Table 2 comparison of classical regression and GWR results
CHD | Classical regression | GWR | ||
|---|---|---|---|---|
| Â | O against E | O = E+GP | O against E | O = E+GP |
Residual sum of squares | 0.032 | 0.026 | 0.026 | 0.017 |
Standard deviation | 0.010 | 0.009 | 0.009 | 0.007 |
Akaike Information Criterion | -2260.43 | -2336.25 | -2285.75 | -2393.81 |
Correlation coefficient | 0.299 | 0.439 | 0.427 | 0.637 |
Adjusted correlation coefficient | 0.295 | 0.434 | 0.387 | 0.585 |
Sum of squares | 0.0 | 0.0 | 0.0 | 0.0 |
Degrees of freedom | 2.00 | 3.00 | 328.09 | 306.86 |
Hypertension | Classical regression | GWR | ||
| Â | O against E | O = E+GP | O against E | O = E+GP |
Residual sum of squares | 0.374 | 0.250 | 0.362 | 0.241 |
Standard deviation | 0.033 | 0.027 | 0.032 | 0.026 |
Akaike Information Criterion | -1400.41 | -1539.57 | -1403.50 | -1543.67 |
Correlation coefficient | 0.121 | 0.412 | 0.150 | 0.432 |
Adjusted correlation coefficient | 0.116 | 0.407 | 0.134 | 0.421 |
Sum of squares | 0.4 | 0.2 | 0.4 | 0.2 |
Degrees of freedom | 2.00 | 3.00 | 344.87 | 344.04 |
Stroke | Classical regression | GWR | ||
| Â | O against E | O = E+GP | O against E | O = E+GP |
Residual sum of squares | 0.007 | 0.006 | 0.005 | 0.003 |
Standard deviation | 0.004 | 0.004 | 0.004 | 0.003 |
Akaike Information Criterion | -2807.25 | -2873.16 | -2838.92 | -2932.93 |
Correlation coefficient | 0.262 | 0.392 | 0.422 | 0.621 |
Adjusted correlation coefficient | 0.258 | 0.387 | 0.374 | 0.561 |
| Â | Classical regression | GWR | ||
| Â | O against E | O = E+GP | O against E | O = E+GP |
Sum of squares | 0.0 | 0.0 | 0.0 | 0.0 |
Degrees of freedom | 2.00 | 3.00 | 324.37 | 302.87 |