Please use this identifier to cite or link to this item: https://hdl.handle.net/10593/10150
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dc.contributor.authorKossowski, T omasz-
dc.contributor.authorHauke, Jan-
dc.date.accessioned2014-02-28T14:20:25Z-
dc.date.available2014-02-28T14:20:25Z-
dc.date.issued2012-
dc.identifier.citationQuaestiones Geographicae vol. 31 (2), 2012pl_PL
dc.identifier.isbn978-83-62662-62-3-
dc.identifier.issn0137-477X-
dc.identifier.urihttp://hdl.handle.net/10593/10150-
dc.description.abstractThe power of today's computers allows us to perform computation on massive quantities of data on the one hand and produces enormous amounts of analysis output on the other, as noted by Griffith in his 2003 book. Besides, visualisation and spatial filtering (the core of considerations in Griffith’s book) have a chance to be widely used in research practice, especially in geosciences and, more precisely, for georeferenced data. Following the idea proposed by Patuelli et al. (2006, 2009), we analysed the labour market in Poland, focusing on metropolitan areas and their surroundings. The analysis was performed on a data set for the unemployment rate in the 2,478 Polish communes. We took into account spatial autocorrelation and used spatial filtering techniques to construct components of an orthogonal map pattern. As shown in Tiefelsdorf & Griffith (2007), the spatial filtering techniques could be employed in both, parametric and semi-parametric approaches. In this paper we adopted a parametric one.pl_PL
dc.language.isoenpl_PL
dc.publisherWydział Nauk Geograficznych i Geologicznych UAMpl_PL
dc.subjectMoran’s I statisticpl_PL
dc.subjectspatial autocorrelationpl_PL
dc.subjectspatial dependencepl_PL
dc.titleAnalysis of the labour market in metropolitan areas: A spatial filtering approach.pl_PL
dc.typeArtykułpl_PL
Appears in Collections:Quaestiones Geographicae vol. 31 (2), 2012

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