Convergence of profile based estimators

A. Orlitsky; N. Santhanam; K. Viswanathan; J. Zhang

doi:10.1109/ISIT.2005.1523664

Convergence of profile based estimators

A. Orlitsky, N. Santhanam, K. Viswanathan, J. Zhang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

9 Scopus citations

Abstract

We consider estimating distributions and their functions when the alphabet size is large compared to the amount of data observed. We establish consistency results and rates of convergence for estimators based on the data's profile - the number of symbols appearing any given number of times, and compare them with those based on empirical-frequency.

Original language	English (US)
Title of host publication	Proceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05
Pages	1843-1847
Number of pages	5
DOIs	https://doi.org/10.1109/ISIT.2005.1523664
State	Published - 2005
Externally published	Yes
Event	2005 IEEE International Symposium on Information Theory, ISIT 05 - Adelaide, Australia Duration: Sep 4 2005 → Sep 9 2005

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
Volume	2005
ISSN (Print)	2157-8099

Other

Other	2005 IEEE International Symposium on Information Theory, ISIT 05
Country/Territory	Australia
City	Adelaide
Period	9/4/05 → 9/9/05

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

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10.1109/ISIT.2005.1523664

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Convergence of profile based estimators. / Orlitsky, A.; Santhanam, N.; Viswanathan, K. et al.
Proceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05. 2005. p. 1843-1847 1523664 (IEEE International Symposium on Information Theory - Proceedings; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Orlitsky, A, Santhanam, N, Viswanathan, K & Zhang, J 2005, Convergence of profile based estimators. in Proceedings of the 2005 IEEE International Symposium on Information Theory, ISIT 05., 1523664, IEEE International Symposium on Information Theory - Proceedings, vol. 2005, pp. 1843-1847, 2005 IEEE International Symposium on Information Theory, ISIT 05, Adelaide, Australia, 9/4/05. https://doi.org/10.1109/ISIT.2005.1523664

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AB - We consider estimating distributions and their functions when the alphabet size is large compared to the amount of data observed. We establish consistency results and rates of convergence for estimators based on the data's profile - the number of symbols appearing any given number of times, and compare them with those based on empirical-frequency.

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ER -

Convergence of profile based estimators

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ASJC Scopus subject areas

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