International Society of Science and Applied Technologies |
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Markov Chain Monte Carlo Approach for Burr Type XII Distribution | ||||
Author | Jianping Zhu
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Co-Author(s) | Hua Xin; Junge Sun; Tzong-Ru Tsai
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Abstract | A Markov chain Monte Carlo procedure for the parameter estimation of three-parameter Burr type XII (3pBurrXII) distribution is analytically derived using the Metropolis-Hastings algorithm, and named the M-H MCMC method. The proposed M-H MCMC method is operational for practitioners and can be used to obtain reliable maximum likelihood estimates or Bayes estimates of the 3pBurrXII distribution parameters. The application of the proposed M-H MCMC method is illustrated with an example about the lifetimes of oil-well pumps.
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Keywords | Gamma distribution, Gibbs sampling, important sampling, Markov chain Monte Carlo method, maximum likelihood estimation | |||
Article #: 23-020 |
August 3-5, 2017 - Chicago, Illinois, U.S.A. |