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
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Likelihood:
mpg ~ regress({mpg:_cons},{sigma2})
Priors:
{mpg:_cons} ~ normal(0,10000)
{sigma2} ~ igamma(.01,.01)
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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
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| 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
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Note: Default priors are used for model parameters.
HTML Code:
. margins, dydx(*) atmeans post last estimates not found r(301);
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