性回歸方程并將xi代入此回歸方程所得到的第代入此回歸方程所得到的第i個觀測個觀測值的預(yù)測值值的預(yù)測值. 多元線性回歸多元線性回歸上機(jī)實驗上機(jī)實驗2. 例例1.2 P25data lreg07;input x1 x2 y ;cards;1.37 9.08 4.93 11.34 1.89 1.86 9.673.06 2.33 0.76 10.2 5.78 17.67 0.050.06 15.91 0.73 0.43 15.74 1.03 0

10、.875.41 6.25 3.86 5.4 6.3 .;symbol i=rl v=star;/*symbol 為繪圖設(shè)置語句為繪圖設(shè)置語句*/* i=rl 要求畫回歸直線要求畫回歸直線*/*v=star 要求用星號表示點(diǎn)要求用星號表示點(diǎn)*/proc gplot;plot y*x1;/*要求畫回歸直線及點(diǎn)要求畫回歸直線及點(diǎn)x1,y*/proc reg;model y=x1/xpx i;run;/*要求建立一元線性回歸方程并作檢驗要求建立一元線性回歸方程并作檢驗*/ proc gplot;plot y*x2;proc reg;model y=x2;run;proc reg; model y=x1

11、 x2/alpha=0.01 cli;run;/*要求建立二元線性回歸方程要求建立二元線性回歸方程 并作檢驗及報答與預(yù)告并作檢驗及報答與預(yù)告*/Y0123456X1024681012141618Y0123456X2012345678910 11Y=5.621170 - 0.319113*X1;F=494.064;ProbF為為0.0001;R-square=0.9880;Y=0.363778 + 0.532975*X2;F=279.602; ProbF為為0.0001;R-square=0.9790;Y=3.610506 - 0.198281*X1 + 0.206755*X2;F=392.51

12、6; ProbF為為0.0001;R-square=0.9937;Model Crossproducts XX XY YYXX INTERCEP X1 X2 YINTERCEP 8 77.87 32.29 20.12X1 77.87 1066.9317 33.7369 97.2483X2 32.29 133.7369 40.0809 .7036Y 20.12 97.2483 .7036 82.4468 XX Inverse, Parameter Estimates, and SSE INTERCEP X1 X2 YINTERCEP 22.8232 -1.3771 2.3025 3.6105X1

13、 -1.3771 0.0841 0.4 -0.1983X2 -2.3025 0.4 0.2368 0.2068Y 3.6105 -0.1983 0.2068 0.2021 Analysis of Variance Sum of MeanSource DF Squares Square F Value Prob FModel 2 31.64346 15.82173 392.516 0.0001Error 5 0.20214 0.04031C Total 7 31.84500Root MSE 0.20077 R-square 0.9937Dep Mean 2.51500 Adj R-sq 0.99

14、11C.V. 7.98289 1)1(*:222 pnRpRRqsRjdA Dep Var Predict Std Err Lower95% Upper95%Obs Y Value Predict Predict Predict Residual 1 4.9300 5.2162 0.120 4.6150 5.8174 -0.2862 2 1.8600 1.7528 0. 1.1252 2.3803 0.1072 3 2.3300 2.3258 0.122 1.7221 2.9295 0.00420 4 5.7800 5.5687 0.154 4.9188 6.2186 0.2113 5 0.0

15、600 0.1172 0.132 -0.4998 0.7343 -0.0572 6 0.4300 0.6068 0.104 0.0251 1.1884 -0.1768 7 0.8700 0.7025 0.110 0.1 1.2914 0.1675 8 3.8600 3.8300 0.092 3.2626 4.3974 0.0300 9 . 3.8423 0.090 3.2763 4.4084 . 觀測值觀測值 預(yù)測值預(yù)測值 規(guī)范誤規(guī)范誤 95%置信下限與上限置信下限與上限 殘差剩余殘差剩余例例1.4 逐漸回歸逐漸回歸data ex; input x1-x4 y ;cards;9.2 2.73

16、1.47 1.14 1.16 9.1 3.73 1.82 0.83 1.15 8.6 4.88 1.83 2.13 1.84 10.23 3.97 1.59 1.35 1.36 5.6 3.73 1.84 1.82 0.86 5.37 4.24 1.87 1.35 0.9 6.13 3.15 1.99 1.65 0.12 8.2 4.65 1.62 4.57 0.9 8.8 4.38 1.54 2.07 1.93 7.6 3.86 1.6 2.42 1.1 9.7 4.38 1.69 1.52 1.4 8.37 5.1 1.81 2.28 1.76 12.17 4.9 1.73 1.58 1.

17、64 10.27 3.73 1.61 1.2 1.47 8.9 4.47 1.88 0.8 0.92 8.23 5.28 1.7 3.07 1.5;proc reg;model y=x1-x4/selection=rsquare b;model y=x1-x4/selection=rsquare adjrsq cp AIC MSE SSE collinoint;run;proc reg;model y=x1-x4/selection=stepwise sle=0.3 sls=0.2; run; / * sls is the level spcified by user*/SLS=0.2定義剔除

18、時的概率程度為定義剔除時的概率程度為0.2，SLE=0.3定義選定義選入時的概率程度為入時的概率程度為0.3例例1.4 共線性診斷共線性診斷data ex; input x1-x4 y ; x5=int(x2+x3+x4)*90)/90;cards;9.2 2.73 1.47 1.14 1.16 9.1 3.73 1.82 0.83 1.15 8.6 4.88 1.83 2.13 1.84 10.23 3.97 1.59 1.35 1.36 5.6 3.73 1.84 1.82 0.86 5.37 4.24 1.87 1.35 0.9 6.13 3.15 1.99 1.65 0.12 8.2

19、4.65 1.62 4.57 0.9 8.8 4.38 1.54 2.07 1.93 7.6 3.86 1.6 2.42 1.1 9.7 4.38 1.69 1.52 1.4 8.37 5.1 1.81 2.28 1.76 12.17 4.9 1.73 1.58 1.64 10.27 3.73 1.61 1.2 1.47 8.9 4.47 1.88 0.8 0.92 8.23 5.28 1.7 3.07 1.5;proc reg data=ex;model y=x1-x5/vif collinoint;run;Analysis of Variance Sum of Mean Source DF

20、 Squares Square F Value Pr F Model 5 2.55497 0.51099 8.03 0.0028 Error 10 0.63672 0.06367 Corrected Total 15 3.19169 Root MSE 0.25233 R-Square 0.8005 Dependent Mean 1.25063 Adj R-Sq 0.7008 Coeff Var 20.17663Parameter Estimates Parameter Standard Variance Variable DF Estimate Error t Value Pr |t| Inf

21、lation Intercept 1 2.82510 1.33994 2.11 0.0612 0 x1 1 0.02693 0.06221 0.43 0.6743 2.85303 x2 1 -27.00023 25.70336 -1.05 0.3182 76421 x3 1 -29.73236 25.68616 -1.16 0.2740 3263.98863 x4 1 -27.81537 25.68282 -1.08 0.3042 920 x5 1 27.58457 25.69586 1.07 0.3083 308366Collinearity Diagnostics (intercept adjusted) Condition Number Eigenvalue Index 1 2.45588 1.00000 2 1.48451 1.28621 3 0.89498 1.65652 4 0.16462 3.86241 5 0.00000190 1.53374 Collinearity Diagnostics (interce