Spatial data modelling and maximum entropy theory

D. Klimešová and E. Ocelíková
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D. Klimešová: Czech University of Agriculture, Prague, Czech Republic & Institute of Information Theory and Automation, Czech Academy of Sciences, Prague
E. Ocelíková: Czech University of Agriculture, Prague, Czech Republic & Institute of Information Theory and Automation, Czech Academy of Sciences, Prague

Agricultural Economics, 2005, vol. 51, issue 2, 80-83

Abstract: Spatial data modelling and consequential error estimation of the distribution function are key points of spatial analysis. For many practical problems, it is impossible to hypothesize distribution function firstly and some distribution models, such as Gaussian distribution, may not suit to complicated distribution in practice. The paper shows the possibility of the approach based on the maximum entropy theory that can optimally describe the spatial data distribution and gives the actual error estimation.

Keywords: spatial data classification; distribution function; error distribution; and maximum entropy approach (search for similar items in EconPapers)
Date: 2005
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Persistent link: https://EconPapers.repec.org/RePEc:caa:jnlage:v:51:y:2005:i:2:id:5080-agricecon

DOI: 10.17221/5080-AGRICECON

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