minmaxBias {ROptEst} | R Documentation |
Generic function for the computation of bias-optimally 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) ## S4 method for signature 'UnivariateDistribution, ## ContNeighborhood, asymmetricBias': minmaxBias(L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo) ## S4 method for signature 'UnivariateDistribution, ## ContNeighborhood, onesidedBias': minmaxBias(L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo) ## S4 method for signature 'UnivariateDistribution, ## TotalVarNeighborhood, BiasType': minmaxBias(L2deriv, neighbor, biastype, symm, trafo, maxiter, tol, warn, Finfo) ## S4 method for signature 'RealRandVariable, ## ContNeighborhood, BiasType': minmaxBias(L2deriv, neighbor, biastype, normtype, Distr, z.start, A.start, z.comp, A.comp, trafo, maxiter, tol)
L2deriv |
L2-derivative of some L2-differentiable family of probability measures. |
neighbor |
object of class "Neighborhood" . |
biastype |
object of class "BiasType" . |
normtype |
object of class "NormType" . |
... |
additional parameters. |
Distr |
object of class "Distribution" . |
symm |
logical: indicating symmetry of L2deriv . |
z.start |
initial value for the centering constant. |
A.start |
initial value for the standardizing matrix. |
z.comp |
logical indicator which indices need to be computed and which are 0 due to symmetry. |
A.comp |
matrix of logical indicator which indices need to be computed and which are 0 due to symmetry. |
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. |
The bias-optimally robust IC is computed.
Matthias Kohl Matthias.Kohl@stamats.de, Peter Ruckdeschel Peter.Ruckdeschel@itwm.fraunhofer.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 One-Sided Bounded Influence Curves. Mathematical Methods in Statistics 14(1), 105-131.
Kohl, M. (2005) Numerical Contributions to the Asymptotic Theory of Robustness. Bayreuth: Dissertation.