logdensity_admkr: Compute the marginal likelihood using Chib's (1995) method
In bbefkr: Bayesian bandwidth estimation and semi-metric selection for the functional kernel regression with unknown error density

The log marginal likelihood can be computed as the log likelihood + log prior - log posterior. The latter one can be estimated from the MCMC.

1	logdensity_admkr(tau2, cpost)

`tau2`	Squared bandwidths recorded at each iteration
`cpost`	Squared bandwidths recorded at only the iteration defined by the variable `step`

The value of the estimated posterior density

Han Lin Shang

S. Chib (1995) ‘Marginal likelihood from the Gibbs output’, Journal of the American Statistical Association, 90(432), 1313-1321.

bbefkr documentation built on May 2, 2019, 3:04 a.m.

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