selection {mixedBayes} | R Documentation |
Variable selection for a mixedBayes object
Description
Variable selection for a mixedBayes object
Usage
selection(obj, sparse)
Arguments
obj |
mixedBayes object. |
sparse |
logical flag. If TRUE, spike-and-slab priors will be used to shrink coefficients of irrelevant covariates to zero exactly.. |
Details
If sparse, the median probability model (MPM) (Barbieri and Berger, 2004) is used to identify predictors that are significantly associated with the response variable. Otherwise, variable selection is based on 95% credible interval. Please check the references for more details about the variable selection.
Value
an object of class ‘selection’ is returned, which is a list with component:
inde |
a vector of indicators of selected effects. |
References
Ren, J., Zhou, F., Li, X., Ma, S., Jiang, Y. and Wu, C. (2022). Robust Bayesian variable selection for gene-environment interactions. Biometrics, (in press) doi:10.1111/biom.13670
Barbieri, M.M. and Berger, J.O. (2004). Optimal predictive model selection. Ann. Statist, 32(3):870–897
See Also
Examples
data(data)
## sparse
fit = mixedBayes(y,e,X,g,w,k,structure=c("group"))
selected=selection(fit,sparse=TRUE)
selected
## non-sparse
fit = mixedBayes(y,e,X,g,w,k,sparse=FALSE,structure=c("group"))
selected=selection(fit,sparse=FALSE)
selected