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2010
ACM

Infinitesimally Robust estimation in general smoothly parametrized models

8 years 6 months ago
Infinitesimally Robust estimation in general smoothly parametrized models
Abstract The aim of the paper is to give a coherent account of the robustness approach based on shrinking neighborhoods in the case of i.i.d. observations, and add some theoretical complements. An important aspect of the approach is that it does not require any particular model structure but covers arbitrary parametric models if only smoothly parametrized. In the meantime, equal generality has been achieved by object-oriented implementation of the optimally robust estimators. Exponential families constitute the main examples in this article. Not pretending a complete data analysis, we evaluate the robust estimates on real datasets from literature by means of our R packages ROptEst and RobLox. Keywords Exponential family
Matthias Kohl, Peter Ruckdeschel, Helmut Rieder
Added 21 May 2011
Updated 21 May 2011
Type Journal
Year 2010
Where SMA
Authors Matthias Kohl, Peter Ruckdeschel, Helmut Rieder
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