Nothing
`goodness.metaMDS` <-
function(object, dis, ...)
{
if (inherits(object, "monoMDS"))
return(NextMethod("goodness", object, ...))
if (missing(dis))
dis <- metaMDSredist(object)
if(attr(dis, "Size") != nrow(object$points))
stop("Dimensions do not match in ordination and dissimilarities")
d <- order(dis)
shep <- Shepard(dis, object$points)
res <- (shep$y - shep$yf)^2/sum(shep$y^2)
stress <- sqrt(sum(res))*100
if ( abs(stress - object$stress) > 0.001)
stop("Dissimilarities and ordination do not match")
res <- res[order(d)]
attr(res, "Size") <- attr(dis, "Size")
attr(res, "Labels") <- attr(dis, "Labels")
class(res) <- "dist"
sqrt(colSums(as.matrix(res))/2*10000)
}
`goodness.monoMDS` <-
function(object, ...)
{
## Return vector 'x' for which sum(x^2) == stress
stresscomp <- function(y, yf, form)
{
num <- (y-yf)^2
if (form == 1)
den <- sum(y^2)
else
den <- sum((y-mean(y))^2)
num/den
}
## Global, local
if (object$model %in% c("global", "linear")) {
x <- stresscomp(object$dist, object$dhat, object$isform)
mat <- matrix(0, object$nobj, object$nobj)
for (i in 1:object$ndis)
mat[object$iidx[i], object$jidx[i]] <- x[i]
res <- sqrt(colSums(mat + t(mat))/2)
}
## Local: returns pointwise components of stress
else if (object$model == "local") {
res <- object$grstress/sqrt(object$ngrp)
} else if (object$model == "hybrid" && object$ngrp == 2) {
mat <- matrix(0, object$nobj, object$nobj)
gr <- seq_len(object$ndis) < object$istart[2]
x <- stresscomp(object$dist[gr], object$dhat[gr], object$isform)
x <- c(x, stresscomp(object$dist[!gr], object$dhat[!gr], object$isform))
i <- object$iidx
j <- object$jidx
for (k in 1:object$ndis) {
mat[i[k], j[k]] <- mat[i[k], j[k]] + x[k]
}
res <- sqrt(colSums(mat + t(mat))/4)
} else {
stop("unknown 'monoMDS' model")
}
res
}
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