Dear list,
here is something I do not understand about cov.rob.
> dat <- rmvnorm(200,rep(0,10),diag(10))
> cov.rob(dat,method="mcd")
> cov.rob(dat,method="mcd",quantile.used= floor(3*211/4))
# All fine; default for quantile.used is floor(211/2)
> dat <- rmvnorm(20,rep(0,10),diag(10))
> cov.rob(dat,method="mcd")
# quantile.used is floor(31/2). Also fine, but...
> cov.rob(dat,method="mcd",quantile.used= floor(3*31/4))
This seems to never come to an end and cannot even be stopped by C-c C-c
(ESS).
I thought that a larger quantile should get more stable results for such
small datasets, and I do not understand where the computational problem
comes from.
> version
_
platform i686-pc-linux-gnu
arch i686
os linux-gnu
system i686, linux-gnu
status
major 1
minor 5.1
year 2002
month 06
day 17
language R
Best,
Christian
--
***********************************************************************
Christian Hennig
Seminar fuer Statistik, ETH-Zentrum (LEO), CH-8092 Zuerich (current)
and Fachbereich Mathematik-SPST/ZMS, Universitaet Hamburg
hennig at stat.math.ethz.ch, http://stat.ethz.ch/~hennig/
hennig at math.uni-hamburg.de, http://www.math.uni-hamburg.de/home/hennig/
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