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Biometrika 1970 57(1):111-122; doi:10.1093/biomet/57.1.111
© 1970 by Biometrika Trust
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Spectral analysis of a stationary time series using initially scarce data

HENRY R. NEAVE

University of Nottingham

This paper studies the estimation of the spectrum of a stationary time series from ‘initially scarce’ data, i.e. data where the sampling period is shortened at some point during the period of observation. Two types of estimators are considered, the ‘simple’ estimators, so-called because they derive immediately from general theory which can essentially be applied to most missing data situations, and ‘alias-improved’ estimators, whose use unfortunately cannot be extended to many other situations. The estimators have been compared in finite situations by Monte Carlo methods, and the alias-improved estimators turn out to be much superior. Asymptotic expressions for the variance are also included.


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