Generates an object of class "Av1CondContIC"
;
i.e., an influence curves \(\eta\) of the form
$$\eta = A x \Lambda_f\min(1,\max(c(x)/(|Ax|\Lambda_f), (c(x)+b)/(|Ax|\Lambda_f)))$$
with lower clipping function \(c\), standardized bias \(b\) and
standardizing matrix \(A\). \(\Lambda_f\) stands for
the L2 derivative of the corresponding error distribution.
Av1CondTotalVarIC(name, CallL2Fam = call("L2RegTypeFamily"),
Curve = EuclRandVarList(RealRandVariable(
Map = list(function(x) {x[1] * x[2]}),
Domain = EuclideanSpace(dimension = 2))),
Risks, Infos, clipUp = Inf, stand = as.matrix(1),
clipLo = RealRandVariable(Map = list(function(x) {-Inf}),
Domain = EuclideanSpace(dimension = 1)),
lowerCase = NULL, neighborRadius = 0)
object of class "character"
.
object of class "call"
:
creates an object of the underlying L2-differentiable
regression type family.
object of class "EuclRandVarList"
object of class "list"
:
list of risks; cf. RiskType-class
.
matrix of characters with two columns
named method
and message
: additional informations.
positive real: standardized bias.
object of class "RealRandVariable"
:
lower clipping function.
matrix: standardizing matrix.
optional constant for lower case solution.
radius of the corresponding (unconditional) contamination neighborhood.
Object of class "Av1CondTotalVarIC"
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
# NOT RUN {
IC1 <- Av1CondTotalVarIC()
IC1
# }
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