BayesMfp Methods {bfp} | 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
## 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)