Approximate conditional inference for location familles

Abstract

Abstract Approximations to exact conditional inference for location familles are considered. Methods which improve the standard normal and chi‐squared approximations to the conditional distributions of pivots arising in standard large‐sample theory are discussed, including the use of parameter transformations for parametrization‐dependent pivots, and the use of scaling factors for the likelihood‐ratio statistic. The methods are illustrated and compared in a series of examples.