Two new approaches to robust estimation in time series

Chan Lam LO, Wai Keung LI

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1 Citation (Scopus)

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 languageEnglish
Pages (from-to)209-255
JournalJournal of Statistical Computation and Simulation
Volume34
Issue number4
DOIs
Publication statusPublished - 1990

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Robust Estimation
Time series
Estimator
Time Series Modelling
Relative Efficiency
Least Square Method
Simulation Experiment
Breakdown
Experiments
Robust estimation
Generalization

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: 10.1080/00949659008811228

Keywords

  • Additive outliers
  • Innovation outliers
  • Autoregressive model
  • Breakdown bound
  • Robust autocorrelation
  • Robust covariance matrix