The PCA-seq method applied to analyze of the dynamics of COVID-19 epidemic indicators

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The PCA-seq method applied to analyze of the dynamics of COVID-19 epidemic indicators	942 KB	Adobe Acrobat PDF	Read	Download
DOI Доступ к ресурсу на сайте издателя			10.1088/1742-6596/1715/1/012025

Title: The PCA-seq method applied to analyze of the dynamics of COVID-19 epidemic indicators
Creator: Efimov, Vadim M.
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Polunin, D. A.
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Kovaleva, Vera Yu.
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Efimov, K. V.
Date: 2021
DOI: 10.1088/1742-6596/1715/1/012025
Description: In time series analysis using the SSA method, a univariate series is converted into the multivariate one by shifts. The resulting trajectory matrix is subjected to principal component analysis (PCA). However, the principal components can also be computed using the PCA-Seq method if segments of the original series are selected as objects. The matrix of Euclidean distances between the objects can be obtained using any method, which offers additional opportunities for time series analysis compared to the conventional SSA. In this study, the PCA-Seq method was used to analyze the dynamics of COVID-19 epidemic indicators.