Generating functions to generate structured input for function robest.
genkStepCtrl(useLast = getRobAStBaseOption("kStepUseLast"),
withUpdateInKer = getRobAStBaseOption("withUpdateInKer"),
IC.UpdateInKer = getRobAStBaseOption("IC.UpdateInKer"),
withICList = getRobAStBaseOption("withICList"),
withPICList = getRobAStBaseOption("withPICList"),
scalename = "scale", withLogScale = TRUE,
withEvalAsVar = NULL, withMakeIC = FALSE)
genstartCtrl(initial.est = NULL, initial.est.ArgList = NULL,
startPar = NULL, distance = CvMDist, withMDE = NULL)
gennbCtrl(neighbor = ContNeighborhood(), eps, eps.lower, eps.upper)
genstartICCtrl(withMakeIC = FALSE, withEvalAsVar = NULL, modifyICwarn = NULL)which parameter estimate (initial estimate or
k-step estimate) shall be used to fill the slots pIC,
asvar and asbias of the return value.
if there is a non-trivial trafo in the model with matrix \(D\), shall the parameter be updated on \({\rm ker}(D)\)?
if there is a non-trivial trafo in the model with matrix \(D\),
the IC to be used for this; if NULL the result of getboundedIC(L2Fam,D) is taken;
this IC will then be projected onto \({\rm ker}(D)\).
logical: shall slot ICList of return value
be filled?
logical: shall slot pICList of return value
be filled?
character: name of the respective scale component.
logical; shall a scale component (if existing and found
with name scalename) be computed on log-scale and backtransformed
afterwards? This avoids crossing 0.
logical or NULL: if TRUE (default), tells R
to evaluate the asymptotic variance or if FALSE just to produces a call
to do so. If withEvalAsVar is NULL (default), the content
of slot .withEvalAsVar in the L2 family is used instead to take
this decision.
logical; if TRUE the [p]IC is passed through
makeIC before return.
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.
initial estimate for unknown parameter. If missing minimum distance estimator is computed.
a list of arguments to be given to argument start if the latter
is a function; this list by default already starts with two unnamed items,
the sample x, and the model L2Fam.
initial information used by optimize resp. optim;
i.e; if (total) parameter is of length 1, startPar is
a search interval, else it is an initial parameter value; if NULL
slot startPar of ParamFamily is used to produce it;
in the multivariate case, startPar may also be of class Estimate,
in which case slot untransformed.estimate is used.
distance function
logical or NULL: Shall a minimum distance estimator be used as
starting estimator in roptest() / robest()---in addition to
the function given in argument startPar of the current function
or, if the argument is NULL, in slot startPar of the L2
family? If NULL (default) the content of slot .withMDE in
the L2 family is used instead to take this decision.
object of class "UncondNeighborhood"
positive real (0 < eps <= 0.5): amount of gross errors.
See details below.
positive real (0 <= eps.lower <= eps.upper):
lower bound for the amount of gross errors. See details below.
positive real (eps.lower <= eps.upper <= 0.5):
upper bound for the amount of gross errors. See details below.
All these functions bundle their respective input to (reusable) lists
which can be used as arguments in function robest.
For details, see this function.
roblox,
L2ParamFamily-class
UncondNeighborhood-class,
RiskType-class
# NOT RUN {
genkStepCtrl()
genstartICCtrl()
genstartCtrl()
gennbCtrl()
# }
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