selection {Blend} | R Documentation |
Variable selection for a Blend object
Description
Variable selection for a Blend object
Usage
selection(obj, sparse)
Arguments
obj |
Blend 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:
method |
posterior samples from the MCMC |
indices |
a list of indices and names of selected variables |
summary |
a summary of selected variables |
References
Ren, J., Zhou, F., Li, X., Ma, S., Jiang, Y. and Wu, C. (2023). Robust Bayesian variable selection for gene-environment interactions. Biometrics, 79(2), 684-694 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(dat)
## sparse
fit = Blend(y,x,t,J,kn,degree)
selected=selection(fit,sparse=TRUE)
selected
## non-sparse
fit = Blend(y,x,t,J,kn,degree,sparse="FALSE")
selected=selection(fit,sparse=FALSE)
selected