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Optimally and computations for relative surprise inferences
Author(s) -
Evans Michael J.,
Guttman Irwin,
Swartz Tim
Publication year - 2006
Publication title -
canadian journal of statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.804
H-Index - 51
eISSN - 1708-945X
pISSN - 0319-5724
DOI - 10.1002/cjs.5550340109
Subject(s) - a priori and a posteriori , surprise , mathematics , humanities , invariant (physics) , philosophy , epistemology , psychology , mathematical physics , social psychology
Abstract Relative surprise inferences are based on how beliefs change from a priori to a posteriori. As they are based on the posterior distribution of the integrated likelihood, inferences of this type are invariant under relabellings of the parameter of interest. The authors demonstrate that these inferences possess a certain optimality property. Further, they develop computational techniques for implementing them, provided that algorithms are available to sample from the prior and posterior distributions.