Probability matching priors for some parameters of the bivariate normal distribution



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Probability matching priors for some parameters of the bivariate normal distribution

Malay Ghosh, Upasana Santra, Dalho Kim

Source: Bertrand Clarke and Subhashis Ghosal, eds., Pushing the Limits of Contemporary Statistics: Contributions in Honor of Jayanta K. Ghosh (Beachwood, Ohio, USA: Institute of Mathematical Statistics, 2008), 71-81.

Abstract

This paper develops some objective priors for certain parameters of the bivariate normal distribution. The parameters considered are the regression coefficient, the generalized variance, and the ratio of the conditional variance of one variable given the other to the marginal variance of the other variable. The criterion used is the asymptotic matching of coverage probabilities of Bayesian credible intervals with the corresponding frequentist coverage probabilities. The paper uses various matching criteria, namely, quantile matching, matching of distribution functions, highest posterior density matching, and matching via inversion of test statistics. One particular prior is found which meets all the matching criteria individually for all the parameters of interest.

Primary Subjects: 62F15, 62F25
Keywords: credible intervals; distribution functions; first order; generalized variance; highest posterior density; likelihood ratio; posteriors; propriety; quantiles; regression coefficient; second order

Full-text: Open access

Links and Identifiers

Permanent link to this document: http://projecteuclid.org/euclid.imsc/1209398461
Digital Object Identifier: doi:10.1214/074921708000000066

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Institute of Mathematical Statistics Collections

Institute of Mathematical Statistics Collections