Abstract
Two new approaches to robust time series modelling are proposed. These approaches are natural generalisations of the Yule—Walker and the least squares methods. The approaches generate further a few viable estimators. Simulation experiments are conducted to investigate the relative efficiency and the breakdown bounds of these estimators. Copyright © 1990 Gordon and Breach, Science Publishers, Inc.
Original language | English |
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Pages (from-to) | 209-255 |
Journal | Journal of Statistical Computation and Simulation |
Volume | 34 |
Issue number | 4 |
DOIs | |
Publication status | Published - 1990 |
Citation
Lo, C. L., & Li, W. K. (1990). Two new approaches to robust estimation in time series. Journal of Statistical Computation and Simulation, 34(4), 209-255. doi: 10.1080/00949659008811228Keywords
- Additive outliers
- Innovation outliers
- Autoregressive model
- Breakdown bound
- Robust autocorrelation
- Robust covariance matrix