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Discussion of The Forward Search: Theory and Data Analysis by Anthony C. Atkinson, Marco Riani, and Andrea Ceroli

  • Søren Johansen

    (Department of Economics, University of Copenhagen)

  • Bent Nielsen

    (Department of Economics, University of Oxford)

The Forward Search Algorithm is a statistical algorithm for obtaining robust estimators of regression coefficients in the presence of outliers. The algorithm selects a succession of subsets of observations from which the parameters are estimated. The present note shows how the theory of empirical processes can contribute to the understanding of how the subsets are chosen and how the sequence of estimators is changing.

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File URL: http://www.econ.ku.dk/english/research/publications/wp/dp_2010/1006.pdf/
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Paper provided by University of Copenhagen. Department of Economics in its series Discussion Papers with number 10-06.

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Length: 13 pages
Date of creation: Feb 2010
Date of revision:
Handle: RePEc:kud:kuiedp:1006
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  1. David Hendry & Hans-Martin Krolzig, 2003. "The Properties of Automatic Gets Modelling," Economics Papers 2003-W14, Economics Group, Nuffield College, University of Oxford.
  2. E ric E ngler & B ent N ielsen, 2009. "The empirical process of autoregressive residuals," Econometrics Journal, Royal Economic Society, vol. 12(2), pages 367-381, 07.
  3. Kevin D. Hoover & Stephen J. Perez, 1999. "Data mining reconsidered: encompassing and the general-to-specific approach to specification search," Econometrics Journal, Royal Economic Society, vol. 2(2), pages 167-191.
  4. Søren Johansen & Bent Nielsen, 2008. "An analysis of the indicator saturation estimator as a robust regression," Discussion Papers 08-03, University of Copenhagen. Department of Economics.
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