질의응답

참고문헌 (32)

1. Anselin, L. (1995), Local indicators of spatial association-LISA, Geographical Analysis, 27(2), 93-115. 

   상세보기

2. Anselin, L. (1988), Spatial econometrics : Methods and models, Kluwer Academic, Dordrecht, Netherland. 

3. Brunsdon, C., Fotheringham, A. S., and Charlton, M. E. (1996), Geographically weighted regression : A method for exploring spatial nonstationarity, Geographical Analysis, 28(4), 281-298. 

   상세보기

4. Burnett, J. W., Bergstrom, J. C., and Dorfman, J. H. (2013), A spatial panel data approach to estimating US state-level energy emissions, Energy Economics, 40, 396-404. 

   상세보기

5. Cheng, Y., Wang, Z., Ye, X., and Wei, Y. D. (2014), Spatiotemporal dynamics of carbon intensity from energy consumption in China, Journal of Geographical Sciences, 24(4), 631-650. 

   상세보기

6. Choi, H. S. and Sohn, S. Y. (2015), Influence of interests in geographical indication on the prediction of price change of agricultural product : case of apples, Journal of Korean Institute of Industrial Engineers, 41(4), 359-367. 

   원문보기 상세보기

7. De Smith, M. J., Goodchild, M. F., and Longley, P. (2007), Geospatial analysis : a comprehensive guide to principles, techniques and software tools, Troubador Publishing, Leicester, UK. 

8. Desipri, K., Legaki, N. Z., and Assimakopoulos, V. (2014), Determinants of domestic electricity consumption and energy behavior : A Greek case study, The 5th International Conference on IEEE in Information, Intelligence, Systems and Applications, IEEE, 144-149. 

9. Glasure, Y. U. and Lee, A. R. (1998), Cointegration, error-correction, and the relationship between GDP and energy : The case of South Korea and Singapore, Resource and Energy Economics, 20(1), 17-25. 

   상세보기

10. Griffin, A. (2014), Domestic energy consumption and social living standards : A GIS analysis within the Greater London authority area, LUMAGIS Thesis, Lund University, Lund, Sweden. 

11. Hurvich, C. M., Simonoff, J. S., and Tsai, C. L. (1998), Smoothing parameter selection in nonparametric regression using an improved Akaike information criterion, Journal of the Royal Statistical Society : Series B (Statistical Methodology), 60(2), 271-293. 

    상세보기

12. IPCC (2007), Climate change 2007 : The physical science basis, Cambridge University Press, 141. 

13. Jiang, L., Ji, M., and Bai, L. (2015), Characterizing China's energy consumption with selective economic factors and energy-resource endowment : A spatial econometric approach, Frontiers of Earth Science, 9(2), 355-368. 

    상세보기

14. Kang, C. D. (2011), Analysis on energy consumption and its policy implication in Seoul with spatial econometrics : focusing on electricity and gas consumption, Seoul Studies, 12(4), 1-22. 

15. Kiehl, J. T. and Trenberth, K. E. (1997), Earth's annual global mean energy budget, Bulletin of the American Meteorological Society, 78(2), 197-208. 

    상세보기

16. Kim, I. H., Oh, K. S., and Jeong, S. H. (2011), Carbon emission model development using urban planning criteria : focusing on the case of Seoul, Journal of Korea Spatial Information Society, 19(6), 12. 

17. Kim, Y. G., An, Q., and Kim, S. W. (2015), The research of difference between public and private section : sort by region in China, Journal of the Korean Operations Research and Management Science Society, 40(1), 139-154. 

    원문보기 상세보기

18. Lee, W. S. and Sohn, S. Y. (2015), Topic model analysis of research trend on spatial big data, Journal of Korean Institute of Industrial Engineers, 41(1), 64-73. 

    원문보기 상세보기

19. Li, Q. and Racine, J. (2004), Cross-validated local linear nonparametric regression, Statistica Sinica, 14(2), 485-512. 

    상세보기

20. Nam, K. C., Lim, U., Kim, H. S., and Lee, J. S. (2010), Building carbon emission model for the change of urban spatial structure and growth management using system dynamics approach, Journal of Korea Regional Science Association, 26(3), 99-114. 

21. Narayan, P. K. and Smyth, R. (2005), Electricity consumption, employment and real income in Australia evidence from multivariate granger causality tests, Energy Policy, 33(9), 1109-1116. 

    상세보기

22. Osland, L. (2010), An application of spatial econometrics in relation to hedonic house price modeling, Journal of Real Estate Research, 32(3), 289-320. 

    상세보기

23. Parajuli, R., Ostergaard, P. A., Dalgaard, T., and Pokharel, G. R. (2014), Energy consumption projection of Nepal : An econometric approach, Renewable Energy, 63, 432-444. 

    상세보기

24. Seoul : Seoul Metropolitan Government (2010), Cartography of Climate and Energy of Seoul-The Third Final Report, Seoul. 

25. Sovacool, B. K. and Brown, M. A. (2010), Twelve metropolitan carbon footprints : A preliminary comparative global assessment, Energy policy, 38(9), 4856-4869. 

    상세보기

26. Tewathia, N. (2014), Determinants of the household electricity consumption : A case study of delhi, International Journal of Energy Economics and Policy, 4(3), 337-348. 

27. Tian, W., Song, J., and Li, Z. (2014), Spatial regression analysis of domestic energy in urban areas, Energy, 76, 629-640. 

    상세보기

28. Videras, J. (2014), Exploring spatial patterns of carbon emissions in the USA : a geographically weighted regression approach, Population and Environment, 36(2), 137-154. 

    상세보기

29. Wang, S., Fang, C., Ma, H., Wang, Y., and Qin, J. (2014), Spatial differences and multi-mechanism of carbon footprint based on GWR model in provincial China, Journal of Geographical Sciences, 24(4), 612-630. 

    상세보기

30. Yang, H. Y. (2000), A note on the causal relationship between energy and GDP in Taiwan, Energy Economics, 22(3), 309-317. 

    상세보기

31. Yu, H. (2012), The influential factors of China's regional energy intensity and its spatial linkages : 1988-2007, Energy Policy, 45, 583-593. 

    상세보기

32. Zhao, X., Burnett, J., and Fletcher, J. J. (2014), Spatial analysis of China province-level CO2 emission intensity, Renewable and Sustainable Energy Reviews, 33, 1-10. 

    상세보기

저자의 다른 논문 :

손소영 (58)