getIneffDiff {ROptEst}R Documentation

Generic Function for the Computation of Inefficiency Differences

Description

Generic function for the computation of inefficiency differencies. This function is rarely called directly. It is used to compute the radius minimax IC and the least favorable radius.

Usage

getIneffDiff(radius, L2Fam, neighbor, risk, ...)

## S4 method for signature 'numeric, L2ParamFamily,
##   UncondNeighborhood, asMSE':
getIneffDiff(
          radius, L2Fam, neighbor, risk, loRad, upRad, loRisk, upRisk, 
          z.start = NULL, A.start = NULL, upper.b, MaxIter, eps, warn,
          loNorm = NULL, upNorm = NULL, verbose = FALSE)

Arguments

radius neighborhood radius.
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.
loRisk the risk at the lower end point of the interval.
upRisk the risk at the upper end point of the interval.
z.start initial value for the centering constant.
A.start initial value for the standardizing matrix.
upper.b upper bound for the optimal clipping bound.
MaxIter the maximum number of iterations
eps the desired accuracy (convergence tolerance).
warn logical: print warnings.
loNorm object of class "NormType"; used in selfstandardization to evaluate the bias of the current IC in the norm of the lower bound
upNorm object of class "NormType"; used in selfstandardization to evaluate the bias of the current IC in the norm of the upper bound
verbose logical: if TRUE, some messages are printed

Value

The inefficieny difference between the left and the right margin of a given radius interval is computed.

Methods

radius = "numeric", L2Fam = "L2ParamFamily", neighbor = "UncondNeighborhood", risk = "asMSE":
computes difference of asymptotic MSE–inefficiency for the boundaries of a given radius interval.

Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

References

Rieder, H., Kohl, M. and Ruckdeschel, P. (2008) The Costs of not Knowing the Radius. Statistical Methods and Applications, 17(1) 13-40.

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, leastFavorableRadius


[Package ROptEst version 0.6.3 Index]