Learn R Programming

RobAStBase (version 1.2.6)

TotalVarIC: Generating function for TotalVarIC-class

Description

Generates an object of class "TotalVarIC"; i.e., an influence curves \(\eta\) of the form $$\eta = c \vee A\Lambda \wedge d$$ with lower clipping bound \(c\), upper clipping bound \(d\) and standardizing matrix \(A\). \(\Lambda\) stands for the L2 derivative of the corresponding L2 differentiable parametric family which can be created via CallL2Fam.

Usage

TotalVarIC(name, CallL2Fam = call("L2ParamFamily"), 
           Curve = EuclRandVarList(RealRandVariable(Map = c(function(x) {x}), 
                                                    Domain = Reals())), 
           Risks, Infos, clipLo = -Inf, clipUp = Inf, stand = as.matrix(1), 
           lowerCase = NULL, neighborRadius = 0, w = new("BdStWeight"),
           normtype = NormType(), biastype = symmetricBias(),
           modifyIC = NULL)

Value

Object of class "TotalVarIC"

Arguments

name

object of class "character".

CallL2Fam

object of class "call": creates an object of the underlying L2-differentiable parametric family.

Curve

object of class "EuclRandVarList".

Risks

object of class "list": list of risks; cf. RiskType-class.

Infos

matrix of characters with two columns named method and message: additional informations.

clipLo

negative real: lower clipping bound.

clipUp

positive real: lower clipping bound.

stand

matrix: standardizing matrix

w

BdStWeight: weight object

lowerCase

optional constant for lower case solution.

neighborRadius

radius of the corresponding (unconditional) contamination neighborhood.

biastype

BiasType: type of the bias

normtype

NormType: type of the norm

modifyIC

object of class "OptionalFunction": function of four arguments: (1) L2Fam an L2 parametric family (2) IC an optional influence curve, (3) withMakeIC a logical argument whether to enforce the IC side conditions by makeIC, and (4) ... for arguments to be passed to calls to E in makeIC. Returns an object of class "IC". This function is mainly used for internal computations!

Author

Matthias Kohl Matthias.Kohl@stamats.de

References

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

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

See Also

IC-class, ContIC

Examples

Run this code
IC1 <- TotalVarIC()
plot(IC1)

Run the code above in your browser using DataLab