On the Moment-Transfer Approach for Random Variables Satisfying a One-Sided Distributional Recurrence
Dublin Core | PKP Metadata Items | Metadata for this Document | |
1. | Title | Title of document | On the Moment-Transfer Approach for Random Variables Satisfying a One-Sided Distributional Recurrence |
2. | Creator | Author's name, affiliation, country | Che-Hao Chen; National Chiao Tung University; Taiwan, Province of China |
2. | Creator | Author's name, affiliation, country | Michael Fuchs; National Chiao Tung University; Taiwan, Province of China |
3. | Subject | Discipline(s) | |
3. | Subject | Keyword(s) | distributional recurrence; moment-transfer approach; central limit theorem; analysis of algorithms |
3. | Subject | Subject classification | 05C05; 60F05; 68Q87 |
4. | Description | 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. |
5. | Publisher | Organizing agency, location | |
6. | Contributor | Sponsor(s) | National Science Council under the grant NSC-99-2115-M-009-007-MY2 |
7. | Date | (YYYY-MM-DD) | 2011-05-10 |
8. | Type | Status & genre | Peer-reviewed Article |
8. | Type | Type | |
9. | Format | File format | |
10. | Identifier | Uniform Resource Identifier | http://ejp.ejpecp.org/article/view/885 |
10. | Identifier | Digital Object Identifier | 10.1214/EJP.v16-885 |
11. | Source | Journal/conference title; vol., no. (year) | Electronic Journal of Probability; Vol 16 |
12. | Language | English=en | |
14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
15. | Rights | Copyright and permissions | The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available. Summary of the Creative Commons Attribution License You are free
|