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Statistical estimation of nonstationaryGaussian processes with long-range dependence and intermittency


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  • Gao, jiti
  • Anh, vo
  • Heyde, christopher
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This paper considers statistical inference for nonstationaryGaussian processes with long-range dependence and intermittency. The existence of such a process has been established by Anh et al. (J. Statist. Plann. Inference 80 (1999) 95–110). We systematically consider the case where the spectral densityof nonstationaryGaussian processes with stationaryincrements is of a general and

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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 11972.

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Date of creation: 13 Dec 1999
Date of revision: 23 Oct 2001
Publication status: Published in Stochastic Processes and Their Applications 1.99(2002): pp. 295-323
Handle: RePEc:pra:mprapa:11972

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Keywords: Asymptotic theory; fractional Riesz–Bessel motion; nonstationary process; long-range dependence; statistical estimation;

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  1. Peter M. Robinson, 1997. "Large-sample inference for nonparametric regression with dependent errors," LSE Research Online Documents on Economics, London School of Economics and Political Science, LSE Library 302, London School of Economics and Political Science, LSE Library.
  2. Hardle, Wolfgang & LIang, Hua & Gao, Jiti, 2000. "Partially linear models," MPRA Paper 39562, University Library of Munich, Germany, revised 01 Sep 2000.
  3. 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, Elsevier, vol. 45(1), pages 169-182, March.
  4. Viano, M. C. & Deniau, C. & Oppenheim, G., 1994. "Continuous-time fractional ARMA processes," Statistics & Probability Letters, Elsevier, Elsevier, vol. 21(4), pages 323-336, November.
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Cited by:
  1. Casas, Isabel, 2008. "Estimation of stochastic volatility with LRD," Mathematics and Computers in Simulation (MATCOM), Elsevier, Elsevier, vol. 78(2), pages 335-340.
  2. 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.
  3. 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, Elsevier, vol. 76(8), pages 781-795, April.
  4. 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.
  5. Anh, V.V. & Leonenko, N.N. & Sakhno, L.M., 2007. "Statistical inference using higher-order information," Journal of Multivariate Analysis, Elsevier, Elsevier, vol. 98(4), pages 706-742, April.


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