摘要：Comparing the means of two normal populations is an old problem
in mathematical statistics, but there is still no consensus about its most appro-
priate solution. In this paper we treat the problem of comparing two normal
means as a Bayesian decision problem with only two alternatives: either to accept
the hypothesis that the two means are equal, or to conclude that the observed
data are, under the assumed model, incompatible with that hypothesis. The com-
bined use of an information-theory based loss function, the intrinsic discrepancy
(Bernardo and Rueda 2002), and an objective prior function, the reference prior
(Bernardo 1979; Berger and Bernardo 1992), produces a new solution to this old
problem which has the invariance properties one should presumably require.
关键词：Bayes factor, BRC, comparison of normal means, intrinsic discrepancy,
precise hypothesis testing, reference prior, two sided tests.
