Least Absolute Deviation Estimation for Regression with ARMA Errors

Richard A. Davis and William T. M. Dunsmuir
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Richard A. Davis: Colorado State University
William T. M. Dunsmuir: University of New South Wales

Journal of Theoretical Probability, 1997, vol. 10, issue 2, 481-497

Abstract: Abstract The asymptotic normality for least absolute deviation estimates of the parameters in a linear regression model with autoregressive moving average errors is established under very general conditions. The method of proof is based on a functional limit theorem for the LAD objective function.

Keywords: ARMA process; regression; least absolute deviation estimation; central limit theorem (search for similar items in EconPapers)
Date: 1997
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DOI: 10.1023/A:1022620818679

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