On finite sample statistics for yule-walker estimates

H.E. Wensink; W.J. Dijkhof

doi:10.1109/TIT.2002.807310

On finite sample statistics for yule-walker estimates

H.E. Wensink, W.J. Dijkhof

Dynamics and Control

Research output: Contribution to journal › Article › Academic › peer-review

6 Citations (Scopus)

Abstract

The expectation of the square of the reflection coefficient in small samples of white noise is derived. This variance of the reflection coefficient in white noise is a key factor in the statistics of the estimation of autoregressive (AR) models in small samples. Approximations of this expectation are constructed that are more accurate than the known first-order Taylor approximation. These better approximations are needed, because in some applications (radar applications, for example) the number of observations is small (say 63 observations) and asymptotic descriptions do not cover the estimates.

Original language	English
Pages (from-to)	509-516
Journal	IEEE Transactions on Information Theory
Volume	49
Issue number	2
DOIs	https://doi.org/10.1109/TIT.2002.807310
Publication status	Published - 2003

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10.1109/TIT.2002.807310

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title = "On finite sample statistics for yule-walker estimates",

abstract = "The expectation of the square of the reflection coefficient in small samples of white noise is derived. This variance of the reflection coefficient in white noise is a key factor in the statistics of the estimation of autoregressive (AR) models in small samples. Approximations of this expectation are constructed that are more accurate than the known first-order Taylor approximation. These better approximations are needed, because in some applications (radar applications, for example) the number of observations is small (say 63 observations) and asymptotic descriptions do not cover the estimates.",

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AU - Dijkhof, W.J.

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AB - The expectation of the square of the reflection coefficient in small samples of white noise is derived. This variance of the reflection coefficient in white noise is a key factor in the statistics of the estimation of autoregressive (AR) models in small samples. Approximations of this expectation are constructed that are more accurate than the known first-order Taylor approximation. These better approximations are needed, because in some applications (radar applications, for example) the number of observations is small (say 63 observations) and asymptotic descriptions do not cover the estimates.

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DO - 10.1109/TIT.2002.807310

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VL - 49

SP - 509

EP - 516

JO - IEEE Transactions on Information Theory

JF - IEEE Transactions on Information Theory

IS - 2

ER -

On finite sample statistics for yule-walker estimates

Abstract

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