Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei

Renhao Jin; Tao Liu; Fang Yan; Jie Zhu

doi:doi:10.11648/j.ajtas.20150404.22

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Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei

Renhao Jin, Tao Liu, Fang Yan, Jie Zhu

Published in American Journal of Theoretical and Applied Statistics (Volume 4, Issue 4)

Received: 1 July 2015 Accepted: 7 July 2015 Published: 17 July 2015

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Abstract

This paper is based on the Moran's I coefficient and Geary's c coefficient, and with the support of SAS statistical analysis software, using the spatial analysis of Beijing-Tianjin-Hebei’s per capita GDP and Geographical coordinates together. The research results show that the Moran's I coefficient is 0.098, Geary's c coefficient is 0.868, which is showing that there is a positive correlation between Beijing-Tianjin- Hebei region’s city economy. But the degree of correlation is low, which is showing that Beijing-Tianj-Hebei collaborative development is still in the initial stage, and regional economic integration has not fully realized.

Published in	American Journal of Theoretical and Applied Statistics (Volume 4, Issue 4)
DOI	10.11648/j.ajtas.20150404.22
Page(s)	312-316
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2015. Published by Science Publishing Group

Keywords

Regional Economic Integration, Collaborative Development, Spatial Analysis

References

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[3]	Cressie, N., & Hawkins, D.M. (1980). Robust estimation of variogram: I. Mathematical Geology 12: 115–125.
[4]	Diggle, P.J., & Ribeiro, P.J. (2007). Model-based geostatistics, New York: Springer.
[5]	Glatzer, E., & Müller, W.G. (2004). Residuals diagnostics for variogram fitting. Computers and Geosciences 30 : 859-866.
[6]	Getis, A. and Ord, J. K. (1992). The analysis of spatial association by use of distance statistics. Geographical Analysis 24, 189--206.
[7]	Griffith, D. (1987). Spatial Autocorrelation: A Primer. Washington, DC: Association of American Geographers Resource Publication.
[8]	Griffith, D. (1992). What is spatial autocorrelation? Reflections on the past 25 years of spatial statistics. l’Espace Ge´ographique 21, 265--280.
[9]	Griffith, D. (1996). Spatial autocorrelation and eigenfunctions of the geographic weights matrix accompanying geo-referenced data. The Canadian Geographer 40, 351--367.
[10]	Mardia, K. and Marshall, R. (1984). Maximum likelihood estimation of models for residual covariance in spatial regression. Biometrika 71, 135--146.
[11]	Richardson, S. and He´ mon, D. (1981). On the variance of the sample correlation between two independent lattice processes. Journal of Applied Probability 18, 943--948.
[12]	Tiefelsdorf, M. and Boots, B. (1995). The exact distribution of Moran’s I. Environment and Planning A 27, 985--999.

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APA Style

Renhao Jin, Tao Liu, Fang Yan, Jie Zhu. (2015). Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei. American Journal of Theoretical and Applied Statistics, 4(4), 312-316. https://doi.org/10.11648/j.ajtas.20150404.22

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ACS Style

Renhao Jin; Tao Liu; Fang Yan; Jie Zhu. Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei. Am. J. Theor. Appl. Stat. 2015, 4(4), 312-316. doi: 10.11648/j.ajtas.20150404.22

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AMA Style

Renhao Jin, Tao Liu, Fang Yan, Jie Zhu. Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei. Am J Theor Appl Stat. 2015;4(4):312-316. doi: 10.11648/j.ajtas.20150404.22

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@article{10.11648/j.ajtas.20150404.22,
  author = {Renhao Jin and Tao Liu and Fang Yan and Jie Zhu},
  title = {Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {4},
  number = {4},
  pages = {312-316},
  doi = {10.11648/j.ajtas.20150404.22},
  url = {https://doi.org/10.11648/j.ajtas.20150404.22},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150404.22},
  abstract = {This paper is based on the Moran's I coefficient and Geary's c coefficient, and with the support of SAS statistical analysis software, using the spatial analysis of Beijing-Tianjin-Hebei’s per capita GDP and Geographical coordinates together. The research results show that the Moran's I coefficient is 0.098, Geary's c coefficient is 0.868, which is showing that there is a positive correlation between Beijing-Tianjin- Hebei region’s city economy. But the degree of correlation is low, which is showing that Beijing-Tianj-Hebei collaborative development is still in the initial stage, and regional economic integration has not fully realized.},
 year = {2015}
}

