getRiskIC: Generic function for the computation of a risk for an IC

Description

Generic function for the computation of a risk for an IC.

Usage

getRiskIC(IC, risk, neighbor, L2Fam, ...)

## S3 method for class 'IC,asCov,missing,missing':
getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,asCov,missing,L2ParamFamily':
getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,trAsCov,missing,missing':
getRiskIC(IC, risk, tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,trAsCov,missing,L2ParamFamily':
getRiskIC(IC, risk, L2Fam, tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,asBias,UncondNeighborhood,missing':
getRiskIC(IC, risk, neighbor, tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,asBias,UncondNeighborhood,L2ParamFamily':
getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,asMSE,UncondNeighborhood,missing':
getRiskIC(IC, risk, neighbor,  tol = .Machine$double.eps^0.25)

## S3 method for class 'IC,asMSE,UncondNeighborhood,L2ParamFamily':
getRiskIC(IC, risk, neighbor, L2Fam, tol = .Machine$double.eps^0.25)

## S3 method for class 'TotalVarIC,asUnOvShoot,UncondNeighborhood,missing':
getRiskIC(IC, risk, neighbor)

## S3 method for class 'IC,fiUnOvShoot,ContNeighborhood,missing':
getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")

## S3 method for class 'IC,fiUnOvShoot,TotalVarNeighborhood,missing':
getRiskIC(IC, risk, neighbor, sampleSize, Algo = "A", cont = "left")

Arguments

Value

The risk of an IC is computed.

concept

influence curve

Details

To make sure that the results are valid, it is recommended to include an additional check of the IC properties of IC using checkIC.

References

Huber, P.J. (1968) Robust Confidence Limits. Z. Wahrscheinlichkeitstheor. Verw. Geb. 10:269--278. Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. 8: 106--115. Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer. Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation. Ruckdeschel, P. and Kohl, M. (2005) Computation of the Finite Sample Risk of M-estimators on Neighborhoods.