grf::causal_forest with low overlap

gistfile1.txt

library(grf)

n <- 100

# X ~ Unif[-5,-2]+[2, 5]
X <- matrix(c(seq(-5, -2, length.out=n/2), seq(2, 5, length.out=n/2)), n, 1)

# P( W=1 | X > 0) = 1  and  P( W=1 | X < 0) = 1
W <- matrix(X[,1] > 0, n, 1)

# Some model
Y <- sin(X*W)

# What does W.hat look like?
cf_w <- grf::regression_forest(X=X, Y=W)
W.hat <- predict(cf_w)$predictions
plot(X, W.hat)

# Truth vs estimated
cf <- grf::causal_forest(X, Y, W) # No error
taux <- sin(X) - sin(0)
tauhatx <- predict(cf)$predictions

plot(taux, tauhatx)