Probability Seminar
Department of Mathematical Sciences |
|
Richard Bradley Indiana University
Title: A strictly stationary, ``causal,'' 5-tuplewise
independent counterexample to the central limit theorem
A strictly stationary sequence of random variables is
constructed with the following properties:
(i) the random variables each take the values -1 and +1
with probability 1/2 each,
(ii) every five of the random variables are independent
of each other,
(iii) the sequence is ``causal'' in a certain sense (and
hence ``isomorphic to a Bernoulli shift''),
(iv) the sequence has a trivial double tail sigma-field,
and
(v) regardless of the normalization used, the partial
sums do not converge to a (nondegenerate) normal law
(even along a subsequence).
The example has appeared in [1], and it has some
features in common with an earlier construction (for an
arbitrary fixed positive integer N), by Alexander Pruss
and the author [2], of a strictly stationary (ergodic)
N-tuplewise independent counterexample to the central
limit theorem.
[1] R.C. Bradley. A strictly stationary, ``causal,''
5-tuplewise independent counterexample to the central
limit theorem. Latin American Journal of Probability
and Mathematical Statistics (ALEA) 7 (2010) 377-450.
[2] R.C. Bradley and A.R. Pruss. A strictly stationary,
N-tuplewise independent counterexample to the central
limit theorem. Stochastic Processes and their
Applications 119 (2009) 3300-3318.
©2010, Department of Mathematical Sciences
Last Modified:
February 26, 2009