Geographically Weighted Regression : A Method for Exploring Spatial Nonstationarity

  title={Geographically Weighted Regression : A Method for Exploring Spatial Nonstationarity},
  author={Chris Brunsdon and Stewart Fotheringham and Martin E. Charlton},
model which allows diferent relationships to exist at diferent points in space. This technique is loosely based on kernel regression. The method itself is introduced and related issues such as the choice of a spatial weighting function are discussed. Following this, a series of related statistical tests are considered which can be described generally as tests f o r spatial nonstationarity. Using Monte Carlo methods, techniques are proposed fo r investigatin the null 
Highly Influential
This paper has highly influenced 31 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS
Highly Cited
This paper has 661 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 220 extracted citations

Spatial analysis of farming viability and its contributing factors in California

2013 21st International Conference on Geoinformatics • 2013
View 9 Excerpts
Highly Influenced

Local entropy map: a nonparametric approach to detecting spatially varying multivariate relationships

International Journal of Geographical Information Science • 2010
View 18 Excerpts
Highly Influenced

Regression kriging as a workhorse in the digital soil mapper ' s toolbox ☆

H. Keskina, S. Grunwalda
View 5 Excerpts
Highly Influenced

Spatial association detector (SPADE)

International Journal of Geographical Information Science • 2018
View 4 Excerpts
Highly Influenced

An Improved Spatial Downscaling Procedure for TRMM 3B43 Precipitation Product Using Geographically Weighted Regression

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing • 2015
View 5 Excerpts
Highly Influenced

Locating a supermarket using a locally calibrated Huff model

International Journal of Geographical Information Science • 2015
View 7 Excerpts
Highly Influenced

662 Citations

Citations per Year
Semantic Scholar estimates that this publication has 662 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-10 of 14 references

The Geography of Parameter Space : An Investigation into Spatial NonStationarity

C. F. Brunsdon

Directional Variation in DistanceDecay

P. A. Rogerson

Estimating Probability Surfaces for Geographical Point Data : An Adaptive Kernel Algorithm

E. Casetti
Computers and Geosciences • 1995

On the Future of Spatial Analysis : The Role of GIS

A. S. Fotheringham, T. C. Pitts

‘ Weighted Spatial Adaptive Filtering : Monte Carlo Studies and Application to Illicit Drug Market Modeling

W. L. Gorr, A. M. Olligschlaeger

Exploratory SpaceTimeAttribute Pattern Analysers

S. Openshaw
Spatid Analysis and CIS • 1993

" Specifying and Estimating Multilevel Models for Geographical Research

K. Jones
Trunsuc - tions of the Institute of British Geographers • 1991

Warped Space : A Geography of Distance Decay

S. A. Foster, W. L. Gorr

Similar Papers

Loading similar papers…