Non-asymptotic bounds for autoregressive approximation

A. Goldenshluger; A. Zeevi

doi:10.1109/ISIT.1998.708909

Non-asymptotic bounds for autoregressive approximation

A. Goldenshluger, A. Zeevi

Department of Statistics

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

Abstract

The subject of this paper is the autoregressive (AR) approximation of a stationary, Gaussian discrete time process, based on a finite sequence of observations. We adopt the nonparametric minimax framework and study how well can the process be approximated by a finite order autoregressive model.

Original language	English
Title of host publication	Proceedings - 1998 IEEE International Symposium on Information Theory, ISIT 1998
Pages	304
Number of pages	1
DOIs	https://doi.org/10.1109/ISIT.1998.708909
State	Published - 1998
Event	1998 IEEE International Symposium on Information Theory, ISIT 1998 - Cambridge, MA, United States Duration: 16 Aug 1998 → 21 Aug 1998

Publication series

Name	IEEE International Symposium on Information Theory - Proceedings
ISSN (Print)	2157-8095

Conference

Conference	1998 IEEE International Symposium on Information Theory, ISIT 1998
Country/Territory	United States
City	Cambridge, MA
Period	16/08/98 → 21/08/98

ASJC Scopus subject areas

Theoretical Computer Science
Information Systems
Modeling and Simulation
Applied Mathematics

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10.1109/ISIT.1998.708909

Cite this

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title = "Non-asymptotic bounds for autoregressive approximation",

abstract = "The subject of this paper is the autoregressive (AR) approximation of a stationary, Gaussian discrete time process, based on a finite sequence of observations. We adopt the nonparametric minimax framework and study how well can the process be approximated by a finite order autoregressive model.",

author = "A. Goldenshluger and A. Zeevi",

year = "1998",

doi = "10.1109/ISIT.1998.708909",

language = "English",

isbn = "0780350006",

series = "IEEE International Symposium on Information Theory - Proceedings",

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Goldenshluger, A & Zeevi, A 1998, Non-asymptotic bounds for autoregressive approximation. in Proceedings - 1998 IEEE International Symposium on Information Theory, ISIT 1998., 708909, IEEE International Symposium on Information Theory - Proceedings, pp. 304, 1998 IEEE International Symposium on Information Theory, ISIT 1998, Cambridge, MA, United States, 16/08/98. https://doi.org/10.1109/ISIT.1998.708909

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AU - Zeevi, A.

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N2 - The subject of this paper is the autoregressive (AR) approximation of a stationary, Gaussian discrete time process, based on a finite sequence of observations. We adopt the nonparametric minimax framework and study how well can the process be approximated by a finite order autoregressive model.

AB - The subject of this paper is the autoregressive (AR) approximation of a stationary, Gaussian discrete time process, based on a finite sequence of observations. We adopt the nonparametric minimax framework and study how well can the process be approximated by a finite order autoregressive model.

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M3 - Conference contribution

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SN - 0780350006

SN - 9780780350007

T3 - IEEE International Symposium on Information Theory - Proceedings

SP - 304

BT - Proceedings - 1998 IEEE International Symposium on Information Theory, ISIT 1998

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Y2 - 16 August 1998 through 21 August 1998

ER -

Non-asymptotic bounds for autoregressive approximation

Abstract

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Conference

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