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第二章. 多元线性回归. §2.1 多元线性回归模型. §2.2 参数的最小二乘估计. 参数估计的性质. §2.3 回归方程的显著性检验. §2.4 回归系数的显著性检验. §2.5 回归系数的置信区间. §2.6 预测. 加权最小二乘法. 例 2.3 的 SAS 实现. data example2; input x1 x2 y; cards; ….. ; run ; proc reg ; model y=x1 x2/p r clm cli; run ;. 方差分析. The REG Procedure

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第二章

多元线性回归


§2.1多元线性回归模型


§2.2 参数的最小二乘估计



§2.3 回归方程的显著性检验


§2.4 回归系数的显著性检验


§2.5 回归系数的置信区间


§2.6 预测



2 3 sas
2.3的SAS实现

data example2;

input x1 x2 y;

cards;

…..

;

run;

procreg;

model y=x1 x2/p r clm cli;

run;


方差分析

  • The REG Procedure

  • Model: MODEL1

  • Dependent Variable: y

  • Analysis of Variance

  • Sum of Mean

  • Source DF Squares Square F Value Pr > F

  • Model 2 2.33292 1.16646 127.71 <.0001

  • Error 25 0.22834 0.00913

  • Corrected Total 27 2.56127

  • Root MSE 0.09557 R-Square 0.9108

  • Dependent Mean 3.78893 Adj R-Sq 0.9037

  • Coeff Var 2.52237



去掉x2

data example2;

input x1 x2 y;

cards;

…..

;

run;

procreg;

model y=x1 /p r clm cli;

run;




上机作业

  • Page 68-69: 2.8;2.9.


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