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Circulant Matrices and Time-series Analysis


  • Stephen Pollock

    (Queen Mary, University of London)


This paper sets forth some of the salient results in the algebra of circulant matrices which can be used in time-series analysis. It provides easy derivations of some results that are central to the analysis of statistical periodograms and empirical spectral density functions. A statistical test for the stationarity or homogeneity of empirical processes is also presented.

Suggested Citation

  • Stephen Pollock, 2000. "Circulant Matrices and Time-series Analysis," Working Papers 422, Queen Mary University of London, School of Economics and Finance.
  • Handle: RePEc:qmw:qmwecw:wp422

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    References listed on IDEAS

    1. Pollock, D.S.G., 1991. "On the criterion function for arma estimation," Serie Research Memoranda 0074, VU University Amsterdam, Faculty of Economics, Business Administration and Econometrics.
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    Cited by:

    1. Pollock, D.S.G., 2006. "Econometric methods of signal extraction," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2268-2292, May.
    2. Stephen Pollock & Iolanda Lo Cascio, 2005. "Orthogonality Conditions for Non-Dyadic Wavelet Analysis," Working Papers 529, Queen Mary University of London, School of Economics and Finance.
    3. D.S.G. Pollock, 2013. "Filtering macroeconomic data," Chapters,in: Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 5, pages 95-136 Edward Elgar Publishing.

    More about this item


    Time-series analysis; Circulant matrices; Discrete Fourier transforms; Periodograms;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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