R: Control Settings for covMcd and ltsReg

rrcov.control {robustbase} | R Documentation

## Control Settings for covMcd and ltsReg

### Description

Auxiliary function for passing the estimation options as parameters to the estimation functions.

### Usage

    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)

### 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.
`method` | a string specifying the “main” function for which `rrcov.control()` is used. This currently only makes a difference to determine the default for `beta`.
`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.
`nmini, kmini` | for `covMcd`: For large n, the algorithm splits the data into maximally kmini subsets of targetted size `nmini`. See `covMcd` for more details.

`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`.
`scalefn` | (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.
`maxcsteps` | integer specifying the maximal number of concentration steps for the deterministic MCD.
`trace` | logical or integer indicating whether to print intermediate results. Default is `trace = FALSE`.
`wgtFUN` | 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.
`beta` | a quantile, experimentally used for some of the prespecified `wgtFUN`s, see e.g., `.wgtFUN.covMcd` and `.wgtFUN.covComed`.
`use.correction` | whether to use finite sample correction factors. Defaults to `TRUE`.
`adjust` | (for `ltsReg()`:) 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

### Author(s)

Valentin Todorov

### See Also

For details, see the documentation about `ltsReg` and `covMcd`, respectively.

### 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)

[Package robustbase version 0.93-6 Index]