Null Hypothesis: Obs F-Statistic Prob.
LNX1 does not Granger Cause LNY 20 4.96260 0.0222
LNY does not Granger Cause LNX1 5.25772 0.0186
LNX2 does not Granger Cause LNY 20 0.15327 0.8592
LNY does not Granger Cause LNX2 1.95299 0.1763
LNX3 does not Granger Cause LNY 20 1.78816 0.2011
LNY does not Granger Cause LNX3 2.74520 0.0964
LNX4 does not Granger Cause LNY 20 2.01400 0.1680
LNY does not Granger Cause LNX4 1.58964 0.2365
请问可以不就行格兰杰检验之间进行多元线性回归吗,回归结果拟合程度很好
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Variable | Coefficient | Std. Error | t-Statistic | Prob. |
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C | 4.404859 | 0.342659 | 12.85492 | 0.0000 |
LNX1 | 0.134631 | 0.022454 | 5.995835 | 0.0000 |
LNX2 | 0.248042 | 0.070127 | 3.537043 | 0.0025 |
LNX3 | 0.121540 | 0.054494 | 2.230359 | 0.0395 |
LNX4 | 0.286037 | 0.084447 | 3.387159 | 0.0035 |
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R-squared | 0.998791 | Mean dependent var | 8.579456 | |
Adjusted R-squared | 0.998507 | S.D. dependent var | 0.904957 | |
S.E. of regression | 0.034973 | Akaike info criterion | -3.671789 | |
Sum squared resid | 0.020792 | Schwarz criterion | -3.423825 | |
Log likelihood | 45.38968 | Hannan-Quinn criter. | -3.613377 | |
F-statistic | 3511.037 | Durbin-Watson stat | 2.235719 | |
Prob(F-statistic) | 0.000000 |
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