Computation of the optimally robust IC for AnMad estimators
The function rlsOptIC.AnMad computes the optimally robust IC for
AnMad estimators in case of normal location with unknown scale and
(convex) contamination neighborhoods. These estimators were
considered in Andrews et al. (1972). A definition of these estimators
can also be found in Subsection 8.5.3 of Kohl (2005).
rlsOptIC.AnMad(r, aUp = 2.5, delta = 1e-06)
r |
non-negative real: neighborhood radius. |
aUp |
positive real: the upper end point of the interval to be searched for a. |
delta |
the desired accuracy (convergence tolerance). |
The optimal value of the tuning constant a can be read off
from the slot Infos of the resulting IC.
Object of class "IC"
Matthias Kohl Matthias.Kohl@stamats.de
Andrews, D.F., Bickel, P.J., Hampel, F.R., Huber, P.J., Rogers, W.H. and Tukey, J.W. (1972) Robust estimates of location. Princeton University Press.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
IC1 <- rlsOptIC.AnMad(r = 0.1) checkIC(IC1) Risks(IC1) Infos(IC1) plot(IC1) infoPlot(IC1)
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