Auxiliary function for passing the estimation options as parameters to the estimation function MCD.robust.moment
MycovRobMcd(
alpha = 1/2,
nsamp = 500,
nmini = 300,
kmini = 5,
scalefn = "hrv2012",
maxcsteps = 200,
seed = NULL,
tolSolve = 1e-14,
wgtFUN = "01.original",
beta,
use.correction = TRUE
)a list of passed parameters
numeric parameter controlling the size of the subsets over which the determinant is minimized. Allowed values are between 0.5 and 1 and the default is 0.5.
number of subsets used for initial estimates or "best", "exact", or "deterministic". Default is nsamp = 500. For nsamp = "best" exhaustive enumeration is done, as long as the number of trials does not exceed 100'000, which is the value of nlarge. For "exact", exhaustive enumeration will be attempted however many samples are needed. In this case a warning message may be displayed saying that the computation can take a very long time. For "deterministic", the deterministic MCD is computed; as proposed by Hubert et al. (2012) it starts from the h most central observations of six (deterministic) estimators.
for n >= 2*n0, n0 := nmini, the algorithm splits the data into maximally kmini (by default 5) subsets, of size approximately, but at least nmini. When nmini*kmini < n, the initial search uses only a subsample of size nmini*kmini. The original algorithm had nmini = 300 and kmini = 5 hard coded.
function to compute a robust scale estimate or character string specifying a rule determining such a function for the deterministic MCD. The default is "hrv2012". Another option value is "v2014".
maximal number of concentration steps in the deterministic MCD
initial seed for random generator
numeric tolerance to be used for inversion of the covariance matrix
a character string or function, specifying how the weights for the reweighting step should be computed. Default is "01.originalz".
a quantile, experimentally used for some of the prespecified wgtFUNs. For our MCD method, the default is 0.975.
whether to use finite sample correction factors; defaults to TRUE.