leastFavorableRadius {ROptEstOld}R Documentation

Generic Function for the Computation of Least Favorable Radii

Description

Generic function for the computation of least favorable radii.

Usage

leastFavorableRadius(L2Fam, neighbor, risk, ...)

## S4 method for signature 'L2ParamFamily,
##   UncondNeighborhood, asGRisk':
leastFavorableRadius(L2Fam, neighbor, risk, rho, upRad = 1, 
            z.start = NULL, A.start = NULL, upper = 100, 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
upRad the upper end point of the radius interval to be searched.
rho The considered radius interval is: [r*rho, r/rho] with 0 < rho < 1.
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 least favorable radius and the corresponding inefficiency are computed.

Methods

L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asGRisk"
computation of the least favorable radius.

Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

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

N <- NormLocationFamily(mean=0, sd=1) 
leastFavorableRadius(L2Fam=N, neighbor=ContNeighborhood(),
                     risk=asMSE(), rho=0.5)

[Package ROptEstOld version 0.5.2 Index]