Assume that you run a model with the "bayes" prefix. For the sake of the argument, let us assume this very simple example.
Code:
sysuse auto bayes: reg mpg
HTML Code:
Burn-in ... Simulation ... Model summary ------------------------------------------------------------------------------ Likelihood: mpg ~ regress({mpg:_cons},{sigma2}) Priors: {mpg:_cons} ~ normal(0,10000) {sigma2} ~ igamma(.01,.01) ------------------------------------------------------------------------------ Bayesian linear regression MCMC iterations = 12,500 Random-walk Metropolis-Hastings sampling Burn-in = 2,500 MCMC sample size = 10,000 Number of obs = 74 Acceptance rate = .4189 Efficiency: min = .1705 avg = .1924 Log marginal likelihood = -244.88981 max = .2144 ------------------------------------------------------------------------------ | Equal-tailed | Mean Std. Dev. MCSE Median [95% Cred. Interval] -------------+---------------------------------------------------------------- mpg | _cons | 21.30411 .6781437 .014646 21.32258 19.96519 22.60581 -------------+---------------------------------------------------------------- sigma2 | 34.45136 5.848324 .141647 33.74739 24.79315 47.5186 ------------------------------------------------------------------------------ Note: Default priors are used for model parameters.
HTML Code:
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