A statistical method for corrupt agents detection

Yury A. Pichugin, Oleg A. Malafeyev, Denis Рылов, Irina Zaitseva

Research outputpeer-review

25 Citations (Scopus)

Abstract

The statistical method is used to identify the hidden leaders of the corruption structure. The method is based on principal component analysis (PCA), linear regression, and Shannon's information. It is applied to study the time series data of corrupt financial activity. Shannon's quantity of information is specified as a function of two arguments: a vector of hidden corruption factors and a subset of corrupt agents. Several optimization problems are solved to determine the contribution of corresponding corrupt agents to the total illegal behavior. An illustrative example is given.

Original languageEnglish
Title of host publicationINTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2017)
EditorsCharalambos Tsitouras, Theodore Simos
Place of PublicationThessaloniki
PublisherAmerican Institute of Physics
Number of pages4
Volume1978
ISBN (Print)978-0-7354-1690-1
DOIs
Publication statusPublished - 10 Jul 2018
EventInternational Conference of Numerical Analysis and Applied Mathematics (ICNAAM) - Thessaloniki
Duration: 25 Sep 201730 Sep 2017

Publication series

NameAIP Conference Proceedings
PublisherAmerican Institute of Physics
Number1
Volume1978
ISSN (Print)0094-243X

Conference

ConferenceInternational Conference of Numerical Analysis and Applied Mathematics (ICNAAM)
CountryGreece
CityThessaloniki
Period25/09/1730/09/17

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    Pichugin, Y. A., Malafeyev, O. A., Рылов, D., & Zaitseva, I. (2018). A statistical method for corrupt agents detection. In C. Tsitouras, & T. Simos (Eds.), INTERNATIONAL CONFERENCE OF NUMERICAL ANALYSIS AND APPLIED MATHEMATICS (ICNAAM 2017) (Vol. 1978). [100014] (AIP Conference Proceedings; Vol. 1978, No. 1). American Institute of Physics. https://doi.org/10.1063/1.5043758, https://doi.org/10.1063/1.5043758