Description Usage Arguments Value Methods Author(s) References See Also
The usual robust optimality problem for given asGRisk searches the optimal
clipping height b of a Hampeltype IC to given radius of the neighborhood.
Instead, again for given asGRisk and for given HampelType IC with
given clipping height b we may determine the radius of the neighborhood
for which it is optimal in the sense of the first sentence. This
radius is determined by getInfRad
. This function is rarely called
directly. It is used withing getRadius
.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45  getInfRad(clip, L2deriv, risk, neighbor, ...)
## S4 method for signature
## 'numeric,UnivariateDistribution,asMSE,ContNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature
## 'numeric,UnivariateDistribution,asMSE,TotalVarNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature
## 'numeric,UnivariateDistribution,asL1,ContNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature
## 'numeric,UnivariateDistribution,asL1,TotalVarNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature
## 'numeric,UnivariateDistribution,asL4,ContNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature
## 'numeric,UnivariateDistribution,asL4,TotalVarNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature 'numeric,EuclRandVariable,asMSE,UncondNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, Distr, stand, cent, trafo, ...)
## S4 method for signature
## 'numeric,UnivariateDistribution,asUnOvShoot,UncondNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)
## S4 method for signature
## 'numeric,UnivariateDistribution,asSemivar,ContNeighborhood'
getInfRad(
clip, L2deriv, risk, neighbor, biastype, cent, symm, trafo)

clip 
positive real: clipping bound 
L2deriv 
L2derivative of some L2differentiable family of probability measures. 
risk 
object of class 
neighbor 
object of class 
... 
additional parameters. 
biastype 
object of class 
cent 
optimal centering constant. 
stand 
standardizing matrix. 
Distr 
object of class 
symm 
logical: indicating symmetry of 
trafo 
matrix: transformation of the parameter. 
The optimal clipping bound is computed.
optimal clipping bound for asymtotic mean square error.
optimal clipping bound for asymtotic mean square error.
optimal clipping bound for asymtotic mean square error.
optimal clipping bound for asymtotic mean absolute error.
optimal clipping bound for asymtotic mean absolute error.
optimal clipping bound for asymtotic mean power 4 error.
optimal clipping bound for asymtotic mean power 4 error.
optimal clipping bound for asymtotic under/overshoot risk.
optimal clipping bound for asymtotic semivariance.
Peter Ruckdeschel [email protected]
Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. 8: 106–115.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for General Loss Functions. Statistics & Decisions 22, 201223.
Ruckdeschel, P. (2005) Optimally OneSided Bounded Influence Curves. Mathematical Methods in Statistics 14(1), 105131.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
ContICclass
, TotalVarICclass
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