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- W2807899554 abstract "In Chap. 2, the use of SSA for analyzing one-dimensional data is thoroughly examined. In this chapter, the use of models is minimal so that the main techniques can be considered as non-parametric and descriptory. Relations with algorithms of space rotation and many other methods aiming at achieving better separability of signal from noise are outlined. The common problems of smoothing, filtration, and splitting of a time series into identifiable components such as trend, seasonality, and noise are thoroughly discussed and illustrated on case studies with real data. An important issue of automatization of the SSA methods is also considered in detail." @default.
- W2807899554 created "2018-06-21" @default.
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- W2807899554 date "2018-01-01" @default.
- W2807899554 modified "2023-09-27" @default.
- W2807899554 title "SSA Analysis of One-Dimensional Time Series" @default.
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- W2807899554 doi "https://doi.org/10.1007/978-3-662-57380-8_2" @default.
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