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Erschienen in:
2003 | OriginalPaper | Buchkapitel
Robust Time Series Estimation via Weighted Likelihood
verfasst von : C. Agostinelli
Erschienen in: Developments in Robust Statistics
Verlag: Physica-Verlag HD
Enthalten in: Professional Book Archive
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In this paper we introduce a method for efficient and robust estimation of the unknown parameters of an autoregressive-moving average model based on weighted likelihood. Two types of outliers, i.e. additive and innovation, are taken into account without knowing their number, position or intensity. A new procedure is used to classify the outliers and to bound the impact of additive outliers in order to improve the breakdown point of the method. Two examples and a Monte Carlo simulation are presented.