Summary Methods for CCA and PLS objects
Produce summary methods for class "rcc", "pls" and
"spls".
## S3 method for class 'mixo_pls'
summary(
object,
what = c("all", "communalities", "redundancy", "VIP"),
digits = 4,
keep.var = FALSE,
...
)
## S3 method for class 'mixo_spls'
summary(
object,
what = c("all", "communalities", "redundancy", "VIP"),
digits = 4,
keep.var = FALSE,
...
)
## S3 method for class 'rcc'
summary(
object,
what = c("all", "communalities", "redundancy"),
cutoff = NULL,
digits = 4,
...
)
## S3 method for class 'pca'
summary(object, ...)object |
object of class inherited from |
what |
character string or vector. Should be a subset of
|
digits |
integer, the number of significant digits to use when
printing. Defaults to |
keep.var |
Logical. If |
... |
not used currently. |
cutoff |
real between 0 and 1. Variables with all correlations components below this cut-off in absolute value are not showed (see Details). |
The information in the rcc, pls or spls object is
summarised, it includes: the dimensions of X and Y data, the
number of variates considered, the canonical correlations (if object
of class "rcc") and the (s)PLS algorithm used (if object of
class "pls" or "spls") and the number of variables selected on
each of the sPLS components (if x of class "spls").
"communalities" in what gives Communalities Analysis.
"redundancy" display Redundancy Analysis. "VIP" gives the
Variable Importance in the Projection (VIP) coefficients fit by pls
or spls. If what is "all", all are given.
For class "rcc", when a value to cutoff is specified, the
correlations between each variable and the equiangular vector between
X- and Y-variates are computed. Variables with at least one
correlation componente bigger than cutoff are showed. The defaults is
cutoff=NULL all the variables are given.
The function summary returns a list with components:
ncomp |
the number of components in the model. |
cor |
the canonical correlations. |
cutoff |
the cutoff used. |
keep.var |
list containing the name of the variables selected. |
mode |
the algoritm used in |
Cm |
list containing the communalities. |
Rd |
list containing the redundancy. |
VIP |
matrix of VIP coefficients. |
what |
subset of
|
digits |
the number of significant digits to use when printing. |
method |
method used: |
Sébastien Déjean, Ignacio González, Kim-Anh Lê Cao, Al J Abadi
## summary 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) more <- summary(nutri.res, cutoff = 0.65) ## Not run: ## summary for objects of class 'pls' data(linnerud) X <- linnerud$exercise Y <- linnerud$physiological linn.pls <- pls(X, Y) more <- summary(linn.pls) ## summary 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)) more <- summary(toxicity.spls, what = "redundancy", keep.var = TRUE) ## End(Not run)
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