ROptEstOld: getIneffDiff – R documentation

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getIneffDiff

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)

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.

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. (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.