%J International Journal of Stochastic Analysis
%R 10.1155/2012/905082
%D 2012
%V 2012
%A Alessandra Bianchi
%A Massimo Campanino
%A Irene Crimaldi
%L eprints1434
%I Hindawi Publishing Corporation
%X 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.
%T Asymptotic Normality of a Hurst Parameter Estimator Based on the Modified Allan Variance
%P 1-20
%K modified Allan variance, log-regression estimator, fractional Brownian motion, long-range dependence, self-similarity