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Algebraic representation of Gaussian Markov combinations

Abstract:

Markov combinations for structural meta-analysis problems provide a way of constructing a statistical model that takes into account two or more marginal distributions by imposing conditional independence constraints between the variables that are not jointly observed. This paper considers Gaussian distributions and discusses how the covariance and concentration matrices of the different combinations can be found via matrix operations. In essence all these Markov combinations correspond to fin...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Publisher's version

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Publisher copy:
10.3150/15-BEJ759

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Institution:
University of Oxford
Department:
Oxford, MPLS, Statistics
Role:
Author
Publisher:
Bernoulli Society for Mathematical Statistics and Probability Publisher's website
Journal:
Bernoulli: official journal of the Bernoulli Society for Mathematical Statistics and Probability Journal website
Publication date:
2015-01-01
DOI:
ISSN:
1573-9759
URN:
uuid:58564abf-725a-48fe-8cf3-3b550ad68cb6
Source identifiers:
574512
Local pid:
pubs:574512

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