Learn R Programming

RobLox (version 1.2.0)

rlsOptIC.AnMad: Computation of the optimally robust IC for AnMad estimators

Description

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).

Usage

rlsOptIC.AnMad(r, aUp = 2.5, delta = 1e-06)

Arguments

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).

Value

Object of class "IC"

Details

The optimal value of the tuning constant a can be read off from the slot Infos of the resulting IC.

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.

Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.

See Also

IC-class

Examples

Run this code
# NOT RUN {
IC1 <- rlsOptIC.AnMad(r = 0.1)
checkIC(IC1)
Risks(IC1)
Infos(IC1)
plot(IC1)
infoPlot(IC1)
# }

Run the code above in your browser using DataLab