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.