bbemkr (version 1.2)

bbeloglikelihood: Calculate the log likelihood used in the Chib's (1995) log marginal density

Description

Calculates the log likelihood using the estimated averaged bandwidths of the regressors and estimated averaged variance of the error density

Usage

bbeloglikelihood(data_x, data_y, x, sigma, kerntype = c("Gaussian", 
    "Epanechnikov", "Quartic", "Triweight", "Triangular", "Uniform"))

Arguments

data_x

Regressors

data_y

Response variable

x

Estimated averaged bandwidths of the regressors, obtained after the MCMC iterations

sigma

Estimated averaged variance of the error density, obtained after the MCMC iterations

kerntype

Type of the kernel function. By default, Gaussian kernel is used

Value

• The value of log likelihood, with parameters estimated from the MCMC iterations

Details

According to Chib (1995), the log marginal density = loglikelihood + logprior - logdensity

References

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.

See Also

bbelogpriors, bbelogdensity, bbeMCMCrecording