Abstract
SSA (Singular Spectrum Analysis) starts to become a popular method in decomposing time series into some separable and interpretable series. This study provides an error evaluation in the SSA-based model for trend and multiple seasonal time series forecasting. This error evaluation is obtained by means of a numerical study on the mean square error of the estimators and mean absolute percentage error of the forecast values. Four distinct types of data generating processes (DGP) with varying sample sizes are considered in this experimental study. The parameters are estimated from the component series of SSA. Each DGP is decomposed into trend, periodic and irregular components. All these components except the irregular one are fitted by appropriate deterministic function separately. Based on the numerical simulation results, the estimated parameters are closer to the true values as the sample size increases. As the illustrative example of the real data set implementation, we used the monthly atmospheric concentrations of CO2 from Moana Loa observatory for period January 1959 to June 1972. The proposed method produces better forecast values than the results of SSA-LRF (Linear Recurrent Formula) and TLSAR (Two Level Seasonal Autoregressive). The results encourage the improvement in the time series modeling on the more complex pattern.
Highlights
Singular Spectrum Analysis (SSA) is a method in time series analysis
The stronger the correlation is shown by the darker the color and the weaker the correlation or the stronger the separability is shown by the lighter color
The simulation study of error evaluation in trend and multiple seasonal time series forecasting based on SSA is presented
Summary
SSA (singular spectrum analysis) is a method in time series analysis. The origination of this method is always associated with the publication of Broomhead and King (1986).Pak.j.stat.oper.res. SSA (singular spectrum analysis) is a method in time series analysis. The origination of this method is always associated with the publication of Broomhead and King (1986). Winita Sulandari, Subanar, Suhartono, Herni Utami, Muhammad Hisyam Lee. Though, in the same year, Fraedrich (1986) developed the SSA and applied the method to the weather and climate system. A number of studies on SSA and its application have been carried out (see, for example, Hassani et al (2009), Hassani et al (2010), Hassani and Zhigljavsky (2009), Vautard and Ghil (1991), and Vautardet al. A number of studies on SSA and its application have been carried out (see, for example, Hassani et al (2009), Hassani et al (2010), Hassani and Zhigljavsky (2009), Vautard and Ghil (1991), and Vautardet al. (1992))
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