Nothing
library(BART)
N = 1000
P = 5 #number of covariates
C = 8
set.seed(12)
x.train=matrix(runif(N*P, -2, 2), N, P)
Ey.train = x.train[ , 1]^3
y.train=rnorm(N, Ey.train, 3)
##run BART with C cores in parallel
post.est = mc.gbart(x.train, y.train, mc.cores=C, seed=99,
sigest=3)
post.fix = mc.gbart(x.train, y.train, mc.cores=C, seed=99,
lambda=0, sigest=3)
plot(post.est$yhat.train.mean, post.fix$yhat.train.mean)
print(cor(post.est$yhat.train.mean, post.fix$yhat.train.mean))
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