rrcov (version 1.4-7)

CovControlOgk: Constructor function for objects of class "CovControlOgk"

Description

This function will create a control object CovControlOgk containing the control parameters for CovOgk

Usage

CovControlOgk(niter = 2, beta = 0.9, mrob = NULL, 
vrob = .vrobGK, smrob = "scaleTau2", svrob = "gk")

Arguments

niter

number of iterations, usually 1 or 2 since iterations beyond the second do not lead to improvement.

beta

coverage parameter for the final reweighted estimate

mrob

function for computing the robust univariate location and dispersion - one could use the tau scale defined in Yohai and Zamar (1998), see scaleTau2. The C version of this function defined by smrob is the default.

vrob

function for computing robust estimate of covariance between two random vectors - one could use the function proposed by Gnanadesikan and Kettenring (1972), see covGK(). The C version of this function defined by svrob is the default.

smrob

a string indicating the name of the function for computing the robust univariate location and dispersion - defaults to scaleTau2 - the scale tau function defined in Yohai and Zamar (1998)

svrob

a string indicating the name of the function for computing robust estimate of covariance between two random vectors - defaults gk, the one proposed by Gnanadesikan and Kettenring (1972)

Value

A CovControlOgk object

Details

If the user does not specify a scale and covariance function to be used in the computations or specifies one by using the arguments smrob and svrob (i.e. the names of the functions as strings), a native code written in C will be called which is by far faster than the R version.

If the arguments mrob and vrob are not NULL, the specified functions will be used via the pure R implementation of the algorithm. This could be quite slow.

References

Maronna, R.A. and Zamar, R.H. (2002) Robust estimates of location and dispersion of high-dimensional datasets; Technometrics 44(4), 307--317.

Yohai, R.A. and Zamar, R.H. (1998) High breakdown point estimates of regression by means of the minimization of efficient scale JASA 86, 403--413.

Gnanadesikan, R. and John R. Kettenring (1972) Robust estimates, residuals, and outlier detection with multiresponse data. Biometrics 28, 81--124.

Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1--47. URL http://www.jstatsoft.org/v32/i03/.

Examples

# NOT RUN {
    ## the following two statements are equivalent
    ctrl1 <- new("CovControlOgk", beta=0.95)
    ctrl2 <- CovControlOgk(beta=0.95)

    data(hbk)
    CovOgk(hbk, control=ctrl1)
# }