Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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Bayesian Estimation via the Griddy Gibbs Sampling for the Laplacian Autoregressive Time Series Model

  • Young Sook Son (Department of Statistics, Chonnam National University, Kwangju, 500-757) ;
  • Sinsup Cho (Department of Computer Science and Statistics, Seoul National University, Seoul, 151-742.)
  • Published : 1995.12.01
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Abstract

This paper deals with the Bayesian estimation for the NLAR(1) model with Laplacian marginals. Assuming the independent uniform priors for two parameters of the NLAT(1) model, the griddy Gbbs sampler by Ritter and Tanner(1992) is used to obtain the Bayesian estimates. Random numbers generated form the uniform priors ate used as the grids for each parameter. Some simulations are conducted and compared with the maximum likelihood estimation result.

Keywords

References

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