Methods for Function getStartIC in Package ‘ROptEst’
getStartIC computes the optimally-robust IC to be used as
argument ICstart in kStepEstimator.
getStartIC(model, risk, ...)
## S4 method for signature 'ANY,ANY'
getStartIC(model, risk, ...)
## S4 method for signature 'L2ParamFamily,asGRisk'
getStartIC(model, risk, ...,
withEvalAsVar = TRUE, withMakeIC = FALSE, ..debug=FALSE,
modifyICwarn = NULL, diagnostic = FALSE)
## S4 method for signature 'L2ParamFamily,asBias'
getStartIC(model, risk, ..., withMakeIC = FALSE,
..debug=FALSE, modifyICwarn = NULL, diagnostic = FALSE)
## S4 method for signature 'L2ParamFamily,asCov'
getStartIC(model, risk, ..., withMakeIC = FALSE,
..debug=FALSE)
## S4 method for signature 'L2ParamFamily,trAsCov'
getStartIC(model, risk, ..., withMakeIC = FALSE,
..debug=FALSE)
## S4 method for signature 'L2ParamFamily,asAnscombe'
getStartIC(model, risk, ...,
withEvalAsVar = TRUE, withMakeIC = FALSE, ..debug=FALSE,
modifyICwarn = NULL, diagnostic = FALSE)
## S4 method for signature 'L2LocationFamily,interpolRisk'
getStartIC(model, risk, ...)
## S4 method for signature 'L2ScaleFamily,interpolRisk'
getStartIC(model, risk, ...)
## S4 method for signature 'L2LocationScaleFamily,interpolRisk'
getStartIC(model, risk, ...)model |
normtype of class |
risk |
normtype of class |
... |
further arguments to be passed to specific methods. |
withEvalAsVar |
logical (of length 1):
if |
withMakeIC |
logical; if |
..debug |
logical; if |
modifyICwarn |
logical: should a (warning) information be added if
|
diagnostic |
logical; if |
getStartIC is used internally in functions robest
and roptest to compute the optimally robust influence function
according to the arguments given to them.
An IC of type HampIC.
signature(model = "ANY", risk = "ANY"):
issue that this is not yet implemented.
signature(model = "L2ParamFamily", risk = "asGRisk"):
depending on the values of argument eps (to be passed on through
the ... argument) computes the optimally robust influence
function on the fly via calls to optIC or radiusMinimaxIC.
signature(model = "L2ParamFamily", risk = "asBias"):
computes the most-bias-robust influence function on the fly via
calls to optIC.
signature(model = "L2ParamFamily", risk = "asCov"):
computes the classically optimal influence function on the fly via
calls to optIC.
signature(model = "L2ParamFamily", risk = "trAsCov"):
computes the classically optimal influence function on the fly via
calls to optIC.
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.