Zobrazeno 1 - 10
of 77
pro vyhledávání: '"A. P. Koldanov"'
Maximum spanning tree (MST) is a popular tool in market network analysis. Large number of publications are devoted to the MST calculation and it's interpretation for particular stock markets. However, much less attention is payed in the literature to
Externí odkaz:
http://arxiv.org/abs/2103.14593
Gaussian graphical model is a graphical representation of the dependence structure for a Gaussian random vector. It is recognized as a powerful tool in different applied fields such as bioinformatics, error-control codes, speech language, information
Externí odkaz:
http://arxiv.org/abs/1701.02071
Model selection for Gaussian concentration graph is based on multiple testing of pairwise conditional independence. In practical applications partial correlation tests are widely used. However it is not known whether partial correlation test is unifo
Externí odkaz:
http://arxiv.org/abs/1610.00316
Autor:
Semenov, L. P., Kalyagin, V. A., Koldanov, P. A., Batsyn, M. V., Golovanova, S. V., Voronina, M. A.
Different network structures are compiared with respect to degree of robustnes of identification statistical procedures. It is shown that threshold (market) graph, cliques and independent sets in the threshold (market) graphs are preferable network s
Externí odkaz:
http://arxiv.org/abs/1801.09883
Akademický článek
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Gaussian Graphical Model selection problem is considered. Concentration graph is identified by multiple decision procedure based on individual tests. Optimal unbiased individual tests are constructed. It is shown that optimal tests are equivalent to
Externí odkaz:
http://arxiv.org/abs/1604.06874
Statistical uncertainty of different filtration techniques for market network analysis is studied. Two measures of statistical uncertainty are discussed. One is based on conditional risk for multiple decision statistical procedures and another one is
Externí odkaz:
http://arxiv.org/abs/1311.2273
Investigation of the market graph attracts a growing attention in market network analysis. One of the important problem connected with market graph is to identify it from observations. Traditional way for the market graph identification is to use a s
Externí odkaz:
http://arxiv.org/abs/1512.06449
Autor:
P.A. Koldanov
Publikováno v:
Учёные записки Казанского университета. Серия Физико-математические науки, Vol 160, Iss 2, Pp 317-326 (2018)
Identification of network structures using the finite-size sample has been considered. The concepts of random variables network and network model, which is a complete weighted graph, have been introduced. Two types of network structures have been inv
Externí odkaz:
https://doaj.org/article/6786e13f3e664fa6aa8f2f55d58dbba8
Akademický článek
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