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Robust time series analysis: a survey. (English) Zbl 0652.62088
Kybernetika 23, Suppl. No. 1-5, 92 pp. (1987).
The paper is divided into 5 chapters. The first chapter introduces general concepts of robustness and standard time series models. The second chapter is devoted to maximum likelihood type estimation (MLTE) in AR and ARMA models. Robust estimation of the location of ARMA models is also included.
Generalized MLTE is described in the third chapter. Some sub-sections are devoted to determining outlier type and to model selection problems. The next chapter deals with robust filtering and robust smoothing. The last chapter contains some Monte Carlo results and topics for further research.
The authors explain basic ideas and important properties of the described procedures. The proofs of assertions are not given in the paper, but the reader is systematically informed where they can be found.
The paper is a readable review of robust methods in time series analysis and brings clear description of algorithms of the corresponding numerical procedures.
Reviewer: J.Anděl

62M10 Time series, auto-correlation, regression, etc. in statistics (GARCH)
62F35 Robustness and adaptive procedures (parametric inference)
Full Text: EuDML
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