| print {integrOmics} | R Documentation |
Produce print methods for class "rcc",
"pls", "spls" and "summary".
## S3 method for class 'rcc': print(x, ...) ## S3 method for class 'pls': print(x, ...) ## S3 method for class 'spls': print(x, ...) ## S3 method for class 'summary': print(x, ...)
x |
object of class inheriting from "rcc", "pls", "spls" or "summary". |
... |
not used currently. |
print method for "rcc", "pls" or "spls" class,
returns a description of the x object including: the function used, the regularization
parameters (if x of class "rcc"),
the (s)PLS algorithm used (if x of class "pls" or "spls"),
the samples size,
the number of variables selected on each of the sPLS components (if x of class "spls")
and the available components of the object.
print method for "summary" class,
gives the (s)PLS algorithm used (if x of class "pls" or "spls"),
the number of variates considered,
the canonical correlations (if x of class "rcc"),
the number of variables selected on each of the sPLS components (if x of class "spls")
and the available components for Communalities Analysis,
Redundancy Analysis and Variable Importance in the Projection (VIP).
Sébastien Déjean Ignacio González and Kim-Anh Lę Cao.
## print for objects of class 'rcc'
data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, lambda1 = 0.064, lambda2 = 0.008)
print(nutri.res)
## print for objects of class 'summary'
more <- summary(nutri.res, ncomp = 3, cutoff = 0.65)
print(more)
## print for objects of class 'pls'
data(linnerud)
X <- linnerud$exercise
Y <- linnerud$physiological
linn.pls <- pls(X, Y)
print(linn.pls)
## print for objects of class 'spls'
data(liver.toxicity)
X <- liver.toxicity$gene
Y <- liver.toxicity$clinic
toxicity.spls <- spls(X, Y, ncomp = 3, keepX = c(50, 50, 50),
keepY = c(10, 10, 10))
print(toxicity.spls, what = "redundancy", keep.var = TRUE)