Bianchi, Alessandra and Campanino, Massimo and Crimaldi, Irene Asymptotic Normality of a Hurst Parameter Estimator Based on the Modified Allan Variance. International Journal of Stochastic Analysis, 2012. pp. 1-20. ISSN 2090-3332 (2012)Full text not available from this repository.
In order to estimate the memory parameter of Internet traffic data, it has been recently proposed a log-regression estimator based on the so-called modified Allan variance (MAVAR). Simulations have shown that this estimator achieves higher accuracy and better confidence when compared with other methods. In this paper we present a rigorous study of the MAVAR log-regression estimator. In particular, under the assumption that the signal process is a fractional Brownian motion, we prove that it is consistent and asymptotically normally distributed. Finally, we discuss its connection with the wavelets estimators.
|Uncontrolled Keywords:||modified Allan variance, log-regression estimator, fractional Brownian motion, long-range dependence, self-similarity|
|Subjects:||H Social Sciences > HA Statistics
Q Science > QA Mathematics
|Research Area:||Economics and Institutional Change|
|Depositing User:||Irene Crimaldi|
|Date Deposited:||28 Nov 2012 13:24|
|Last Modified:||29 Nov 2012 13:17|
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