- Suppose
has a
distribution with
partitioned as
and Variance covariance
- Show that
if and only if
and
are independent. Use my definition of MVN; you are not allowed
to assume that X has a density. A mathematically careful argument my
rely on the fact that if
are independent and
are (measurable) functions then
are independent. - Show that whether or not
is singular, each column of
is in the column space of
. - Show that there is a matrix A which is
such that
. - Let h be a column of
and
and
be any vectors
such that
for i=1,2. Show that
. - Show that if
for i=1,2 then
. - Show that
implies
for any
. - Suppose x is such that
implies
. Show that the conditional distribution
of
given
is well-defined and is multivariate
normal with mean
and variance covariance
where a is any solution of
and A is any solution of
.
NOTE: Most facts about
variates X can be demonstrated
by writing
for well chosen A.
- Fix
. Minimize and maximize
subject to
. - Fix
. Minimize and maximize
subject to
for a given symmetric positive definite matrix Q. - Write out the spectral decomposition of the matrix
and then find a symmetric square root.
- Suppose
has a MVN distribution with
and
Find the conditional distribution of
given
and
. For which
values of
and
does this make sense?