Summary Admissibility of estimators under vague prior information on the distribution of the unknown parameter is studied which leads
to the notion of gamma-admissibility. A sufficient condition for an estimator of the formδ(x)=(ax+b)/(cx+d) to be gamma-admissible in the one-parameter exponential family under squared error loss is established. As an application
of this result two equalizer rules are shown to be unique gamma-minimax estimators by proving their gamma-admissibility.