ON THE EFFECTS OF NON-STATIONARITY IN LONG-RANGE DEPENDENCE TESTS

Careful statistical analyses indicate that the measured tr affic traces from live packet networks often contain non-stationary effects like level shifts or polyno mial trends. In these cases several popular tests for long-range dependence can result in wrong conclus ions and unreliable estimate of the Hurst parameter. In this paper both analytical and simulation inv estigations of the implications of these effects on several tests are presented. The results are also dem nstrated with examples based on measured ATM traces. The use of these results can be utilized to avoid pitfalls in LRD traffic modeling.

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