mixOmics (version 6.3.0)

print: Print Methods for CCA, (s)PLS, PCA and Summary objects

Description

Produce print methods for class "rcc", "pls", "spls", "pca", "rgcca", "sgcca" and "summary".

Usage

# S3 method for rcc
print(x, …)
# S3 method for pls
print(x, …)
# S3 method for spls
print(x, …)
# S3 method for pca
print(x, …)
# S3 method for spca
print(x, …)
# S3 method for rgcca
print(x, …)
# S3 method for sgcca
print(x, …)
# S3 method for summary
print(x, …)

Arguments

x

object of class inheriting from "rcc", "pls", "spls", "pca", "spca", "rgcca", "sgcca"or "summary".

…

not used currently.

Details

print method for "rcc", "pls", "spls" "pca", "rgcca", "sgcca" 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).

See Also

rcc, pls, spls, vip.

Examples

# NOT RUN {
## print for objects of class 'rcc'
data(nutrimouse)
X <- nutrimouse$lipid
Y <- nutrimouse$gene
nutri.res <- rcc(X, Y, ncomp = 3, lambda1 = 0.064, lambda2 = 0.008)
print(nutri.res)

## print for objects of class 'summary'
more <- summary(nutri.res, 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)
# }