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Entropy2016,18, 433 Those categories are canonically equivalent. Further theactions thegroupGin those categories lead to the samemoduli space m= GM(Ξ,Ω) G = FB(MSE) G . Werephrase the theoremonmoduli space. Theorem21. The functor [E,p]→ qp∈BF(M) parametrizes themoduli spacem. Thisends thechallenge2. 10.TheHomologicalStatisticalModels In this section we introduce the theory of homological statistical models (HSM in short). Weaddress the linksbetweenthis theoryandthe local theoryas in [17]. The theory of homological statistical models is useful for strengthening the central role played by the theory of KV homology in the information geometry and in the topology of the information[14,16–18,22,30,37,60,61]. We introduce the theoryof localizationofhomologicalmodels. Weuse it tohighlight the role playedbylocal cohomologicalvanishingtheoremsaswellas theroleplayedbyglobalcohomological vanishingtheorems. Theframework is thecategoryFB(Γ,Ξ). Let [E,π,M,D]beanm-dimensionalobjectof thecategoryFB(Γ,Ξ), vizm= dim(M). TheKV algebra of (M,D) is denoted byA. The smoothmanifoldRm supports a sheaf ofKValgebras A˜. This sheaf is locally isomorphic toA. ThevectorspaceC∞(Rm) isa leftmoduleof A˜. Theaffineaction ofΓ inRm is A˜-preserving. Let (U,ΦU×φU) be a local chart of [E,π,M,D]. We recall that dφU is the differential of φU. Wehave dφU(A)= A˜(φU(U)). Definition61. Ahomologicalmodel consists of the following data. The datum [E,π,M,D] is an object of the categoryFB(Γ,Ξ). Every x ∈Mhas an openneighborhoodUwhich is the domain of a local chart of [E,π,M,D], namely (ΦU×φU).Weset ΘU×Ξ=ΦU(EU). Thosedataare subject to the followingrequirements. HSM.1 :Θ×Ξ supports anonnegative randomsymmetric2-cocycle ΘU×Ξ (θ,ξ)→QU(θ,ξ)∈Z2KV(A˜,R). HSM.2 :Let [U,ΦU×φU,QU]and [U∗,ΦU∗×φU∗,QU∗]as inHSM.1. Ifweassumethat U∩U∗ =∅ then there existsγUU∗ ∈Γ such that HSM.2.1 ΦU∗(e)=γUU∗ ·ΦU(e) ∀e∈EU∩U∗, HSM.2.2 QU(ΦU(e))=γ∗UU∗ · [QU∗(ΦU∗(e))]. 221
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Differential Geometrical Theory of Statistics
Titel
Differential Geometrical Theory of Statistics
Autoren
Frédéric Barbaresco
Frank Nielsen
Herausgeber
MDPI
Ort
Basel
Datum
2017
Sprache
englisch
Lizenz
CC BY-NC-ND 4.0
ISBN
978-3-03842-425-3
Abmessungen
17.0 x 24.4 cm
Seiten
476
Schlagwörter
Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
Kategorien
Naturwissenschaften Physik
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Differential Geometrical Theory of Statistics