Noninformative priors for maximal invariant parameter in group models

Abstract

For an Euclidean groupG acting freely on the parameter space, we derive, among several noninformative priors, the reference priors of Berger-Bernardo and Chang-Eaves for our parameter of interest θ₁, a scalar maximal invariant parametric function. Identifying the nuisance parameter vector with the group element, we derive a simple structure of the information matrix which is used to obtain different noninformative priors. We compare these priors using the marginalization paradox and the probability-matching criteria. The Chang-Eaves and the Berger-Bernardo reference priors appear to be the most attractive choice. Several illustrative examples are considered.