JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE) ›› 2025, Vol. 60 ›› Issue (3): 116-126.doi: 10.6040/j.issn.1671-9352.0.2023.474

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Bayesian parametric estimations for spatial error models based on slice-Gibbs sampling

LI Aogui1, ZHAO Yuanying2,3*   

  1. 1. College of Mathematics and Statistic, Guizhou University, Guiyang 550025, Guizhou, China;
    2. College of Science, Guiyang University, Guiyang 550005, Guizhou, China;
    3. Department of Railway Engineering, Guizhou Communications Polytechnic University, Guiyang 551400, Guizhou, China
  • Published:2025-03-10

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Abstract: A Markov chain Monte Carlo(MCMC)technique called the slice-Gibbs sampling algorithm is proposed to calculate joints Bayesian estimations of unknown parameters for spatial error models, the proposed algorithm and Bayesian approach are illustrated by two simulation studies, the model and methodology are demonstrated by a real example.

Key words: Bayesian estimation, Gibbs sampling, slice sampling, spatial error model

CLC Number: 

  • O212.8
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