REVIEW 1 cited by
Functional distribution monads in functional-analytic contexts
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
Signed reviews
abstract
We give a general categorical construction that yields several monads of measures and distributions as special cases, alongside several monads of filters. The construction takes place within a categorical setting for generalized functional analysis, called a $\textit{functional-analytic context}$, formulated in terms of a given monad or algebraic theory $\mathcal{T}$ enriched in a closed category $\mathcal{V}$. By employing the notion of $\textit{commutant}$ for enriched algebraic theories and monads, we define the $\textit{functional distribution monad}$ associated to a given functional-analytic context. We establish certain general classes of examples of functional-analytic contexts in cartesian closed categories $\mathcal{V}$, wherein $\mathcal{T}$ is the theory of $R$-modules or $R$-affine spaces for a given ring or rig $R$ in $\mathcal{V}$, or the theory of $\textit{$R$-convex spaces}$ for a given preordered ring $R$ in $\mathcal{V}$. We prove theorems characterizing the functional distribution monads in these contexts, and on this basis we establish several specific examples of functional distribution monads.
Forward citations
Cited by 1 Pith paper
-
A synthetic approach to Markov kernels, conditional independence and theorems on sufficient statistics
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.
Discussion (0). Continue with ORCID to comment.