Hostname: page-component-848d4c4894-xfwgj Total loading time: 0 Render date: 2024-07-06T21:38:21.548Z Has data issue: false hasContentIssue false
  • English
  • Français

On non-uniform and global descriptions of the rate of convergence of Asymptotic expansions in the central limit theorem

Part of: Stochastic processes Limit theorems

Published online by Cambridge University Press:  09 April 2009

Peter Hall  and
T. Nakata
Peter Hall
Affiliation:
Department of Statistics, Faculty of Economics and Commerce, Australian National University, G.P.O. Box 4 Canberra, A.C.T. 2601, Australia
T. Nakata
Affiliation:
Department of Mathematics, Chukyo University, 101-2 Yagota Honmachi, Showa-Ku, Nagoya 468, Japan
Rights & Permissions [Opens in a new window]

Abstract

Core share and HTML view are not available for this content. However, as you have access to this content, a full PDF is available via the ‘Save PDF’ action button.

The leading term approach to rates of convergence is employed to derive non-uniform and global descriptions of the rate of convergence in the central limit theorem. Both upper and lower bounds are obtained, being of the same order of magnitude, modulo terms of order n-r. We are able to derive general results by considering only those expansions with an odd number of terms.

MSC classification

Secondary: 60F05: Central limit and other weak theorems 60G50: Sums of independent random variables; random walks
Type
Research Article
Information
Journal of the Australian Mathematical Society , Volume 41 , Issue 3 , December 1986 , pp. 326 - 335
Copyright
Copyright © Australian Mathematical Society 1986

References

[1]Hall, P., Rates of convergence in the central limit theorem (Pitman, London, 1982).Google Scholar
[2]Hall, P., ‘A leading term approach to asymptotic expansions in the central limit theorem’, Proc. London Math. Soc. 49 (1984), 423–444.Google Scholar
[3]Heyde, C. C. and Nakata, T., ‘On the asymptotic equivalence of Lp metrics for convergence to normality’, Z. Wahrsch. Verw. Gebiete 68 (1984), 97–106.Google Scholar
[4]Petrov, V. V., Sums of independent random variables (Springer-Verlag, Berlin, 1975).Google Scholar