BayesMfp Methods | R Documentation |
Print the object (print
),
get fitted values (fitted
) and corresponding residuals (residuals
).
## S3 method for class 'BayesMfp'
print(x, ...)
## S3 method for class 'BayesMfp'
fitted(object, design = getDesignMatrix(object), post =
getPosteriorParms(object, design = design), ...)
## S3 method for class 'BayesMfp'
residuals(object, ...)
x |
valid |
object |
valid |
design |
design matrix of the first model in the object, which can be supplied by the caller if it is computed beforehand |
post |
posterior parameters of the normal-gamma distribution (defaults to the posterior expected mean, marginalized over the covariance factor g) |
... |
unused |
Daniel Saban\'es Bov\'e
BayesMfp
, BmaSamples Methods
## 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")
## the print method
test
## extract fitted values and corresponding residuals
fitted(test)
residuals(test)
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