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 an other method of common use based on wavelet analysis. Here we link it to the wavelets setting and stress why a different analysis for the two approaches is required. We then focus on the asymptotic analysis of the MAVAR log-regression estimator and provide new formulas for the related confidence intervals. By numerical evaluation, we analyze these formulas and make a comparison between three suitable choices on the regression weights, also optimizing over different choices on the data progression.

Analysis of a Hurst Parameter Estimator Based on the Modified Allan Variance

Crimaldi I;
2012-01-01

Abstract

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 an other method of common use based on wavelet analysis. Here we link it to the wavelets setting and stress why a different analysis for the two approaches is required. We then focus on the asymptotic analysis of the MAVAR log-regression estimator and provide new formulas for the related confidence intervals. By numerical evaluation, we analyze these formulas and make a comparison between three suitable choices on the regression weights, also optimizing over different choices on the data progression.
2012
978-1-4673-0921-9
Self-similarity,Long range dependence; Modified Allan variance; Hurst parameter estimator
File in questo prodotto:
File Dimensione Formato  
Article-BiaBreCriFer-Globecom2012-06503362.pdf

non disponibili

Licenza: Non specificato
Dimensione 1.46 MB
Formato Adobe PDF
1.46 MB Adobe PDF   Visualizza/Apri   Richiedi una copia
ArticleISBN-BiaBreCriFer-Globecom2012-06503053.pdf

non disponibili

Licenza: Non specificato
Dimensione 30.69 kB
Formato Adobe PDF
30.69 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11771/2969
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
social impact