rlsOptIC.Hu1 {RobLox} | R Documentation |
Computation of the optimally robust IC for Hu1 estimators
Description
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).
Usage
rlsOptIC.Hu1(r, kUp = 2.5, delta = 1e-06)
Arguments
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). |
Details
The optimal value of the tuning constant k can be read off
from the slot Infos
of the resulting IC.
Value
Object of class "IC"
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de
References
Huber, P.J. (1964) Robust estimation of a location parameter. Ann. Math. Stat. 35: 73–101.
M. Kohl (2005). Numerical Contributions to the Asymptotic Theory of Robustness. Dissertation. University of Bayreuth. https://epub.uni-bayreuth.de/id/eprint/839/2/DissMKohl.pdf.
See Also
Examples
IC1 <- rlsOptIC.Hu1(r = 0.1)
checkIC(IC1)
Risks(IC1)
Infos(IC1)
plot(IC1)
infoPlot(IC1)