3 citations · 7 across the 6 of their papers we have counts for
6 papers
Consequences of Higher Order Asymptotics for the MSE of M-estimators on Neighborhoods
Peter Ruckdeschel
In Ruckdeschel[10], we derive an asymptotic expansion of the maximal mean squared error (MSE) of location M-estimators on suitably thinned out, shrinking gross error neighborhoods.…
Higher order asymptotics for the MSE of the sample median on shrinking neighborhoods
Peter Ruckdeschel
We provide an asymptotic expansion of the maximal mean squared error (MSE) of the sample median to be attained on shrinking gross error neighborhoods about an ideal central distrib…
Higher Order Expansion for the MSE of M-estimators on shrinking neighborhoods
Peter Ruckdeschel
We consider estimation of a one-dimensional location parameter by means of M-estimators S_n with monotone influence curve psi. For growing sample size n, on suitably thinned out co…
Fisher Information in Group-Type Models
Peter Ruckdeschel
In proofs of L_2-differentiability, Lebesgue densities of a central distribution are often assumed right from the beginning. Generalizing Theorem 4.2 of Huber[81], we show that in…
Optimally Robust Kalman Filtering at Work: AO-, IO-, and Simultaneously IO- and AO- Robust Filters
Peter Ruckdeschel
We take up optimality results for robust Kalman filtering from Ruckdeschel[2001,2010] where robustness is understood in a distributional sense, i.e.; we enlarge the distribution as…
Optimally (Distributional-)Robust Kalman Filtering
Peter Ruckdeschel
We present optimality results for robust Kalman filtering where robustness is understood in a distributional sense, i.e.; we enlarge the distribution assumptions made in the ideal…