A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore
Annals of the American Association of Geographers
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2019
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sg-nus-scholar.10635-1533052020-11-06T03:21:46Z A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore Kai Cao Mi Diao DEPT OF GEOGRAPHY DEPT OF REAL ESTATE Annals of the American Association of Geographers 109 1 173-186 2019-04-17T02:43:00Z 2019-04-17T02:43:00Z 2018-10-02 Article Kai Cao, Mi Diao (2018-10-02). A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore. Annals of the American Association of Geographers 109 (1) : 173-186. ScholarBank@NUS Repository. 2469-4452 https://scholarbank.nus.edu.sg/handle/10635/153305 Taylor & Francis Taylor & Francis |
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Singapore Singapore |
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Annals of the American Association of Geographers |
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DEPT OF GEOGRAPHY |
author_facet |
DEPT OF GEOGRAPHY Kai Cao Mi Diao |
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Article |
author |
Kai Cao Mi Diao |
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Kai Cao Mi Diao A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore |
author_sort |
Kai Cao |
title |
A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore |
title_short |
A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore |
title_full |
A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore |
title_fullStr |
A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore |
title_full_unstemmed |
A Big-Data-based Geographically Weighted Regression Model for Public Housing Prices: A Case Study in Singapore |
title_sort |
big-data-based geographically weighted regression model for public housing prices: a case study in singapore |
publisher |
Taylor & Francis |
publishDate |
2019 |
url |
https://scholarbank.nus.edu.sg/handle/10635/153305 |
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1683424764878651392 |