The weighted likelihood

Abstract

Abstract The authors consider a weighted version of the classical likelihood that applies when the need is felt to diminish the role of some of the data in order to trade bias for precision. They propose an axiomatic derivation of the weighted likelihood, for which they show that aspects of classical theory continue to obtain. They suggest a data‐based method of selecting the weights and show that it leads to the James‐Stein estimator in various contexts. They also provide applications.