EMVSbest: Select the Best Model with EMVS
In EMVS: The Expectation-Maximization Approach to Bayesian Variable Selection
Description
Usage
Arguments
Value
Author(s)
References
See Also
Description
EMVSbest outputs indices of the variables included in the model with the highest posterior probability found.
Usage
1
EMVSbest(result)
Arguments
result
List object outputed by the EMVS procedure
Value
log_g_function
The highest log-g-function found along the regularization path
indices
The indices of the variables included in the best model found
Author(s)
Veronika Rockova
References
Rockova, V. and George, E. I. (2014) EMVS: The EM Approach to Bayesian Variable Selection. Journal of the American Statistical Association
See Also
EMVS documentation built on Oct. 13, 2021, 5:09 p.m.
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Description Usage Arguments Value Author(s) References See Also
Description
EMVSbest outputs indices of the variables included in the model with the highest posterior probability found.
Usage
1 | EMVSbest(result)
|
Arguments
result |
List object outputed by the EMVS procedure |
Value
log_g_function |
The highest log-g-function found along the regularization path |
indices |
The indices of the variables included in the best model found |
Author(s)
Veronika Rockova
References
Rockova, V. and George, E. I. (2014) EMVS: The EM Approach to Bayesian Variable Selection. Journal of the American Statistical Association
See Also
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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