Study of automatic choice of parameters for forecasting in singular spectrum analysis.
Source
Statistics and its Interface. v. 16, 1, p. 109-116
Author
Al-Marhoobiyah, Safia.
Publisher
International Press, Inc.
English abstract
Singular spectrum analysis (SSA) is a popular tool for analysing and forecasting time series. The SSA forecasting algorithms have two parameters which should be chosen by the researcher or using the so-called automatic choice based on the root mean squared errors (RMSE) of retrospective forecasts. We study the sensitivity of the RMSE and investigate the reliability of the automatic choice of parameters for forecasting monthly temperature and humidity recorded at three meteorological stations in Oman.
