Bayesian Poisson models for the graphical combination of dependent expert information
UNSPECIFIED. (2000) Bayesian Poisson models for the graphical combination of dependent expert information. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 62 (Part 3). pp. 525-544. ISSN 1369-7412Full text not available from this repository.
A supra-Bayesian (SB) wants to combine the information from a group of k experts to produce her distribution of a probability theta. Each expert gives his counts of what he thinks are the numbers of successes and failures in a sequence of independent trials, each with probability a of success. These counts, used as a surrogate for each expert's own individual probability assessment (together with his associated level of confidence in his estimate), allow the SE to build various plausible conjugate models. Such models reflect her beliefs about the reliability of different experts and take account of different possible patterns of overlap of information between them. Corresponding combination rules are then obtained and compared with other more established rules and their properties examined.
|Item Type:||Journal Article|
|Subjects:||Q Science > QA Mathematics|
|Journal or Publication Title:||JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY|
|Publisher:||BLACKWELL PUBL LTD|
|Number of Pages:||20|
|Page Range:||pp. 525-544|
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