ordiParseFormula(formula, data, xlev = NULL, na.action = na.fail, subset = NULL)
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 = 1e-8)
hierParseFormula(formula, data)
GowerDblcen(x, na.rm = TRUE)
addLingoes(d)
addCailliez(d)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. 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. Function permuted.index was used earlier
to generate permutations, but it is now deprecated.
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.
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, capscale). Function
cmdscale implements the Cailliez method. The argument
is a matrix of dissimilarities.