getStartIC
computes the optimally-robust IC to be used as
argument ICstart
in kStepEstimator
.
getStartIC(model, risk, ...)
# S4 method for L2ScaleShapeUnion,interpolRisk
getStartIC(model, risk, ...,
withMakeIC = FALSE, ..debug=FALSE, modifyICwarn = NULL)
# S4 method for L2LocScaleShapeUnion,interpolRisk
getStartIC(model, risk, ...,
withMakeIC = FALSE, ..debug=FALSE, modifyICwarn = NULL)
# S4 method for ParetoFamily,interpolRisk
getStartIC(model, risk, ...,
withMakeIC = FALSE)
An IC of type HampIC
.
normtype of class NormType
normtype of class NormType
further arguments to be passed to specific methods.
logical; if TRUE
the IC is passed through
makeIC
before return.
logical; if TRUE
information for debugging is issued.
logical: should a (warning) information be added if
modifyIC
is applied and hence some optimality information could
no longer be valid? Defaults to NULL
in which case this value
is taken from RobAStBaseOptions
.
signature(model = "L2ScaleShapeUnion", risk = "interpolRisk")
:
computes the optimally robust influence function by interpolation
on a grid (using internal helper function .getPsi
).
signature(model = "L2LocScaleShapeUnion", risk = "interpolRisk")
:
computes the optimally robust influence function by interpolation
on a grid (using internal helper function .getPsi.wL
).
signature(model = "ParetoFamily", risk = "interpolRisk")
:
computes the optimally robust influence function by interpolation
on a grid (using internal helper function .getPsi.P
).
All of these methods recenter and restandardize the obtained ICs to warrant centeredness and Fisher consistency.
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
getStartIC
is used internally in functions robest
and roptest
to compute the optimally robust influence function
according to the arguments given to them.
robest
,optIC
, radiusMinimaxIC