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ROptEst (version 0.5.0)

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, ...)

## S3 method for class '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.

concept

  • radius minimax influence curve
  • influence curve

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

Run this code
N <- NormLocationFamily(mean=0, sd=1) 
radiusMinimaxIC(L2Fam=N, neighbor=ContNeighborhood(), 
                risk=asMSE(), loRad=0.1, upRad=0.5)

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