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Biometrika
Article . 1988 . Peer-reviewed
Data sources: Crossref
Biometrika
Article . 1988 . Peer-reviewed
Data sources: Crossref
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On frequency estimation

Authors: John Rice; Murray Rosenblatt;

On frequency estimation

Abstract

A time series model of the form \[ X_ t=a\cos (wt+f)+e_ t \] where \(e_ t\) is a stationary noise sequence is considered. The paper discusses a least squares procedure for estimating a, w and f of the harmonic component. One aim of the paper is to see how reliable the asymptotic theory of the estimates of w is. It was found that the product of the amplitude and the sample size, n, must be quite large in order for the asymptotic theory to be meaningful. Otherwise the frequency estimate is much more variable than indicated by the asymptotic theory and the amplitude estimate is biased. This suggests that a general application of the asymptotic results can be quite misleading when there are small peaks in the periodogram (small amplitude). The paper is also concerned with computational issues of solving the nonlinear estimation equations. The numerical problems increase with sample size n, there are many local minima and the convergence of the iterative search is extremely sensitive to the starting values.

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Keywords

time series model, amplitude estimate, nonlinear estimation equations, iterative search, least squares procedure, periodogram, stationary noise sequence, numerical problems, Time series, auto-correlation, regression, etc. in statistics (GARCH), harmonic analysis, Inference from stochastic processes and spectral analysis, frequency estimate, Asymptotic properties of parametric estimators

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
107
Top 10%
Top 1%
Average
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