Abstract
Singular Spectrum Analysis (SSA) is a promising non-parametric time series modelling technique that has proved to be successful in data preprocessing in diverse application fields. It is a window length-based method and the appropriate selection of window length plays a crucial role in the accuracy of SSA. However, there are no specific methods depicted in the literature about its selection. In this study, the method of SSA in time series analysis is presented in detail and a sensitivity analysis of window length is carried out based on an observed daily rainfall time series.
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Unnikrishnan, P., Jothiprakash, V. (2018). Selection of Window Length in Singular Spectrum Analysis of a Time Series. In: Bertail, P., Blanke, D., Cornillon, PA., Matzner-Løber, E. (eds) Nonparametric Statistics. ISNPS 2016. Springer Proceedings in Mathematics & Statistics, vol 250. Springer, Cham. https://doi.org/10.1007/978-3-319-96941-1_21
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DOI: https://doi.org/10.1007/978-3-319-96941-1_21
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