On multivariate network analysis of statistical data sets with different measures of association
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The main goal of the present paper is the development of a general framework of multivariate network analysis of statistical data sets. A general method of multivariate network construction, on the basis of measures of association, is proposed. In this paper we consider Pearson correlation network, sign similarity network, Fechner correlation network, Kruskal correlation network, Kendall correlation network, and the Spearman correlation network. The problem of identification of the threshold graph in these networks is discussed. Different multiple decision statistical procedures are proposed. It is shown that a statistical procedure used for threshold graph identification in one network can be efficiently used for any other network. Our approach allows us to obtain statistical procedures with desired properties for any network.
KeywordsNetwork analysis Multivariate networks Statistical data sets Measures of association Threshold graph Multiple decision statistical procedures
Mathematics Subject Classification (2010)Primary 90B15 Secondary 62H15 62H20
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