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Entropy2016,18, 433 Weintendto face the followingchallenges. Challenge1. Revisit the theoryofgeometric statisticalmodels formeasurablesets. Challenge2. TheSearch forageometric characteristic invariant for statisticalmodels.Werecall that suchan invariantwill encode thepoints themoduli spaceofmodels. Before continuingwe recall somedefinitions. Definition42. Ageometric invariantof amodel for (Ξ,Ω) is adatumwhich is invariantunder theactionof the symmetrygroupAut(Ξ,Ω). Theframeworkwhich isuseful for re-establishingthe theoryofstatisticalmodels is thecategory of locally trivialfiberbundles. Aswehavementionedtheneedfor introducinganewtheoryofstatisticalmodelemerges from somecriticisms.Werecall thedefinitionastatisticalmodel [18,22,24]. Definition43. Anm-dimensional statisticalmodel for ameasurable set (Ξ,Ω) is a pair (Θ,P)having the propertieswhich follow. (1) ThemanifoldΘ is anopensubset of them-dimensionalEuclideanspaceRm. (2) P is apositive realvalued function Θ×Ξ (θ,ξ)→P(θ,ξ)∈R subject to the requirementswhich follow. (3) The functionP(θ,ξ) isdifferentiablewith respect toθ∈Θ. (4) For everyfixedθ∈Θoneset Pθ=P(θ,−) then the triple (Ξ,Ω,Pθ) is aprobability space, viz ∫ Ξ Pθ(ξ)dξ=1 Furthermore theoperationofdifferentiation dθ= d dθ commuteswith theoperationof integration ∫ Ξ. (5) (Θ,P) is identifiable, viz forθ,θ∗ ∈Θ Pθ=Pθ∗ if andonly if θ= θ∗ (6) TheFisher information gθ(X,Y)= ∫ Ξ P(θ,ξ)[dθlog(P(θ,ξ))]⊗2(X,Y)dξ ispositivedefinite. SomeCriticisms. TheFirstCritique 200
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Differential Geometrical Theory of Statistics
Title
Differential Geometrical Theory of Statistics
Authors
Frédéric Barbaresco
Frank Nielsen
Editor
MDPI
Location
Basel
Date
2017
Language
English
License
CC BY-NC-ND 4.0
ISBN
978-3-03842-425-3
Size
17.0 x 24.4 cm
Pages
476
Keywords
Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
Categories
Naturwissenschaften Physik
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Differential Geometrical Theory of Statistics