ordiGetData(call, env)
ordiParseFormula(formula, data, xlev = NULL, envdepth = 2,
na.action = na.fail, subset = NULL)
ordiTerminfo(d, data)
ordiNAexclude(x, excluded)
ordiNApredict(omit, x)
ordiArrowMul(x, at = c(0,0), fill = 0.75)
ordiArgAbsorber(..., shrink, origin, scaling, triangular,
display, choices, const, FUN)
centroids.cca(x, mf, wt)
permuted.index(n, strata)
pasteCall(call, prefix = "Call:")
veganCovEllipse(cov, center = c(0, 0), scale = 1, npoints = 100)get or ::: to directly call these
functions.
ordiGetData finds the model frame of constraints and
conditions in constrained ordination in the defined
environment. 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 and argument envdepth specifies the
depth at which the community data (dependent data) are evaluated;
default envdepth = 2 evaluates that in the environment of the
parent of the calling function, and envdepth = 1 within the
calling function (see
eval.parent). 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 puts pads the result object with these or with
WA scores similarly as napredict. ordiArgAbsorber absorbs arguments of scores
function of FUN. If you implement
scores functions with new arguments, you should update
ordiArgAbsorber.
centroids.cca finds the weighted centroids of variables.
permuted.index creates permuted index of length n
possibly stratified within strata. This is the basic shuffle in the future releases of shuffle.
pasteCall prints the function call so that it is nicely wrapped
in Sweave output.
veganCovEllipse finds the coordinates for drawing a
covariance ellipse.