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Entropy2016,18, 407 andthen ∂g ∂α (β,λ)= 1 2 ∫ T [ϕ−1(q)−ϕ−1(p)]ϕ′(cβ+λu0)dμ. (20) Forβ∈ (α0,α1)andλ∈ (0,κ0), the function inside the integral sign in (20) isdominatedby f. Asaresult,aseconduseof theDominatedConvergenceTheoremshowsthat ∂g∂α iscontinuousat (α,κ): lim (β,λ)→(α,κ) ∂g ∂α (β,λ)= ∂g ∂α (α,κ). Usingsimilararguments,onecanshowthat ∂g∂κ(α,κ)existsandiscontinuousatanyα∈ (α0,α1) andκ>0,andisgivenby ∂g ∂κ (α,κ)= ∫ T u0ϕ′(cα+κu0)dμ. (21) Clearly,expression(21) implies that ∂g∂κ(α,κ)>0 forallα∈ (0,α0)andκ>0. Weprovedthat items(i)–(iii) aresatisfied.Asconsequence, thederivativeofκ(α)existsatany α∈ (α0,α1). Expression(16) for thederivativeofκ(α) followsfrom(17), (20)and(21). Asan immediateconsequenceofLemma2,weget thepropositionbelow. Proposition1. Assumethat ϕ(·) is continuouslydifferentiable. (a) If, for someα0<−1, expression (15) is satisfied forallα∈ [α0,−1), then D(−1)ϕ (p‖ q)= lim α↓−1 D(α)ϕ (p‖ q)=2∂κ∂α(−1)=Dϕ(p‖ q)<∞. (b) If, for someα1>1, expression (15) is satisfied forallα∈ (1,α1], then D(1)ϕ (p‖ q)= lim α↑1 D(α)ϕ (p‖ q)=−2∂κ∂α(1)=Dϕ(q‖ p)<∞. 4.GeneralizedStatisticalManifolds Statisticalmanifoldsconsistofacollectionofprobabilitydistributionsendowedwithametric andα-connections,whicharedefinedin termsof thederivativeof l(t;θ)= logp(t;θ). Inageneralized statisticalmanifold, themetricandconnectionaredefinedintermsof f(t;θ)= ϕ−1(p(t;θ)). Instead of the logarithm,weconsider the inverse ϕ−1(·)of a ϕ-function. Generalizedstatisticalmanifolds were introducedbytheauthors in [17,18]. Amongexamplesof thegeneralizedstatisticalmanifold, (parametric)ϕ-familiesofprobabilitydistributionsareofgreatest importance. Thenon-parametric counterpartwas investigated in [11,12]. Themetric inϕ-familiescanbedefinedas theHessianofa function; i.e., ϕ-familiesareHessianmanifolds [30]. In [17,18], the ϕ-divergencegives rise toapair ofdualconnectionsD(−1) andD(1); andthenforα∈ (−1,1) theα-connectionD(α) isdefinedas the convexcombinationD(α) = 1−α2 D (−1)+ 1+α2 D (1). In thepresentpaper,weshowthat theconnection inducedbyD(α)ϕ (· ‖ ·), thegeneralizationofRényidivergence, corresponds toD(α). 4.1.Definitions Let ϕ:R→ (0,∞)bea ϕ-function. Ageneralized statisticalmanifoldP= {p(t;θ) : θ ∈Θ} is a collectionofprobabilitydistributions pθ(t) := p(t;θ), indexedbyparametersθ=(θ1, . . . ,θn)∈Θ in aone-to-onerelation, suchthat (m1) Θ isadomain(openandconnectedset) inRn; (m2) p(t;θ) isdifferentiablewithrespect toθ; 278
zurück zum  Buch Differential Geometrical Theory of Statistics"
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
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Differential Geometrical Theory of Statistics