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On the eigenstructure of generalized fractional processes

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  • Palma, Wilfredo
  • Bondon, Pascal

Abstract

This work establishes bounds for the eigenvalues of the covariance matrix from a general class of stationary processes. These results are applied to the statistical analysis of the large sample behavior of estimates and testing procedures of generalized long memory models, including Seasonal ARFIMA and k-factor GARMA processes, among others.

Suggested Citation

  • Palma, Wilfredo & Bondon, Pascal, 2003. "On the eigenstructure of generalized fractional processes," Statistics & Probability Letters, Elsevier, vol. 65(2), pages 93-101, November.
    • Handle: RePEc:eee:stapro:v:65:y:2003:i:2:p:93-101
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    References listed on IDEAS

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    1. Hassler, Uwe & Wolters, Jurgen, 1995. "Long Memory in Inflation Rates: International Evidence," Journal of Business & Economic Statistics, American Statistical Association, vol. 13(1), pages 37-45, January.
    2. Ray, Bonnie K., 1993. "Long-range forecasting of IBM product revenues using a seasonal fractionally differenced ARMA model," International Journal of Forecasting, Elsevier, vol. 9(2), pages 255-269, August.
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    Cited by:

    1. Henghsiu Tsai & Heiko Rachinger & Edward M.H. Lin, 2015. "Inference of Seasonal Long-memory Time Series with Measurement Error," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 137-154, March.
    2. Yuanyuan Li & Dietmar Bauer, 2020. "Modeling I(2) Processes Using Vector Autoregressions Where the Lag Length Increases with the Sample Size," Econometrics, MDPI, vol. 8(3), pages 1-28, September.

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