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On probability matching priors
Author(s) -
Staicu AnaMaria,
Reid Nancy M.
Publication year - 2008
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.5550360408
Subject(s) - prior probability , frequentist inference , mathematics , matching (statistics) , posterior probability , bayesian probability , orthogonality , quantile , bayesian inference , inference , statistics , computer science , artificial intelligence , geometry
First‐order probability matching priors are priors for which Bayesian and frequentist inference, in the form of posterior quantiles, or confidence intervals, agree to a second order of approximation. The authors show that the matching priors developed by Peers (1965) and Tibshirani (1989) are readily and uniquely implemented in a third‐order approximation to the posterior marginal density. The authors further show how strong orthogonality of parameters simplifies the arguments. Several examples illustrate their results.