A note on shrinkage sliced inverse regression

By Liqiang Ni, R. Dennis Cook, Chih-Ling Tsai. 2005

98 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computational Mechanics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/43523a5a8b64170b9cf4de15ecf35ce9277bda9e

How researchers see this paper

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

In Artificial Intelligence

1. Yingcun Xia
2. Lexin Li
3. Hansheng Wang
4. Howard D. Bondell
5. Heng Lian
6. Xiangrong Yin
7. Peter Buhlmann
8. Chenlei Leng

In Computational Mechanics

1. Hansheng Wang
2. Howard D. Bondell
3. Yingcun Xia
4. Lexin Li

In Statistics and Probability

1. Yingcun Xia
2. Lexin Li
3. Hansheng Wang
4. Howard D. Bondell
5. Heng Lian
6. Xiangrong Yin
7. Chenlei Leng
8. Bing Li

Citations in the corpus

• Sequential sufficient dimension reduction for large p, small n problems (2015, unknown): “See Ni et al. (2005), Li and Nachtsheim (2006), Li (2007), Zhou and He (2008), Wang and Yin (2008) and Chen et al. (2010).”
• Sliced Regression for Dimension Reduction (2008, methodology): “Model I is the same as our Example 1, and models II–IV are borrowed from Duan and Li (1991), Ni, Cook, and Tsai (2005), and Chen and Li (1998).”
• Shrinkage inverse regression estimation for model‐free variable selection (2009, methodology): “Ni et al. (2005) demonstrated the good empirical performance of shrinkage SIR but did not explore its theoretical properties.”