Internal vegan functions

Internal vegan functions that are not intended to be called directly, but only within other functions.

Usage

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, optimize, arrows, 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)

Details

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.