Accept – reject Metropolis – Hastings sampling and marginal likelihood estimation

@inproceedings{Olin2005AcceptR,
  title={Accept – reject Metropolis – Hastings sampling and marginal likelihood estimation},
  author={John M. Olin},
  year={2005}
}
We describe a method for estimating the marginal likelihood, based on CHIB (1995) and CHIB and JELIAZKOV (2001), when simulation from the posterior distribution of the model parameters is by the accept– reject Metropolis–Hastings (ARMH) algorithm. The method is developed for one-block and multiple-block ARMH algorithms and does not require the (typically) unknown normalizing constant of the proposal density. The problem of calculating the numerical standard error of the estimates is also… CONTINUE READING
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