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> sheng<-readOGR(".","shengditu")

OGR data source with driver: ESRI Shapefile

Source: ".", layer: "shengditu"

with 30 features and 7 fields

Feature type: wkbPolygon with 2 dimensions

> sheng_nb<-poly2nb(sheng)

> sheng_nblist<-nb2listw(sheng_nb)

> Y<-log(sheng$INCOME)

> X1<-log(sheng$CAIZHENG)

> X2<-log(sheng$YONGDIAN)

> M0=lm(sheng$INCOME~sheng$CAIZHENG+sheng$YONGDIAN)

> M0

Call:

lm(formula = sheng$INCOME ~ sheng$CAIZHENG + sheng$YONGDIAN)

Coefficients:

   (Intercept)  sheng$CAIZHENG  sheng$YONGDIAN  

     2242.7762          1.9409          0.8433  

> bptest(M0)

        studentized Breusch-Pagan test

data:  M0

BP = 13.3794, df = 2, p-value = 0.001244

> M1=lm(Y~X1+X2)

> M1

Call:

lm(formula = Y ~ X1 + X2)

Coefficients:

(Intercept)           X1           X2  

     5.9063       0.1410       0.2403  

> bptest(M1)

        studentized Breusch-Pagan test

data:  M1

BP = 1.0727, df = 2, p-value = 0.5849

空间同步自回归误差模型

M5SEAR<-errorsarlm(form=Y~X1+X2,listw=sheng_nblist,etype="error")

> M5SEAR

Call:

errorsarlm(formula = Y ~ X1 + X2, listw = sheng_nblist, etype = "error")

Type: error

Coefficients:

     lambda (Intercept)          X1          X2

  0.6803705   6.2439714   0.1698298   0.1567685

Log likelihood: 16.28129

空间杜宾误差模型

M6SDEM<-errorsarlm(formula=Y~X1+X2,listw=sheng_nblist,etype="emixed")

> M6SDEM

Call:

errorsarlm(formula = Y ~ X1 + X2, listw = sheng_nblist, etype = "emixed")

Type: error

Coefficients:

     lambda (Intercept)          X1          X2      lag.X1      lag.X2

0.383941329 5.606443895 0.174980753 0.125294150 0.127128572 0.005312641

Log likelihood: 18.43699

空间自回归滞后模型

> M7SAR<-lagsarlm(Y~X1+X2,listw=sheng_nblist,type="lag")

> M7SAR

Call:

lagsarlm(formula = Y ~ X1 + X2, listw = sheng_nblist, type = "lag")

Type: lag

Coefficients:

        rho (Intercept)          X1          X2

  0.4977138   2.5142894   0.1598273   0.1208989

Log likelihood: 19.10202

空间杜宾模型

> M8SDM<-lagsarlm(Y~X1+X2,list=sheng_nblist,type="mixed")

> M8SDM

Call:

lagsarlm(formula = Y ~ X1 + X2, listw = sheng_nblist, type = "mixed")

Type: mixed

Coefficients:

        rho (Intercept)          X1          X2      lag.X1

0.44734778  2.94168844  0.15733944  0.12553596  0.03462418

     lag.X2

-0.05020476

Log likelihood: 19.35204

一般空间模型SAC

SARAR

M9SAC<-sacsarlm(Y~X1+X2,listw=sheng_nblist,type="sac")

> M9SAC

Call:

sacsarlm(formula = Y ~ X1 + X2, listw = sheng_nblist, type = "sac")

Type: sac

Coefficients:

        rho      lambda (Intercept)          X1          X2

  0.6237129  -0.3867786   1.6820435   0.1402677   0.1090523

Log likelihood: 19.50472

M9SARMA<-sacsarlm(Y~X1+X2,listw=sheng_nblist,type="sacmixed")

> M9SARMA

Call:

sacsarlm(formula = Y ~ X1 + X2, listw = sheng_nblist, type = "sacmixed")

Type: sacmixed

Coefficients:

        rho      lambda (Intercept)

0.72462052 -0.52029281  1.26735141

         X1          X2      lag.X1

0.13794167  0.13100192 -0.02403913

     lag.X2

-0.07284195

Log likelihood: 19.859

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