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))