Techniques for estimation with incomplete assumptions

The subject of this paper is the sensitivity of regression estimates to the choice of prior distribution and the choice of sampling distribution. The prior is assumed to be normal with mean vector b* and covariance matrix V. The sampling distribution is assumed to be normal with covariance matrix ∨. Families of values for b*, V and Σ are selected, and the corresponding sets of posterior means are defined.