getInfStandRegTS: Generic Function for the Computation of the Standardizing...

In ROptRegTS: Optimally Robust Estimation for Regression-Type Models

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

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	L2-derivative of ErrorDistr.
Regressor	regressor.
neighbor	object of class "Neighborhood".
...	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 [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, Av1CondContIC-class, Av2CondContIC-class, Av1CondTotalVarIC-class, CondContIC, CondTotalVarIC

ROptRegTS documentation built on May 2, 2019, 6:51 p.m.