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#Helper function to compute linear gregElasticNet total for bootstrapping
library(glmnet)
gregElasticNett <- function(data, xpopd, indices, alpha, lambda){
#data: 1st column:y, 2nd column:pis, rest: xsample_d
d <- data[indices,]
#y
y <- d[,1]
#pis
pis <- d[,2]
#Length of xsample_d
p <- dim(d)[2] - 2
#xsample_d
xsample_d <- d[, 3:(p + 2)]
#beta-hats
pred.mod <- glmnet(x = as.matrix(xsample_d[,-1]), y = y, alpha = alpha, family = "gaussian", standardize = FALSE, weights = pis^{-1})
beta_hat <- predict(pred.mod, s = lambda, type = "coefficients")[1:dim(xsample_d)[2],]
return(beta_hat %*% (xpopd) + t(y - xsample_d %*% beta_hat) %*% pis^(-1))
}
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