getInfStandRegTS {ROptRegTS}R Documentation

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

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 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

ContIC-class, TotalVarIC-class, Av1CondContIC-class, Av2CondContIC-class, Av1CondTotalVarIC-class, CondContIC, CondTotalVarIC


[Package ROptRegTS version 0.6.1 Index]