Generic Function for the Computation of the Optimal Clipping Bound
Description
Generic function for the computation of the optimal clipping bound.
This function is rarely called directly. It is called by getInfClipRegTS
to compute optimally robust ICs.
Usage
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 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89  getInfGammaRegTS(ErrorL2deriv, Regressor, risk, neighbor, ...)
## S4 method for signature
## 'UnivariateDistribution,UnivariateDistribution,asMSE,ContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## asMSE,
## Av1CondContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## asMSE,
## Av1CondTotalVarNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,
## MultivariateDistribution,
## asMSE,
## ContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,
## MultivariateDistribution,
## asMSE,
## Av1CondContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,
## MultivariateDistribution,
## asMSE,
## Av1CondTotalVarNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,Distribution,asMSE,Av2CondContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, z.comp, stand, cent, clip)
## S4 method for signature
## 'RealRandVariable,Distribution,asMSE,ContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, ErrorDistr, stand, cent,
clip)
## S4 method for signature
## 'RealRandVariable,Distribution,asMSE,Av1CondContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, ErrorDistr, stand, cent,
clip)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## asUnOvShoot,
## ContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## asUnOvShoot,
## TotalVarNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, cent, clip)
## S4 method for signature
## 'UnivariateDistribution,numeric,asUnOvShoot,CondContNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, clip)
## S4 method for signature
## 'UnivariateDistribution,numeric,asUnOvShoot,CondTotalVarNeighborhood'
getInfGammaRegTS(
ErrorL2deriv, Regressor, risk, neighbor, clip)

Arguments
ErrorL2deriv 
L2derivative of 
Regressor 
regressor. 
risk 
object of class 
neighbor 
object of class 
... 
additional parameters. 
clip 
optimal clipping bound. 
cent 
optimal centering constant/function. 
stand 
standardizing matrix. 
z.comp 
which components of the centering constant/function have to be computed. 
ErrorDistr 
error distribution. 
Details
The function is used in case of asymptotic Grisks; confer Ruckdeschel and Rieder (2004).
Methods
 ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asMSE", neighbor = "ContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asMSE", neighbor = "Av1CondContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asMSE", neighbor = "Av1CondTotalVarNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asMSE", neighbor = "ContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asMSE", neighbor = "Av1CondContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", risk = "asMSE", neighbor = "Av1CondTotalVarNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", risk = "asMSE", neighbor = "Av2CondContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asMSE", neighbor = "ContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", risk = "asMSE", neighbor = "Av1CondContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "ContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "TotalVarNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "numeric", risk = "asUnOvShoot", neighbor = "CondContNeighborhood"

used by
getInfClipRegTS
.  ErrorL2deriv = "UnivariateDistribution", Regressor = "numeric", risk = "asUnOvShoot", neighbor = "CondTotalVarNeighborhood"

used by
getInfClipRegTS
.
Author(s)
Matthias Kohl Matthias.Kohl@stamats.de
References
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 (submitted).
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
See Also
asMSEclass
, asUnOvShootclass
,
ContICclass
, Av1CondContICclass
,
Av2CondContICclass
, Av1CondTotalVarICclass
,
CondContICclass
, CondTotalVarICclass
Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker. Vote for new features on Trello.