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Conditional probability approach to spatial interaction

Published online by Cambridge University Press:  01 July 2016

Julian Besag
Julian Besag*
Affiliation:
University of Liverpool
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Extract

The merits of a conditional probability (or Markovian) approach to the analysis of local spatial interaction lie in its intuitive appeal and its ability to cope with non-Gaussian situations. Whilst relationships between plausible spatial-temporal models and Markov fields may sometimes be obtained, this does not remove the need for a purely spatial approach to be available. In addition to promoting the above point of view, some Monte Carlo simulation results, due to Mr. D. H. Green, were presented. Analytical progress on coding efficiency was reported.

Type
Analysis of Spatial Interaction
Information
Advances in Applied Probability , Volume 7 , Issue 3 , September 1975 , pp. 454
Copyright
Copyright © Applied Probability Trust 1975 

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References

Besag, J. E. (1974a) Spatial interaction and the statistical analysis of lattice systems (with discussion). J. R. Statist. Soc. B, 36, 192–236.Google Scholar
Besag, J. E. (1974b) On spatial-temporal models and Markov fields. Proc. 1974 European Meeting of Statisticians, Prague, To appear.Google Scholar
Besag, J. E. and Moran, P. A. P. (1975) On the estimation and testing of spatial interaction in Gaussian lattice processes. Biometrika, To appear.Google Scholar