getInfRobIC {ROptEstOld}R Documentation

Generic Function for the Computation of Optimally Robust ICs

Description

Generic function for the computation of optimally robust ICs in case of infinitesimal robust models. This function is rarely called directly.

Usage

getInfRobIC(L2deriv, risk, neighbor, ...)

## S4 method for signature 'UnivariateDistribution, asCov,
##   ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)

## S4 method for signature 'UnivariateDistribution, asCov,
##   TotalVarNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Finfo, trafo)

## S4 method for signature 'RealRandVariable, asCov,
##   ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Distr, Finfo, trafo)

## S4 method for signature 'UnivariateDistribution, asBias,
##   ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
             upper, maxiter, tol, warn)

## S4 method for signature 'UnivariateDistribution, asBias,
##   TotalVarNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
             upper, maxiter, tol, warn)

## S4 method for signature 'RealRandVariable, asBias,
##   ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
             L2derivDistrSymm, Finfo, z.start, A.start, trafo, upper, maxiter, tol, warn)

## S4 method for signature 'UnivariateDistribution,
##   asHampel, UncondNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
             upper, maxiter, tol, warn)

## S4 method for signature 'RealRandVariable, asHampel,
##   ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
             L2derivDistrSymm, Finfo, trafo, z.start, A.start, upper, maxiter, tol, warn)

## S4 method for signature 'UnivariateDistribution,
##   asGRisk, UncondNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
             upper, maxiter, tol, warn)

## S4 method for signature 'RealRandVariable, asGRisk,
##   ContNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, Distr, DistrSymm, L2derivSymm, 
             L2derivDistrSymm, Finfo, trafo, z.start, A.start, upper, maxiter, tol, warn)

## S4 method for signature 'UnivariateDistribution,
##   asUnOvShoot, UncondNeighborhood':
getInfRobIC(L2deriv, risk, neighbor, symm, Finfo, trafo, 
             upper, maxiter, tol, warn)

Arguments

L2deriv L2-derivative of some L2-differentiable family of probability measures.
risk object of class "RiskType".
neighbor object of class "Neighborhood".
... additional parameters.
Distr object of class "Distribution".
symm logical: indicating symmetry of L2deriv.
DistrSymm object of class "DistributionSymmetry".
L2derivSymm object of class "FunSymmList".
L2derivDistrSymm object of class "DistrSymmList".
Finfo Fisher information matrix.
z.start initial value for the centering constant.
A.start initial value for the standardizing matrix.
trafo matrix: transformation of the parameter.
upper upper bound for the optimal clipping bound.
maxiter the maximum number of iterations.
tol the desired accuracy (convergence tolerance).
warn logical: print warnings.

Value

The optimally robust IC is computed.

Methods

L2deriv = "UnivariateDistribution", risk = "asCov", neighbor = "ContNeighborhood"
computes the classical optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv = "UnivariateDistribution", risk = "asCov", neighbor = "TotalVarNeighborhood"
computes the classical optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv = "RealRandVariable", risk = "asCov", neighbor = "ContNeighborhood"
computes the classical optimal influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv = "UnivariateDistribution", risk = "asBias", neighbor = "ContNeighborhood"
computes the bias optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv = "UnivariateDistribution", risk = "asBias", neighbor = "TotalVarNeighborhood"
computes the bias optimal influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv = "RealRandVariable", risk = "asBias", neighbor = "ContNeighborhood"
computes the bias optimal influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv = "UnivariateDistribution", risk = "asHampel", neighbor = "UncondNeighborhood"
computes the optimally robust influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv = "RealRandVariable", risk = "asHampel", neighbor = "ContNeighborhood"
computes the optimally robust influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv = "UnivariateDistribution", risk = "asGRisk", neighbor = "UncondNeighborhood"
computes the optimally robust influence curve for L2 differentiable parametric families with unknown one-dimensional parameter.
L2deriv = "RealRandVariable", risk = "asGRisk", neighbor = "ContNeighborhood"
computes the optimally robust influence curve for L2 differentiable parametric families with unknown k-dimensional parameter (k > 1) where the underlying distribution is univariate.
L2deriv = "UnivariateDistribution", risk = "asUnOvShoot", neighbor = "UncondNeighborhood"
computes the optimally robust influence curve for one-dimensional L2 differentiable parametric families and asymptotic under-/overshoot risk.

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

InfRobModel-class


[Package ROptEstOld version 0.5.2 Index]