1 |
Cleveland, W. S. and Devlin, S. J. (1988). Locally weighted regression: An approach to regression analysis by local fitting. Journal of the American Statistical Association, 83, 596-610.
DOI
|
2 |
Fotheringham, A. S., Crespo, R. and Yao, J. (2015). Geographical and temporal weighted regression (GTWR). Geographical Analysis, 47, 431-452.
DOI
|
3 |
Hong, H. Y. and Lee, J. H. (2015). A time series and spatial analysis of factors affecting housing prices in Seoul. Seoul City Research, 16, 87-108.
|
4 |
Huang, B, Wu, B. and Barry, M. (2010). Geographically and temporally weighted regression for modeling spatio -temporal variation in house prices. International Journal of Geographical Information Science, 24, 383-401.
DOI
|
5 |
Kang, C. D. (2010). GWR approach for real estate appraisal : The case of Seoul apartment. Korean Appraisal Review, 20, 107-132.
|
6 |
Kim J. J. (2015). Cluster analysis for Seoul apartment price using symbolic data. Journal of the Korean Data & Information Science Society, 26 1239-1247.
DOI
|
7 |
Lee, S. W., Yoon, S. D., Park, J. Y. and Min, S. H. (2006). The practice on spatial econometric model, Pakyoungsa, Seoul
|
8 |
Lee, W. J. and Park, C. Y. (2015). Prediction of apartment prices per unit in Daegu-Gyeongbuk areas by spatial regression models. Journal of the Korean Data & Information Science Society, 26, 561-568.
DOI
|
9 |
Oh, Y. K., Kang, J. G. and Kim, J. M. (2014). Analysis of regional characteristics that affect housing prices using a GWR model - Focused on Busan metropolitan city. Tax Accounting Research, 40, 1-17.
|
10 |
Xuan, H., Li, S. and Amin, M. (2015). Statistical inference of geographically and temporally weighted regression model. Pakistan Journal of Statistics, 31, 307-325.
|