Nothing
`summary.cca` <- function (object, scaling = "species", axes = 6,
display=c("sp","wa","lc","bp","cn"),
digits = max(3, getOption("digits") - 3),
correlation = FALSE, hill = FALSE, ...)
{
axes <- min(axes, sum(object$CCA$rank, object$CA$rank))
summ <- list()
## scaling is stored in return object so must be in numeric format
scaling <- scalingType(scaling = scaling, correlation = correlation,
hill = hill)
if (axes && length(display) && !anyNA(display) && !is.null(display))
summ <- scores(object, scaling = scaling, choices = 1:axes, display = display,
...)
## scores() drops list to a matrix if there is only one item: workaround below.
if (!is.list(summ) && length(display) == 1) {
nms <- c("species", "sites", "constraints", "biplot", "centroids")
names(nms) <- c("sp","wa","lc","bp","cn")
summ <- list(summ)
names(summ) <- nms[display]
}
if (length(display) > 0) {
for (i in seq_along(summ)) {
if (is.matrix(summ[[i]]))
rownames(summ[[i]]) <-
rownames(summ[[i]], do.NULL = FALSE,
prefix = substr(names(summ)[i], 1, 3))
}
}
summ$call <- object$call
summ$tot.chi <- object$tot.chi
## only the Real component for capscale() with negative eigenvalues
if (!is.null(object$CA$imaginary.chi))
summ$tot.chi <- summ$tot.chi - object$CA$imaginary.chi
summ$partial.chi <- object$pCCA$tot.chi
summ$constr.chi <- object$CCA$tot.chi
summ$unconst.chi <- object$CA$tot.chi
## nested list cont$importance needed to keep vegan pre-2.5-0 compatibility
summ$cont$importance <- summary(eigenvals(object))
if (!is.null(object$CCA) && object$CCA$rank > 0)
summ$concont$importance <- summary(eigenvals(object, model = "constrained"))
summ$ev.head <- c(summ$ev.con, summ$ev.uncon)[seq_len(axes)]
summ$scaling <- scaling
summ$digits <- digits
summ$inertia <- object$inertia
summ$method <- object$method
class(summ) <- "summary.cca"
summ
}
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