Detection of Heterogeneity in Three-Dimensional Data Sequences: Algorithm and Applications

Authors

  • Evgueni A. Haroutunian Institute for Informatics and Automation Problems of NAS RA
  • Irina A. Safaryan Institute for Informatics and Automation Problems of NAS RA
  • Aram R. Nazaryan Institute for Informatics and Automation Problems of NAS RA
  • Narine S. Harutyunyan Institute for Informatics and Automation Problems of NAS RA

Keywords:

Change-point problem, Rank score test, Threshold copula, Cut-point selection method

Abstract

We present a nonparametric algorithm which allows reducing the investigations of changes of the joint distribution of chronologically ordered multidimensional random sequence to the investigations of some one-dimensional conditional distributions. The algorithm is implemented with the statistical software package R. The action of the program is demonstrated on applications. The first one concerns the retrospective analysis of the changes in the concentration of chemical components of ground water preceding major seismic events. The second refers to the definition of cut-points in two-dimensional life time data sets of the imatinib-treated chronic myeloid leukemia patients.

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Published

2021-12-10

How to Cite

Haroutunian, E. A. ., Safaryan, I. A. ., Nazaryan, A. R. ., & Harutyunyan, N. S. . (2021). Detection of Heterogeneity in Three-Dimensional Data Sequences: Algorithm and Applications. Mathematical Problems of Computer Science, 42, 63–72. Retrieved from http://mpcs.sci.am/index.php/mpcs/article/view/216

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