Hostname: page-component-586b7cd67f-r5fsc Total loading time: 0 Render date: 2024-11-24T05:41:22.046Z Has data issue: false hasContentIssue false

On an inequality of Heyde

Published online by Cambridge University Press:  14 July 2016

R. J. Tomkins*
Affiliation:
University of Saskatchewan, Regina Campus

Extract

In [3] Heyde proposed an extended version of the well-known Hájek-Rényi inequality to include random variables without finite moments. The purpose of this note is to point out that the theorem in [3] is in error, and to prove the following theorem in its stead:

Theorem. Let X1, X2, ··· be any sequence of random variables, and define be independent random variables, each with mean zero and finite variance, and define Zk = Xk - Yk for k ≧ 1. Let c1, c2, ··· be a non-increasing sequence of positive numbers.

Type
Short Communications
Copyright
Copyright © Applied Probability Trust 1970 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1] Gnedenko, B. V. (1963) The Theory of Probability. Chelsea, New York.Google Scholar
[2] Hájek, J. and Rényi, A. (1955) Generalization of an inequality of Kolmogorov. Acta Math. Acad. Sci. Hung. 6, 281283.Google Scholar
[3] Heyde, C. C. (1968) An extension of the Hájek-Rényi inequality for the case without moment conditions. J. Appl. Prob. 5, 481483.CrossRefGoogle Scholar