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Bimonoidal Structure of Probability Monads

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arxiv 1804.03527 v4 pith:A3FS4OLL submitted 2018-04-10 math.PR cs.LOmath.CTmath.QA

classification math.PRcs.LOmath.CTmath.QA
keywords monoidalstructurebimonoidalcartesiancategorymonadprobabilitycategories
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We give a conceptual treatment of the notion of joints, marginals, and independence in the setting of categorical probability. This is achieved by endowing the usual probability monads (like the Giry monad) with a monoidal and an opmonoidal structure, mutually compatible (i.e. a bimonoidal structure). If the underlying monoidal category is cartesian monoidal, a bimonoidal structure is given uniquely by a commutative strength. However, if the underlying monoidal category is not cartesian monoidal, a strength is not enough to guarantee all the desired properties of joints and marginals. A bimonoidal structure is then the correct requirement for the more general case. We explain the theory and the operational interpretation, with the help of the graphical calculus for monoidal categories. We give a definition of stochastic independence based on the bimonoidal structure, compatible with the intuition and with other approaches in the literature for cartesian monoidal categories. We then show as an example that the Kantorovich monad on the category of complete metric spaces is a bimonoidal monad for a non-cartesian monoidal structure.

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  1. A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics

    math.ST 2019-08 conditional novelty 7.0 of 10

    Markov categories provide a synthetic, axiom-based framework in which conditional independence, sufficiency, completeness, and classical theorems such as Basu and Bahadur hold uniformly across many probability theories.

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