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.
h
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.
maxcsteps
maximal number of concentration steps in the
deterministic MCD; should not be reached.
rho
regularization parameter. Normally NULL and will be estimated from the data.
target
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). Default is target="identity"
maxcond
maximum condition number allowed
(see step 3.4 in algorithm 1). Default is maxcond=50
trace
whether to print intermediate results. Default is trace = FALSE
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("CovControlMrcd", alpha=0.75)
ctrl2 <- CovControlMrcd(alpha=0.75)
data(hbk)
CovMrcd(hbk, control=ctrl1)