1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
|
\name{rrcov.control}
\alias{rrcov.control}
%%% FIXME --- naming and more --------------
%%% -----
\title{Control object for the estimation parameters }
\description{
Auxiliary function for passing the estimation options as parameters to the
estimation functions.
\bold{NOTE: The name WILL change !!!!}
}
\usage{
rrcov.control(alpha = 1/2, nsamp = 500, nmini = 300,
seed = NULL, tolSolve = 1e-14, trace = FALSE,
use.correction = TRUE, adjust = FALSE)
}
\arguments{
\item{alpha}{This parameter controls the size of the subsets over
which the determinant is minimized, i.e., \code{alpha*n} observations
are used for computing the determinant. Allowed values are between 0.5
and 1 and the default is 0.5. }
\item{nsamp}{number of subsets used for initial estimates or \code{"best"}
or \code{"exact"}. Default is \code{nsamp = 500}.
If \code{nsamp="best"} exhaustive enumeration is done, as far as
the number of trials do not exceed 5000. If \code{nsamp="exact"}
exhaustive enumeration will be attempted however many samples
are needed. In this case a warning message will be displayed
saying that the computation can take a very long time. }
\item{nmini}{for \code{\link{covMcd}}: For large \eqn{n}, the algorithm
splits the data into maximally \eqn{k_{\mathrm{rep}} = 5}{krep = 5}
subsets of size \code{nmini}.}%%- more details see --- ./covMcd.Rd
\item{seed}{initial seed for R's random number generator; see
\code{\link{.Random.seed}} and the description of the \code{seed}
argument in \code{\link{lmrob.control}}.}
\item{tolSolve}{numeric tolerance to be used for inversion
(\code{\link{solve}}) of the covariance matrix in
\code{\link{mahalanobis}}.}
\item{trace}{whether to print intermediate results. Default is
\code{trace = FALSE}}
\item{use.correction}{whether to use finite sample correction factors.
Defaults to \code{TRUE}.}
\item{adjust}{whether to perform intercept adjustment at each
step. Because this can be quite time consuming, the default is
\code{adjust = FALSE}.}
}
\details{
For details about the estimation options see the corresponding
estimation functions.
}
\value{
A list with components, as the parameters passed by the invocation
}
\author{Valentin Todorov}
% \references{
% }
\examples{
data(Animals, package = "MASS")
brain <- Animals[c(1:24, 26:25, 27:28),]
data(hbk)
hbk.x <- data.matrix(hbk[, 1:3])
ctrl <- rrcov.control(alpha=0.75, trace=TRUE)
covMcd(hbk.x, control = ctrl)
covMcd(log(brain), control = ctrl)
}
\keyword{robust}
\keyword{multivariate}
|
