Models in quantitative geography

Daisuke Murakami, Yoshiki Yamagata

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter introduces approaches in quantitative geography. After the introduction in Section 6.1, Sections 6.2 and 6.3 explain the geographically weighted regression and the spatial filtering approaches, respectively. Section 6.4 describes extensions of these approaches for large spatial dataset.

Original languageEnglish
Title of host publicationSpatial Analysis Using Big Data
Subtitle of host publicationMethods and Urban Applications
PublisherElsevier
Pages159-178
Number of pages20
ISBN (Electronic)9780128131329
ISBN (Print)9780128131275
DOIs
Publication statusPublished - 2019 Nov 2
Externally publishedYes

Keywords

  • Eigenvector spatial filtering
  • Geographically weighted regression
  • Regression
  • Spatially varying coefficients

ASJC Scopus subject areas

  • Economics, Econometrics and Finance(all)
  • Business, Management and Accounting(all)

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