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On the implementation of local probability matching priors for interest parameters

Sweeting, TJ; (2005) On the implementation of local probability matching priors for interest parameters. BIOMETRIKA , 92 (1) 47 - 57. Green open access

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Abstract

Probability matching priors are priors for which the posterior probabilities of certain specified sets are exactly or approximately equal to their coverage probabilities. These priors arise as solutions of partial differential equations that may be difficult to solve, either analytically or numerically. Recently Levine & Casella (2003) presented an algorithm for the implementation of probability matching priors for an interest parameter in the presence of a single nuisance parameter. In this paper we develop a local implementation that is very much more easily computed. A local probability matching prior is a data-dependent approximation to a probability matching prior and is such that the asymptotic order of approximation of the frequentist coverage probability is not degraded. We illustrate the theory with a number of examples, including three discussed in Levine & Casella (2003).

Type: Article
Title: On the implementation of local probability matching priors for interest parameters
Open access status: An open access version is available from UCL Discovery
Keywords: coverage probability bias, data-dependent prior, higher-order asymptotics, Metropolis-Hastings algorithm, nuisance parameter, probability matching prior, PROVIDING FREQUENTIST VALIDITY, BAYESIAN-INFERENCE, NONINFORMATIVE PRIORS, APPROXIMATIONS, DISTRIBUTIONS, RATIO
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science
URI: https://discovery.ucl.ac.uk/id/eprint/1575
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