Asymptotic normality of simultaneous estimators of cyclic long-memory processes

ELECTRONIC JOURNAL OF STATISTICS(2022)

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摘要
Spectral singularities at non-zero frequencies play an important role in investigating cyclic or seasonal time series. The publication [2] introduced the generalized filtered method-of-moments approach to simultaneously estimate singularity location and long-memory parameters. This paper continues studies of these simultaneous estimators. A wide class of Gegenbauer-type semi-parametric models is considered. Asymptotic normality of several statistics of the cyclic and long-memory parameters is proved. New adjusted estimates are proposed and investigated. The theoretical findings are illustrated by numerical results. The methodology includes wavelet transformations as a particular case.
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关键词
Central limit theorem, cyclic long-memory, filter, wavelet, estimators of parameters, asymptotic normality
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