Categorical Probability Theory
Kirk Sturtz
Abstract
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Kirk Sturtz
Abstract
Open-access reader
We present a categorical viewpoint of probability measures by showing that a probability measure can be viewed as a weakly averaging affine measurable functional taking values in the unit interval which preserves limits. The probability measures on a space are the elements of a submonad of a double dualization monad on the category of measurable spaces into the unit interval, and this monad is naturally isomorphic to the Giry monad. We show this submonad is the codensity monad of a functor from the category of convex spaces to the category of measurable spaces. A theorem proving the integral operator acting on the space of measurable functions and the space of probability measures on the domain space of those functions is given using the strong monad structure of the Giry monad.
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We present a categorical viewpoint of probability measures by showing that a probability measure can be viewed as a weakly averaging affine measurable functional taking values in the unit interval which preserves limits. The probability measures on a space are the elements of a submonad of a double dualization monad on the category of measurable spaces into the unit interval, and this monad is naturally isomorphic to the Giry monad. We show this submonad is the codensity monad of a functor from the category of convex spaces to the category of measurable spaces. A theorem proving the integral operator acting on the space of measurable functions and the space of probability measures on the domain space of those functions is given using the strong monad structure of the Giry monad.
Key concepts: Monad (category theory), Probability measure, Mathematics, Unit interval, Functor, Categorical variable, Pure mathematics, Space (punctuation)