eigenvals  R Documentation 
Function extracts eigenvalues from an object that has them. Many multivariate methods return such objects.
eigenvals(x, ...)
## S3 method for class 'cca'
eigenvals(x, model = c("all", "unconstrained", "constrained"),
constrained = NULL, ...)
## S3 method for class 'decorana'
eigenvals(x, kind = c("additive", "axiswise", "decorana"),
...)
## S3 method for class 'eigenvals'
summary(object, ...)
x 
An object from which to extract eigenvalues. 
object 
An 
model 
Which eigenvalues to return for objects that inherit from class

constrained 
Return only constrained eigenvalues. Deprecated as of vegan
2.50. Use 
kind 
Kind of eigenvalues returned for 
... 
Other arguments to the functions (usually ignored) 
This is a generic function that has methods for cca
,
wcmdscale
, pcnm
, prcomp
,
princomp
, dudi
(of ade4), and
pca
and pco
(of
labdsv) result objects. The default method also
extracts eigenvalues if the result looks like being from
eigen
or svd
. Functions
prcomp
and princomp
contain square roots
of eigenvalues that all called standard deviations, but
eigenvals
function returns their squares. Function
svd
contains singular values, but function
eigenvals
returns their squares. For constrained ordination
methods cca
, rda
and
capscale
the function returns the both constrained and
unconstrained eigenvalues concatenated in one vector, but the partial
component will be ignored. However, with argument
constrained = TRUE
only constrained eigenvalues are returned.
The summary
of eigenvals
result returns eigenvalues,
proportion explained and cumulative proportion explained. The result
object can have some negative eigenvalues (wcmdscale
,
dbrda
, pcnm
) which correspond to
imaginary axes of Euclidean mapping of nonEuclidean distances
(Gower 1985). In these case real axes (corresponding to positive
eigenvalues) will "explain" proportion >1 of total variation, and
negative eigenvalues bring the cumulative proportion to
1. capscale
will only find the positive eigenvalues
and only these are used in finding proportions. For
decorana
the importances and cumulative proportions
are only reported for kind = "additive"
, because other
alternatives do not add up to total inertia of the input data.
An object of class "eigenvals"
, which is a vector of
eigenvalues.
The summary
method returns an object of class
"summary.eigenvals"
, which is a matrix.
Jari Oksanen.
Gower, J. C. (1985). Properties of Euclidean and nonEuclidean distance matrices. Linear Algebra and its Applications 67, 81–97.
eigen
, svd
, prcomp
,
princomp
, cca
, rda
,
capscale
, wcmdscale
,
cca.object
.
data(varespec)
data(varechem)
mod < cca(varespec ~ Al + P + K, varechem)
ev < eigenvals(mod)
ev
summary(ev)
## choose which eignevalues to return
eigenvals(mod, model = "unconstrained")
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