Table 6 The optional regression models of ANLI and ACRHP after eliminating the abnormal errors.

From: Study on Average Housing Prices in the Inland Capital Cities of China by Night-time Light Remote Sensing and Official Statistics Data

City

Optional Regression Model

R2

Changchun

ACRHP = 43.53ANLI2 − 384.7ANLI + 2942

0.8316

Changsha

ACRHP = −9.176ANLI2 + 686ANLI − 1329

0.9113

Chengdu

ACRHP = −22.84ANLI2 + 1076ANLI − 4904

0.8906

Chongqing

ACRHP = −66.95ANLI2 + 2379ANLI − 1152

0.9512

Guiyang

ACRHP = −38.14ANLI2 + 1173ANLI − 2865

0.8710

Harbin

ACRHP = 31.16ANLI2 + 380.2ANLI + 422.1

0.8312

Hefei

ACRHP = −10.36ANLI2 + 623.2ANLI − 2009

0.8831

Hohhot

ACRHP = 48.33ANLI2 + 26.62ANLI + 868.4

0.9446

Kunming

ACRHP = −0.8514ANLI2 + 601.9ANLI + 142.8

0.9640

Lanzhou

ACRHP = 2.221ANLI2 + 728.4ANLI − 956.9

0.8097

Nanchang

ACRHP = 643.5e0.1961 ANLI

0.9047

Taiyuan

ACRHP=5.554ANLI2 + 501.6ANLI − 3219

0.8816

Urumqi

ACRHP = 61.19ANLI2-483ANLI + 3035

0.9151

Wuhan

ACRHP = −12.92ANLI2 + 852.6ANLI − 6196

0.9327

Xi’an

ACRHP = 5.921ANLI2 + 298ANLI − 872.7

0.9610

Xining

ACRHP = 711.6e0.2474ANLI

0.9317

Yinchuan

ACRHP = 25.34ANLI2−183.8ANLI + 2481

0.8724

Zhengzhou

ACRHP = 3.981ANLI2 + 49.85 ANLI + 250.7

0.8899

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