## generate a BayesMfp object
set.seed(19)
x1 <- rnorm(n=15)
x2 <- rbinom(n=15, size=20, prob=0.5)
x3 <- rexp(n=15)
y <- rt(n=15, df=2)
test <- BayesMfp(y ~ bfp (x2, max = 4) + uc (x1 + x3), nModels = 100,
method="exhaustive")
## predict new responses at (again random) covariates
predict(test,
newdata = list(x1 = rnorm (15),
x2 = rbinom (n=15, size=5, prob=0.2) + 1,
x3 = rexp (15)))
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