Table 10 Results of the bayesian discriminant analysis.
Cities | \(\:{{Y}}_{1}\)​ | \(\:{{Y}}_{2}\) | \(\:{{Y}}_{3}\)​ | Max value | Cluster assignment |
|---|---|---|---|---|---|
Nanjing City | 784.97 | 744.99 | 746.05 | \(\:{Y}_{1}\)=784.97 | 1 |
Wuxi City | 768.97 | 733.09 | 731.59 | \(\:{Y}_{1}\)=768.97 | 1 |
Suzhou City | 776.33 | 737.82 | 727.21 | \(\:{Y}_{1}\)=776.33 | 1 |
Xuzhou City | 688.76 | 723.41 | 678.43 | \(\:{Y}_{2}\)=723.41 | 2 |
Nantong City | 634.44 | 663.75 | 635.91 | \(\:{Y}_{2}\)=663.75 | 2 |
Yancheng City | 692.68 | 743.09 | 685.96 | \(\:{Y}_{2}\)=743.09 | 2 |
Changzhou City | 594.01 | 583.99 | 619.47 | \(\:{Y}_{3}\)=619.47 | 3 |
Lianyungang City | 457.78 | 473.44 | 513.54 | \(\:{Y}_{3}\)=513.54 | 3 |
Huaian City | 576.42 | 575.97 | 617.29 | \(\:{Y}_{3}\)=617.29 | 3 |
Yangzhou City | 501.21 | 497.80 | 536.66 | \(\:{Y}_{3}\)=536.66 | 3 |
Zhenjiang City | 496.88 | 494.27 | 546.13 | \(\:{Y}_{3}\)=546.13 | 3 |
Taizhou City | 527.85 | 530.63 | 582.19 | \(\:{Y}_{3}\)=582.19 | 3 |
Suqian City | 519.79 | 507.28 | 563.18 | \(\:{Y}_{3}\)=563.18 | 3 |
