Dependent Variable: Y
Method: Least Squares
Date: 05/31/13 Time: 21:41
Sample: 1 447
Included observations: 447
Weighting series: W
White Heteroskedasticity-Consistent Standard Errors & Covariance
Variable Coefficient Std. Error t-Statistic Prob.
X1 -0.005624 0.000314 -17.92112 0.0000
X2 0.002468 0.000564 4.377477 0.0000
X3 0.052839 0.001201 44.00255 0.0000
X4 -0.006844 0.000538 -12.71158 0.0000
X5 0.002209 0.000117 18.92643 0.0000
X6 -0.004717 0.000155 -30.40011 0.0000
X7 0.539690 0.001109 486.8223 0.0000
X8 0.076661 0.004117 18.62282 0.0000
D1 0.003758 0.000681 5.518461 0.0000
D2 0.005701 0.000323 17.67119 0.0000
D3 0.013808 0.000676 20.41796 0.0000
D4 0.044849 0.000719 62.36516 0.0000
C 0.002451 0.000760 3.226999 0.0013
Weighted Statistics
R-squared 1.000000 Mean dependent var 0.046893
Adjusted R-squared 1.000000 S.D. dependent var 0.962515
S.E. of regression 8.92E-06 Akaike info criterion -20.38804
Sum squared resid 3.45E-08 Schwarz criterion -20.26873
Log likelihood 4569.727 Hannan-Quinn criter. -20.34100
F-statistic 2.99E+08 Durbin-Watson stat 1.909347
Prob(F-statistic) 0.000000
Unweighted Statistics
R-squared 0.478334 Mean dependent var 0.047795
Adjusted R-squared 0.463911 S.D. dependent var 0.076505
S.E. of regression 0.056016 Sum squared resid 1.361786
Durbin-Watson stat 2.252200
用最加权最小二乘法估计,得到的R为1,麻烦帮忙看看是不是有什么问题,谢谢啦