## construct 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 = 200, method="exhaustive")
## get the design matrix of the fifth best model
a <- bfp:::getDesignMatrix(test[5])
attr(a, "shifts")
## and once again but without centering
b <- bfp:::getDesignMatrix(test[5], center=FALSE)
stopifnot(all(attr(b, "shifts") == 0))
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