Factor modeling for clustering high-dimensional time series
We propose a new unsupervised learning method for clustering a large number of time series based on a latent factor structure. Each cluster is characterized by its own cluster-specific factors in addition to some common factors which impact on all the time series concerned. Our setting also offers t...
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| Main Authors: | , , , |
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| 其他作者: | |
| 格式: | Article |
| 語言: | English |
| 出版: |
2023
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| 主題: | |
| 在線閱讀: | https://hdl.handle.net/10356/172172 |
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