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Statistical maps: a categorical approach

In: Mathematica Slovaca, vol. 57, no. 1
Roman Frič

Details:

Year, pages: 2007, 41 - 57
About article:
In probability theory, each random variable $f$ can be viewed as channel through which the probability $p$ of the original probability space is transported to the distribution $pf$, a probability measure on the real Borel sets. In the realm of fuzzy probability theory, fuzzy probability measures (equivalently states) are transported via statistical maps (equivalently, fuzzy random variables, operational random variables, Markov kernels, observables). We deal with categorical aspects of the transportation of (fuzzy) probability measures on one measurable space into probability measures on another measurable spaces. A key role is played by $D$-posets (equivalently effect algebras) of fuzzy sets.
How to cite:
ISO 690:
Frič, R. 2007. Statistical maps: a categorical approach. In Mathematica Slovaca, vol. 57, no.1, pp. 41-57. 0139-9918.

APA:
Frič, R. (2007). Statistical maps: a categorical approach. Mathematica Slovaca, 57(1), 41-57. 0139-9918.