This lecture discusses pointwise convergence, first for sequences of random variables and then for sequences of random vectors.
Let
be a sequence of random variables defined on a
sample space
.
Let us consider a single sample
point
and a generic random variable
belonging to the sequence.
is a function
.
However, once we fix
,
the realization
associated to the sample point
is just a real number. By the same token, once we fix
,
the sequence
is just a sequence of real numbers.
Therefore, for a fixed
,
it is very easy to assess whether the sequence
is convergent; this is done employing the usual definition of
convergence of sequences of real numbers.
If, for a fixed
,
the sequence
is convergent, we denote its limit by
,
to underline that the limit depends on the specific
we have fixed.
A sequence of random variables is said to be pointwise convergent if and only
if the sequence
is convergent for any choice of
.
Definition
Let
be a sequence of random variables defined on a sample space
.
We say that
is pointwise convergent to a random variable
defined on
if and only if
converges to
for all
.
is called the pointwise limit of the sequence and convergence
is indicated
by
Roughly speaking, using pointwise convergence we somehow circumvent the
problem of defining the concept of distance between random variables: by
fixing
,
we reduce ourselves to the familiar problem of measuring distance between two
real numbers, so that we can employ the usual notion of convergence of
sequences of real numbers.
Example
Let
be a sample space with two sample points
(
and
).
Let
be a sequence of random variables such that a generic term
of the sequence
satisfies
We
need to check the convergence of the sequences
for all
,
i.e. for
and for
:
(1) the sequence
,
whose generic term is
,
is a sequence of real numbers converging to
;
(2) the sequence
,
whose generic term is
,
is a sequence of real numbers converging to
.
Therefore, the sequence of random variables
converges pointwise to the random variable
,
where
is defined as
follows:
The above notion of convergence generalizes to sequences of random vectors in a straightforward manner.
Let
be a sequence of random vectors defined on a
sample space
,
where each random vector
has dimension
.
If we fix a single sample point
,
the sequence
is a sequence of real
vectors.
By the standard criterion for
convergence, the sequence of real vectors
is convergent to a vector
if
where
is the distance between a generic term of the sequence
and the limit
.
The distance between
and
is defined to be equal to the Euclidean norm of their
difference:
where
the second subscript is used to indicate the individual components of the
vectors
and
.
Thus, for a fixed
,
the sequence of real vectors
is convergent to a vector
if
A sequence of random vectors
is said to be pointwise convergent if and only if the sequence
is convergent for any choice of
.
Definition
Let
be a sequence of random vectors defined on a sample space
.
We say that
is pointwise convergent to a random vector
defined on
if and only if
converges to
for all
(i.e.
).
is called the pointwise limit of the sequence and convergence
is indicated
by
Now, denote by
the sequence of the
-th
components of the vectors
.
It can be proved that the sequence of random vectors
is pointwise convergent if and only if all the
sequences of random variables
are pointwise convergent:
Proposition
Let
be a sequence of random vectors defined on a sample space
.
Denote by
the sequence of random variables obtained by taking the
-th
component of each random vector
.
The sequence
converges pointwise to the random vector
if and only if
converges pointwise to the random variable
(the
-th
component of
)
for each
.
Below you can find some exercises with explained solutions.
Let the sample space
be:
i.e. the sample space
is the set of all real numbers between
and
.
Define a sequence of random variables
as
follows:
Find the pointwise limit of the sequence
.
For a fixed sample point
,
the sequence of real numbers
has
limit
Therefore, the sequence of random variables
converges pointwise to the random variable
defined as
follows:
Suppose the sample space
is as in the previous
exercise:
Define a sequence of random variables
as
follows:
Find the pointwise limit of the sequence
.
For a given sample point
,
the sequence of real numbers
has
limit
(note that this limit is encountered very frequently and you can find a proof
of it in most calculus textbooks). Thus, the sequence of random variables
converges pointwise to the random variable
defined as
follows:
Suppose the sample space
is as in the previous
exercises:
Define a sequence of random variables
as
follows:
Define a random variable
as
follows:
Does
the sequence
converge pointwise to the random variable
?
For
,
the sequence of real numbers
has
limit
However,
for
,
the sequence of real numbers
has
limit
Thus,
the sequence of random variables
does not converge pointwise to the random variable
,
but it converges pointwise to the random variable
defined as
follows:
Please cite as:
Taboga, Marco (2021). "Pointwise convergence", Lectures on probability theory and mathematical statistics. Kindle Direct Publishing. Online appendix. https://www.statlect.com/asymptotic-theory/pointwise-convergence.
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