| rlsOptIC.An2 {RobLox} | R Documentation |
Computation of the optimally robust IC for An2 estimators
Description
The function rlsOptIC.An2 computes the optimally robust IC for
An2 estimators in case of normal location with unknown scale and
(convex) contamination neighborhoods. The definition of
these estimators can be found in Subsection 8.5.3 of Kohl (2005).
Usage
rlsOptIC.An2(r, a.start = 1.5, k.start = 1.5, delta = 1e-06, MAX = 100)
Arguments
r |
non-negative real: neighborhood radius. |
a.start |
positive real: starting value for a. |
k.start |
positive real: starting value for k. |
delta |
the desired accuracy (convergence tolerance). |
MAX |
if a or k are beyond the admitted values,
|
Details
The computation of the optimally robust IC for An2 estimators
is based on optim where MAX is used to
control the constraints on a and k. The optimal values of the
tuning constants a and 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
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.
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.An2(r = 0.1)
checkIC(IC1)
Risks(IC1)
Infos(IC1)
plot(IC1)
infoPlot(IC1)