Research output: Contribution to Journal/Magazine › Journal article › peer-review
<mark>Journal publication date</mark> | 2011 |
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<mark>Journal</mark> | Journal of Applied Statistics |
Issue number | 7 |
Volume | 38 |
Number of pages | 27 |
Pages (from-to) | 1407-1433 |
Publication Status | Published |
<mark>Original language</mark> | English |
Long-range-dependent time series are endemic in the statistical analysis of Internet traffic. The Hurst parameter provides a good summary of important self-similar scaling properties. We compare a number of different Hurst parameter estimation methods and some important variations. This is done in the context of a wide range of simulated, laboratory-generated, and real data sets. Important differences between the methods are highlighted. Deep insights are revealed on how well the laboratory data mimic the real data. Non-stationarities, which are local in time, are seen to be central issues and lead to both conceptual and practical recommendations.