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Bootstrap Procedures for Online Monitoring of Changes in Autoregressive Models |
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| Authors: | Z Hlávka M Hušková C Kirch S G Meintanis |
| Institution: | 1. Department of Statistics, Faculty of Mathematics and Physics, Charles University in Prague, Prague, Czech Republic;2. Institute of Stochastics, Karlsruhe Institute of Technology, Karlsruhe, Germany;3. Department of Economics, National and Kapodistrian University of Athens, Athens, Greece;4. Unit for Business Mathematics and Informatics, North-West University, Potchefstroom, South Africa |
| Abstract: | We compare the behavior of several bootstrap procedures for monitoring changes in the error distribution of autoregressive time series. The proposed procedures are designed to control the overall significance level and include classical tests based on the empirical distribution function as well as Fourier-type methods that utilize the empirical characteristic function, both functions being computed on the basis of properly estimated residuals. The Monte Carlo study incorporates different estimators and a variety of sampling situations with and without outliers. |
| Keywords: | Bootstrap Change point analysis Empirical distribution function Robustness Time series |