Electronic Journal of Probability

On the Moment-Transfer Approach for Random Variables Satisfying a One-Sided Distributional Recurrence

Che-Hao Chen and Michael Fuchs

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Abstract

The moment-transfer approach is a standard tool for deriving limit laws of sequences of random variables satisfying a distributional recurrence. However, so far the approach could not be applied to certain "one-sided" recurrences with slowly varying moments and normal limit law. In this paper, we propose a modified version of the moment-transfer approach which can be applied to such recurrences. Moreover, we demonstrate the usefulness of our approach by re-deriving several recent results in an almost automatic fashion.

Article information

Source
Electron. J. Probab., Volume 16 (2011), paper no. 30, 903-928.

Dates
Accepted: 10 May 2011
First available in Project Euclid: 1 June 2016

Permanent link to this document
https://projecteuclid.org/euclid.ejp/1464820199

Digital Object Identifier
doi:10.1214/EJP.v16-885

Mathematical Reviews number (MathSciNet)
MR2801455

Zentralblatt MATH identifier
1227.05121

Subjects
Primary: 05C05: Trees
Secondary: 60F05: Central limit and other weak theorems 68Q87: Probability in computer science (algorithm analysis, random structures, phase transitions, etc.) [See also 68W20, 68W40]

Keywords
distributional recurrence moment-transfer approach central limit theorem analysis of algorithms

Rights
This work is licensed under aCreative Commons Attribution 3.0 License.

Citation

Chen, Che-Hao; Fuchs, Michael. On the Moment-Transfer Approach for Random Variables Satisfying a One-Sided Distributional Recurrence. Electron. J. Probab. 16 (2011), paper no. 30, 903--928. doi:10.1214/EJP.v16-885. https://projecteuclid.org/euclid.ejp/1464820199


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