On the notion of ‘bandwidth’ in geographically weighted regression models of spatially varying processes

A. Stewart Fotheringham, Hanchen Yu, Levi John Wolf, Taylor M. Oshan, Ziqi Li

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

Abstract

Models designed to capture spatially varying processes are now employed extensively in the social and environmental sciences. The main strength of such models is their ability to represent relationships that vary across locations through locally varying parameter estimates. However, local models of spatial processes also provide information on the nature of these spatially varying relationships through the estimation of a ‘bandwidth’ parameter. This paper examines bandwidth at a conceptual, operational and empirical level within the framework of geographically weighted regression, one of the more frequently employed local spatial models. We outline how bandwidth relates to three characteristics of spatial processes: variation, dependence and strength.

Original languageEnglish (US)
Pages (from-to)1485-1502
Number of pages18
JournalInternational Journal of Geographical Information Science
Volume36
Issue number8
DOIs
StatePublished - 2022
Externally publishedYes

Keywords

  • Bandwidth
  • MGWR
  • spatial processes
  • spatial scale
  • spatially varying coefficients

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development
  • Library and Information Sciences

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