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LIMIT THEOREMS FOR RADIAL RANDOM WALKS ON EUCLIDEAN SPACES OF HIGH DIMENSIONS

Published online by Cambridge University Press:  25 July 2014

WALDEMAR GRUNDMANN*
Affiliation:
Technische Universitat Dortmund, Dortmund, Nordrhein-Westfalen, Germany email [email protected], [email protected]
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Abstract

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Let $\def \xmlpi #1{}\def \mathsfbi #1{\boldsymbol {\mathsf {#1}}}\let \le =\leqslant \let \leq =\leqslant \let \ge =\geqslant \let \geq =\geqslant \def \Pr {\mathit {Pr}}\def \Fr {\mathit {Fr}}\def \Rey {\mathit {Re}}\nu \in M^1([0,\infty [)$ be a fixed probability measure. For each dimension $p\in \mathbb{N}$, let $(X_n^{p})_{n\geq 1}$ be independent and identically distributed $\mathbb{R}^p$-valued random variables with radially symmetric distributions and radial distribution $\nu $. We investigate the distribution of the Euclidean length of $S_n^{p}:=X_1^{p}+\cdots + X_n^{p}$ for large parameters $n$ and $p$. Depending on the growth of the dimension $p=p_n$ we derive by the method of moments two complementary central limit theorems (CLTs) for the functional $\| S_n^{p}\| _2$ with normal limits, namely for $n/p_n \to \infty $ and $n/p_n \to 0$. Moreover, we present a CLT for the case $n/p_n \to c\in \, (0,\infty )$. Thereby we derive explicit formulas and asymptotic results for moments of radial distributed random variables on $\mathbb{R}^p$. All limit theorems are also considered for orthogonal invariant random walks on the space $\mathbb{M}_{p,q}(\mathbb{R})$ of $p\times q$ matrices instead of $\mathbb{R}^p$ for $p\to \infty $ and some fixed dimension $q$.

Type
Research Article
Copyright
Copyright © 2014 Australian Mathematical Publishing Association Inc. 

References

Bentkus, V., ‘Dependence of the Berry–Esseen estimate on the dimension’, Lith. Math. J. 26 (1986), 110113.Google Scholar
Bentkus, V. and Götze, F., ‘Uniform rates of convergence in the CLT for quadratic forms’, Probab. Theory Related Fields 109 (1997), 367416.Google Scholar
Billingsley, P., Probability and Measure, 2nd edn (J. Wiley, New York, 1986).Google Scholar
Faraut, J. and Korányi, A., Analysis on Symmetric Cones (Oxford Science Publications, Clarendon Press, Oxford, 1994).CrossRefGoogle Scholar
Gupta, A. K. and Nagar, D. K., Matrix Variate Distributions (Chapman & Hall/CR. Oxford Science Publications, Clarendon Press, Oxford, 1994).Google Scholar
Herz, C. S., ‘Bessel functions of matrix argument’, Ann. of Math. (2) 61 (1955), 474523.Google Scholar
Horn, R. A. and Johnson, C. R., Topics in Matrix Analysis (Cambridge University Press, Cambridge, 1991).Google Scholar
Jewett, R. I., ‘Spaces with an abstract convolution of measures’, Adv. Math. 18 (1975), 1101.Google Scholar
Rösler, M., ‘Bessel convolutions on matrix cones’, Compositio Math. 143 (2007), 749779.Google Scholar
Rösler, M. and Voit, M., ‘Limit theorems for radial random walks on p × q matrices as p tends to infinity’, Math. Nachr. 284 (2011), 87104.Google Scholar
Stanley, R. P., Enumerative Combinatorics, Cambridge Studies in Advanced Mathematics, 49 (Cambridge University Press, New York, 2005).Google Scholar
Triantafyllopoulos, K., ‘On the central moments of the multidimensional Gaussian distribution’, Math. Sci. 28 (2003), 125128.Google Scholar
Voit, M., ‘Central limit theorems for radial random walks on p × q matrices for p’, Adv. Pure Appl. Math. 3 (2012), 231246.Google Scholar