a=lagsarlm(y$V3~y$V1+y$V3,data=y,w7,type="lag",quiet=F)
Spatial lag model
Jacobian calculated using neighbourhood matrix eigenvalues
Computing eigenvalues ...
rho: -0.6064125 function value: -64.62934
rho: 0.007182481 function value: -56.62672
rho: 0.386405 function value: -53.7844
rho: 0.8675345 function value: -55.51743
rho: 0.4873392 function value: -53.49033
rho: 0.5218755 function value: -53.449
rho: 0.5518338 function value: -53.44028
rho: 0.5472179 function value: -53.43991
rho: 0.5468185 function value: -53.43991
rho: 0.5468636 function value: -53.43991
rho: 0.546863 function value: -53.43991
rho: 0.5468631 function value: -53.43991
rho: 0.5468631 function value: -53.43991
rho: 0.5468631 function value: -53.43991
Hessian: rho: 0.5468631 function value: -53.43991
Hessian: rho: 0.5468664 function value: -53.43991
Hessian: rho: 0.5468631 function value: -53.43991
Hessian: rho: 0.5468631 function value: -53.43991
Hessian: rho: 0.5468598 function value: -53.43991
Hessian: rho: 0.5468631 function value: -53.43991
Hessian: rho: 0.5468631 function value: -53.43991
Hessian: rho: 0.5468664 function value: -53.43991
Hessian: rho: 0.5468664 function value: -53.43991
Hessian: rho: 0.5468631 function value: -53.43991
Warning messages:
1: In model.matrix.default(mt, mf) : 在公式右手的反应略过不用
2: In model.matrix.default(mt, mf) : 模型矩阵的2项有问题: 没有指定的列
3: In lagsarlm(y$V3 ~ y$V1 + y$V3, data = y, w7, type = "lag", quiet = F) :
inversion of asymptotic covariance matrix failed for tol.solve = 1e-10
倒条件数=2.05938e-13 - using numerical Hessian.
|