Infinitesimally Robust Estimation in General Smoothly Parametrized Models
Methodology
2010-08-04 v1 Applications
Abstract
We describe the shrinking neighborhood approach of Robust Statistics, which applies to general smoothly parametrized models, especially, exponential families. Equal generality is achieved by object oriented implementation of the optimally robust estimators. We evaluate the estimates on real datasets from literature by means of our R packages ROptEst and RobLox.
Cite
@article{arxiv.0901.3531,
title = {Infinitesimally Robust Estimation in General Smoothly Parametrized Models},
author = {Matthias Kohl and Peter Ruckdeschel and Helmut Rieder},
journal= {arXiv preprint arXiv:0901.3531},
year = {2010}
}