scores
function is generic in
vegan, and vegan ordination functions have their own
scores
functions that are documented separately with the
method (see e.g. scores.cca
,
scores.metaMDS
, scores.decorana
). This
help file documents the default scores
method that is only
used for non-vegan ordination objects.
"scores"(x, choices, display=c("sites", "species"), ...)
sites
or
species
.scores
is a generic method in vegan. Several
vegan functions have their own scores
methods with their
own defaults and with some new arguments. This help page describes
only the default method. For other methods, see, e.g.,
scores.cca
, scores.rda
,
scores.decorana
. All vegan ordination functions should have a scores
method which should be used to extract the scores instead of
directly accessing them. Scaling and transformation of scores should
also happen in the scores
function. If the scores
function is available, the results can be plotted using
ordiplot
, ordixyplot
etc., and the
ordination results can be compared in procrustes
analysis.
The scores.default
function is used to extract scores from
non-vegan ordination results. Many standard ordination
methods of libraries do not have a specific class
, and no
specific method can be written for them. However,
scores.default
guesses where some commonly used functions
keep their site scores and possible species scores.
If x
is a matrix, scores.default
returns the chosen
columns of that matrix, ignoring whether species or sites were
requested (do not regard this as a bug but as a feature, please).
Currently the function seems to work at least for isoMDS
,
prcomp
, princomp
and some ade4 objects.
It may work in other cases or fail mysteriously.
scores
functions include (but are not limited to)
scores.cca
, scores.rda
,
scores.decorana
, scores.envfit
,
scores.metaMDS
, scores.monoMDS
and
scores.pcnm
. These have somewhat different interface
-- scores.cca
in particular -- but all work with
keywords display="sites"
and return a matrix. However, they
may also return a list of matrices, and some other scores
methods will have quite different arguments.
data(varespec)
vare.pca <- prcomp(varespec)
scores(vare.pca, choices=c(1,2))
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