ASYMPTOTIC NORMALITY OF SAMPLE AUTOCOVARIANCES WITH AN APPLICATION IN FREQUENCY ESTIMATION

被引：15

作者：

LI, TH

KEDEM, B

YAKOWITZ, S

机构：

[1] UNIV MARYLAND, DEPT MATH, COLLEGE PK, MD 20742 USA

[2] UNIV MARYLAND, COLLEGE PK, MD 20742 USA

[3] UNIV ARIZONA, DEPT SYST & IND ENGN, TUCSON, AZ 85721 USA

来源：

STOCHASTIC PROCESSES AND THEIR APPLICATIONS | 1994年 / 52卷 / 02期

关键词：

ASYMPTOTIC NORMALITY; AUTOCOVARIANCE; FILTER; FREQUENCY ESTIMATION; MIXED SPECTRUM; SPECTRAL ANALYSIS; TIME SERIES;

D O I：

10.1016/0304-4149(94)90032-9

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

The asymptotic normality of sample autocovariances is proved for time series with mixed-spectra a, which extends the classical results of Bartlett for linear processes. It is also shown that the asymptotic normality remains valid after linear filtering, if the filter is strictly stable so that the end-point effect of finite sample can be ignored. The developed theory is then employed to establish the asymptotic normality of a recently proposed fast frequency estimation procedure.

引用

页码：329 / 349

页数：21

共 18 条

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