Breakdown points of t-type regression estimators

By Xuming He, D. Simpson, Guangyu Wang. 2000

48 citations recorded by the source corpus.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/05f16d5b390c0c06def87d1e2df73d786e4514f6

How researchers see this paper

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

In Statistics and Probability

1. Mia Hubert
2. Peter J. Rousseeuw
3. S. Van Aelst
4. Xuming He
5. Zhongyi Zhu
6. Wing Kam Fung
7. Dacheng Tao
8. Chao Xu

Citations in the corpus

• High-Breakdown Robust Multivariate Methods (2008, methodology): “Maxbias curves of robust regression estimators have been studied in Martin, Yohai and Zamar (1989), He and Simpson (1993) , Croux, Rousseeuw and H¨ossjer (1994), Adrover and Zamar (2004) and Berrendero and Zamar (2001).”
• Robust Estimation in Generalized Partial Linear Models for Clustered Data (2005, methodology): “Similar weight functions have been used in the robust linear regression literature (see Hampel, Ronchetti, Rousseeuw, and Stahel 1986; He, Simpson, and Wang 2000).”
• Multi-View Intact Space Learning (2015, methodology): “To enhance the robustness of the model, we measure the reconstruction error from different views using the Cauchy loss, which is robust to outliers and has an optimal breakdown point compared with conventional L 2 and L 1 losses [41].”