cov_chol: Calculate log marginal likeliood from MCMC output
In bbemkr: Bayesian bandwidth estimation for multivariate kernel regression with Gaussian error
Description
Usage
Arguments
Value
Author(s)
References
See Also
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
Arguments
xpost
MCMC output
data_x
Regressor
data_y
Response
alpha
Quantile of the critical value in calculating Geweke's log marginal likelihood
prior_p
Hyperparameter of the inverse-gamma prior
prior_st
Hyperparameter of inverse-gamma prior
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_gaussian, logdensity_gaussian, logpriors_gaussian, loglikelihood_gaussian, mcmcrecord_gaussian
bbemkr documentation built on May 1, 2019, 10:53 p.m.
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Description Usage Arguments Value Author(s) References See Also
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 |
Arguments
xpost |
MCMC output |
data_x |
Regressor |
data_y |
Response |
alpha |
Quantile of the critical value in calculating Geweke's log marginal likelihood |
prior_p |
Hyperparameter of the inverse-gamma prior |
prior_st |
Hyperparameter of inverse-gamma prior |
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_gaussian, logdensity_gaussian, logpriors_gaussian, loglikelihood_gaussian, mcmcrecord_gaussian
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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