Computation of the optimally robust IC for Hu1 estimators
The function rlsOptIC.Hu1 computes the optimally robust IC for
Hu1 estimators in case of normal location with unknown scale and
(convex) contamination neighborhoods. These estimators were
proposed by Huber (1964), Proposal 2. A definition of these
estimators can also be found in Subsection 8.5.1 of Kohl (2005).
rlsOptIC.Hu1(r, kUp = 2.5, delta = 1e-06)
r |
non-negative real: neighborhood radius. |
kUp |
positive real: the upper end point of the interval to be searched for k. |
delta |
the desired accuracy (convergence tolerance). |
The optimal value of the tuning constant k can be read off
from the slot Infos of the resulting IC.
Object of class "IC"
Matthias Kohl Matthias.Kohl@stamats.de
Huber, P.J. (1964) Robust estimation of a location parameter. Ann. Math. Stat. 35: 73–101.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
IC1 <- rlsOptIC.Hu1(r = 0.1) checkIC(IC1) Risks(IC1) Infos(IC1) plot(IC1) infoPlot(IC1)
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