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The Minkowski approach for choosing the distance metric in geographically weighted regression / B. Lu in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 30 n° 1-2 (January - February 2016) . - pp 351 - 368 Titre : The Minkowski approach for choosing the distance metric in geographically weighted regression Type de document : Article/Communication Auteurs : B. Lu, Auteur ; M. Charlton, Auteur ; C. Brunsdon, Auteur ; P. Harris, Auteur Année de publication : 2016 Article en page(s) : pp 351 - 368 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] analyse spatiale [Termes IGN] distance [Termes IGN] espace-temps [Termes IGN] régression géographiquement pondérée Résumé : (auteur) In this study, the geographically weighted regression (GWR) model is adapted to benefit from a broad range of distance metrics, where it is demonstrated that a well-chosen distance metric can improve model performance. How to choose or define such a distance metric is key, and in this respect, a ‘Minkowski approach’ is proposed that enables the selection of an optimum distance metric for a given GWR model. This approach is evaluated within a simulation experiment consisting of three scenarios. The results are twofold: (1) a well-chosen distance metric can significantly improve the predictive accuracy of a GWR model; and (2) the approach allows a good approximation of the underlying ‘optimal distance metric’, which is considered useful when the ‘true’ distance metric is unknown. Numéro de notice : A2016-090 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1087001 En ligne : https://doi.org/10.1080/13658816.2015.1087001 Format de la ressource électronique : URL sommaire Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79875 [article]

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079-2016011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Visual comparison of moving-window kriging models / Urška Demšar in Cartographica, vol 46 n° 4 (December 2011)  

Public [article]  inCartographica > vol 46 n° 4 (December 2011) . - pp 211 - 226 Titre : Visual comparison of moving-window kriging models Type de document : Article/Communication Auteurs : Urška Demšar, Auteur ; P. Harris, Auteur Année de publication : 2011 Article en page(s) : pp 211 - 226 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse comparative [Termes IGN] krigeage [Termes IGN] visualisation cartographique Résumé : (Auteur) Kriging is a spatial prediction method that is core to the geo-statistical paradigm. Commonly applied in the environmental sciences, it enables a prediction at an unsampled location coupled with a measure of confidence in its accuracy. Many variations of kriging exist, some of them complex, especially those that allow many parameters to vary spatially. Calibrating such a kriging model and interpreting its results can therefore be quite daunting. We suggest that visualization and visual exploration can help with this task. In particular, we focus on the moving-window kriging model, evaluating three newly developed robust variants of this model against a basic counterpart. We use star icon maps and plots to visually explore model results to evaluate model parameterization, specification, and performance. Numéro de notice : A2011-483 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3138/carto.46.4.211 En ligne : https://doi.org/10.3138/carto.46.4.211 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31377 [article]

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031-2011041	SL	Revue	Centre de documentation	Revues en salle	Disponible