rrcov.control: Control object for the estimation parameters

Description

Auxilary function for passing the estimation options as parameters to the estimation functions. NOTE: The name WILL change !!!!

Usage

rrcov.control(alpha = 1/2, nsamp = 500, seed = NULL, tolSolve = 1e-14,
              trace = FALSE,
              use.correction = TRUE, adjust = FALSE)

Arguments

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

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.

Value

A list with components, as the parameters passed by the invocation

Details

For details about the estimation options see the corresponding estimation functions.

Examples

Run this code

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)