getInfClip: Generic Function for the Computation of the Optimal Clipping...

In ROptEstOld: Optimally Robust Estimation - Old Version

Description

Generic function for the computation of the optimal clipping bound in case of infinitesimal robust models. This function is rarely called directly. It is used to compute optimally robust ICs.

Usage

getInfClip(clip, L2deriv, risk, neighbor, ...)

## S4 method for signature 
## 'numeric,UnivariateDistribution,asMSE,ContNeighborhood'
getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)

## S4 method for signature 
## 'numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood'
getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)

## S4 method for signature 'numeric,EuclRandVariable,asMSE,ContNeighborhood'
getInfClip(clip, L2deriv, risk, neighbor, Distr, stand, cent, trafo)

## S4 method for signature 
## 'numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood'
getInfClip(clip, L2deriv, risk, neighbor, cent, symm, trafo)

Arguments

clip	positive real: clipping bound
L2deriv	L2-derivative of some L2-differentiable family of probability measures.
risk	object of class "RiskType".
neighbor	object of class "Neighborhood".
...	additional parameters.
cent	optimal centering constant.
stand	standardizing matrix.
Distr	object of class "Distribution".
symm	logical: indicating symmetry of L2deriv.
trafo	matrix: transformation of the parameter.

Value

The optimal clipping bound is computed.

Methods

clip = "numeric", L2deriv = "UnivariateDistribution", risk = "asMSE", neighbor = "ContNeighborhood"

optimal clipping bound for asymtotic mean square error.

clip = "numeric", L2deriv = "UnivariateDistribution", risk = "asMSE", neighbor = "TotalVarNeighborhood"

optimal clipping bound for asymtotic mean square error.

clip = "numeric", L2deriv = "EuclRandVariable", risk = "asMSE", neighbor = "ContNeighborhood"

optimal clipping bound for asymtotic mean square error.

clip = "numeric", L2deriv = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "UncondNeighborhood"

optimal clipping bound for asymtotic under-/overshoot risk.

Author(s)

Matthias Kohl [e-mail]

References

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.

See Also

ContIC-class, TotalVarIC-class

ROptEstOld documentation built on May 2, 2019, 12:51 p.m.