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TY  - JOUR
T1  - Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei
AU  - Renhao Jin
AU  - Tao Liu
AU  - Fang Yan
AU  - Jie Zhu
Y1  - 2015/07/17
PY  - 2015
N1  - https://doi.org/10.11648/j.ajtas.20150404.22
DO  - 10.11648/j.ajtas.20150404.22
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 312
EP  - 316
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20150404.22
AB  - This paper is based on the Moran's I coefficient and Geary's c coefficient, and with the support of SAS statistical analysis software, using the spatial analysis of Beijing-Tianjin-Hebei’s per capita GDP and Geographical coordinates together. The research results show that the Moran's I coefficient is 0.098, Geary's c coefficient is 0.868, which is showing that there is a positive correlation between Beijing-Tianjin- Hebei region’s city economy. But the degree of correlation is low, which is showing that Beijing-Tianj-Hebei collaborative development is still in the initial stage, and regional economic integration has not fully realized.
VL  - 4
IS  - 4
ER  -

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Author Information

Renhao Jin

School of Information, Beijing Wuzi University, Beijing, China
Tao Liu

School of Information, Beijing Wuzi University, Beijing, China
Fang Yan

School of Information, Beijing Wuzi University, Beijing, China
Jie Zhu

School of Information, Beijing Wuzi University, Beijing, China

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APA Style

Renhao Jin, Tao Liu, Fang Yan, Jie Zhu. (2015). Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei. American Journal of Theoretical and Applied Statistics, 4(4), 312-316. https://doi.org/10.11648/j.ajtas.20150404.22

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ACS Style

Renhao Jin; Tao Liu; Fang Yan; Jie Zhu. Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei. Am. J. Theor. Appl. Stat. 2015, 4(4), 312-316. doi: 10.11648/j.ajtas.20150404.22

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AMA Style

Renhao Jin, Tao Liu, Fang Yan, Jie Zhu. Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei. Am J Theor Appl Stat. 2015;4(4):312-316. doi: 10.11648/j.ajtas.20150404.22

Copy | Download

@article{10.11648/j.ajtas.20150404.22,
  author = {Renhao Jin and Tao Liu and Fang Yan and Jie Zhu},
  title = {Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei},
  journal = {American Journal of Theoretical and Applied Statistics},
  volume = {4},
  number = {4},
  pages = {312-316},
  doi = {10.11648/j.ajtas.20150404.22},
  url = {https://doi.org/10.11648/j.ajtas.20150404.22},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20150404.22},
  abstract = {This paper is based on the Moran's I coefficient and Geary's c coefficient, and with the support of SAS statistical analysis software, using the spatial analysis of Beijing-Tianjin-Hebei’s per capita GDP and Geographical coordinates together. The research results show that the Moran's I coefficient is 0.098, Geary's c coefficient is 0.868, which is showing that there is a positive correlation between Beijing-Tianjin- Hebei region’s city economy. But the degree of correlation is low, which is showing that Beijing-Tianj-Hebei collaborative development is still in the initial stage, and regional economic integration has not fully realized.},
 year = {2015}
}

Copy | Download

TY  - JOUR
T1  - Spatial Correlation Analysis of 2013 Per capita GDP in the Area of Beijing, Tianjin and Hebei
AU  - Renhao Jin
AU  - Tao Liu
AU  - Fang Yan
AU  - Jie Zhu
Y1  - 2015/07/17
PY  - 2015
N1  - https://doi.org/10.11648/j.ajtas.20150404.22
DO  - 10.11648/j.ajtas.20150404.22
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 312
EP  - 316
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20150404.22
AB  - This paper is based on the Moran's I coefficient and Geary's c coefficient, and with the support of SAS statistical analysis software, using the spatial analysis of Beijing-Tianjin-Hebei’s per capita GDP and Geographical coordinates together. The research results show that the Moran's I coefficient is 0.098, Geary's c coefficient is 0.868, which is showing that there is a positive correlation between Beijing-Tianjin- Hebei region’s city economy. But the degree of correlation is low, which is showing that Beijing-Tianj-Hebei collaborative development is still in the initial stage, and regional economic integration has not fully realized.
VL  - 4
IS  - 4
ER  -

Copy | Download