| edgecluster {edci} | R Documentation |
edgecluster is a simple combination of edgepoints
and oregMclust. It just passes the results of
edgepoints to oregMclust.
edgecluster(data, h1n, h2n,
maxval,
bw = max(h1n,h2n)/qnorm(0.975),
asteps = 4,
estimator = "M_median",
kernel = "gauss",
score = "gauss",
sigma = 1,
kernelfunc = NULL)
data |
See description of edgepoints. |
h1n, h2n |
See description of edgepoints. |
asteps |
See description of edgepoints. |
estimator |
See description of edgepoints. |
kernel |
See description of edgepoints. |
score |
See description of edgepoints. |
sigma |
See description of edgepoints. |
kernelfunc |
See description of edgepoints. |
maxval |
See description of eplist. |
bw |
See description of oregMclust. See default
gives the observations within the 'edgecluster-window' 95% of
the weight. |
Return value is a list of two numerical matrices. The first matrix
contains the results of oregMclust, which are the
'edgeclusters'. The second matrix contains the result of
edgepoints.
Tim Garlipp, garlipp@mathematik.uni-oldenburg.de
edgepoints, oregMclust,
eplist
y <- matrix(rep(0,60*60),nrow=60)
y[21:40,21:40]<-1
y <- y + matrix(rnorm(60*60,0,0.2),nrow=60)
image(y,col=gray(seq(0,1,1/255)))
ec <- edgecluster(y,0.05,0.05,0.7,
estimator="M_median",kernel="gauss")
plot(bestMclust(ec[[1]],4),ec[[2]],xlim=c(0,1),ylim=c(0,1))