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dc.contributor.authorBivand, Roger
dc.date.accessioned2015-08-26T07:24:13Z
dc.date.accessioned2015-08-26T07:49:07Z
dc.date.available2015-08-26T07:24:13Z
dc.date.available2015-08-26T07:49:07Z
dc.date.issued2015
dc.identifier.citationProcedia Environmental Sciences 2015, 27:106-111nb_NO
dc.identifier.issn1878-0296
dc.identifier.urihttp://hdl.handle.net/11250/297963
dc.description-Copyright © 2015 Published by Elsevier B.V.nb_NO
dc.description.abstractTorsten Hägerstrand’s 1953 study of innovation diffusion [1] was pathbreaking in many ways. It was based on an explicit micro-model of information spread, and on Monte Carlo simulation of the hypothesised spatial process. Using the original aggregated data and Hope-type tests of the ability of the simulations to capture the observed adoptions, (author?) [2] and (author?) [3] and others found problems. This study attempts to examine the extent to which we may be able to "do better" with a range of approaches drawn from spatial statistics, including using a SAR lattice model, geostatistical modelling, Moran eigenvectors, and other approaches.nb_NO
dc.language.isoengnb_NO
dc.publisherElsevier B.Vnb_NO
dc.rightsNavngivelse-Ikkekommersiell-IngenBearbeidelse 3.0 Norge*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/no/*
dc.subjectspatial diffusionnb_NO
dc.subjectspatial processesnb_NO
dc.subjectspatial statisticsnb_NO
dc.titleSpatial diffusion and spatial statistics: revisting Hägerstrand’s study of innovation diffusion.nb_NO
dc.typeJournal articlenb_NO
dc.typePeer reviewednb_NO
dc.date.updated2015-08-26T07:24:13Z
dc.source.pagenumber106-111nb_NO
dc.source.volume27nb_NO
dc.source.journalProcedia Environmental Sciencesnb_NO
dc.identifier.doi10.1016/j.proenv.2015.07.103
dc.identifier.cristin1259849


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Navngivelse-Ikkekommersiell-IngenBearbeidelse 3.0 Norge
Except where otherwise noted, this item's license is described as Navngivelse-Ikkekommersiell-IngenBearbeidelse 3.0 Norge