The non-parametric version of Information Geometry has been developed in recent years. The first basic result was the construction of the manifold structure on M-mu the maximal statistical models associated to an arbitrary measure mu (see Ref. 48). Using this construction we first show in this paper that the pretangent and the tangent bundles on M-mu are the natural domains for the mixture connection and for its dual, the exponential connection. Second we show how to define a generalized Amari embedding A(Phi): M-mu --> S-Phi from the Exponential Statistical Manifold (ESM) M-mu to the unit sphere S-Phi of an arbitrary Orlicz space L-Phi. Finally we show that, in the non-parametric case, the cr-connections del(alpha) (alpha is an element of ...
Statistical manifolds are representations of smooth families of probability density functions that a...
Divergence functions are the non-symmetric “distance” on the manifold, Μθ, of parametric probability...
Statistical manifolds are representations of smooth families of probability density functions that a...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Statistical manifolds are representations of smooth families of probability density functions (ie su...
For the family of non-parametric q-exponential statistical models, in a former paper, written by the...
We develop a family of infinite-dimensional (non-parametric) manifolds of probability measures. The...
Statistical manifolds are representations of smooth families of probability density functions that a...
Divergence functions are the non-symmetric “distance” on the manifold, Μθ, of parametric probability...
Statistical manifolds are representations of smooth families of probability density functions that a...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
The non-parametric version of Information Geometry has been developed in recent years. The first bas...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Let N be a statistical manifold of density operators, with respect to an n.s.f. trace tau on a semif...
Statistical manifolds are representations of smooth families of probability density functions (ie su...
For the family of non-parametric q-exponential statistical models, in a former paper, written by the...
We develop a family of infinite-dimensional (non-parametric) manifolds of probability measures. The...
Statistical manifolds are representations of smooth families of probability density functions that a...
Divergence functions are the non-symmetric “distance” on the manifold, Μθ, of parametric probability...
Statistical manifolds are representations of smooth families of probability density functions that a...