ROptEstOld (version 1.2.0)

radiusMinimaxIC: Generic function for the computation of the radius minimax IC

Description

Generic function for the computation of the radius minimax IC.

Usage

radiusMinimaxIC(L2Fam, neighbor, risk, ...)
# S4 method for L2ParamFamily,UncondNeighborhood,asGRisk
radiusMinimaxIC(L2Fam, neighbor, risk, 
        loRad, upRad, z.start = NULL, A.start = NULL, upper = 1e5, 
        maxiter = 100, tol = .Machine$double.eps^0.4, warn = FALSE)

Arguments

L2Fam

L2-differentiable family of probability measures.

neighbor

object of class "Neighborhood".

risk

object of class "RiskType".

…

additional parameters.

loRad

the lower end point of the interval to be searched.

upRad

the upper end point of the interval to be searched.

z.start

initial value for the centering constant.

A.start

initial value for the standardizing matrix.

upper

upper bound for the optimal clipping bound.

maxiter

the maximum number of iterations

tol

the desired accuracy (convergence tolerance).

warn

logical: print warnings.

Value

The radius minimax IC is computed.

Methods

L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asGRisk":

computation of the radius minimax IC for an L2 differentiable parametric family.

References

Rieder, H., Kohl, M. and Ruckdeschel, P. (2001) The Costs of not Knowing the Radius. Submitted. Appeared as discussion paper Nr. 81. SFB 373 (Quantification and Simulation of Economic Processes), Humboldt University, Berlin; also available under www.uni-bayreuth.de/departments/math/org/mathe7/RIEDER/pubs/RR.pdf

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

See Also

radiusMinimaxIC

Examples

# NOT RUN {
N <- NormLocationFamily(mean=0, sd=1) 
radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(), 
                risk=asMSE(), loRad=0.1, upRad=0.5)
# }