Description Usage Arguments Details Value Author(s) References See Also
View source: R/oneStepEstimator.R
Function for the computation of onestep estimates.
1 2 3 4 5 6  oneStepEstimator(x, IC, start = NULL,
useLast = getRobAStBaseOption("kStepUseLast"),
withUpdateInKer = getRobAStBaseOption("withUpdateInKer"),
IC.UpdateInKer = getRobAStBaseOption("IC.UpdateInKer"),
na.rm = TRUE, startArgList = NULL, withMakeIC = FALSE, ...,
E.argList = NULL)

x 
sample 
IC 
object of class 
start 
initial estimate (for full parameter,i.e. in dimension k respective
joint length of main and nuisance part of the parameter):
either a numerical value, or an object of class 
useLast 
which parameter estimate (initial estimate or
onestep estimate) shall be used to fill the slots 
withUpdateInKer 
if there is a nontrivial trafo in the model with matrix D, shall the parameter be updated on ker(D)? 
IC.UpdateInKer 
if there is a nontrivial trafo in the model with matrix D,
the IC to be used for this; if 
na.rm 
logical: if 
startArgList 
a list of arguments to be given to argument 
withMakeIC 
logical; if 
... 
additional arguments 
E.argList 

Given an initial estimation start
, a sample x
and an influence curve IC
the corresponding onestep
estimator is computed.
In case IC
is an object of class "IC"
the slots asvar
and asbias
of the return
value are filled (based on the initial estimate).
The default value of argument useLast
is set by the
global option kStepUseLast
which by default is set to
FALSE
. In case of general models useLast
remains unchanged during the computations. However, if
slot CallL2Fam
of IC
generates an object of
class "L2GroupParamFamily"
the value of useLast
is changed to TRUE
.
Explicitly setting useLast
to TRUE
should
be done with care as in this situation the influence curve
is recomputed using the value of the onestep estimate
which may take quite a long time depending on the model.
If useLast
is set to TRUE
and slot modifyIC
of IC
is filled with some function (which can be
used to recompute the IC for a different parameter), the
computation of asvar
, asbias
and IC
is
based on the onestep estimate.
Object of class "kStepEstimate"
Matthias Kohl [email protected],
Peter Ruckdeschel [email protected]
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
InfluenceCurveclass
, kStepEstimateclass
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