چکیده مقاله
Singular Spectrum Analysis SSA is a powerful and widely used non parametric method to analyze and forecast time series Although SSA has proven to outperform traditional parametric methods, one of the steps of the SSA algorithm is the singular value decomposition SVD of the trajectory matrix, which is very sensitive to the presence of outliers because it uses the 𝐿2 norm optimization The main aim of this paper is to introduce two robust alternatives to the SSA The proposed robust SSA alternatives are compared with the SSA and one available robust SSA algorithm, in terms of model fit via Monte Carlo simulations, considering several contamination scenarios
کلیدواژهها
نویسندگان
Mohammad Kazemi
Department of Statistics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
شیوه ارجاع
Kazemi, Mohammad,1400,Robust Analysis of Time Series,Fourth International Conference on Soft Computing
ارائهشده در
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