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A Generalization of the k-Means Method for Trends of Time Series

In: Quantitative Methods and Data Analysis in Applied Demography - Volume 2

Author

Listed:
  • Norio Watanabe

    (Chuo University, Department of Data Science for Business Innovation)

Abstract

The clustering is one of important methods in multivariate analysis. The clustering of time series is also important and several clustering methods are available. Recently, a k-means type method was proposed for trends of time series. In this method each object for clustering consists of univariate time series. In this study, a generalization of this method is proposed for the case where each object consists of multivariate time series. The applicability of the proposed method is examined by simulation studies. Moreover the clustering of time series on COVID-19 cases is considered by applying the proposed method.

Suggested Citation

  • Norio Watanabe, 2025. "A Generalization of the k-Means Method for Trends of Time Series," The Springer Series on Demographic Methods and Population Analysis, in: Christos H. Skiadas & Charilaos Skiadas (ed.), Quantitative Methods and Data Analysis in Applied Demography - Volume 2, chapter 0, pages 51-63, Springer.
    • Handle: RePEc:spr:ssdmcp:978-3-031-82279-7_6
    DOI: 10.1007/978-3-031-82279-7_6
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