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The Markov order is a crucial measure of the memory of a process and its information is essential for appropriate simulation of aspects of the process. In this paper we suggest a robust and straightforward exact significance test based on generating surrogate data to assess the Markov order of a time series. This method is valid for any sample size and certifies a uniform sampling from the set of sequences that definitely have the nth order characteristics of the observed data. The Markov property and order of IEEE802.11a errors are investigated using this test.

Testing The Order of Markov Dependence in Error Data of IEEE802.11a Standard