Page - 217 - in Differential Geometrical Theory of Statistics
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Entropy2016,18, 433
(4) thecategoryF(LC,BF)whoseobjectsare functors
GMāBF.
Deļ¬nition60. TheHessian functor is the functor
GM M=[E,Ļ,M,D,p]ā qMāF(LC,BL)
HereqM isdeļ¬nedby
qM[ā]=ā2log(p).
Reminder.
Werecall that forvectorļ¬eldsX,Ythebilinear formqM[ā](X,Y) isdeļ¬nedby
qM[ā](X,Y)=X Ā·(Y Ā· log(p))āāXY Ā· log(p)
ThefunctorqM is calledtheHessianfunctorof themodel
M=[E,Ļ,M,D,p].
Ouraimistodemonstratethefollowingclaim.UptoisomorphismastatisticalmodelM isdeļ¬ned
byitsHessianfunctorqM. The functorqM isansigniļ¬cantcontributionto the informationgeometry.
We ļ¬x an object ofFB(Ī,Ī), namely [E,Ļ,M,D]. LetP(E) be the convex set of probability
densities in [E,Ļ,M,D]. Themultiplicativegroupofpositive real valued functionsdeļ¬ned inĪ is
denotedbyRĪ+. ThequotientofP(E)moduloRĪ+ isdenotedby
PRO(E)=P(E)
RĪ+ .
Lemma6. Forevery pāP(E) the imageof
M=[E,p],
namelyqMdependsonlyon the class [p]āPRO(E)
Proof. Weconsider
M=[E,Ļ,M,D,p],
M
ā=[E,Ļ,M,D,pā].
Weassumethat
qM= qMā.
Thus inevery local trivializationĪUĆĪonehas the identity
X(Ylog( pā(x,ξ)
p(x,ξ) )āāXYlog(p ā(x,ξ)
p(x,ξ) ))=0
forallX,YāĪ(TĪ), forallāāLC(Ī). That identityholds ifandonly if the function
(x,ξ)ā p ā(x,ξ)
p(x,ξ)
belongs toRĪ+. Thisends the idea.
217
Differential Geometrical Theory of Statistics
- Title
- Differential Geometrical Theory of Statistics
- Authors
- FrƩdƩric Barbaresco
- Frank Nielsen
- Editor
- MDPI
- Location
- Basel
- Date
- 2017
- Language
- English
- License
- CC BY-NC-ND 4.0
- ISBN
- 978-3-03842-425-3
- Size
- 17.0 x 24.4 cm
- Pages
- 476
- Keywords
- Entropy, Coding Theory, Maximum entropy, Information geometry, Computational Information Geometry, Hessian Geometry, Divergence Geometry, Information topology, Cohomology, Shape Space, Statistical physics, Thermodynamics
- Categories
- Naturwissenschaften Physik