Seite - 406 - in Differential Geometrical Theory of Statistics
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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
deïŹnedbelowthatweights inïŹnitesimalmovementsonMusingtheparallel transportof the frameu.
Optimalpaths for thismetricaresub-Riemanniangeodesicsgiving the familyofmostprobablepaths for
thedrivingprocess that thispaperconcerns. Figure1showsonesuchpathforananisotropicnormal
distributionwithManellipsoidembeddedinR3.
2. FrameBundles,StochasticDevelopment,andAnisotropicDiffusions
LetMbeaïŹnitedimensionalmanifoldofdimensiondwithconnectionC, andletx0 beaïŹxed
point inM.WhenaRiemannianmetric ispresent,andC is itsLeviâCivitaconnection,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)ofïŹniteenergypaths.
Let now u = (u1, . . . ,ud) be a frame for TxM, x â 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 â TxMwithu(ei) = ui,where e1, . . . ,ed denotes the standardbasis inRd.
Stochasticdevelopment (e.g., [4])providesan invertiblemapÏu fromW(Rd) toW(M). ThroughÏu,
Euclidean semi-martingales map to stochastic processes on M. When M is Riemannian and u
orthonormal, theresult is theEellsâElworthyâMalliavinconstructionofBrownianmotion[17].Wehere
outline thegeometrybehinddevelopment, stochasticdevelopment, theconnection, andcurvature,
focusing inparticularonframebundlegeometry.
2.1. TheFrameBundle
For eachpoint x â M, let FxMbe the set of frames forTxM (i.e., the set of orderedbases for
TxM). Theset{FxM}xâM canbegivenanaturaldifferential structureasaïŹberbundleonM called
the framebundleFM. It canequivalentlybedeïŹnedas theprincipalbundleGL(Rd,TM).Welet the
mapÏ :FMâMdenote thecanonicalprojection. ThekernelofÏâ :TFMâTM is thesub-bundle
ofTFM thatconsistsofvectors tangent to theïŹbersÏâ1(x). It isdenotedthevertical subspaceVFM.
Wewilloftenwork ina local trivializationu=(x,u1, . . . ,ud)âFM,wherex=Ï(u)âMdenotes the
basepoint,andforeach i=1,. . . ,d,uiâTxM is the ith framevector. ForvâTxManduâFMwith
Ï(u)= x, thevectoruâ1vâRd expressesv incomponents in termsof the frameu.Wewilldenote the
vectoruâ1v 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 â FM. Such
paths are calledhorizontal, andhave zero acceleration in the sense C(uËi,t) = 0. For each x â 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=HFMâVFM). Thesplit inducesamapÏâ : HFMâTM, seeFigure3. ForïŹxed
uâFM, therestrictionÏâ|HuFM :HuFMâTxM isanisomorphism. Its inverseiscalledthehorizontal
lift and isdenotedhu in the following. Usinghu, horizontalvectorïŹeldsHe onFMaredeïŹnedfor
vectors eâRdbyHe(u)= hu(ue). Inparticular, thestandardbasis (e1, . . . ,ed)onRdgivesdglobally
deïŹnedhorizontal vector ïŹelds Hi â HFM, i = 1,. . . ,dby Hi = Hei. Intuitively, theïŹelds Hi(u)
model inïŹnitesimal transformations inMofx0 indirectionui=ueiwithcorresponding inïŹnitesimal
406
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