Test Equation:
Dependent Variable: RESID^2
Method: Least Squares
Date: 06/01/04 Time: 13:23
Sample(adjusted): 2 18
Included observations: 17 after adjusting endpoints
Variable Coefficient Std. Error t-Statistic Prob.
C 2.78E+15 1.15E+15 2.404733 0.0296
RESID^2(-1) -0.079423 0.256625 -0.309492 0.7612
R-squared 0.006345 Mean dependent var 2.59E+15
Adjusted R-squared -0.059898 S.D. dependent var 3.96E+15
S.E. of regression 4.07E+15 Akaike info criterion 74.83501
Sum squared resid 2.49E+32 Schwarz criterion 74.93303
Log likelihood -634.0975 F-statistic 0.095785
Durbin-Watson stat 1.955451 Prob(F-statistic) 0.761205
由于Obs*R-squared=0.107868,表明模型随机误差项不存在异方差。四、自相关检验
由上表得DW=1.955451,而在n=18, k=2,时,du=1.535,DW>du,故模型不存在一阶自相关。五、滞后性分析x1滞后一阶回归结果
Dependent Variable: Y
Method: Least Squares
Date: 08/28/04 Time: 13:07
Sample(adjusted): 1900:2 1904:1
Included observations: 16 after adjusting endpoints
R-squared 0.680134 Mean dependent var 42437533
Adjusted R-squared 0.630924 S.D. dependent var 27872456
S.E. of regression 16932976 Akaike info criterion 36.29478
Sum squared resid 3.73E+15 Schwarz criterion 36.43965
Log likelihood -287.3583 F-statistic 13.82100
Durbin-Watson stat 1.373841 Prob(F-statistic) 0.000606
X2滞后一阶回归结果
Dependent Variable: Y
Method: Least Squares
Date: 08/28/04 Time: 13:08
Sample(adjusted): 1900:2 1904:1
Included observations: 16 after adjusting endpoints
R-squared 0.556395 Mean dependent var 42437533
Adjusted R-squared 0.488148 S.D. dependent var 27872456
S.E. of regression 19941026 Akaike info criterion 36.62182
Sum squared resid 5.17E+15 Schwarz criterion 36.76668
Log likelihood -289.9745 F-statistic 8.152669
Durbin-Watson stat 2.145500 Prob(F-statistic) 0.005075
X1 X2 同滞后一阶回归结果
Dependent Variable: Y
Method: Least Squares
Date: 08/28/04 Time: 13:08
Sample(adjusted): 1900:2 1904:1
Included observations: 16 after adjusting endpoints