Selected article for: "MCMC Markov Chain Monte Carlo method and posterior distribution"
Author: Mizumoto, Kenji; Chowell, Gerardo
Title: Transmission potential of the novel coronavirus (COVID-19) onboard the diamond Princess Cruises Ship, 2020
  • Document date: 2020_2_29
    • ID: ue7g2vpx_15
    Snippet: We estimated model parameters and made projections using a Monte Carlo Markov Chain (MCMC) method in a Bayesian framework. Point estimates and corresponding 95% credibility intervals were drawn from the posterior probability distribution. All statistical analyses were conducted in R version 3.5.2 (R Foundation for Statistical Computing, Vienna, Austria) and the 'rstan' package (No-U-Turn-Sampler (NUTS)) (see Table 1 )......
    Document: We estimated model parameters and made projections using a Monte Carlo Markov Chain (MCMC) method in a Bayesian framework. Point estimates and corresponding 95% credibility intervals were drawn from the posterior probability distribution. All statistical analyses were conducted in R version 3.5.2 (R Foundation for Statistical Computing, Vienna, Austria) and the 'rstan' package (No-U-Turn-Sampler (NUTS)) (see Table 1 ).

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