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Smoothed periodogram asymptotics and estimation for processes and fields with possible long-range dependence


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  • Heyde, C. C.
  • Gay, R.
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    In this paper we establish central limit theorems for the smoothed unbiased periodogram [integral operator][pi]-[pi]...[integral operator][pi]-[pi]g([omega],[theta]){I*T,X([omega])-EI*T,X([omega])}d[omega]1...d[omega]r, where {Xt} is a stationary r-dimensional random process or random field, possibly with long-range dependence, which is not necessarily Gaussian. Here I*T,X([omega]) is the unbiased periodogram and g([omega],[theta]) is a smoothing function satisfying modest regularity conditions. This result implies asymptotic normality of the asymptotic quasi-likelihood estimator of a distributional characteristic [theta] of the process {Xt} under very general conditions. In particular, these results show the asymptotic optimality of the Whittle estimation procedure for both short and long-range dependence in the absence of the Gaussian assumption, and extend those of Giraitis and Surgailis (1990) for the case r = 1.

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    Bibliographic Info

    Article provided by Elsevier in its journal Stochastic Processes and their Applications.

    Volume (Year): 45 (1993)
    Issue (Month): 1 (March)
    Pages: 169-182

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    Handle: RePEc:eee:spapps:v:45:y:1993:i:1:p:169-182

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    Cited by:
    1. Casas, Isabel & Gao, Jiti, 2006. "Econometric estimation in long-range dependent volatility models: Theory and practice," MPRA Paper 11981, University Library of Munich, Germany, revised Aug 2007.
    2. Ravishanker, Nalini & Ray, Bonnie K., 2002. "Bayesian prediction for vector ARFIMA processes," International Journal of Forecasting, Elsevier, vol. 18(2), pages 207-214.
    3. Peter M Robinson & J Vidal Sanz, 2005. "Modified Whittle Estimation of Multilateral Models on a Lattice," STICERD - Econometrics Paper Series /2005/492, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    4. Pai, Jeffrey & Ravishanker, Nalini, 2009. "A multivariate preconditioned conjugate gradient approach for maximum likelihood estimation in vector long memory processes," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1282-1289, May.
    5. Hosoya, Yuzo, 1996. "The quasi-likelihood approach to statistical inference on multiple time-series with long-range dependence," Journal of Econometrics, Elsevier, vol. 73(1), pages 217-236, July.
    6. Zaffaroni, Paolo & d'Italia, Banca, 2003. "Gaussian inference on certain long-range dependent volatility models," Journal of Econometrics, Elsevier, vol. 115(2), pages 199-258, August.
    7. Arteche, Josu, 2004. "Gaussian semiparametric estimation in long memory in stochastic volatility and signal plus noise models," Journal of Econometrics, Elsevier, vol. 119(1), pages 131-154, March.
    8. Hualde, Javier, 2013. "A simple test for the equality of integration orders," Economics Letters, Elsevier, vol. 119(3), pages 233-237.
    9. 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.
    10. Gao, Jiti, 2002. "Modeling long-range dependent Gaussian processes with application in continuous-time financial models," MPRA Paper 11973, University Library of Munich, Germany, revised 18 Sep 2003.
    11. Jaroslav Mohapl, 1998. "On Maximum Likelihood Estimation for Gaussian Spatial Autoregression Models," Annals of the Institute of Statistical Mathematics, Springer, vol. 50(1), pages 165-186, March.
    12. Ayache, Antoine & Lévy Véhel, Jacques, 2004. "On the identification of the pointwise Hölder exponent of the generalized multifractional Brownian motion," Stochastic Processes and their Applications, Elsevier, vol. 111(1), pages 119-156, May.
    13. Beran, Jan & Ghosh, Sucharita & Schell, Dieter, 2009. "On least squares estimation for long-memory lattice processes," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2178-2194, November.
    14. Gao, jiti & Anh, vo & Heyde, christopher, 1999. "Statistical estimation of nonstationaryGaussian processes with long-range dependence and intermittency," MPRA Paper 11972, University Library of Munich, Germany, revised 23 Oct 2001.
    15. Pai, Jeffrey & Ravishanker, Nalini, 2009. "Maximum likelihood estimation in vector long memory processes via EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4133-4142, October.
    16. Leonenko, N.N. & Sakhno, L.M., 2006. "On the Whittle estimators for some classes of continuous-parameter random processes and fields," Statistics & Probability Letters, Elsevier, vol. 76(8), pages 781-795, April.


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