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Entropy2017,19, 7 Bydifferentiatingtheaboveequation,wecandefinemutuallydual torsion-freeaffineconnections ∇M(e) and∇M(m): ΓM(e)ij,k (θ) := ∫ Ω (∂i∂j lnq pθ)(∂kpθ)dx, ΓM(m)ij,k (θ) := ∫ Ω (∂k lnq pθ)(∂i∂jpθ)dx, whereΓM(e)ij,k andΓ M(m) ij,k are theChristoffel symbolsof∇M(e) and∇M(m)of thefirstkind, respectively. It is known that gM is aHessianmetric, and thequadruplet (Sq,gM,∇M(e),∇M(m)) is aduallyflat space. Inaddition,anaturalparameter{θi} isa∇M(e)-affinecoordinatesysem.Therefore, thecubic formfor (Sq,∇M(e),gM) is CMijk(θ)=Γ M(m) ij,k (θ). (19) We remark that the statistical manifold structure (Sq,∇M(e),gM) is induced from a β-divergence [17,26] (oradensitypowerdivergence [27]): D1−q(p,r) := ∫ Ω { p(x) p(x)1−q−r(x)1−q 1−q − p(x)2−q−r(x)2−q 2−q } dx. (20) Theorem3. Forthestatisticalmanifoldstructure(Sq,∇M(e),gM), theescortrepresentationsoftheRiemannian metric gM andthe cubic formCM aregivenas follows: gMij (θ) = ∫ Ω (∂i lnq pθ)(∂j lnq pθ)Pq(x;θ)dx, (21) CMijk(θ) = ∫ Ω (∂i lnq pθ)(∂j lnq pθ)(∂k lnq pθ)P˜q(x;θ)dx. (22) Proof. For the Riemannian metric gM, since ∂ipθ = (∂i lnq pθ)Pq(x;θ), we immediately obtain Equation(21) fromthedefinitionofgM. Letusconsider theexpressionforcubic form(22). Theq-score function∂i lnq pθ isunbiasedunder theq-expectation. In fact, Eq,p[∂i lnq pθ]= ∫ Ω (∂j lnq pθ)Pq(x;θ)dx= ∫ Ω ∂jpθdx=0. FromEquation(19),weobtain CMijk(θ) = Γ M(m) ij,k (x;θ) = ∫ Ω (∂k lnq pθ)(∂i∂jpθ)dx = ∫ Ω (∂k lnq pθ)∂i {( ∂j lnq pθ ) Pq(x;θ) } dx = −∂ijψ(θ) ∫ Ω (∂k lnq pθ)Pq(x;θ)dx+ ∫ Ω (∂k lnq pθ)(∂j lnq pθ){∂iPq(x;θ)}dx = ∫ Ω (∂k lnq pθ)(∂j lnq pθ)(∂i lnq pθ)P˜q(x;θ)dx. WeremarkthatNaudts [5]gaveanothergeneralizationofFishermetricgN,which isdefinedby gNij (θ) := ∫ Ω 1 Pescq (x;θ) (∂ipθ)(∂jpθ)dx, 321
zurĂźck zum  Buch Differential Geometrical Theory of Statistics"
Differential Geometrical Theory of Statistics
Titel
Differential Geometrical Theory of Statistics
Autoren
FrĂŠdĂŠric 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
SchlagwĂśrter
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