The Annals of Statistics

On Large-Sample Estimation for the Mean of a Stationary Random Sequence

Rolf K. Adenstedt

Full-text: Open access

Abstract

For a wide class of stationary random sequences possessing a spectral density function, the variance of the best linear unbiased estimator for the mean is seen to depend asymptotically only on the behavior of the spectral density near the origin. Asymptotically efficient estimators based only on this behavior may be chosen. For spectral densities behaving like $\lambda^\nu$ at the origin, $\nu > -1$ a constant, the minimum variance decreases like $n^{-\nu-1}$, where $n$ is the sample size. Asymptotically efficient estimators depending on $\nu$ are given. Finally, the consequences of over- or under-estimating the value of $\nu$ in choosing an estimator are considered.

Article information

Source
Ann. Statist., Volume 2, Number 6 (1974), 1095-1107.

Dates
First available in Project Euclid: 12 April 2007

Permanent link to this document
https://projecteuclid.org/euclid.aos/1176342867

Digital Object Identifier
doi:10.1214/aos/1176342867

Mathematical Reviews number (MathSciNet)
MR368354

Zentralblatt MATH identifier
0296.62081

JSTOR
links.jstor.org

Keywords
62 55 Linear estimation stationary time series mean spectral density efficiency

Citation

Adenstedt, Rolf K. On Large-Sample Estimation for the Mean of a Stationary Random Sequence. Ann. Statist. 2 (1974), no. 6, 1095--1107. doi:10.1214/aos/1176342867. https://projecteuclid.org/euclid.aos/1176342867


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