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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Denis Filyakin
Measurement of dependence for random values and practical usage
8
2018
The task of identifying network structures is one of the most important when working with complex networks. Its solution is necessary to obtain the necessary information about the nature of the network, its parameters, which in turn is necessary for solving many practical problems, for example, prediction tasks when working with the network model of the stock market. In turn, working with the network model of the market largely depends on which measure of the dependence of the random variables lies at its basis. The paper presents data on the comparison of the three communication measures - the Pearson correlation, the Spearman correlation, and the sign correlation function at various time intervals.

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