Abstract :
Most model selection mechanisms work in an “overall” modus, providing models
without specific concern for how the selected model is going to be used afterward+
The focused information criterion ~FIC!, on the other hand, is geared toward
optimum model selection when inference is required for a given estimand+ In this
paper the FIC method is extended to weighted versions+ This allows one to rank
and select candidate models for the purpose of handling a range of similar tasks
well, as opposed to being forced to focus on each task separately+ Applications
include selecting regression models that perform well for specified regions of
covariate values+ We derive these weighted focused information criteria ~wFIC!,
give asymptotic results, and apply the methods to real data+ Formulas for easy
implementation are provided for the class of generalized linear models+
