getAsRisk: Generic Function for Computation of Asymptotic Risks

Description

Generic function for the computation of asymptotic risks. This function is rarely called directly. It is used by other functions.

Usage

getAsRisk(risk, L2deriv, neighbor, biastype, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand, trafo, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand, trafo, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand, trafo, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand, trafo, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand = NULL, trafo, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand = NULL, trafo, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand = NULL, trafo, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand = NULL, trafo, ...)
"getAsRisk"( risk,L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent = NULL, stand = NULL, Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, Finfo, trafo, z.start, A.start, maxiter, tol, warn, verbose = NULL, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL,  clip = NULL, cent = NULL, stand = NULL, Distr, DistrSymm, L2derivSymm, L2derivDistrSymm, Finfo, trafo, z.start, A.start, maxiter, tol, warn, verbose = NULL, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip, cent, stand, trafo = NULL, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip, cent, stand, trafo = NULL, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype = NULL, clip = NULL, cent, stand, Distr, trafo = NULL, V.comp =  matrix(TRUE, ncol = nrow(stand), nrow = nrow(stand)), w, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip, cent, stand, trafo = NULL, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype, clip, cent, stand, Distr, trafo = NULL,  V.comp =  matrix(TRUE, ncol = nrow(stand), nrow = nrow(stand)), w, ...) 
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip, cent, stand, trafo = NULL, FI, ...)
"getAsRisk"(risk, L2deriv, neighbor, biastype, normtype, clip, cent, stand, Distr, trafo = NULL,  V.comp =  matrix(TRUE, ncol = nrow(stand), nrow = nrow(stand)), FI, w, ...) 
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip, cent, stand, trafo, ...)
"getAsRisk"( risk, L2deriv, neighbor, biastype, normtype = NULL, clip, cent, stand, trafo, ...)

Arguments

risk

object of class "asRisk".

L2deriv

L2-derivative of some L2-differentiable family of probability distributions.

neighbor

object of class "Neighborhood".

biastype

object of class "ANY".

...

additional parameters; often used to enable flexible calls.

clip

optimal clipping bound.

cent

optimal centering constant.

stand

standardizing matrix.

Finfo

matrix: the Fisher Information of the parameter.

trafo

matrix: transformation of the parameter.

Distr

object of class "Distribution".

DistrSymm

object of class "DistributionSymmetry".

L2derivSymm

object of class "FunSymmList".

L2derivDistrSymm

object of class "DistrSymmList".

z.start

initial value for the centering constant.

A.start

initial value for the standardizing matrix.

maxiter

the maximum number of iterations

tol

the desired accuracy (convergence tolerance).

warn

logical: print warnings.

normtype

object of class "NormType".

V.comp

matrix: indication which components of the standardizing matrix have to be computed.

object of class RobWeight; current weight

trace of the respective Fisher Information

verbose

logical: if TRUE some diagnostics are printed out.

Value

Methods

Details

This function is rarely called directly. It is used by other functions/methods.

References

Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.

Ruckdeschel, P. and Rieder, H. (2004) Optimal Influence Curves for General Loss Functions. Statistics & Decisions 22, 201-223.

Ruckdeschel, P. (2005) Optimally One-Sided Bounded Influence Curves. Mathematical Methods in Statistics 14(1), 105-131.

Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.