A Mixed Geographically and Temporally Weighted Regression: Exploring Spatial-Temporal Variations from Global and Local Perspectives

A Mixed Geographically and Temporally Weighted Regression: Exploring Spatial-Temporal Variations from Global and Local Perspectives

To capture both global stationarity and spatiotemporal non-stationarity, a novel mixed geographically and temporally weighted regression (MGTWR) model accounting for global and local effects in both space and time is presented. Since the constant and spatial-temporal varying coefficients could not b...

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Bibliographic Details
Main Authors: Jiping Liu, Yangyang Zhao, Yi Yang, Shenghua Xu, Fuhao Zhang, Xiaolu Zhang, Lihong Shi, Agen Qiu
Format: Article
Language:English
Published: MDPI AG 2017-01-01
Series:Entropy
Subjects:
MGTWR
two-stage least squares estimation
global stationarity and spatiotemporal non-stationarity
spatial modeling
Online Access:http://www.mdpi.com/1099-4300/19/2/53

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