## 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")
## now draw samples from the Bayesian model average
testBma <- BmaSamples (test)
## the print method:
testBma
## the fitted method:
fitted(testBma)
## and the corresponding residuals:
residuals(testBma)
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