library(hdm)
set.seed(1)
n = 100 #sample size
p = 100 # number of variables
s = 7 # number of non-zero variables
X = matrix(rnorm(n*p), ncol=p)
colnames(X) <- paste("X", 1:p, sep="")
beta = c(rep(3,s), rep(0,p-s))
y = 1 + X%*%beta + rnorm(n)
data = data.frame(cbind(y,X))
colnames(data)[1] <- "y"
lasso.effect = rlassoEffects(X, y, index=c(1,2,3,50),
method = "double selection")
coef(lasso.effect) # standard use of coef() - without selection matrix
# with selection matrix
coef(lasso.effect, selection.matrix = TRUE)
# prettier output with print_coef (identical options as coef())
print_coef(lasso.effect, selection.matrix = TRUE)
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