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An experimental evaluation of choices of SSA forecasting parameters (2403.16507v1)

Published 25 Mar 2024 in cs.CE

Abstract: Six time series related to atmospheric phenomena are used as inputs for experiments offorecasting with singular spectrum analysis (SSA). Existing methods for SSA parametersselection are compared throughout their forecasting accuracy relatively to an optimal aposteriori selection and to a naive forecasting methods. The comparison shows that awidespread practice of selecting longer windows leads often to poorer predictions. It alsoconfirms that the choices of the window length and of the grouping are essential. Withthe mean error of rainfall forecasting below 1.5%, SSA appears as a viable alternative forhorizons beyond two weeks.

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References (28)
  1. “The approximation of one matrix by another of lower rank” In Psychometrika 1, 1936, pp. 211–218
  2. Roger Penrose “On best approximate solutions of linear matrix equations” In Mathematical Proceedings of the Cambridge Philosophical Society 52.1, 1956, pp. 17–19
  3. Leonard E. Baum “An Inequality and Associated Maximization Technique in Statistical Estimation of Probabilistic Functions of a Markov Process” In Inequalities 3, 1972, pp. 1–8
  4. David S. Broomhead and Gregory P. King “Extracting Qualitative Dynamics From Experimental Data” In Physica D: Nonlinear Phenomena 20, 1986, pp. 217–236
  5. Lawrence R. Rabiner “A tutorial on Hidden Markov Models and selected applications in speech” In Proceedings of the IEEE 77.2, 1989, pp. 257–286
  6. “Singular Spectrum Analysis in Nonlinear Dynamics with Applications to Paleoclimatic Time Series” In Physica D: Nonlinear Phenomena 35.3, 1989, pp. 395–424
  7. James R. Elsner and Anastasio A. Tsonis “Singular Spectrum Analysis: a New Tool in Time Series Analysis” Springer, 1996
  8. Nina Golyandina, Vladimir Nekrutkin and Anatol Zhigljavsky “Analysis of Time Series Structure: SSA and Related Mehtods” ChapmanHall, 2001
  9. Loyd R. Welch “Hidden Markov models and the Baum-Welch Algorithm” In IEEE Information Theory Society Newsletter 53.4, 2003, pp. 1\bibrangessep10–13 URL: http://www.itsoc.org/publications/nltr/it%5C_dec%5C_03final.pdf
  10. “The Singular Spectrum Analysis - MultiTaper Method (SSA-MTM) Toolkit”, UCLA Theoretical Climate Dynamics group, 2007 URL: http://research.atmos.ucla.edu/tcd/ssa/
  11. Peter Grünwald “The minimum description length principle” The MIT Press, 2007
  12. George Tzagkarakis, Maria Papadopouli and Panagiotis Tsakalides “Trend forecasting based on Singular Spectrum Analysis of traffic workload in a large-scale wireless LAN” In Performance Evaluation 66, 2009, pp. 173–190
  13. Md Atikur Rahman Khan and Donald S. Poskitt “Description Length Based Signal Detection in Singular Spectrum Analysis”, 2010, pp. 23 pp
  14. Daniel Hsu, Sham M. Kakade and Tong Zhang “A spectral algorithm for learning Hidden Markov Models” In Journal of Computer and System Sciences 78.5, 2012, pp. 1460–1480
  15. “Determine a proper window length for singular spectrum analysis” In IET International Conference on Radar Systems (Radar 2012), 2012, pp. 1–6
  16. Md Atikur Rahman Khan and Donald S. Poskitt “A note on window length selection in singular spectrum analysis” In Australian & New Zealand Journal of Statistics 55.2, 2013, pp. 87–108
  17. Md Atikur Rahman Khan and Donald S. Poskitt “Moment tests for window length selection in singular spectrum analysis of short– and long–memory processes” In Journal of Time Series Analysis 34.2, 2013, pp. 141–155
  18. Michael R. Thon and Herbert Jaeger “Links between multiplicity automata, observable operator models and predictive state representations: a unified learning framework” In Journal of Machine Learning Research 16, 2015, pp. 103–147
  19. “Selection of window length for singular spectrum analysis” In Journal of the Franklin Institute 352.4, 2015, pp. 1541–1560
  20. Md Atikur Rahman Khan and Donald S. Poskitt “Forecasting stochastic processes using singular spectrum analysis: Aspects of the theory and application” In International Journal of Forecasting 33.1, 2017, pp. 199–213
  21. Nina Golyandina, Anton Korobeynikov and Anatol Zhigljavsky “Singular Spectrum Analysis with R” Springer, 2018
  22. João P. Hespanha “Linear Systems Theory” Princeton University Press, 2018
  23. “Singular Spectrum Analysis for Time Series” Springer, 2020
  24. “Minimum description length revisited” In International Journal of Mathematics for Industry 11.1, 2020, pp. 29 pp
  25. Hansika Hewamalage, Christoph Bergmeir and Kasun Bandara “Recurrent Neural Networks for Time Series Forecasting: Current status and future directions” In International Journal of Forecasting 37.1, 2021, pp. 388–427
  26. “Rssa: a collection of methods for singular spectrum analysus”, The Comprehensive R Archive Network, 2021 URL: http://CRAN.R-project.org/package=Rssa
  27. “Image Completion in Embedded Space Using Multistage Tensor Ring Decomposition” In Frontiers in Artificial Intelligence 4, 2021, pp. 11 pp URL: https://doi.org/10.3389/frai.2021.687176
  28. Rob J Hyndman and George Athanasopoulos “Forecasting: Principles and Practice”, 2023 URL: https://otexts.com/fpp3/

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