Hyper Markov Non-Parametric Processes for Mixture Modeling and Model Selection
Markov distributions describe multivariate data with conditional independence structures. Dawid and Lauritzen (1993) extended this idea to hyper Markov laws for prior distributions. A hyper Markov law is a distribution over Markov distributions whose marginals satisfy the same conditional independen...
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| Format: | Others |
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Research Showcase @ CMU
2010
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| Online Access: | http://repository.cmu.edu/dissertations/11 http://repository.cmu.edu/cgi/viewcontent.cgi?article=1010&context=dissertations |