Time series analysis: recursive methods and their modifications for time series with outliers and missing observations

• Autores: Tomáš Cipra, Juan Trujillo Mondéjar, Agripina Petra Rubio Flores
• Localización: Extracta mathematicae, ISSN-e 0213-8743, Vol. 6, Nº 2-3, 1991, págs. 64-95
• Idioma: inglés
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• Resumen

  • The recursive methods are popular in time series analysis since they are computationally efficient and flexible enough to treat various changes in character of data. This paper gives a survey of the most important type of these methods including their classification and relationships existing among them. Special attention is devoted to i) robustification of some recursive methods, capable of facing outliers in time series, and ii) modifications of recursive methods for time series with missing observations.