Research Article
Choosing the Right Spatial Weighting Matrix in a Quantile Regression Model
Table 8
Estimation results at the 0.5th quantile.
| | LSA | Full path | SCAD | | Coefficient | P value | Coefficient | P value | Coefficient | P value |
| Intercept |
1.991
|
0.000
|
1.948
|
0.000
|
1.799
|
0.000
| CRIM | −0.007 |
0.000
| −0.007 |
0.000
| −0.007 |
0.000
| ZN | | |
0.000
|
0.290
|
0.000
|
0.518
| INDUS | | |
0.002
|
0.216
|
0.003
|
0.178
| CHAS | | | | |
0.012
|
0.712
| NOX2 | | | | | | | RM2 |
0.013
|
0.000
|
0.013
|
0.000
|
0.014
|
0.000
| AGE | −0.001 |
0.102
| −0.001 |
0.206
| −0.001 |
0.096
| log (DIS) | −0.111 |
0.000
| −0.102 |
0.001
| −0.082 |
0.013
| log (RAD) |
0.054
|
0.002
|
0.057
|
0.001
|
0.050
|
0.007
| TAX |
0.000
|
0.001
|
0.000
|
0.000
|
0.000
|
0.002
| PTRATIO | −0.009 |
0.021
| −0.009 |
0.027
| −0.010 |
0.020
| B |
0.000
|
0.000
|
0.000
|
0.000
|
0.000
|
0.000
| log (LSTAT) | −0.189 |
0.000
| −0.187 |
0.000
| −0.164 |
0.000
| n5w0.4 | | |
0.256
|
0.296
| | | n6w0.4 |
0.406
|
0.000
|
0.146
|
0.547
|
0.416
|
0.000
|
|
|