Linear estimation of the regression model with arma disturbances: A simulation study

Askar H. Choudhury, Simon Power, Robert St Louis

Research output: Contribution to journalArticle

1 Scopus citations

Abstract

Koreisha and Pukkila (1990a) have recently proposed a computationally convenient three-step GLS-type linear estimator for the regression model with ARMA disturbances involving three sequential applications of least squares. One potential drawback to this estimation procedure is that it entails dropping a significant number of initial observations. This paper uses Monte Carlo methods to evaluate its performance vis-à-vis existing OLS and GLS linear estimators.

Original languageEnglish (US)
Pages (from-to)315-332
Number of pages18
JournalCommunications in Statistics Part B: Simulation and Computation
Volume26
Issue number1
DOIs
StatePublished - Jan 1 1997

Keywords

  • Approximate GLS estimator
  • Autocorrelation
  • Regression

ASJC Scopus subject areas

  • Statistics and Probability
  • Modeling and Simulation

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