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  • An evaluation of spatial patterns and a clustering play an important role among methods of spatial statistics. However, traditional clustering techniques are seldom suitable for analyses of spatial data and patterns because they usually do not count on spatial relations and qualities of objects. This paper aims to introduce usage of methods of spatial clustering estimation, which are based mainly on the position of events and not only on the events attribute space. Firstly, the methods of the spatial clustering or randomness estimation are introduced and applied on a real dataset, then spatial clusters are identified and the intensity of processes is quantified. Non-spatial properties and a time are considered together with the location data. Also methods of the multivariate statistics are used for the purpose of the classification of regions with similar properties. Particularly, occurrence data of selected infectious diseases in Olomouc Region in period 2004 - 2010 provided by Regional Public Health Service in Olomouc are used for the case study.
  • An evaluation of spatial patterns and a clustering play an important role among methods of spatial statistics. However, traditional clustering techniques are seldom suitable for analyses of spatial data and patterns because they usually do not count on spatial relations and qualities of objects. This paper aims to introduce usage of methods of spatial clustering estimation, which are based mainly on the position of events and not only on the events attribute space. Firstly, the methods of the spatial clustering or randomness estimation are introduced and applied on a real dataset, then spatial clusters are identified and the intensity of processes is quantified. Non-spatial properties and a time are considered together with the location data. Also methods of the multivariate statistics are used for the purpose of the classification of regions with similar properties. Particularly, occurrence data of selected infectious diseases in Olomouc Region in period 2004 - 2010 provided by Regional Public Health Service in Olomouc are used for the case study. (en)
Title
  • On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic
  • On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic (en)
skos:prefLabel
  • On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic
  • On Estimation of the Spatial Clustering: Case Study of Epidemiological Data In Olomouc Region, Czech Republic (en)
skos:notation
  • RIV/61989592:15310/13:33145314!RIV14-MSM-15310___
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http://linked.open...avai/riv/aktivita
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  • P(EE2.3.20.0170)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
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  • 93701
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  • RIV/61989592:15310/13:33145314
http://linked.open...riv/jazykVysledku
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  • Spatial clustering, Spatial autocorrelation, Disease mapping, Spatial pattern (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [1C9E12F4705B]
http://linked.open...v/mistoKonaniAkce
  • Písek
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  • Ostrava
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the Dateso 2013 Annual International Workshop on DAtabases, TExts, Specifications and Objects
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http://linked.open...UplatneniVysledku
http://linked.open...iv/tvurceVysledku
  • Dvorský, Jiří
  • Tuček, Pavel
  • Marek, Lukáš
  • Pászto, Vít
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 1613-0073
number of pages
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  • Vysoká škola báňská - Technická univerzita Ostrava
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  • 978-80-248-2968-5
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  • 15310
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