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Integration of fuzzy and geostatistical models for estimating missing multivariate observations.
Bioinformatics Applications Research Center, James Cook University School of Information Technology Townsville, QLD 4811, Australia.ORCID iD: 0000-0002-4255-5130
2005 (English)In: WSEAS Transactions on Systems, Vol. 4, no 4, 233-237 p.Article in journal (Refereed) Published
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Abstract [en]

The estimation of missing observations is an important research field which has practical applications in many science and engineering disciplines. In analyzing the variability of a particular data set which can be spatially related, classical statistical methods make no use of this type of information; whereas geostatistics accomodates the spatial information of the data set in its regression analysis for estimating missing observations or unknown data. This paper incorporates the modeling of fuzzy protoptyes in the cokriging system of geostatistics in order to improve the accuracy of the estimates and alleviate the computational complexity of cokriging.

Place, publisher, year, edition, pages
2005. Vol. 4, no 4, 233-237 p.
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-125021OAI: oai:DiVA.org:liu-125021DiVA: diva2:902772
Conference
Proceedings of the 6th WSEAS Int. Conf. on FUZZY SYSTEMS, Lisbon, Portugal, June 16-18, 2005 (pp29-33)
Available from: 2016-02-12 Created: 2016-02-12 Last updated: 2016-02-23

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Pham, Tuan D
Probability Theory and Statistics

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • oxford
  • Other style
More styles
Language
  • de-DE
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  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
  • html
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  • asciidoc
  • rtf