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Differential Geometrical Theory of Statistics
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Entropy2016,18, 386 Wewrite f the linear representationofLiealgebragofG,deïŹnedby fandq therestriction togof thedifferential toq (f andq thedifferentialof fandq respectively),Koszulhasprovedthat: f(X)q(Y)− f(Y)q(X)= q([X,Y]) ∀X,Y∈ g with f : g→ gl(E)andq : g →E (103) wheregl(E) thesetofall linearendomorphismsofE, theLiealgebraofGL(E). Usingthecomputation, q(AdsY)= dq(s ·etY ·s−1) dt ∣∣∣∣ t=0 = f(s)f(Y)q(s−1)+f(s)q(Y) (104) Wecanobtain: q([X,Y])= dq(AdetXY) dt ∣∣∣∣ t=0 = f(X)q(Y)q(e)+f(e)f(Y)(−q(X))+ f(X)q(Y) (105) where e is theunitelement inG. Since f(e) is the identitymappingandq(e)=0,wehave theequality: f(X)q(Y)− f(Y)q(X)= q([X,Y]) . Apair (f,q)ofa linearrepresentation f ofaLiealgebragonEanda linearmappingq fromg toE isanafïŹnerepresentationofgonE, if it satisïŹes f(X)q(Y)− f(Y)q(X)= q([X,Y]) . Conversely, if we assume that g admits an afïŹne representation (f,q) on E, using an afïŹne coordinate system { x1,...,xn } on E, we can express an afïŹnemapping v → f(X)v+q(Y) by an (n+1)×(n+1)matrixrepresentation: af f(X)= [ f(X) q(X) 0 0 ] (106) where f(X) isan×nmatrixandq(X) isan rowvector. X → af f(X) isan injectiveLiealgebrahomomorphismfromg in theLiealgebraofall (n+1)× (n+1)matrices,gl(n+1,R): ∣∣∣∣∣ g→ gl(n+1,R)X → af f(X) (107) Ifwedenotegaf f = af f(g),wewriteGaf f the linearLiesubgroupofGL(n+1,R)generatedby gaf f . Anelementof s∈Gaf f isexpressedby: Af f(s)= [ f(s) q(s) 0 1 ] (108) LetMaf f be the orbit ofGaf f through the origin o, thenMaf f = q(Gaf f) = Gaf f/Kaf f where Kaf f = { s∈Gaf f/q(s)=0 } =Ker(q). Example.LetΩbeaconvexdomain inRn containingnocompletestraight lines,wedeïŹneaconvex coneV(Ω) inRn+1 = Rn×RbyV(Ω) = {(λx,x)∈Rn×R/x∈Ω,λ∈R+}. Then there exists an afïŹneembedding: : x∈Ω → [ x 1 ] ∈V(Ω) (109) 76
zurĂŒck 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