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Graphical Methods For Determining The Presence Of Periodic Correlation

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  • Harry L. Hurd
  • Neil L. Gerr

Abstract

. Methods for determining whether an observed time series is, or contains, a periodically correlated sequence are presented. They are based on the fact that the support of the spectral measure for a harmonizable periodically correlated stochastic sequence is contained in a set of equally spaced lines parallel to the main diagonal in the bifrequency plane. We show how a coherence statistic devised by N. R. Goodman can be used to test for the presence of spectral support (correlation) along diagonal lines, thus providing a test for the presence of periodic correlation. Plots of this coherence statistic as a function of two frequency variables visually reveal the presence of diagonal support lines. Two additional tests for the presence of diagonal support lines are constructed by collapsing the two‐dimensional coherence plots into one‐dimensional plots of difference frequency.

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  • Harry L. Hurd & Neil L. Gerr, 1991. "Graphical Methods For Determining The Presence Of Periodic Correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 12(4), pages 337-350, July.
    • Handle: RePEc:bla:jtsera:v:12:y:1991:i:4:p:337-350
    DOI: 10.1111/j.1467-9892.1991.tb00088.x
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    Cited by:

    1. Baek, Changryong & Davis, Richard A. & Pipiras, Vladas, 2017. "Sparse seasonal and periodic vector autoregressive modeling," Computational Statistics & Data Analysis, Elsevier, vol. 106(C), pages 103-126.
    2. Mahmoudi, Mohammad Reza & Heydari, Mohammad Hossein & Roohi, Reza, 2019. "A new method to compare the spectral densities of two independent periodically correlated time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 160(C), pages 103-110.
    3. A. R. Nematollahi & A. R. Soltani & M. R. Mahmoudi, 2017. "Periodically correlated modeling by means of the periodograms asymptotic distributions," Statistical Papers, Springer, vol. 58(4), pages 1267-1278, December.
    4. Lenart, Łukasz, 2013. "Non-parametric frequency identification and estimation in mean function for almost periodically correlated time series," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 252-269.
    5. Lukasz Lenart, 2015. "Discrete Spectral Analysis. The Case of Industrial Production in Selected European Countries," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 27-47.
    6. Łukasz Lenart, 2017. "Examination of Seasonal Volatility in HICP for Baltic Region Countries: Non-Parametric Test versus Forecasting Experiment," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(1), pages 29-67, March.
    7. Mohammad Reza Mahmoudi & Mohsen Maleki, 2017. "A new method to detect periodically correlated structure," Computational Statistics, Springer, vol. 32(4), pages 1569-1581, December.
    8. Jeremy Penzer & Yorghos Tripodis, 2007. "Single-season heteroscedasticity in time series," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(3), pages 189-202.
    9. Mohammadi, M. & Rezakhah, S. & Modarresi, N., 2020. "Semi-Lévy driven continuous-time GARCH process," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    10. Sarnaglia, A.J.Q. & Reisen, V.A. & Lévy-Leduc, C., 2010. "Robust estimation of periodic autoregressive processes in the presence of additive outliers," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2168-2183, October.
    11. A. R. Soltani & A. R. Nematollahi & M. R. Mahmoudi, 2019. "On the asymptotic distribution of the periodograms for the discrete time harmonizable simple processes," Statistical Inference for Stochastic Processes, Springer, vol. 22(2), pages 307-322, July.
    12. Soumya Das & Marc G. Genton & Yasser M. Alshehri & Georgiy L. Stenchikov, 2021. "A cyclostationary model for temporal forecasting and simulation of solar global horizontal irradiance," Environmetrics, John Wiley & Sons, Ltd., vol. 32(8), December.
    13. Mohammad Reza Mahmoudi, 2023. "Cyclic clustering approach to impute missing values for cyclostationary hydrological time series," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(3), pages 2619-2639, June.
    14. Jentsch, Carsten & Subba Rao, Suhasini, 2015. "A test for second order stationarity of a multivariate time series," Journal of Econometrics, Elsevier, vol. 185(1), pages 124-161.

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