用eviews进行拉姆齐检验的结果如下:
Ramsey RESET Test
Equation: UNTITLED
Specification: LNVSH C LNVSH(-1) LNVSH(-2) LNVSH(-3) LNVSH(-4)
LNVSH(-5) RSH RSH(-1) T
Omitted Variables: Squares of fitted values
Value df Probability
QLR L-statistic 6.307887 1 0.0120
QLR Lambda-statistic 6.304282 1 0.0120
L-test summary:
Value df
Restricted Objective 318.0451 3890
Unrestricted Objective 317.6818 3889
Scale 0.115209
Lambda-test summary:
Value df
Restricted Log Obj. 5.762193 3890
Unrestricted Log Obj. 5.761050 3889
Scale 0.000363
Unrestricted Test Equation:
Dependent Variable: LNVSH
Method: Quantile Regression (Median)
Date: 02/23/13 Time: 19:42
Sample: 6 3904
Included observations: 3899
Bootstrap Standard Errors & Covariance
Bootstrap method: XY-pair, reps=100, rng=kn, seed=1086359667
Sparsity method: Kernel (Epanechnikov) using residuals
Bandwidth method: Hall-Sheather, bw=0.061728
Estimation successfully identifies unique optimal solution
Variable Coefficient Std. Error t-Statistic Prob.
C 2.300708 0.759356 3.029815 0.0025
LNVSH(-1) 0.507095 0.068143 7.441603 0.0000
LNVSH(-2) 0.087587 0.021357 4.101151 0.0000
LNVSH(-3) 0.076503 0.023114 3.309759 0.0009
LNVSH(-4) 0.039050 0.023229 1.681057 0.0928
LNVSH(-5) 0.045775 0.019255 2.377258 0.0175
RSH 2.665327 0.500658 5.323650 0.0000
RSH(-1) 3.164771 0.477422 6.628870 0.0000
T 3.94E-05 7.87E-06 5.011993 0.0000
FITTED^2 0.006048 0.002792 2.166389 0.0303
Pseudo R-squared 0.852057 Mean dependent var 17.04146
Adjusted R-squared 0.851715 S.D. dependent var 1.240486
S.E. of regression 0.220354 Objective 317.6818
Quantile dependent var 16.88666 Restr. objective 2147.326
Sparsity 0.460838 Quasi-LR statistic 31762.06
Prob(Quasi-LR stat) 0.000000
不知道该怎么解释T.T原假设是什么?怎么看是否通过呀?求教!谢谢了!