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Robust Trend Estimation for AR(1) Disturbances

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  • Fried, Roland
  • Gather, Ursula

Abstract

We discuss the robust estimation of a linear trend if the noise follows an autoregressive process of first order. We find the ordinary repeated median to perform well except for negative correlations. In this case it can be improved by a Prais-Winsten transformation using a robust autocorrelation estimator.

Suggested Citation

  • Fried, Roland & Gather, Ursula, 2004. "Robust Trend Estimation for AR(1) Disturbances," Technical Reports 2004,64, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    • Handle: RePEc:zbw:sfb475:200464
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    References listed on IDEAS

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    3. Meintanis, S. G. & Donatos, G. S., 1999. "Finite-sample performance of alternative estimators for autoregressive models in the presence of outliers," Computational Statistics & Data Analysis, Elsevier, vol. 31(3), pages 323-339, September.
    4. Chipman, John S, 1979. "Efficiency of Least-Squares Estimation of Linear Trend when Residuals are Autocorrelated," Econometrica, Econometric Society, vol. 47(1), pages 115-128, January.
    5. Beach, Charles M & MacKinnon, James G, 1978. "A Maximum Likelihood Procedure for Regression with Autocorrelated Errors," Econometrica, Econometric Society, vol. 46(1), pages 51-58, January.
    6. Park, Rolla Edward & Mitchell, Bridger M., 1980. "Estimating the autocorrelated error model with trended data," Journal of Econometrics, Elsevier, vol. 13(2), pages 185-201, June.
    7. Yanyuan Ma & Marc G. Genton, 2000. "Highly Robust Estimation of the Autocovariance Function," Journal of Time Series Analysis, Wiley Blackwell, vol. 21(6), pages 663-684, November.
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