Asymptotic distributions and subsampling in spectral analysis for almost periodically correlated time series
Ł Lenart - 2011 - projecteuclid.org
Ł Lenart
2011•projecteuclid.orgThe aim of this article is to establish asymptotic distributions and consistency of subsampling
for spectral density and for magnitude of coherence for non-stationary, almost periodically
correlated time series. We show the asymptotic normality of the spectral density estimator
and the limiting distribution of a magnitude of coherence statistic for all points from the
bifrequency square. The theoretical results hold under α-mixing and moment conditions.
for spectral density and for magnitude of coherence for non-stationary, almost periodically
correlated time series. We show the asymptotic normality of the spectral density estimator
and the limiting distribution of a magnitude of coherence statistic for all points from the
bifrequency square. The theoretical results hold under α-mixing and moment conditions.
Abstract
The aim of this article is to establish asymptotic distributions and consistency of subsampling for spectral density and for magnitude of coherence for non-stationary, almost periodically correlated time series. We show the asymptotic normality of the spectral density estimator and the limiting distribution of a magnitude of coherence statistic for all points from the bifrequency square. The theoretical results hold under -mixing and moment conditions.
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