CovSde {rrcov} | R Documentation |
Compute a robust estimate of location and scale using the Stahel-Donoho projection based estimator
CovSde(x, nsamp, maxres, tune = 0.95, eps = 0.5, prob = 0.99, seed = NULL, trace = FALSE, control)
x |
a matrix or data frame. |
nsamp |
a positive integer giving the number of resamples required;
nsamp may not be reached if too many of the p -subsamples,
chosen out of the observed vectors, are in a hyperplane.
If nsamp = 0 all possible subsamples are taken.
If nsamp is omitted, it is calculated to provide a breakdown point
of eps with probability prob . |
maxres |
a positive integer specifying the maximum number of
resamples to be performed including those that are discarded due to linearly
dependent subsamples. If maxres is omitted it will be set to 2 times nsamp . |
tune |
a numeric value between 0 and 1 giving the fraction of the data to receive non-zero weight.
Defaults to 0.95 |
prob |
a numeric value between 0 and 1 specifying the probability of high breakdown point;
used to compute nsamp when nsamp is omitted. Defaults to 0.99 . |
eps |
a numeric value between 0 and 0.5 specifying the breakdown point; used to compute
nsamp when nresamp is omitted. Defaults to 0.5 . |
seed |
starting value for random generator. Default is seed = NULL . |
trace |
whether to print intermediate results. Default is trace = FALSE . |
control |
a control object (S4) of class CovControlSde-class
containing estimation options - same as these provided in the fucntion
specification. If the control object is supplied, the parameters from it
will be used. If parameters are passed also in the invocation statement, they will
override the corresponding elements of the control object. |
An S4 object of class CovSde-class
which is a subclass of the
virtual class CovRobust-class
.
The Fortran code for the Stahel-Donoho method was taken almost with no changes from
package robust
which in turn has it from the Insightful Robust Library
(thanks to by Kjell Konis).
Valentin Todorov valentin.todorov@chello.at and Kjell Konis kjell.konis@epfl.ch
R. A. Maronna and V.J. Yohai (1995) The Behavior of the Stahel-Donoho Robust Multivariate Estimator. Journal of the American Statistical Association 90 (429), 330–341.
R. A. Maronna, D. Martin and V. Yohai (2006). Robust Statistics: Theory and Methods. Wiley, New York.
data(hbk) hbk.x <- data.matrix(hbk[, 1:3]) CovSde(hbk.x) ## the following four statements are equivalent c0 <- CovSde(hbk.x) c1 <- CovSde(hbk.x, nsamp=2000) c2 <- CovSde(hbk.x, control = CovControlSde(nsamp=2000)) c3 <- CovSde(hbk.x, control = new("CovControlSde", nsamp=2000)) ## direct specification overrides control one: c4 <- CovSde(hbk.x, nsamp=100, control = CovControlSde(nsamp=2000)) c1 summary(c1) plot(c1) ## Use the function CovRobust() - if no estimation method is ## specified, for small data sets CovSde() will be called cr <- CovRobust(hbk.x) cr