Class of (partial) influence curves.
Objects can be created by calls of the form new("IC", ...).
More frequently they are created via the generating function
IC.
CallL2FamObject of class "call":
creates an object of the underlying L2-differentiable
parametric family.
modifyICobject 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!
nameObject of class "character".
CurveObject of class "EuclRandVarList".
RisksObject of class "list":
list of risks; cf. RiskType-class.
InfosObject of class "matrix"
with two columns named method and message:
additional informations.
Class "InfluenceCurve", directly.
signature(object = "IC"):
accessor function for slot CallL2Fam.
signature(object = "IC"):
replacement function for slot CallL2Fam.
signature(object = "IC"):
accessor function for slot modifyIC.
signature(IC = "IC", L2Fam = "missing"):
check centering and Fisher consistency of IC assuming
the L2-differentiable parametric family which can
be generated via the slot CallL2Fam of IC.
signature(IC = "IC", L2Fam = "L2ParamFamily"):
check centering and Fisher consistency of IC assuming
the L2-differentiable parametric family L2Fam.
signature(IC = "IC", x = "numeric"):
evaluate IC at x.
signature(IC = "IC", x = "matrix"):
evaluate IC at the rows of x.
signature(object = "IC"):
Plot absolute and relative information of IC.
signature(x = "IC", y = "missing")
signature(object = "IC")
Matthias Kohl Matthias.Kohl@stamats.de
Hampel et al. (1986) Robust Statistics. The Approach Based on Influence Functions. New York: Wiley.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
InfluenceCurve-class, IC