LM检验
模型1:
Diagnostics
------------------------------------------------------------
Test | Statistic df p-value
-------------------------------+----------------------------
Spatial error: |
Moran's I | 3.828 1 0.000
Lagrange multiplier | 8.134 1 0.004
Robust Lagrange multiplier | 16.569 1 0.000
|
Spatial lag: |
Lagrange multiplier | 0.612 1 0.434
Robust Lagrange multiplier | 9.046 1 0.003
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模型2:
Diagnostics
------------------------------------------------------------
Test | Statistic df p-value
-------------------------------+----------------------------
Spatial error: |
Moran's I | 1.440 1 0.150
Lagrange multiplier | 0.495 1 0.482
Robust Lagrange multiplier | 4.966 1 0.026
|
Spatial lag: |
Lagrange multiplier | 0.287 1 0.592
Robust Lagrange multiplier | 4.758 1 0.029
------------------------------------------------------------
模型3:
Diagnostics
------------------------------------------------------------
Test | Statistic df p-value
-------------------------------+----------------------------
Spatial error: |
Moran's I | 2.034 1 0.042
Lagrange multiplier | 1.532 1 0.216
Robust Lagrange multiplier | 0.010 1 0.920
|
Spatial lag: |
Lagrange multiplier | 1.953 1 0.162
Robust Lagrange multiplier | 0.432 1 0.511
------------------------------------------------------------
模型4:
Diagnostics
------------------------------------------------------------
Test | Statistic df p-value
-------------------------------+----------------------------
Spatial error: |
Moran's I | 3.075 1 0.002
Lagrange multiplier | 4.728 1 0.030
Robust Lagrange multiplier | 4.218 1 0.040
|
Spatial lag: |
Lagrange multiplier | 1.654 1 0.198
Robust Lagrange multiplier | 1.144 1 0.285
------------------------------------------------------------
模型5:
Diagnostics
------------------------------------------------------------
Test | Statistic df p-value
-------------------------------+----------------------------
Spatial error: |
Moran's I | 0.618 1 0.537
Lagrange multiplier | 0.001 1 0.971
Robust Lagrange multiplier | 3.806 1 0.051
|
Spatial lag: |
Lagrange multiplier | 0.721 1 0.396
Robust Lagrange multiplier | 4.526 1 0.033
------------------------------------------------------------
wald检验:
模型1:
1.整体拟合
chi2( 15) =12636.11
2.wald检验值
chi2(15) = 26313.20
Prob > chi2 = 0.0000
模型2:
1.整体拟合
chi2( 14) = 6.4e+09
2.wald检验值
chi2(15) = 188217.04
Prob > chi2 = 0.0000
模型3:
1.整体拟合
chi2( 14) = 1.4e+07
2.wald检验值
chi2(15) = 4514.57
Prob > chi2 = 0.0000
模型4:
1.整体拟合
chi2( 13) = 3.4e+08
2.wald检验值
chi2(15) = 17563.48
Prob > chi2 = 0.0000
模型5:
1.整体拟合
chi2( 14) = 3.4e+08
2.wald检验值
chi2(15) = 17679.42
Prob > chi2 = 0.0000