A consistent estimator for spectral density matrix of a discrete time periodically correlated process

Azimmohseni, Majid; Soltani, Aboozar; Khalafi, Mahnaz; Ghalesary, Naeemeh Akbari

doi:10.19195/0208-4147.38.1.12

Cited by 3 publications

(1 citation statement)

References 2 publications

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“…For further details on asymptotic distributions of the finite Fourier transform and periodogram of PC processes, one can refer to the work of Azimmohseni et al (2018).…”

Section: Pc Processesmentioning

confidence: 99%

On the spectral coherence between two periodically correlated processes

et al. 2021

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We introduce a general class of multivariate periodically correlated processes and their corresponding time‐domain and spectral‐domain characterizations. A spectral coherence based on the Hilbert–Schmidt inner product of the Fourier transforms is introduced to measure the dependence of two periodically correlated (PC) processes. An estimator for the spectral coherence is introduced and studied. A hypothesis on the presence of significant dependence is formulated and the corresponding testing procedure established. Numerical illustrations on the performance of the spectral coherence and its estimator are given using simulated and real PC time series.

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“…For further details on asymptotic distributions of the finite Fourier transform and periodogram of PC processes, one can refer to the work of Azimmohseni et al (2018).…”

Section: Pc Processesmentioning

confidence: 99%

On the spectral coherence between two periodically correlated processes

et al. 2021

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On the asymptotic distribution for the periodograms of almost periodically correlated (cyclostationary) processes

Mahmoudi

Heydari

Avazzadeh

2018

Digital Signal Processing

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Asymptotic Analysis About the Periodogram of a General Class of Time Series Models With Spectral Supportson Lines Not Parallel to the Main Diagonal

et al. 2022

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The aim of this paper is to make inference about a general class of time series models including fractional Brownian motion. The spectral of these processes is supported on lines not parallel to the diagonal [Formula: see text], [Formula: see text], [Formula: see text], in spectral square [Formula: see text], and this class includes stationary, cyclostationary, almost cyclostationary time series and specially fractional Brownian motions. First, the periodogram of these processes is defined and auxiliary operator is applied to explore the distribution of the periodogram. Then the asymptotical estimation for the spectral density function is proposed and asymptotical Wishart function is found. Finally, the validity of the theoretical results is studied using simulated data sets.

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A consistent estimator for spectral density matrix of a discrete time periodically correlated process

Cited by 3 publications

References 2 publications

On the spectral coherence between two periodically correlated processes

On the spectral coherence between two periodically correlated processes

On the asymptotic distribution for the periodograms of almost periodically correlated (cyclostationary) processes

Asymptotic Analysis About the Periodogram of a General Class of Time Series Models With Spectral Supportson Lines Not Parallel to the Main Diagonal

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