Nothing
plot.pMST<-function (x, ...)
{
# require(rgl)
drin = x$sample
data = x$data
x6 = x$x6
x6 <- x6[-1, ]
x7 <- x6[which(duplicated(x6[, 1]) == F), ]
x7 <- x7[which(x7[, 3] >= floor(dim(data)[1]/2) + 1), ]
N = length(drin)
n <- dim(data)[1]
f <- 1:n
if (dim(data)[2] == 3) {
plot3d(data, size = 4)
points3d(data[drin, ], col = "red", size = 8)
}
if (dim(data)[2] == 2) {
plot(data, xlab = "x", ylab = "y")
points(data[drin, ], col = "red")
dev.new()
}
if (!is.null(nrow(x7))) {
par(mfrow = c(2, 2))
}
else {
par(mfrow = c(1, 2))
}
plot(mahalanobis(data, colMeans(data[drin, ]), cov(data[drin,
])), xlab = "observation", ylab = "mahalanobis distance",
main = "Mahalanobis distances (in-)to subsample")
points(f[-drin], mahalanobis(data, colMeans(data[drin, ]),
cov(data[drin, ]))[-drin], col = "red")
distl <- as.matrix(dist(data, upper = T, diag = T))
distl[, -drin] <- rep(max(distl), n)
diag(distl) <- rep(max(distl), n)
minIn <- apply(distl[drin, ], 1, min)
minOut <- apply(distl[-drin, ], 1, min)
plot(1:n, rep(-1, n), ylim = c(0, max(max(minIn, minOut))),
xlab = "observation", ylab = "euclidean distance", main = "Minimal distances (in-)to subsample")
points(f[drin], minIn)
points(f[-drin], minOut, col = "red")
if (!is.null(nrow(x7))) {
plot(x7[, 2], x7[, 1], xlab = "edge length", ylab = "length of largest sub-tree (of MST)",
main = "Length-connection-plot (LC plot)")
lines(x7[, 2], x7[, 1])
x7 <- cbind(x7, (x7[, 1] - mean(x7[, 1]))/sd(x7[, 1]),
(x7[, 2] - mean(x7[, 2]))/sd(x7[, 2]))
x8 <- as.vector(as.matrix(dist(x7[, 1:2])))
x9 <- x8[which(x8 == 0) + 1]
n <- length(x9)
dx7 <- diff(x7)
dx7 <- cbind(dx7, dx7[, 4]/dx7[, 5], sqrt(dx7[, 4]^2 +
dx7[, 5]^2))
plot(x7[-1, 3], dx7[, 7]/dx7[, 6], xlab = "obs. in relevant subsample",
ylab = "edge-length/ascent ratio (LC plot)", main = "Ascent-length criterion (AL plot)")
lines(x7[-1, 3], dx7[, 7]/dx7[, 6])
}
}
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