Web-Books
im Austria-Forum
Austria-Forum
Web-Books
Naturwissenschaften
Physik
Differential Geometrical Theory of Statistics
Seite - 406 -
  • Benutzer
  • Version
    • Vollversion
    • Textversion
  • Sprache
    • Deutsch
    • English - Englisch

Seite - 406 - in Differential Geometrical Theory of Statistics

Bild der Seite - 406 -

Bild der Seite - 406 - in Differential Geometrical Theory of Statistics

Text der Seite - 406 -

Entropy2016,18, 425 Euclideanspace. Thedistance is thusweightedby theanisotropyofu, andu canbe interpretedas asquarerootcovariancematrixÎŁ1/2. However, the above approachdoesnot specifyhowu changeswhenmoving away from the basepoint x0. TheuseofLogx0x effectively linearises thegeometryaround x0, butageometrically naturalwaytorelateuatpointsnearbytox0willbe toparallel transport it, equivalentlyspecifying thatuwhentransporteddoesnotchangeasmeasuredfromthecurvedgeometry. Thisconstraint is nonholonomic, andit implies thatanypathfromx0 tox carrieswith itaparallel transportofu lifting paths fromM topaths in the framebundleFM. It thereforebecomesnatural toequipFMwitha form ofmetric thatencodestheanisotropyrepresentedbyu. Theresult is thesub-RiemannianmetriconFM deïŹnedbelowthatweights inïŹnitesimalmovementsonMusingtheparallel transportof the frameu. Optimalpaths for thismetricaresub-Riemanniangeodesicsgiving the familyofmostprobablepaths for thedrivingprocess that thispaperconcerns. Figure1showsonesuchpathforananisotropicnormal distributionwithManellipsoidembeddedinR3. 2. FrameBundles,StochasticDevelopment,andAnisotropicDiffusions LetMbeaïŹnitedimensionalmanifoldofdimensiondwithconnectionC, andletx0 beaïŹxed point inM.WhenaRiemannianmetric ispresent,andC is itsLevi–Civitaconnection,wedenote the metricgR. Foragiven interval [0,T],we letW(M)denote theWienerspaceofcontinuouspaths inM startingatx0. Similarly,W(Rd) is theWienerspaceofpaths inRd.WeletH(Rd)denote thesubspace ofW(Rd)ofïŹniteenergypaths. Let now u = (u1, . . . ,ud) be a frame for TxM, x ∈ M; i.e., u1, . . . ,ud is an ordered set of linearly independent vectors in TxM with span{u1, . . . ,ud} = TxM. We can regard the frame as an isomorphismu :Rd → TxMwithu(ei) = ui,where e1, . . . ,ed denotes the standardbasis inRd. Stochasticdevelopment (e.g., [4])providesan invertiblemapϕu fromW(Rd) toW(M). Throughϕu, Euclidean semi-martingales map to stochastic processes on M. When M is Riemannian and u orthonormal, theresult is theEells–Elworthy–MalliavinconstructionofBrownianmotion[17].Wehere outline thegeometrybehinddevelopment, stochasticdevelopment, theconnection, andcurvature, focusing inparticularonframebundlegeometry. 2.1. TheFrameBundle For eachpoint x ∈ M, let FxMbe the set of frames forTxM (i.e., the set of orderedbases for TxM). Theset{FxM}x∈M canbegivenanaturaldifferential structureasaïŹberbundleonM called the framebundleFM. It canequivalentlybedeïŹnedas theprincipalbundleGL(Rd,TM).Welet the mapπ :FM→Mdenote thecanonicalprojection. Thekernelofπ∗ :TFM→TM is thesub-bundle ofTFM thatconsistsofvectors tangent to theïŹbersπ−1(x). It isdenotedthevertical subspaceVFM. Wewilloftenwork ina local trivializationu=(x,u1, . . . ,ud)∈FM,wherex=π(u)∈Mdenotes the basepoint,andforeach i=1,. . . ,d,ui∈TxM is the ith framevector. Forv∈TxMandu∈FMwith π(u)= x, thevectoru−1v∈Rd expressesv incomponents in termsof the frameu.Wewilldenote the vectoru−1v framecoordinatesofv. Foradifferentiable curve xt inMwith x= x0, a frameu forTx0M canbeparallel transported along xt by parallel transporting each vector in the frame, thus giving a path ut ∈ FM. Such paths are calledhorizontal, andhave zero acceleration in the sense C(u˙i,t) = 0. For each x ∈ M, their derivatives form a d-dimensional subspace of the d+d2-dimensional tangent space TuFM. Thishorizontal subspaceHFMandthevertical subspaceVFM togethersplit the tangentbundleof FM (i.e.,TFM=HFM⊕VFM). Thesplit inducesamapπ∗ : HFM→TM, seeFigure3. ForïŹxed u∈FM, therestrictionπ∗|HuFM :HuFM→TxM isanisomorphism. Its inverseiscalledthehorizontal lift and isdenotedhu in the following. Usinghu, horizontalvectorïŹeldsHe onFMaredeïŹnedfor vectors e∈RdbyHe(u)= hu(ue). Inparticular, thestandardbasis (e1, . . . ,ed)onRdgivesdglobally deïŹnedhorizontal vector ïŹelds Hi ∈ HFM, i = 1,. . . ,dby Hi = Hei. Intuitively, theïŹelds Hi(u) model inïŹnitesimal transformations inMofx0 indirectionui=ueiwithcorresponding inïŹnitesimal 406
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
Kategorien
Naturwissenschaften Physik
Web-Books
Bibliothek
Datenschutz
Impressum
Austria-Forum
Austria-Forum
Web-Books
Differential Geometrical Theory of Statistics