getStartIC-methods: Methods for Function getStartIC in Package `RobExtremes'

Description

getStartIC computes the optimally-robust IC to be used as argument ICstart in kStepEstimator.

Usage

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)

Arguments

model

normtype of class NormType

risk

normtype of class NormType

…

further arguments to be passed to specific methods.

withMakeIC

logical; if TRUE the IC is passed through makeIC before return.

..debug

logical; if TRUE information for debugging is issued.

modifyICwarn

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.

Value

An IC of type HampIC.

Methods

getStartIC: signature(model = "L2ScaleShapeUnion", risk = "interpolRisk"): computes the optimally robust influence function by interpolation on a grid (using internal helper function .getPsi).
getStartIC: signature(model = "L2LocScaleShapeUnion", risk = "interpolRisk"): computes the optimally robust influence function by interpolation on a grid (using internal helper function .getPsi.wL).
getStartIC: 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.

Details

getStartIC is used internally in functions robest and roptest to compute the optimally robust influence function according to the arguments given to them.