summary | R Documentation |
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 algorithm 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
rcc
, pls
, spls
,
vip
.
## 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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