relation: http://eprints.imtlucca.it/1132/
title: Analysis of a Hurst parameter estimator based on the modified Allan variance
creator: Bianchi, Alessandra
creator: Bregni, Stefano
creator: Crimaldi, Irene
creator: Ferrari, Marco
subject: HA Statistics
subject: QA Mathematics
description: In order to estimate the Hurst 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 of common use. Here we link it to the wavelets setting and provide an asymptotic analysis in the case the signal process is a fractional Brownian motion. In particular we show that the MAVAR log-regression estimator is consistent and asymptotically normal, providing the related confidence intervals for a suitable choice on the regression weights. Finally, we show some numerical examples.
date: 2012
type: Working Paper
type: NonPeerReviewed
identifier:   Bianchi, Alessandra and Bregni, Stefano and Crimaldi, Irene and Ferrari, Marco  Analysis of a Hurst parameter estimator based on the modified Allan variance.  Technical Report       (Submitted)   
relation: 3214