Probabilistic Set-membership Approach for Robust Regression

@article{Jaulin2010ProbabilisticSA,
  title={Probabilistic Set-membership Approach for Robust Regression},
  author={Luc Jaulin},
  journal={Journal of Statistical Theory and Practice},
  year={2010},
  volume={4},
  pages={155-167}
}
  • L. Jaulin
  • Published 1 March 2010
  • Mathematics
  • Journal of Statistical Theory and Practice
Interval constraint propagation methods have been shown to be efficient and reliable to solve difficult nonlinear bounded-error estimation problems. However they are considered as unsuitable in a probabilistic context, where the approximation of a probability density function by a set cannot be accepted as reliable. This paper shows how probabilistic estimation problems can be transformed into a set estimation problem by assuming that some rare events will never happen. Since the probability of… Expand

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