6 citations · 13 across the 4 of their papers we have counts for
5 papers
Neighborhoods as Nuisance Parameters? Robustness vs. Semiparametrics
Helmut Rieder
Deviations from the center within a robust neighborhood of a parametric model distribution may naturally be considered an infinite dimensional nuisance parameter. Thus, the semipar…
One-Sided Confidence About Functionals Over Tangent Cones
Helmut Rieder
In the setup of i.i.d.~observations and a real valued differentiable functional~, locally asymptotic upper bounds are derived for the power of one-sided tests (simple, versus la…
Connections between Semiparametrics and Robustness
Helmut Rieder
Robust and semiparametric statistics are of the same historical origin and largely employ the same locally asymptotically normal framework. In our talk, we consider he following mo…
Fisher Information of Scale
Peter Ruckdeschel, Helmut Rieder
Motivated by the information bound for the asymptotic variance of M-estimates for scale, we define Fisher information of scale of any distribution function F on the real line as a…
Infinitesimally Robust Estimation in General Smoothly Parametrized Models
Matthias Kohl, Peter Ruckdeschel, Helmut Rieder
We describe the shrinking neighborhood approach of Robust Statistics, which applies to general smoothly parametrized models, especially, exponential families. Equal generality is a…