Displaying similar documents to “Time series analysis: recursive methods and their modifications for time series with outliers and missing observations.”

Computational aspects of robust Holt-Winters smoothing based on M -estimation

Christophe Croux, Sarah Gelper, Roland Fried (2008)

Applications of Mathematics

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To obtain a robust version of exponential and Holt-Winters smoothing the idea of M -estimation can be used. The difficulty is the formulation of an easy-to-use recursive formula for its computation. A first attempt was made by Cipra (Robust exponential smoothing, J. Forecast. (1992), 57–69). The recursive formulation presented there, however, is unstable. In this paper, a new recursive computing scheme is proposed. A simulation study illustrates that the new recursions result in smaller...

Dynamic credibility with outliers and missing observations

Tomáš Cipra (1996)

Applications of Mathematics

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In actuarial practice the credibility models must face the problem of outliers and missing observations. If using the M -estimation principle from robust statistics in combination with Kalman filtering one obtains the solution of this problem that is acceptable in the numerical framework of the practical actuarial credibility. The credibility models are classified as static and dynamic in this paper and the shrinkage is used for the final ratemaking.

Exponential smoothing and resampling techniques in time series prediction

Maria Manuela Neves, Clara Cordeiro (2010)

Discussiones Mathematicae Probability and Statistics

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Time series analysis deals with records that are collected over time. The objectives of time series analysis depend on the applications, but one of the main goals is to predict future values of the series. These values depend, usually in a stochastic manner, on the observations available at present. Such dependence has to be considered when predicting the future from its past, taking into account trend, seasonality and other features of the data. Some of the most successful forecasting...