Auxiliary function for passing the estimation options as parameters to the estimation functions.
rrcov.control(alpha = 1/2, method = c("covMcd", "covComed", "ltsReg"),
nsamp = 500, nmini = 300, kmini = 5,
seed = NULL, tolSolve = 1e-14,
scalefn = "hrv2012", maxcsteps = 200,
trace = FALSE,
wgtFUN = "01.original", beta,
use.correction = identical(wgtFUN, "01.original"),
adjust = FALSE)
A list with components, as the parameters passed by the invocation
This parameter controls the size of the subsets over
which the determinant is minimized, i.e., alpha*n
observations
are used for computing the determinant. Allowed values are between 0.5
and 1 and the default is 0.5.
a string specifying the “main” function for which
rrcov.control()
is used. This currently only makes a
difference to determine the default for beta
.
number of subsets used for initial estimates or "best"
or "exact"
. Default is nsamp = 500
.
If nsamp="best"
exhaustive enumeration is done, as far as
the number of trials do not exceed 5000. If 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.
for covMcd
: For large \(n\), the algorithm
splits the data into maximally \(kmini\) subsets of targetted size
nmini
. See covMcd
for more details.
initial seed for R's random number generator; see
.Random.seed
and the description of the seed
argument in lmrob.control
.
numeric tolerance to be used for inversion
(solve
) of the covariance matrix in mahalanobis
.
(for deterministic covMcd()
:) a character
string or function
for computing a robust scale
estimate. The current default "hrv2012"
uses the recommendation
of Hubert et al (2012); see covMcd
for more.
integer specifying the maximal number of concentration steps for the deterministic MCD.
logical or integer indicating whether to print
intermediate results. Default is trace = FALSE
.
a character string or function
, specifying
how the weights for the reweighting step should be computed, see
ltsReg
, covMcd
or
covComed
, respectively. The default is specified by
"01.original"
, as the resulting weights are 0 or 1. Alternative
string specifications need to match names(.wgtFUN.covComed)
-
which currently is experimental.
a quantile, experimentally used for some of the prespecified
wgtFUN
s, see e.g., .wgtFUN.covMcd
and
.wgtFUN.covComed
.
whether to use finite sample correction factors.
Defaults to TRUE
.
(for ltsReg()
:) whether to perform
intercept adjustment at each step. Because this can be quite time
consuming, the default is adjust = FALSE
.
Valentin Todorov
For details, see the documentation about ltsReg
and
covMcd
, respectively.
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)
Run the code above in your browser using DataLab