This function will create a control object CovControlOgk
containing the control parameters for CovOgk
1 2  CovControlOgk(niter = 2, beta = 0.9, mrob = NULL,
vrob = .vrobGK, smrob = "scaleTau2", svrob = "gk")

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 
vrob 
function for computing robust estimate
of covariance between two random vectors  one could use the function
proposed by Gnanadesikan and Kettenring (1972), see

smrob 
a string indicating the name of the function for computing
the robust univariate location and dispersion  defaults to

svrob 
a string indicating the name of the function for computing
robust estimate of covariance between two random vectors  defaults 
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.
A CovControlOgk
object
Valentin Todorov valentin.todorov@chello.at
Maronna, R.A. and Zamar, R.H. (2002) Robust estimates of location and dispersion of highdimensional 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/.
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