Convergence rate in CLT for vector-valued random fields with self-normalization

• Autorzy: Bulinski A. , Kryzhanovskaya N.
• Języki publikacji: EN

Abstrakty

EN

Statistical version of the central limit theorem (CLT) with random matrix normalization is established for random fields with values in a space R^k (k ≥ 1). Dependence structure of the field under consideration is described in terms of the covariance inequalities for the class of bounded Lipschitz ”test functions” defined on finite disjoint collections of random vectors constituting the field. The main result provides an estimate of the convergence rate, over a family of convex bounded sets, in the CLT with random normalization.

Słowa kluczowe

EN

random fields; dependence conditions; CLT; central limit theorem; random matrix normalization; convergence rate

• Wydawca: Wrocław University of Science and Technology
• Czasopismo: Probability and Mathematical Statistics
• Rocznik: 2006
• Tom: Vol. 26, Fasc. 2
• Strony: 261--281
• Opis fizyczny: Bibliogr. 27 poz.

Twórcy

autor

Bulinski A.

• Department of Mathematics and Mechanics, Moscow State University, Moscow 119992, Russia

autor

Kryzhanovskaya N.

• Department of Mathematics and Mechanics, Moscow State University, Moscow 119992, Russia

Bibliografia

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Uwagi

To the memory of Professor Kazimierz Urbanik.