Bayesian models for sparse probability tables
UNSPECIFIED. (1996) Bayesian models for sparse probability tables. ANNALS OF STATISTICS, 24 (5). pp. 2178-2198. ISSN 0090-5364Full text not available from this repository.
We wish to make inferences about the conditional probabilities p(y/x), many of which are zero, when the distribution of X is unknown and one observes only a multinomial sample of the Y variates. To do this, fixed likelihood ratio models and quasi-incremental distributions are defined. It is shown that quasi-incremental distributions are intimately linked to decomposable graphs and that these graphs can guide us to transformations of X and Y which admit a conjugate Bayesian analysis on a reparametrization of the conditional probabilities of interest.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics|
|Journal or Publication Title:||ANNALS OF STATISTICS|
|Publisher:||INST MATHEMATICAL STATISTICS|
|Number of Pages:||21|
|Page Range:||pp. 2178-2198|
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