Articles

EXACT MAXIMUM LIKELIHOOD ESTIMATOR FOR DRIFT FRACTIONAL BROWNIAN MOTION AT DISCRETE OBSERVATION

  • HU Yao-Zhong ,
  • Nualart David ,
  • XIAO Wei-Lin ,
  • ZHANG Wei-Guo
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  • Department of Mathematics, University of Kansas, 405 Snow Hall, Lawrence, Kansas 66045-2142, USA; School of Business and Administration, South China University of Technology, Guangzhou 510641, China

Received date: 2010-03-27

  Revised date: 2010-07-11

  Online published: 2011-09-20

Supported by

This work was supported by the National Science Foundations (DMS0504783; DMS0604207), National Science Fund for Distinguished Young Scholars of China (70825005).

Abstract

This paper deals with the problems of consistency and strong consistency of the maximum likelihood estimators of the mean and variance of the drift fractional Brownian motions observed at discrete time instants. Both the central limit theorem and the Berry-Ess´een bounds for these estimators are obtained by using the Stein’s method via Malliavin calculus.

Cite this article

HU Yao-Zhong , Nualart David , XIAO Wei-Lin , ZHANG Wei-Guo . EXACT MAXIMUM LIKELIHOOD ESTIMATOR FOR DRIFT FRACTIONAL BROWNIAN MOTION AT DISCRETE OBSERVATION[J]. Acta mathematica scientia, Series B, 2011 , 31(5) : 1851 -1859 . DOI: 10.1016/S0252-9602(11)60365-2

References

[1] Beran J. Statistics for Long-Memory Processes. New York: Chapman and Hall, 1994

[2] Biagini F, Hu Y, Øksendal B, Zhang T. Stochastic Calculus for Fractional Brownian Motion and Appli-cations. New York: Springer-Verlag, 2008

[3] Fox R, Taqqu M S. Large-sample properties of parameter estimates for strongly dependent stationary Gaussian time series. Ann Statist, 1986, 14(2): 517–532

[4] Golub G H, van Loan C F. Matrix Computations. 3rd ed. Baltimore and London: Hopkins University Press, 1996

[5] Hannan E J. The asymptotic theory of linear time-series models. J Appl Probability. 1973, 10(3): 130–145

[6] Hu Y. A unified approach to several inequalities for Gaussian and diffusion measures//Az´ema J, Emery M, Ledoux M, Yor M, ed. S´eminaire de Probabilit´es XXXIV. Lecture Notes in Math Vol 1729. Berlin: Springer-Verlag, 2000: 329–335

[7] Hu Y, Nualart D. Parameter estimation for fractional Ornstein-Uhlenbeck processes. Statist Probab Lett, 2010, 80(11/12): 1030–1038.

[8] Nourdin I, Peccati G. Stein’s method and exact Berry-Ess´een asymptotics for functionals of Gaussian fields. Ann Probab, 2009, 37(6): 2231–2261

[9] Nualart D. The Malliavin Calculus and Related Topics. 2nd ed. Berlin: Springer-Verlag, 2006

[10] Nualart D, Ortiz S. Central limit theorems for multiple stochastic integrals and Malliavin calculus. Stoc Proc Appl, 2008, 118(4): 614–628

[11] Palma W. Long-Memory Time Series: Theory and Methods. Hoboken, New Jersey: Wiley-Interscience, 2007

[12] Paxson V. Fast, approximate synthesis of fractional Gaussian noise for generating self-similar network traffic. Comput Commun Rev, 1997, 27(5): 5–18

[13] Privault N, R´eveillac A. Stein estimation for the drift of Gaussian processes using the Malliavin calculus. Ann Statist, 2008, 36(5): 2531–2550

[14] Wei L, Zhang W. Empirical Bayes test problems for variance components in randon effects model. Acta Math Sci, 2005, 25B(2): 274–282

[15] Zhang W, Wei L. The superiority of empirical Bayes estimation of parameters in partitioned normal linear model. Acta Math Sci, 2008, 28B(4): 955–962

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