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R-estimation for ARMA models

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Author Info

  • Allal, Jelloul
  • Kaaouachi, Abdelali
  • Paindaveine, Davy

Abstract

This paper is devoted to the R-estimation problem for the parameter of a stationary ARMA model. The asymptotic uniform linearity of a suitable vector of rank statistics leads to the asymptotic normality of √n-consistent R-estimates resulting from the minimization of the norm of this vector. By using a discretized √n-consistent preliminary estimate, we construct a new class of one-step R-estimators. We compute the asymptotic relative efficiency of the proposed estimators with respect to the LS estimator. Efficiency properties are investigated via a Monte-Carlo study in the particular case of an AR(1) model.

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File URL: http://mpra.ub.uni-muenchen.de/21167/
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Bibliographic Info

Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 21167.

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Date of creation: 2001
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Handle: RePEc:pra:mprapa:21167

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Related research

Keywords: R-estimation; ARMA models; local asymptotic normality; asymptotic linearity;

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References

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  1. Hallin, M. & Puri, M. L., 1994. "Aligned Rank Tests for Linear Models with Autocorrelated Error Terms," Journal of Multivariate Analysis, Elsevier, vol. 50(2), pages 175-237, August.
  2. Marc Hallin & Jean-François Ingenbleek & Madan L. Puri, 1984. "Linear serial rank tests for randomness against ARMA alternatives," ULB Institutional Repository 2013/2167, ULB -- Universite Libre de Bruxelles.
  3. Marc Hallin, 1994. "On the Pitman nonadmissibility of correlogram-based time series methods," ULB Institutional Repository 2013/2049, ULB -- Universite Libre de Bruxelles.
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Cited by:
  1. Hallin, Marc & Swan, Yvik & Verdebout, Thomas & Veredas, David, 2013. "One-step R-estimation in linear models with stable errors," Journal of Econometrics, Elsevier, vol. 172(2), pages 195-204.

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