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- W4362508185 abstract "Principal Geodesic Analysis (PGA) is applied to a climate time series. First, we transform each multidimensional sequence into the path signature. Since the signature lives in a curved space, usual principal component analysis (PCA) is not applicable. Instead, we treat the signature space as a geodesic manifold. By replacing the notion of straight lines with that of geodesics, the domain of PCA can be extended to the curved space. Then, the first principal component is derived as the geodesic that minimizes the unexplained variance in the data. As an application, we computed the leading modes for one-year NINO SST time series, which are divided into segments that represent annual variations of monthly averages. It is interesting that some months in a year reveal characteristic undulations that could indicate the early signs of upcoming El Nin~{o} events." @default.
- W4362508185 created "2023-04-06" @default.
- W4362508185 creator A5035910453 @default.
- W4362508185 date "2023-03-29" @default.
- W4362508185 modified "2023-09-28" @default.
- W4362508185 title "Principal Geodesic Analysis applied to climate time series" @default.
- W4362508185 doi "https://doi.org/10.48550/arxiv.2303.17613" @default.
- W4362508185 hasPublicationYear "2023" @default.
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