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Estimation of a nonparametric regression spectrum for multivariate time series

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  • Beran, Jan
  • Heiler, Mark A.

Abstract

Estimation of a nonparametric regression spectrum based on the periodogram is considered. Neither trend estimation nor smoothing of the periodogram are required. Alternatively, for cases where spectral estimation of phase shifts fails and the shift does not depend on frequency, a time domain estimator of the lag-shift is defined. Asymptotic properties of the frequency and time domain estimators are derived. Simulations and a data example illustrate the methods.

Suggested Citation

  • Beran, Jan & Heiler, Mark A., 2007. "Estimation of a nonparametric regression spectrum for multivariate time series," CoFE Discussion Papers 07/12, University of Konstanz, Center of Finance and Econometrics (CoFE).
    • Handle: RePEc:zbw:cofedp:0712
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    References listed on IDEAS

    as
    1. Ori Rosen & David S. Stoffer, 2007. "Automatic estimation of multivariate spectra via smoothing splines," Biometrika, Biometrika Trust, vol. 94(2), pages 335-345.
    2. Jan Beran & Sucharita Ghosh, 2000. "Estimation of the Dominating Frequency for Stationary and Nonstationary Fractional Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(5), pages 517-533, September.
    3. Iain M. Johnstone & Bernard W. Silverman, 1997. "Wavelet Threshold Estimators for Data with Correlated Noise," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 59(2), pages 319-351.
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