This paper is an attempt to reconcile Bayesian and non-Bayesian approaches to statistical inference, by casting both in terms of a broader formalism. In particular, this paper is an attempt to show that when one extends coventional Bayesian analysis to distinguish the truth from one's guess for the truth, one gains a broader perspective which allows the inclusion on non-Bayesian formalisms. Amongst other things, this perspective shows how it is possible for non-Bayesian techniques to perform well, dispite their handicaps.
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Paper provided by Santa Fe Institute in its series Working Papers with number
93-09-054.