Journal
JOURNAL OF THEORETICAL PROBABILITY
Volume 29, Issue 3, Pages 797-825Publisher
SPRINGER/PLENUM PUBLISHERS
DOI: 10.1007/s10959-015-0611-2
Keywords
Uniform probability; Foundations of probability; Kolmogorov axioms; Finite additivity
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In this paper, we address the problem of constructing a uniform probability measure on . Of course, this is not possible within the bounds of the Kolmogorov axioms, and we have to violate at least one axiom. We define a probability measure as a finitely additive measure assigning probability 1 to the whole space, on a domain which is closed under complements and finite disjoint unions. We introduce and motivate a notion of uniformity which we call weak thinnability, which is strictly stronger than extension of natural density. We construct a weakly thinnable probability measure, and we show that on its domain, which contains sets without natural density, probability is uniquely determined by weak thinnability. In this sense, we can assign uniform probabilities in a canonical way. We generalize this result to uniform probability measures on other metric spaces, including .
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