rrcov.control {robustbase} | R Documentation |
Auxilary function for passing the estimation options as parameters to the estimation functions.
NOTE: The name WILL change !!!!
rrcov.control(alpha = 1/2, nsamp = 500, seed = NULL, tolSolve = 1e-14, trace = FALSE, use.correction = TRUE, adjust = FALSE)
alpha |
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. |
nsamp |
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. |
seed |
initial seed for R's random number generator; see
.Random.seed and the description of the seed
argument in lmrob.control . |
tolSolve |
numeric tolerance to be used for inversion
(solve ) of the covariance matrix in
mahalanobis . |
trace |
whether to print intermediate results. Default is
trace = FALSE |
use.correction |
whether to use finite sample correction factors.
Defaults to TRUE . |
adjust |
whether to perform intercept adjustment at each
step. Because this can be quite time consuming, the default is
adjust = FALSE . |
For details about the estimation options see the corresponding estimation functions.
A list with components, as the parameters passed by the invocation
Valentin Todorov
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)