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.Abstract
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.
| Item Type: | Article |
|---|---|
| Identification Number: | https://doi.org/10.1155/2012/905082 |
| 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 |
| URI: | http://eprints.imtlucca.it/id/eprint/1434 |
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