Generic Function for the Computation of the Standardizing Matrix
Description
Generic function for the computation of the standardizing matrix which takes care of the Fisher consistency of the corresponding IC. This function is rarely called directly. It is used 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  getInfStandRegTS(ErrorL2deriv, Regressor, neighbor, ...)
## S4 method for signature
## 'UnivariateDistribution,UnivariateDistribution,ContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature
## 'UnivariateDistribution,UnivariateDistribution,TotalVarNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, clip, cent)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## CondTotalVarNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, clip, cent)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## Av1CondContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature
## 'UnivariateDistribution,
## UnivariateDistribution,
## Av1CondTotalVarNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature
## 'UnivariateDistribution,MultivariateDistribution,ContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature
## 'UnivariateDistribution,
## MultivariateDistribution,
## Av1CondContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature
## 'UnivariateDistribution,
## MultivariateDistribution,
## Av1CondTotalVarNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature
## 'UnivariateDistribution,Distribution,Av2CondContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, z.comp, clip, cent, stand, trafo)
## S4 method for signature 'RealRandVariable,Distribution,ContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, ErrorDistr, A.comp, stand, clip,
cent, trafo)
## S4 method for signature
## 'RealRandVariable,Distribution,Av1CondContNeighborhood'
getInfStandRegTS(
ErrorL2deriv, Regressor, neighbor, ErrorDistr, A.comp, stand, clip,
cent, trafo)

Arguments
ErrorL2deriv 
L2derivative of 
Regressor 
regressor. 
neighbor 
object of class 
... 
additional parameters. 
ErrorDistr 
error distribution. 
clip 
optimal clipping bound/function. 
cent 
optimal centering constant/function. 
stand 
standardizing matrix. 
z.comp 
which components of the centering constant/function have to be computed. 
A.comp 
which components of the standardizing matrix have to be computed. 
trafo 
matrix: transformation of the parameter. 
Value
The standardizing matrix is computed.
Methods
 ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "ContNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "TotalVarNeighborhood"

computes standardizing constant.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "CondTotalVarNeighborhood"

computes standardizing constant.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "Av1CondContNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "UnivariateDistribution", neighbor = "Av1CondTotalVarNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", neighbor = "ContNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", neighbor = "Av1CondContNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "MultivariateDistribution", neighbor = "Av1CondTotalVarNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "UnivariateDistribution", Regressor = "Distribution", neighbor = "Av2CondContNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", neighbor = "ContNeighborhood"

computes standardizing matrix.
 ErrorL2deriv = "RealRandVariable", Regressor = "Distribution", neighbor = "Av1CondContNeighborhood"

computes standardizing matrix.
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.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
See Also
ContICclass
, TotalVarICclass
,
Av1CondContICclass
, Av2CondContICclass
,
Av1CondTotalVarICclass
, CondContIC
,
CondTotalVarIC