Theoretical and Applied Aspects of Automating Multivariate Analysis Procedures

  • O. V. SyuntyurenkoEmail author
General Section


This paper addresses some important theoretical and applied aspects of modern computer science that are associated with analytical processing of scientific, technical, and economic information. The main trends in using automated non-parametric procedures for logical and mathematical processing of arrays (flows) of digital data are discussed. Some methodological aspects of developing new technological approaches and algorithms for analytical post-processing that allow one to design a wide range of multi-step procedures for assessment and multivariate analysis of scientific, technical, and economic data based on polygram estimation of functionals are considered. It is shown that the procedures and algorithms based on these methods of non-parametric statistics and multivariate data analysis can be useful in various applications, including the development of analytical technologies for big data.


computer science data analysis analytical post-processing non-parametric statistics cluster analysis forecasting and big data 


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© Allerton Press, Inc. 2018

Authors and Affiliations

  1. 1.Library for Natural SciencesRussian Academy of SciencesMoscowRussia

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