This function will create a control object CovControlOgk
containing the control parameters for CovOgk
CovControlOgk(niter = 2, beta = 0.9, mrob = NULL,
vrob = .vrobGK, smrob = "scaleTau2", svrob = "gk")
A CovControlOgk
object
number of iterations, usually 1 or 2 since iterations beyond the second do not lead to improvement.
coverage parameter for the final reweighted estimate
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.
function for computing robust estimate
of covariance between two random vectors - one could use the function
proposed by Gnanadesikan and Kettenring (1972), see
covOGK()
. The C version of this function defined
by svrob
is the default.
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)
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)
Valentin Todorov valentin.todorov@chello.at
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.
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. tools:::Rd_expr_doi("10.18637/jss.v032.i03").
## the following two statements are equivalent
ctrl1 <- new("CovControlOgk", beta=0.95)
ctrl2 <- CovControlOgk(beta=0.95)
data(hbk)
CovOgk(hbk, control=ctrl1)
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