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• W2058520912 abstract "In the present paper we show that every stochastic kernel mapping the measurable space is generated according to a probability measure on the set of all -measurable functions – only provided contains all sets {x}xeX. This theorem is the generalization of the wellknown statement that every stochastic matrix may be represented as a convex linear combination of permutation matrices. The result is applied to comparison relations for statistical experiments." @default.
• W2058520912 created "2016-06-24" @default.
• W2058520912 creator A5060525927 @default.
• W2058520912 date "1982-01-01" @default.
• W2058520912 modified "2023-10-18" @default.
• W2058520912 title "A representation theorem for stochastic kernels and its application in comparison of experiments" @default.
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• W2058520912 doi "https://doi.org/10.1080/02331888208801669" @default.
• W2058520912 hasPublicationYear "1982" @default.
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