minmaxBias  R Documentation 
Generic function for the computation of biasoptimally robust ICs in case of infinitesimal robust models. This function is rarely called directly.
minmaxBias(L2deriv, neighbor, biastype, ...)
## S4 method for signature 'UnivariateDistribution,ContNeighborhood,BiasType'
minmaxBias(L2deriv,
neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo, verbose = NULL)
## S4 method for signature
## 'UnivariateDistribution,ContNeighborhood,asymmetricBias'
minmaxBias(
L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo, verbose = NULL)
## S4 method for signature
## 'UnivariateDistribution,ContNeighborhood,onesidedBias'
minmaxBias(
L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo, verbose = NULL)
## S4 method for signature
## 'UnivariateDistribution,TotalVarNeighborhood,BiasType'
minmaxBias(
L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo, verbose = NULL)
## S4 method for signature 'RealRandVariable,ContNeighborhood,BiasType'
minmaxBias(L2deriv,
neighbor, biastype, normtype, Distr, z.start, A.start, z.comp, A.comp,
Finfo, trafo, maxiter, tol, verbose = NULL, ...)
## S4 method for signature 'RealRandVariable,TotalVarNeighborhood,BiasType'
minmaxBias(L2deriv,
neighbor, biastype, normtype, Distr, z.start, A.start, z.comp, A.comp,
Finfo, trafo, maxiter, tol, verbose = NULL, ...)
L2deriv 
L2derivative of some L2differentiable family of probability measures. 
neighbor 
object of class 
biastype 
object of class 
normtype 
object of class 
... 
additional arguments to be passed to 
Distr 
object of class 
symm 
logical: indicating symmetry of 
z.start 
initial value for the centering constant. 
A.start 
initial value for the standardizing matrix. 
z.comp 

A.comp 

trafo 
matrix: transformation of the parameter. 
maxiter 
the maximum number of iterations. 
tol 
the desired accuracy (convergence tolerance). 
warn 
logical: print warnings. 
Finfo 
Fisher information matrix. 
verbose 
logical: if 
The biasoptimally robust IC is computed.
computes the bias optimal influence curve for symmetric bias for L2 differentiable parametric families with unknown onedimensional parameter.
computes the bias optimal influence curve for asymmetric bias for L2 differentiable parametric families with unknown onedimensional parameter.
computes the bias optimal influence curve for symmetric bias for L2 differentiable parametric families with unknown onedimensional parameter.
computes the bias optimal influence curve for symmetric bias for L2 differentiable
parametric families with unknown k
dimensional parameter
(k > 1
) where the underlying distribution is univariate.
computes the bias optimal influence curve for symmetric bias for L2 differentiable
parametric families in a setting where we are interested in a p=1
dimensional aspect of an unknown k
dimensional parameter
(k > 1
) where the underlying distribution is univariate.
Matthias Kohl Matthias.Kohl@stamats.de, Peter Ruckdeschel peter.ruckdeschel@unioldenburg.de
Rieder, H. (1980) Estimates derived from robust tests. Ann. Stats. 8: 106–115.
Rieder, H. (1994) Robust Asymptotic Statistics. New York: Springer.
Ruckdeschel, P. (2005) Optimally OneSided Bounded Influence Curves. Mathematical Methods in Statistics 14(1), 105131.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.
InfRobModelclass
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