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Determining The Number Of Terms In A Trigonometric Regression

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  • L. Kavalieris
  • E. J. Hannan

Abstract

. We consider the estimation of the number of sinusoidal terms in a time series contaminated by additive noise with unknown correlation structure. The method fits sinusoidal terms by least squares and models the noise component using a high order autoregression. A criterion based on the minimum description length principle is used to select the number of sinusoidal terms and the order of the noise model. The small sample efficacy of the model selection procedure is examined by simulations and the analysis of some astronomical data. Consistency is proved under quite general conditions on the noise spectrum.

Suggested Citation

  • L. Kavalieris & E. J. Hannan, 1994. "Determining The Number Of Terms In A Trigonometric Regression," Journal of Time Series Analysis, Wiley Blackwell, vol. 15(6), pages 613-625, November.
    • Handle: RePEc:bla:jtsera:v:15:y:1994:i:6:p:613-625
    DOI: 10.1111/j.1467-9892.1994.tb00216.x
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    Cited by:

    1. Hidalgo, Javier, 2005. "Semiparametric estimation for stationary processes whose spectra have an unknown pole," LSE Research Online Documents on Economics 6842, London School of Economics and Political Science, LSE Library.
    2. James Rude & Jean-Philippe Gervais, 2009. "Biases in Calculating Dumping Margins: The Case of Cyclical Products," Review of Agricultural Economics, Agricultural and Applied Economics Association, vol. 31(1), pages 122-142.
    3. Javier Hidalgo, 2005. "Semiparametric Estimation for Stationary Processes whose Spectra have an Unknown Pole," STICERD - Econometrics Paper Series 481, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Hidalgo, Javier, 2002. "Consistent order selection with strongly dependent data and its application to efficient estimation," LSE Research Online Documents on Economics 6856, London School of Economics and Political Science, LSE Library.
    5. Barry G. Quinn, 2021. "Fisher's g Revisited," International Statistical Review, International Statistical Institute, vol. 89(2), pages 402-419, August.
    6. Hidalgo, Javier, 2002. "Consistent order selection with strongly dependent data and its application to efficient estimation," Journal of Econometrics, Elsevier, vol. 110(2), pages 213-239, October.
    7. Javier Hidalgo, 2002. "Consistent Order Selection with Strongly Dependent Data and its Application to Efficient Estimation," STICERD - Econometrics Paper Series 430, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.

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