Fröhlich, Derr and Williamson
Towards A Strictly Frequentist Theory of Imprecise Probability
Strict frequentism defines probability as the limiting relative frequency in an infinite sequence. What if the limit does
not exist? We present a broader theory, which is applicable also to statistical phenomena that exhibit diverging
relative frequencies. In doing so, we develop a close connection with imprecise probability: the cluster points of relative frequencies yield a coherent upper prevision. We show that a natural
frequentist definition of conditional probability recovers the generalized Bayes rule. We prove constructively that, for a finite set of elementary events, there exists a sequence for which the cluster points of relative frequencies coincide with a prespecified set, thereby providing strictly frequentist semantics for coherent upper previsions.