vegan-internal | R Documentation |
Internal vegan functions that are not intended to be called directly, but only within other functions.
ordiParseFormula(formula, data, xlev = NULL, na.action = na.fail,
subset = NULL, X)
ordiTerminfo(d, data)
ordiNAexclude(x, excluded)
ordiNApredict(omit, x)
ordiArgAbsorber(..., shrink, origin, scaling, triangular,
display, choices, const, truemean, FUN)
centroids.cca(x, mf, wt)
getPermuteMatrix(perm, N, strata = NULL)
howHead(x, ...)
pasteCall(call, prefix = "Call:")
veganCovEllipse(cov, center = c(0, 0), scale = 1, npoints = 100)
veganMahatrans(x, s2, tol = sqrt(.Machine$double.eps), na.rm = FALSE)
hierParseFormula(formula, data)
GowerDblcen(x, na.rm = TRUE)
addLingoes(d)
addCailliez(d)
The description here is only intended for vegan
developers: these functions are not intended for users, but they
only should be used within functions. In general, these functions
are not exported to the namespace, but you must use
get
or :::
to directly call these
functions.
ordiParseFormula
returns a list of three matrices (dependent
variables, and model.matrix
of constraints and
conditions, possibly NULL
) needed in constrained
ordination. Argument xlev
is passed to
model.frame
. If the left-hand-side was already
evaluated in calling code, it can be given as argument X
and
will not be re-evaluated. ordiTermInfo
finds the term
information for constrained ordination as described in
cca.object
. ordiNAexclude
implements
na.action = na.exclude
for constrained ordination finding WA
scores of CCA components and site scores of unconstrained component
from excluded
rows of observations. Function
ordiNApredict
pads the result object with these or with WA
scores similarly as napredict
.
ordiArgAbsorber
absorbs arguments of scores
function of vegan so that these do not cause superfluous
warnings in graphical function FUN
. If you implement
scores
functions with new arguments, you should update
ordiArgAbsorber
.
centroids.cca
finds the weighted centroids of variables.
getPermuteMatrix
interprets user input and returns a
permutation matrix where each row gives indices of observations for
a permutation. The input perm
can be a single number for the
number of simple permutations, a result of
how
defining a permutation scheme or a
permutation matrix.
howHead
formats the permutation scheme of
how
for display. The formatting is more
compact than the one used in print
in the permute
package, and shows only non-default choices. This output is normally
used when printing the results of vegan permutations.
pasteCall
prints the function call so that it is nicely wrapped
in Sweave
output.
veganCovEllipse
finds the coordinates for drawing a
covariance ellipse.
veganMahatrans
transforms data matrix so that its Euclidean
distances are Mahalanobis distances. The input data x
must be
a matrix centred by columns, and s2
its covariance matrix. If
s2
is not given, covariance matrix is found from x
within the function. If na.rm = TRUE
, cov
is
called with use = "pairwise.complete.obs"
.
hierParseFormula
returns a list of one matrix (left hand side)
and a model frame with factors representing hierarchy levels
(right hand side) to be used in adipart
,
multipart
and hiersimu
.
GowerDblcen
performs the Gower double centring of a matrix of
dissimilarities. Similar function was earlier available as a compiled
code in stats, but it is not a part of official API, and
therefore we have this poorer replacement.
addLingoes
and addCailliez
find the constant added to
non-diagonal (squared) dissimilarities to make all eigenvalues
non-negative in Principal Co-ordinates Analysis
(wcmdscale
, dbrda
,
capscale
). Function cmdscale
implements
the Cailliez method. The argument is a matrix of dissimilarities.
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