Mathematical Geology

, Volume 22, Issue 7, pp 763–777 | Cite as

A Bayesian/maximum-entropy view to the spatial estimation problem

  • George Christakos


The purpose of this paper is to stress the importance of a Bayesian/maximum-entropy view toward the spatial estimation problem. According to this view, the estimation equations emerge through a process that balances two requirements: High prior information about the spatial variability and high posterior probability about the estimated map. The first requirement uses a variety of sources of prior information and involves the maximization of an entropy function. The second requirement leads to the maximization of a so-called Bayes function. Certain fundamental results and attractive features of the proposed approach in the context of the random field theory are discussed, and a systematic spatial estimation scheme is presented. The latter satisfies a variety of useful properties beyond those implied by the traditional stochastic estimation methods.

Key words

spatial estimation entropy Bayes law information geostatistics 


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Copyright information

© International Association for Mathematical Geology 1990

Authors and Affiliations

  • George Christakos
    • 1
  1. 1.Department of Environmental Sciences and EngineeringThe University of North CarolinaChapel Hill

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