Generalized Measures of Information, Bayes' Likelihood Ratio and Jaynes' Formalism

L March and M Batty
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L March: Department of Systems Design, University of Waterloo, Ontario, N2L 3GI, Canada
M Batty: Department of Civil Engineering, University of Waterloo, Ontario, N2L 3GI, Canada

Environment and Planning B, 1975, vol. 2, issue 1, 99-105

Abstract: This paper relates generalized measures of information to expected likelihood functions (ELFs) derived from Bayes' equation. It then demonstrates that Jaynes' formalism may be extended to formulate a class of minimally-prejudiced models of which those derived from Shannon's measure are but a limiting and special case. The rôle of probable inference and of information-minimizing models in design is commented on.

Date: 1975
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Persistent link: https://EconPapers.repec.org/RePEc:sae:envirb:v:2:y:1975:i:1:p:99-105

DOI: 10.1068/b020099

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