Description Usage Arguments Details Value Methods Author(s) References See Also Examples
Generic function for the computation of the radius minimax IC.
1 2 3 4 5 6 7 8 9 10  radiusMinimaxIC(L2Fam, neighbor, risk, ...)
## S4 method for signature 'L2ParamFamily,UncondNeighborhood,asGRisk'
radiusMinimaxIC(
L2Fam, neighbor, risk, loRad = 0, upRad = Inf, z.start = NULL, A.start = NULL,
upper = NULL, lower = NULL, OptOrIter = "iterate",
maxiter = 50, tol = .Machine$double.eps^0.4,
warn = FALSE, verbose = NULL, loRad0 = 1e3, ...,
returnNAifProblem = FALSE, loRad.s = NULL, upRad.s = NULL,
modifyICwarn = NULL)

L2Fam 
L2differentiable family of probability measures. 
neighbor 
object of class 
risk 
object of class 
loRad 
the lower end point of the interval to be searched in the inner optimization (for the least favorable situation to the userguessed radius). 
upRad 
the upper end point of the interval to be searched in the inner optimization (for the least favorable situation to the userguessed radius). 
z.start 
initial value for the centering constant. 
A.start 
initial value for the standardizing matrix. 
upper 
upper bound for the optimal clipping bound. 
lower 
lower bound for the optimal clipping bound. 
OptOrIter 
character; which method to be used for determining Lagrange
multipliers 
maxiter 
the maximum number of iterations 
tol 
the desired accuracy (convergence tolerance). 
warn 
logical: print warnings. 
verbose 
logical: if 
loRad0 
for numerical reasons: the effective lower bound for the zero search;
internally set to 
... 
further arguments to be passed on to 
returnNAifProblem 
logical (of length 1):
if 
loRad.s 
the lower end point of the interval
to be searched in the outer optimization
(for the userguessed radius); if 
upRad.s 
the upper end point of the interval to be searched in the
outer optimization (for the userguessed radius); if

modifyICwarn 
logical: should a (warning) information be added if

In case the neighborhood radius is unknown, Rieder et al. (2001, 2008) and Kohl (2005) show that there is nevertheless a way to compute an optimally robust IC  the socalled radiusminimax IC  which is optimal for some radius interval.
The radius minimax IC is computed.
computation of the radius minimax IC for an L2 differentiable parametric family.
Matthias Kohl [email protected], Peter Ruckdeschel [email protected]
Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing the Radius. Statistical Methods and Applications, 17(1) 1340.
Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing the Radius. Appeared as discussion paper Nr. 81. SFB 373 (Quantification and Simulation of Economic Processes), Humboldt University, Berlin; also available under www.unibayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
1 2 3 4  N < NormLocationFamily(mean=0, sd=1)
radIC < radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(),
risk=asMSE(), loRad=0.1, upRad=0.5)
checkIC(radIC)

Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.