kStepEstimatorStart-methods: Methods for function kStepEstimator.start in Package...

In RobAStBase: Robust Asymptotic Statistics

Methods for function kStepEstimator.start in Package ‘RobAStBase’

Description

kStepEstimator.start-methods; these are called from within kStepEstimator to produce a numeric value of for the starting estimator in the end.

Usage

kStepEstimator.start(start, ...)
## S4 method for signature 'numeric'
kStepEstimator.start(start, nrvalues, ...)
## S4 method for signature 'Estimate'
kStepEstimator.start(start, nrvalues, ...)
## S4 method for signature 'function'
kStepEstimator.start(start, x, nrvalues, na.rm, L2Fam, startList)

Arguments

start	the start slot of an object of class kStepEstimator
nrvalues	numeric; dimension k of the original model, i.e.; length of the untransformed parameter, or joint length of main and nuisance part of the parameter.
x	the data at which the starting estimator is to be evaluated.
na.rm	logical: if TRUE, the estimator is evaluated at complete.cases(x).
startList	a list of arguments to be given to the call to start if this is a function;
L2Fam	the parametric famliy;
...	further arguments for kStepEstimator.start.

Value

a numeric vector with the corresponding value of the start estimator (in k space)

Methods

kStepEstimator.start

signature(start = "numeric"): returns the unchanged argument start if it has the correct length; otherwise throws an error.

kStepEstimator.start

signature(start = "Estimate"): returns slot untransformed.estimate of start if it is not NULL, and else slot estimate if the latter has dimension nrvalues.

kStepEstimator.start

signature(start = "function"): returns kStepEstimator.start(do.call(start, args=c(list(x,L2Fam),startList) where, if na.rm == TRUE, beforehand x has been modified to x <- complete.cases(x).

Author(s)

Peter Ruckdeschel [e-mail]

References

Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.

See Also

kStepEstimator,ALEstimate-class

RobAStBase documentation built on April 12, 2025, 1:39 a.m.