R: Internal vegan functions

vegan-internal {vegan} | R Documentation

## Internal vegan functions

### Description

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)
    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)

### 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`. `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.

[Package vegan version 2.4-3 Index]