loglikelihood_admkr {bbemkr} | R Documentation |
Log marginal likelihood = Log likelihood + Log prior - Log density
loglikelihood_admkr(h2, data_x, data_y)
h2 |
Square of re-parameterized bandwidths |
data_x |
Regressors |
data_y |
Response variable |
Calculates the log likelihood using the estimated averaged bandwidths of the regressors and estimated averaged variance of the error density
The value of log likelihood, with parameters (bandwidths) estimated from the MCMC iterations
Han Lin Shang
S. Chib and I. Jeliazkov (2001) Marginal likelihood from the Metropolis-Hastings output, Journal of the American Statistical Association, 96, 453, 270-281.
S. Chib (1995) Marginal likelihood from the Gibbs output, Journal of the American Statistical Association, 90, 432, 1313-1321.
M. A. Newton and A. E. Raftery (1994) Approximate Bayesian inference by the weighted likelihood bootstrap (with discussion), Journal of the Royal Statistical Society, 56, 3-48.
logpriors_admkr
, logdensity_admkr
, mcmcrecord_admkr