Partial robust M-regression

By Sven Serneels, Christophe Croux, Peter Filzmoser, Pierre J. Van Espen. 2005

194 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Food Science, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/164268164759628d3d1b49a1fffe9674c11e876f

How researchers see this paper

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

In Analytical Chemistry

1. Klaus Nordhausen
2. Mark Werner
3. Ricardo A. Maronna
4. Peter Filzmoser

In Food Science

1. Klaus Nordhausen
2. Peter Filzmoser

In Statistics and Probability

1. Peter Filzmoser
2. Klaus Nordhausen
3. Mark Werner
4. Ricardo A. Maronna
5. Karel Hron
6. Patrick L. Combettes
7. Rob J Hyndman
8. Jieping Ye

Citations in the corpus

• Robust linear regression for high‐dimensional data: An overview (2020, methodology): “The proposal of Filzmoser and Kurnaz (2018) provides these properties, and the idea is similar to Maronna (2011) by including weights, in this case originating from a PRM estimator (Serneels et al., 2005).”
• Outlier identification in high dimensions (2008, background): “The last 38 observations are clearly visible as multivariate outliers in the intermediate steps of the algorithm; these are the previously mentioned leverage points (see Serneels et al. (2005)).”