Compute (versions of) the (multivariate) “Comedian” covariance, i.e., multivariate location and scatter estimator
1 2 3  covComed(X, n.iter = 2, reweight = FALSE, tolSolve = control$tolSolve,
trace = control$trace, wgtFUN = control$wgtFUN,
control = rrcov.control())

X 
data matrix of dimension, say n x p. 
n.iter 
number of comedian() iterations. Can be as low as zero. 
reweight 
logical indicating if the final distances and weights
should be recomputed from the final 
tolSolve 
a numerical tolerance passed to 
trace 
logical (or integer) indicating if intermediate results
should be printed; defaults to 
wgtFUN 
a character string or 
control 
a list with estimation options  this includes those
above provided in the function specification, see

.. not yet ..
an object of class "covComed"
which is basically a list with components
comp1 
Description of 'comp1' 
comp2 
Description of 'comp2' 
... FIXME ...
Maria Anna di Palma (initial), Valentin Todorov and Martin Maechler
Falk, M. (1997) On mad and comedians. Annals of the Institute of Statistical Mathematics 49, 615–644.
Falk, M. (1998). A note on the comedian for elliptical distributions. Journal of Multivariate Analysis 67, 306–317.
covMcd
, etc
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19  data(hbk)
hbk.x < data.matrix(hbk[, 1:3])
(cc1 < covComed(hbk.x))
(ccW < covComed(hbk.x, reweight=TRUE))
cc0 < covComed(hbk.x, n.iter=0)
cc0W < covComed(hbk.x, n.iter=0, reweight=TRUE)
stopifnot(all.equal(unclass(cc0), # here, the 01 weights don't change:
cc0W[names(cc0)], tol=1e12),
which(cc1$weights == 0) == 1:14,
which(ccW$weights == 0) == 1:14,
which(cc0$weights == 0) == 1:14)
## Martin's smooth reweighting:
## List of experimental prespecified wgtFUN() creators:
## Cutoffs may depend on (n, p, control$beta) :
str(.wgtFUN.covComed)

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