Statistics and Its Interface
Volume 16 (2023)
Study of automatic choice of parameters for forecasting in singular spectrum analysis
Pages: 109 – 116
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.
recurrent SSA, vector SSA, temperature, humidity
2010 Mathematics Subject Classification
The work of A. Pepelyshev was partially supported by the Russian Foundation for Basic Research (project no. 20-01-00096).
Received 28 April 2021
Accepted 6 November 2021
Published 27 July 2022