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Hyper Markov laws in the statistical analysis of decomposable graphical models

Abstract:

This paper introduces and investigates the notion of a hyper Markov law, which is a probability distribution over the set of probability measures on a multivariate space that (i) is concentrated on the set of Markov probabilities over some decomposable graph, and (ii) satisfies certain conditional independence restrictions related to that graph. A stronger version of this hyper Markov property is also studied. Our analysis starts by reconsidering the properties of Markov probabilities, using ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University College London
Role:
Author
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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Oxford college:
Jesus College
Role:
Author
Publisher:
Institute of Mathematical Statistics Publisher's website
Journal:
Annals of Statistics Journal website
Volume:
21
Issue:
3
Pages:
1272-1317
Publication date:
1993-09-01
ISSN:
00905364

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