Revision as of 05:53, 14 July 2008 by imported>Jitse Niesen
Almost sure convergence is one of the four main modes of stochastic convergence. It may be viewed as a notion of convergence for random variables that is similar to, but not the same as, the notion of pointwise convergence for real functions.
Definition
In this section, a formal definition of almost sure convergence will be given for complex vector-valued random variables, but it should be noted that a more general definition can also be given for random variables that take on values on more abstract topological spaces. To this end, let
be a probability space (in particular,
) is a measurable space). A (
-valued) random variable is defined to be any measurable function
, where
is the sigma algebra of Borel sets of
. A formal definition of almost sure convergence can be stated as follows:
A sequence
of random variables is said to converge almost surely to a random variable
if
for all
, where
is some measurable set satisfying
. An equivalent definition is that the sequence
converges almost surely to
if
for all
, where
is some measurable set with
. This convergence is often expressed as:
or
.
Important cases of almost sure convergence
If we flip a coin n times and record the percentage of times it comes up heads, the result will almost surely approach 50% as
.
This is an example of the strong law of large numbers.