Description Value NA Action and Subset capscale Note Author(s) References See Also Examples
Ordination methods cca
, rda
and
capscale
return similar result objects. Function
capscale
inherits
from rda
and rda
inherits from cca
. This inheritance structure is due to
historic reasons: cca
was the first of these implemented in
vegan. Hence the nomenclature in cca.object
reflects
cca
. This help page describes the internal structure of the
cca
object for programmers.
A cca
object has the following elements:
call 
the function call. 
colsum, rowsum, rowsum.excluded 
Column and row sums in

grand.total 
Grand total of community data in 
inertia 
Text used as the name of inertia. 
method 
Text used as the name of the ordination method. 
terms 
The 
terminfo 
Further information on terms with three subitems:

tot.chi 
Total inertia or the sum of all eigenvalues. 
na.action 
The result of 
pCCA, CCA, CA 
Actual ordination results for conditioned
(partial), constrained and unconstrained components of the
model. If constraints or conditions are not given, the
corresponding components

If the constraints had missing values or subsets, and na.action
was set to na.exclude
or na.omit
, the
result will have some extra items:
subset
subset evaluated as a logical vector
(TRUE
for included cases).
na.action
The object returned by
na.action
which is a named vector of indices of
removed items. The class of the vector is either "omit"
or
"exclude"
as set by na.action
. The na.action
is applied after subset
so that the indices refer to the subset
data.
residuals.zombie
A zombie vector of the length of
number of rows in the residual ordination. R versions before 2.13.0
may use this vector to find the number of valid observations,
and it is provided for their use although this is useless in R 2.13.0
and in vegan. Currently R uses nobs.cca
to find
the number of observations.
rowsum.excluded
Row sums of removed observations. Only
in cca
.
CCA$wa.excluded
The WA scores for sites (found from
community data) in constrained ordination if
na.action
was na.exclude
and the
scores could be calculated. The scores cannot be found for
capscale
and in partial ordination.
CA$u.excluded
Row scores for sites in unconstrained ordination with identical conditions as above.
Function capscale
may add some items depending on its arguments:
metaMDSdist
The data set name if
metaMDSdist = TRUE
.
ac
Additive constant used if add = TRUE
.
adjust
Adjustment of dissimilarities: see
capscale
, section “Notes”.
In old versions of vegan the object also included scores
scaled by eigenvalues (u.eig
, v.eig
and wa.eig
),
but these were removed in vegan 2.20. The scores are scaled
when they are accessed with scores
function. It is
advisable to always use scores
in accessing the
results instead of directly accessing the elements of the the
cca
object.
Jari Oksanen
Legendre, P. and Legendre, L. (2012) Numerical Ecology. 3rd English ed. Elsevier.
The description here provides a hacker's interface. User
level functions for further analysis and handling of cca
objects are described in this section in cca
. Also for
a hacker interface, it may be better to use following low level
functions to access the results:
scores.cca
(which also scales results),
predict.cca
(which can also use newdata
),
fitted.cca
, residuals.cca
,
alias.cca
, coef.cca
,
model.frame.cca
, model.matrix.cca
,
deviance.cca
, eigenvals.cca
,
RsquareAdj.cca
,
weights.cca
, nobs.cca
, or rda
variants of these functions.
You can use as.mlm
to cast a cca.object
into
result of multiple response
linear model (lm
) in order to more easily find some
statistics (which in principle could be directly found from the
cca
object as well).
This section in cca
gives a more complete list of
methods to handle the constrained ordination result object.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  # Some species will be missing in the analysis, because only a subset
# of sites is used below.
data(dune)
data(dune.env)
mod < cca(dune[1:15,] ~ ., dune.env[1:15,])
# Look at the names of missing species
attr(mod$CCA$v, "na.action")
# Look at the names of the aliased variables:
mod$CCA$alias
# Access directly constrained weighted orthonormal species and site
# scores, constrained eigenvalues and margin sums.
spec < mod$CCA$v
sites < mod$CCA$u
eig < mod$CCA$eig
rsum < mod$rowsum
csum < mod$colsum

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