cov_chol_admkr: Calculate log marginal likelihood from MCMC output
In bbemkr: Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error
Description
Usage
Arguments
Value
Author(s)
References
See Also
View source: R/cov_chol_admkr.R
Description
It is a type of candidate estimator for calculating log marginal likelihood, where the MCMC outputs are used for estimating posterior density.
Usage
1
cov_chol_admkr(xpost, alpha, data_x, data_y)
Arguments
xpost
MCMC output
alpha
Quantile of the critical value in calculating Geweke's log marginal likelihood
data_x
Regressors
data_y
Response variable
Value
Log marginal likelihood
Author(s)
Han Lin Shang
References
J. Geweke (1998) Using simulation methods for Bayesian econometric models: inference, development, and communication, Econometric Reviews, 18(1), 1-73.
See Also
LaplaceMetropolis_admkr, logdensity_admkr, logpriors_admkr, loglikelihood_admkr, mcmcrecord_admkr
bbemkr documentation built on May 1, 2019, 10:53 p.m.
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Description Usage Arguments Value Author(s) References See Also
View source: R/cov_chol_admkr.R
Description
It is a type of candidate estimator for calculating log marginal likelihood, where the MCMC outputs are used for estimating posterior density.
Usage
1 | cov_chol_admkr(xpost, alpha, data_x, data_y)
|
Arguments
xpost |
MCMC output |
alpha |
Quantile of the critical value in calculating Geweke's log marginal likelihood |
data_x |
Regressors |
data_y |
Response variable |
Value
Log marginal likelihood
Author(s)
Han Lin Shang
References
J. Geweke (1998) Using simulation methods for Bayesian econometric models: inference, development, and communication, Econometric Reviews, 18(1), 1-73.
See Also
LaplaceMetropolis_admkr, logdensity_admkr, logpriors_admkr, loglikelihood_admkr, mcmcrecord_admkr
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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