#-------------------------------------------------------------------
## function for cross validation using linear model
#-------------------------------------------------------------------
runlinear=function(
x,
y,
nPredics,
fwerRate=0.25,
adjust_method="fdr"
){
results=list()
bootResu<-lm_sparse(x = x, y = y)
p_value_est<-bootResu[,4]
p_value_est_noint<-p_value_est[-seq(1,length(p_value_est),by=(nPredics+1))]
p_value_est_noint_adj<-p.adjust(p_value_est_noint,adjust_method)
p_value_est_noint_adj[is.na(p_value_est_noint_adj)]<-1
coef_est<-abs(bootResu[,1])
coef_est_noint<-coef_est[-seq(1,length(coef_est),by=(nPredics+1))]
coef_est_noint[is.na(coef_est_noint)]<-max(coef_est_noint,na.rm = TRUE)
# return
results$betaNoInt=p_value_est_noint_adj<fwerRate
results$betaInt=p_value_est
results$coef_est_noint=coef_est_noint
return(results)
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.