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R-estimation for ARMA models

By Jelloul Allal, Abdelali Kaaouachi and Davy Paindaveine

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.

Topics: C13 - Estimation: General, C14 - Semiparametric and Nonparametric Methods: General
Year: 2001
OAI identifier: oai:mpra.ub.uni-muenchen.de:21167

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