Journal of the Korean Statistical Society

The Korean Statistical Society (한국통계학회)
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Maximum Likelihood Estimation for the Laplacian Autoregressive Time Series Model

  • Son, Young-Sook (Department of Statistics, Chonnam National University) ;
  • Cho, Sin-Sup (Department of Statistics, Seoul National University)
  • Published : 1996.09.01
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Abstract

The maximum likelihood estimation is discussed for the NLAR model with Laplacian marginals. Since the explicit form of the estimates cannot be obtained due to the complicated nature of the likelihood function we utilize the automatic computer optimization subroutine using a direct search complex algorithm. The conditional least square estimates are used as initial estimates in maximum likelihood procedures. The results of a simulation study for the maximum likelihood estimates of the NLAR(1) and the NLAR(2) models are presented.

Keywords

References

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  3. Journal of Royal Statistical Society, Series B v.50 Consistent estimates for the NEAR(2) and NLAR(2) time series models Karlsen, H.;Tjostheim,D.
  4. The Annals of Statistics v.6 On conditional least squares estimation for stochastic processes Klimko, L.A.;Nelson, P.I.
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