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A Conditional Nearest-Neighbor Spatial-Association Measure for the Analysis of Conditional Locational Interdependence

Bibliographic Data

ID4142261
AuthorsAtsuyuki Okabe (0000-0003-4663-8053, The University of Tokyo), Fujio Miki
Year1984
Volume16
Issue2
Pages163-171
Publication date1984-02-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueEnvironment and Planning A Economy and Space (JOURNAL)
Journal identifiersISSN: 0308-518X • E-ISSN: 1472-3409
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1068/a160163
OpenAlexW2067605057
LanguageEN
Citations received7
References cited3

The objective of this paper is to examine descriptively the locational phenomena that the distribution of one type of establishment is conditioned by the location of another type, such as barbers near hotels or newspaper stands around stations. First, a model is formulated in which points of one type are probabilistically distributed in relation to another type of points whose location is fixed. Second, in this context, a conditional nearest-neighbor spatial-association measure is proposed. Third, as the calculation of this measure is complex, a computational method is shown. Fourth, by the use of this method, eight types of establishments in Toshima-ward in Tokyo are examined for spatial association with railway stations

Data mining · Econometrics · Geography · k-nearest neighbors algorithm · Statistics · Computer Science · Mathematics · Psychology · Spatial and Panel Data Analysis · Urban and spatial planning · Urban Transport and Accessibility · Artificial Intelligence

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  • Formation of the Residential Structure of the Taipei Metropolitan Area

    Sue-Ching Jou•Asian Geographer•1995

  • The Statistical Analysis through a Computational Method of a Distribution of Points in Relation to its Surrounding Network

    Open Access•Atsuyuki Okabe, Akira Fujii•Environment and Planning A…•1984

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  • A Nearest-Neighbor Spatial-Association Measure for the Analysis of Firm Interdependence

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Unique citing works7
Citations per year0,17
Citation span1984 - 2026 (43)
Citation velocitycurrent
Highly citedNo
Citation typesNeutral: 7

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