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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Bibliographic Details
Main Authors: Kai Cao, Mi Diao
Other Authors: DEPT OF GEOGRAPHY
Format: Article
Published: Taylor & Francis 2019
Online Access:https://scholarbank.nus.edu.sg/handle/10635/153305
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Institution: National University of Singapore
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spelling 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
institution National University of Singapore
building NUS Library
continent Asia
country Singapore
Singapore
content_provider NUS Library
collection ScholarBank@NUS
description Annals of the American Association of Geographers
author2 DEPT OF GEOGRAPHY
author_facet DEPT OF GEOGRAPHY
Kai Cao
Mi Diao
format Article
author Kai Cao
Mi Diao
spellingShingle 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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