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Statistical inference using higher-order information

Author

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  • Anh, V.V.
  • Leonenko, N.N.
  • Sakhno, L.M.

Abstract

This paper presents a class of minimum contrast estimators for stochastic processes with possible long-range dependence based on the information on higher-order spectral densities. The results on consistency and asymptotic normality of the proposed estimators are provided.

Suggested Citation

  • Anh, V.V. & Leonenko, N.N. & Sakhno, L.M., 2007. "Statistical inference using higher-order information," Journal of Multivariate Analysis, Elsevier, vol. 98(4), pages 706-742, April.
    • Handle: RePEc:eee:jmvana:v:98:y:2007:i:4:p:706-742
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    References listed on IDEAS

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    1. John C. Cox & Jonathan E. Ingersoll Jr. & Stephen A. Ross, 2005. "A Theory Of The Term Structure Of Interest Rates," World Scientific Book Chapters, in: Sudipto Bhattacharya & George M Constantinides (ed.), Theory Of Valuation, chapter 5, pages 129-164, World Scientific Publishing Co. Pte. Ltd..
    2. Ole E. Barndorff‐Nielsen & Neil Shephard, 2002. "Econometric analysis of realized volatility and its use in estimating stochastic volatility models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(2), pages 253-280, May.
    3. Paul Doukhan & Patrice Bertail & Philippe Soulier, 2006. "Dependence in Probability and Statistics," Post-Print hal-00268232, HAL.
    4. Zhang, Hong-Ching & Shaman, Paul, 1991. "On the calculation of cumulants of estimators arising from a linear time series regression model," Journal of Multivariate Analysis, Elsevier, vol. 37(2), pages 135-150, May.
    5. Gao, Jiti & Anh, Vo & Heyde, Chris, 2002. "Statistical estimation of nonstationary Gaussian processes with long-range dependence and intermittency," Stochastic Processes and their Applications, Elsevier, vol. 99(2), pages 295-321, June.
    6. Valery Buldygin & Frederic Utzet & Vladimir Zaiats, 2004. "Asymptotic Normality of Cross-correlogram Estimates of the Response Function," Statistical Inference for Stochastic Processes, Springer, vol. 7(1), pages 1-34, March.
    7. Paul Doukhan & Patrice Bertail & Philippe Soulier, 2006. "Dependence in Probability and Statistics," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00268232, HAL.
    8. Heyde, C. C. & Gay, R., 1993. "Smoothed periodogram asymptotics and estimation for processes and fields with possible long-range dependence," Stochastic Processes and their Applications, Elsevier, vol. 45(1), pages 169-182, March.
    9. Jiti Gao & Vo Anh & Chris Heyde & Quang Tieng, 2001. "Parameter Estimation of Stochastic Processes with Long‐range Dependence and Intermittency," Journal of Time Series Analysis, Wiley Blackwell, vol. 22(5), pages 517-535, September.
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