Artikel

A statistical toolbox for mining and modeling spatial data

Most data mining projects in spatial economics start with an evaluation of a set of attribute variables on a sample of spatial entities, looking for the existence and strength of spatial autocorrelation, based on the Moran's and the Geary's coefficients, the adequacy of which is rarely challenged, despite the fact that when reporting on their properties, many users seem likely to make mistakes and to foster confusion. My paper begins by a critical appraisal of the classical definition and rational of these indices. I argue that while intuitively founded, they are plagued by an inconsistency in their conception. Then, I propose a principled small change leading to corrected spatial autocorrelation coefficients, which strongly simplifies their relationship, and opens the way to an augmented toolbox of statistical methods of dimension reduction and data visualization, also useful for modeling purposes. A second section presents a formal framework, adapted from recent work in statistical learning, which gives theoretical support to our definition of corrected spatial autocorrelation coefficients. More specifically, the multivariate data mining methods presented here, are easily implementable on the existing (free) software, yield methods useful to exploit the proposed corrections in spatial data analysis practice, and, from a mathematical point of view, whose asymptotic behavior, already studied in a series of papers by Belkin & Niyogi, suggests that they own qualities of robustness and a limited sensitivity to the Modifiable Areal Unit Problem (MAUP), valuable in exploratory spatial data analysis.

Sprache
Englisch

Erschienen in
Journal: Comparative Economic Research. Central and Eastern Europe ; ISSN: 2082-6737 ; Volume: 19 ; Year: 2016 ; Issue: 5 ; Pages: 5-24 ; Warsaw: De Gruyter

Klassifikation
Wirtschaft
Thema
duality diagram
spatial autocorrelation
Moran'index
Moran's Eigenvector Maps
Laplace operator
spatial eigenfunction filtering

Ereignis
Geistige Schöpfung
(wer)
d' Aubigny, Gérard
Ereignis
Veröffentlichung
(wer)
De Gruyter
(wo)
Warsaw
(wann)
2016

DOI
doi:10.1515/cer-2016-0035
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • d' Aubigny, Gérard
  • De Gruyter

Entstanden

  • 2016

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