CovControlMrcd-class | R Documentation |
This class extends the CovControl
class
and contains the control parameters for "CovMrcd"
Objects can be created by calls of the form new("CovControlMrcd", ...)
or by calling the constructor-function CovControlMrcd
.
alpha
:numeric parameter controlling 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.
the size of the subset (can be between ceiling(n/2) and n).
Normally NULL and then it h
will be calculated as
h=ceiling(alpha*n)
. If h
is provided, alpha
will be calculated as alpha=h/n
.
maximal number of concentration steps in the deterministic MCD; should not be reached.
regularization parameter. Normally NULL and will be estimated from the data.
structure of the robust positive definite target matrix: a) "identity": target matrix is diagonal matrix with robustly estimated univariate scales on the diagonal or b) "equicorrelation": non-diagonal target matrix that incorporates an equicorrelation structure (see (17) in paper).
maximum condition number allowed (see step 3.4 in algorithm 1).
trace
, tolSolve
:from the "CovControl"
class.
Class "CovControl"
, directly.
signature(obj = "CovControlMrcd")
: the generic
function restimate
allows the different methods for robust estimation to be
used polymorphically - this function will call CovMrcd
passing it the control
object and will return the obtained CovRobust
object
Valentin Todorov valentin.todorov@chello.at
Todorov V & Filzmoser P (2009), An Object Oriented Framework for Robust Multivariate Analysis. Journal of Statistical Software, 32(3), 1–47. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.18637/jss.v032.i03")}.
"CovControlMcd"
## the following two statements are equivalent
ctrl1 <- new("CovControlMrcd", alpha=0.75)
ctrl2 <- CovControlMrcd(alpha=0.75)
data(hbk)
CovMrcd(hbk, control=ctrl1)
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