We consider the confidence interval centered on a frequentist model averaged
estimator that was proposed by Buckland, Burnham & Augustin (1997). In the
context of a simple testbed situation involving two linear regression models,
we derive exact expressions for the confidence interval and then for the
coverage and scaled expected length of the confidence interval. We use these
measures to explore the exact finite sample performance of the
Buckland-Burnham-Augustin confidence interval. We also explore the limiting
asymptotic case (as the residual degrees of freedom increases) and compare our
results for this case to those obtained for the asymptotic coverage of the
confidence interval by Hjort & Claeskens (2003).Comment: Journal of Statistical Planning and Inference (2019
