relation: http://eprints.imtlucca.it/1434/
title: Asymptotic Normality of a Hurst Parameter Estimator Based on the Modified Allan Variance
creator: Bianchi, Alessandra
creator: Campanino, Massimo
creator: Crimaldi, Irene
subject: HA Statistics
subject: QA Mathematics
description: 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.
publisher: Hindawi Publishing Corporation
date: 2012
type: Article
type: PeerReviewed
identifier:   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)  
relation: http://www.hindawi.com/journals/ijsa/2012/905082/
relation: 10.1155/2012/905082