Likelihood regions are shown to be robust in the sense that their posterior probability content is relatively insensitive to contaminations of the prior. This provides a Bayesian interpretation of regions that are commonly used by frequentists to construct confidence intervals and whose use are also advocated by the pure likelihood approach.
@article{1176347277,
author = {Wasserman, Larry Alan},
title = {A Robust Bayesian Interpretation of Likelihood Regions},
journal = {Ann. Statist.},
volume = {17},
number = {1},
year = {1989},
pages = { 1387-1393},
language = {en},
url = {http://dml.mathdoc.fr/item/1176347277}
}
Wasserman, Larry Alan. A Robust Bayesian Interpretation of Likelihood Regions. Ann. Statist., Tome 17 (1989) no. 1, pp. 1387-1393. http://gdmltest.u-ga.fr/item/1176347277/