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Admissible Representations of Probability Measures

Admissible representations for probability measures
Authors: Matthias Schröder 0001;

Admissible Representations of Probability Measures

Abstract

AbstractIn a recent paper, probabilistic processes are used to generate Borel probability measures on topological spacesXthat are equipped with a representation in the sense of type‐2 theory of effectivity. This gives rise to a natural representation of the set of Borel probability measures onX. We compare this representation to a canonically constructed representation which encodes a Borel probability measure as a lower semicontinuous function from the open sets to the unit interval. We show that this canonical representation is admissible with respect to the weak topology on Borel probability measures. Moreover, we prove that for countably‐based topological spaces the representation via probabilistic processes is equivalent to the canonical representation and thus admissible with respect to the weak topology. (© 2007 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Keywords

Set functions and measures on topological spaces (regularity of measures, etc.), Theoretical Computer Science, measure theory, Higher-type and set recursion theory, type-2 theory of effectivity, Type 2 Theory of Effectivity, admissibility, probabilistic processes, Measure Theory, Probabilistic Processes, Admissible Representations, Theory of numerations, effectively presented structures, Constructive and recursive analysis, Computer Science(all)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Average
Top 10%
Top 10%
gold
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