| Autor: |
Cerqueti, Roy, Mattera, Raffaele, Scepi, Germana |
| Předmět: |
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| Zdroj: |
Computational Statistics; Feb2024, Vol. 39 Issue 1, p51-92, 42p |
| Abstrakt: |
This paper proposes a clustering approach for multivariate time series with time-varying parameters in a multiway framework. Although clustering techniques based on time series distribution characteristics have been extensively studied, methods based on time-varying parameters have only recently been explored and are missing for multivariate time series. This paper fills the gap by proposing a multiway approach for distribution-based clustering of multivariate time series. To show the validity of the proposed clustering procedure, we provide both a simulation study and an application to real air quality time series data. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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