Neighbourhoods of Independence for Random Processes via Information Geometry
Khadiga Arwini
C. T. J. Dodson
2. Submanifolds of the Freund 4-Manifold F
We consider four submanifolds
of the 4-manifold F of Freund bivariate exponential distributions (1)
, which includes the case of statistically independent random variables. It also includes the special case of an Absolutely Continuous Bivariate Exponential Distribution called ACBED (or ACBVE) by Block and Basu (compare Hutchinson and Lai [10]). We use the coordinate system
for the submanifolds
,
and the coordinate system
for ACBED of the Block and Basu case.
2.1. Submanifold
and 
The distributions are of the form:
where
are the density functions of the one-dimensional exponential distributions with the parameters
. This is the case for statistical independence of X and Y, so the space
is the direct product of two Riemannian spaces:
and
Proposition 2.1 The Fisher information metric
is given by
Proposition 2.2 The components of
are given by
while the other components are zero.
Proposition 2.3 The
-curvature tensor,
-Ricci tensor, and
-scalar curvature of
are zero.
2.2. Submanifold
and 
The distributions are of the form:
with parameters
. The covariance, correlation coefficient, and marginal functions of
and
are given by
Note that
when
.
forms an exponential family, with natural parameters
and the potential function
Proposition 2.4 The submanifold
is an isometric diffeomorph of the submanifold
.
Proof: Since
is a potential function, the Fisher information metric is given by the Hessian of
, that is,
Then we have the Fisher information metric (10) by a straightforward calculation.
2.2.1 Mutually Dual Foliations
Since
,
is a
-affine coordinate system, and the
-affine coordinate system is given by
These coordinates have the potential function
So the coordinates
and
are mutually dual with respect to the Fisher metric, and the tetrad
is a dually flat space. Therefore,
has dually orthogonal foliations.
For example, take
as a coordinate system for
; then
and the Fisher information metric is
2.2.2 Neighbourhoods of Independence in
An important practical application of the Freund submanifold
is the representation of a bivariate stochastic process for which the marginals are identical exponentials. The next result is important because it provides a topological neighbourhood of that subspace W in
consisting of the bivariate processes that have zero covariance: we obtain a neighbourhood of independence for random, that is, exponentially distributed processes.
Proposition 2.5 Let
be the manifold
with Fisher metric
and exponential connection
. Then
can be realized in
by the graph of a potential function, namely,
can be realized by the affine immersion 
where
and
is the transversal vector field along
.
In
, the submanifold W consisting of the independent case
is represented by the curve
This is illustrated in the graphic that shows
, an affine embedding of
as a surface in
, and
an
-tubular neighbourhood of W, as the curve
in the surface. This curve represents all bivariate distributions having identical exponential marginals and zero covariance; its tubular neighbourhood represents departures from independence. We parametrize here with
,
.
2.3. Submanifold 
The distributions are of the form:
with parameters
,
. The covariance, correlation coefficient, and marginal functions of
and
are given by
Note that the correlation coefficient is positive.
Proposition 2.6 The Fisher information metric
is given by
Proposition 2.7 The
-connection components of
are given by
while the other independent components are zero.
Proposition 2.8 The
-curvature tensor,
-Ricci tensor, and
-scalar curvature of
are zero.
2.4. Submanifold
of Block and Basu
The distributions are of the form:
where the parameters
are positive, and
. This distribution was derived originally by omitting the singular part of Marshall and Olkin's distribution (compare [10]); Block and Basu called it the ACBED to emphasize that it is an absolutely continuous part of a bivariate exponential distribution. Alternatively, it can be derived from the Freund distribution (1), with
By substitution we obtained the covariance, correlation coefficient, and marginal functions of
and
:
Note that the correlation coefficient is positive, and the marginal functions are a negative mixture of two exponentials.
The Christoffel symbols, curvature tensor, Ricci tensor, sectional curvatures, mean curvatures, and scalar curvature were computed, but are not listed because they are somewhat cumbersome.
When
, this family of distributions becomes an exponential family with natural parameters
and potential function
, so it would be easy to derive the
-geometry, for example,
and the
components are as follows:
while the
-curvatures vanish.