Seite - 316 - in Differential Geometrical Theory of Statistics
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Entropy2017,19, 7
Sinceadifferentialofapower function isalsoapower function,wecangiveacharacterization
forescortdistributions.
Proposition1. Suppose that Sq is a q-exponential family defined by (1). Then the n-th escort distribution
is givenby the n-th differential of q-exponential function. That is, by settingu(t) = (expq t) ′,wehave the
following formula:
pq(x;θ) = expq (
n
∑
i=1 θiFi(x)−ψ(θ) )
,
Pq(x;θ)=Pq,(1)(x;θ) = u (
n
∑
i=1 θiFi(x)−ψ(θ) )
,
P˜q(x;θ)=Pq,(2)(x;θ) = u ′ (
n
∑
i=1 θiFi(x)−ψ(θ) )
,
... ...
Pq,(n)(x;θ) = u (n−1) (
n
∑
i=1 θiFi(x)−ψ(θ) )
,
... ...
Proof. Sinceaq-exponential function isexpq(x)=(1+(1−q))1/(1−q), itsdifferential isgivenby
u(x)= 1−q
1−q(1+(1−q)x) 1
1−q−1=(1+(1−q)x) q
1−q ={expq x}q.
Therefore,weobtainPq(x;θ)=u ( ∑ni=1θ iFi(x)−ψ(θ) )
.
Byinduction, then-thdifferentialofu(x)coincideswiththen-thescortdistributionPq,(n),whichis
givenbyEquation(5).
4. StatisticalManifoldsandTheirGeneralizedConformalStructures
In this section,weus reviewthegeometryof statisticalmanifolds. Formoredetails about the
geometryofstatisticalmanifolds, see [18,19].
Let (S,g)beaRiemannianmanifoldand∇beatorsion-freeaffineconnectiononS.Wesaythat
thetriplet (S,∇,g) isa statisticalmanifold if∇g is totallysymmetric. In thiscase,wecandefineatotally
symmetric (0,3)-tensorfieldby
C(X,Y,Z) :=(∇Xg)(Y,Z) = Xg(Y,Z)−g(∇XY,Z)−g(Y,∇XZ),
where X,Y and Z are arbitrary vector fields on S. The tensor field C is called a cubic form or an
Amari–Chentsov tensorfield.
Thenotionofstatisticalmanifoldwas introducedbyLauritzen[20].Hecalled the triplet (S,g,C)
a statisticalmanifold. In this paper, the definition is followed toKurose [18]. Though these two
definitions aredifferent, theother statisticalmanifold structure canbeobtained fromagivenone,
However, themotivationfor thenotionofconformalequivalenceusing (S,g,C) isdifferent fromthat
oneusing (S,∇,g),whichwewilldiscuss in the latterpartof this section.
Foragivenstatisticalmanifold (S,∇,g),wecandefineanother torsion-freeaffineconnection∇∗
onSby
Xg(Y,Z)= g(∇XY,Z)+g(Y,∇∗XZ).
316
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