A framework for statistical inferential decisions in spatial pattern analysis.
The desire of many geographical information science (GIS) practitioners to undertake sophisticated spatial pattern analysis has been facilitated by the increasing availability of specialised software and the appearance of pedagogic papers illustrating the application of various techniques. However,...
| Publicado en: | Canadian Geographer Vol. 49; no. 2; pp. 172 - 180 |
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| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Wiley-Blackwell
Summer 2005
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=510435816&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 510435816 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 00083658 CGE jtl: Canadian Geographer issn: 00083658 maglogo: N pubinfo: dt: Summer 2005 vid: 49 iid: 2 pid: 480 pub: Wiley-Blackwell artinfo: ui: 510435816 10.1111/j.0008-3658.2005.00087.x ppf: 172 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P size: 542KB tig: atl: A framework for statistical inferential decisions in spatial pattern analysis. aug: au: Csillag, Ferenc Boots, Barry su: Geography -- Methodology Geography -- Statistical methods Spatial analysis (Statistics) Geographic information systems sug: subj: Geography -- Methodology Geography -- Statistical methods Spatial analysis (Statistics) Geographic information systems ab: The desire of many geographical information science (GIS) practitioners to undertake sophisticated spatial pattern analysis has been facilitated by the increasing availability of specialised software and the appearance of pedagogic papers illustrating the application of various techniques. However, the appropriate use of these techniques also requires an understanding of the nature of hypothesis testing and statistical inference for spatial data. Since there is little information currently available to aid the GIS practitioner in this regard, we offer such guidance here. We do so by revisiting the steps involved in spatial pattern analysis. Our perspective is based on the notion of spatial stochastic models and is presented as a decision tree. The four levels of the tree (i.e., sequential decisions) are associated with the assumptions, the type of data representation and the types of questions asked by the analyst. We emphasise the scientific and educational challenges involved. Le désir de nombreux practiciens, utilisant des systèmes d'information géographique (SIC), d'effectuer des analyses spatiales sophistiquées a été facilité par la disponibilité grandissante de logiciels spécialisés et d'articles pédagogiques illustrant l'application de ces diverses techniques. Cependant, I'usage approprié de ces techniques exige aussi une compréhension des notions de test d'hypothèse et d'inférence statistique se rapportant aux données spatiales. Étant donnéquejusqu'd récemmentil n'y avait que très peu de ressources disponibles à cet égard, nous offrons de tels conseils ici. Nous accomplissons cet objectifen revisitant les étapes impliquées dans l'analyse de structures spatiales. Notre perspective est basée sur la notion de modèles stochastiques spatiaux et est présentée comme un arbre decisionnel. Le quatre niveaux de I'arbre (c.-à-d., les décisions séquentielles) sont associés aux prémisses, au type de représentation de données et aux types de question posées. Nous soulignons les défis et les implications scientifiques ainsi que pédagogiques quant à l'emploi de ces techniques. Reprinted by permission of the publisher. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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