Breakdown points of trimmed likelihood estimators and related estimators in generalized linear models

By Christine H. Müller, C. V. Ossietzky, N. Neykov. 2003

71 citations recorded by the source corpus.

Subfields: Management Science and Operations Research, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/ff5c8fa2165efb752b39fbd999e35931a46390c1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Management Science and Operations Research

1. Mia Hubert
2. Peter J. Rousseeuw
3. S. Van Aelst
4. Christine H. Müller
5. N. Neykov

In Statistics and Probability

1. Mia Hubert
2. Peter J. Rousseeuw
3. S. Van Aelst
4. Christine H. Müller
5. N. Neykov
6. K. V. Branden
7. Peter Filzmoser
8. Andrea Cerioli

Citations in the corpus

• High-Breakdown Robust Multivariate Methods (2008, methodology): “For generalized linear models, robust approaches have been proposed by Cantoni and Ronchetti (2001), Künsch, Stefanski and Carroll (1989), Markatou, Basu and Lindsay (1998), Müller and Neykov (2003) and Rousseeuw and Christmann (2003).”
• Breakdown Point and Computation of Trimmed Likelihood Estimators in Generalized Linear Models (2003, methodology): “Müller and Neykov [19] relaxed the compactness condition in the above definition assuming only that the set Lg(θ)(C) is contained in a compact set.”