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Differential Geometrical Theory of Statistics
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Entropy2016,18, 425 Letnowutbeapath inFM, andchoosea local trivializationut=(xt,u1,t, . . . ,ud,t) suchthat the matrix [uiα,t] represents thesquarerootcovariancematrixÎŁ 1/2 atxt. SinceutbeingaframedeïŹnesan invertiblemapRd→TxtM, thenorm‖·‖Σ abovehasadirectanalogue in thenorm‖·‖ut deïŹnedby the innerproduct 〈v,w〉ut = 〈 u−1t v,u −1 t w âŒȘ Rd (5) forvectorsv,w∈TxtM. The transportof the framealongpaths ineffectdeïŹnesa transportof inner productalongsamplepaths: thepathscarrywith themthe innerproductweightedbytheprecision matrix,which in turn isa transportof thesquarerootcovarianceu0 atx0. The innerproductcanequivalentlybedeïŹnedasametricgu :T∗xM→TxM. Againusing that u can be considered amapRd → TxM, gu is deïŹned by Ο → u(Ο◊u) , where is the standard identiïŹcation (Rd)∗→Rd. ThesequenceofmappingsdeïŹninggu is illustratedbelow: T∗xM → (Rd)∗ → Rd → TxM Ο → Ο◊u → (Ο◊u) → u(Ο◊u) . (6) ThisdeïŹnitionuses theRd innerproduct in thedeïŹnitionof . Its inversegives the cometric g−1u :TxM→T∗xM; i.e.,v → (u−1v) ◩u−1. TxM → Rd → (Rd)∗ → T∗xM v → u−1v → (u−1) → (u−1) ◩u−1. (7) 3.1. Sub-RiemannianMetric on theHorizontalDistribution Wenow lift the path-dependentmetric deïŹned above to a sub-Riemannianmetric on HFM. Foranyw,w˜∈HuFM, the liftof (5)byπ∗ is the innerproduct 〈w,w˜〉= 〈 u−1π∗w,u−1π∗w˜ âŒȘ Rd . The innerproduct inducesasub-RiemannianmetricgFM :TFM∗→HFM⊂TFMby 〈w,gFM(Ο)〉=(Ο|w) , ∀w∈HuFM (8) with (Ο|w)denoting the evaluation Ο(w) for the covector Ο ∈ T∗FM. The metric gFM gives FM a non-bracket-generating sub-Riemannian structure [23] on FM (see also Figure 3). It is equivalent to the lift Ο → hu(gu(Ο◊hu)) , Ο∈TuFM (9) of themetricgu above. In framecoordinates, themetric takes the form u−1π∗gFM(Ο)= ⎛⎜⎝Ο(H1(u))... Ο(Hd(u)) ⎞⎟⎠ . (10) In terms of the adapted coordinates for TFM described in Section 2.3, with w = wjDj and w˜= w˜jDj,wehave 〈w,w˜〉= 〈 wiDi,w˜jDj âŒȘ = 〈 u−1wi∂xi,u −1w˜j∂xj âŒȘ = 〈 wiuαi ,w˜ juαj âŒȘ Rd = ΎαÎČwiuαi w˜ juÎČj =Wijw iw˜j 410
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