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Distribution and moment convergence of martingales
Authors:H Teicher
Institution:(1) Department of Statistics, Hill Center for Mathematical Sciences, Rutgers University, 08903 New Brunswick, NJ, USA
Abstract:Summary If 
$$S_{n,k}  = \mathop \Sigma \limits_{1 \leqq i_1  < i_k  \leqq m_n } X_{ni_1 } ...{\text{ }}X_{ni_k } $$
where {X n j ,ℱ n j 1≦jm n ↑∞, n≧1} is a martingale difference array, conditions are given for the distribution and moment convergence of S n,k to the distribution and moments of 
$$\frac{1}{{k!}}H_k (Z)$$
where H k is the Hermite polynomial of degree k and Z is a standard normal variable. This is intimately related to an identity (*) for multiple Wiener integrals. Under alternative conditions, similar results hold for S n, k /U n k and S n, k /V n k where 
$$U_n^2  = \sum\limits_{j = 1}^{m_n } {X_{n j}^2 }$$
and V n 2 V n 2 is the conditional variance. Research supported by the National Science Foundation under Grant DMS-8601346
Keywords:
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