• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Measurement of dependence for random values and practical usage

Student: Filyakin Denis

Supervisor: Alexander P. Koldanov

Faculty: Faculty of Informatics, Mathematics, and Computer Science (HSE Nizhny Novgorod)

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Final Grade: 8

Year of Graduation: 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.

Full text (added May 17, 2018)

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses