GWR

GWR4 is a new release of a Microsoft Windows-based application software for calibrating geographically weighted regression (GWR) models, which can be used to explore geographically varying relationships between dependent/response variables and independent/explanatory variables. A GWR model can be considered a type of regression model with geographically varying parameters.

Geographically Weighted Regression
  191

Contributor

contributed at 2018-08-09

Authorship

Affiliation:  
School of Geographical Sciences and Urban Planning, Arizona State university
Email:  
Stewart.Fotheringham@asu.edu
Homepage:  
View
Is authorship not correct? Feed back

Classification(s)

Geography SubjectGIScience & Remote SensingGeostatistics

Detailed Description

GWR4 (Geographically Weighted Regression)

What is GWR4? 

GWR4 is a new release of a Microsoft Windows-based application software for calibrating geographically weighted regression (GWR) models, which can be used to explore geographically varying relationships between dependent/response variables and independent/explanatory variables. A GWR model can be considered a type of regression model with geographically varying parameters.

 A most remarkable feature of this release is the function to fit semiparametric GWR models, which allow you to mix globally fixed terms and locally varying terms of explanatory variables simultaneously. The function can be applied to popular types of generalized linear modelling including Gaussian, Poisson, and logistic regressions.

 

GWR 4 Development Team 

Tomoki Nakaya (Department of Geography, Ritsumeikan University), Martin Charlton, Chris Brunsdon, Paul Lewis (National Centre of Geocomputation, National University of Ireland), Jing Yao (School of Social and Political Sciences, University of Glasgow), A Stewart Fotheringham (School of Geographical Sciences &  Urban Planning, Arizona State University)

 

GWR4 Link 

 

 

 

 

 

 

 

 

How to cite

Stewart Fotheringham (2018). GWR, Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/6078f0f2-f754-44a7-b3de-77f82b726347
Copy

QR Code

Contributor

contributed at 2018-08-09

Authorship

Affiliation:  
School of Geographical Sciences and Urban Planning, Arizona State university
Email:  
Stewart.Fotheringham@asu.edu
Homepage:  
View
Is authorship not correct? Feed back

QR Code

You can link related {{typeName}} from your personal space to this model item, or you can create a new {{typeName.toLowerCase()}}.

Model Content & Service

These authorship information will be submitted to the contributor to review.