Sliced Regression for Dimension Reduction

By Hansheng Wang, Yingcun Xia. 2008

150 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistical and Nonlinear Physics, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/1a3dda17ad8353686de12970d4241612677977bc

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. Xiangrong Yin
2. Bing Li
3. Wenhui Sheng
4. Haileab Hilafu
5. Wolfgang Karl Härdle
6. Xia Cui
7. Lixing Zhu
8. Lexin Li

In Statistical and Nonlinear Physics

1. Wolfgang Karl Härdle
2. Xia Cui
3. Bing Li
4. Xiangrong Yin
5. Lixing Zhu
6. Wenhui Sheng

In Statistics and Probability

1. Xiangrong Yin
2. Wenhui Sheng
3. Haileab Hilafu
4. Bing Li
5. Lexin Li
6. Li-Xing Zhu
7. Wolfgang Karl Härdle
8. Xia Cui

Citations in the corpus

• Groupwise Dimension Reduction (2010, background): “The other class, including MAVE and recent proposals of Xia (2007) and Wang and Xia (2008), relies on estimation of the derivatives of forward conditional moments such as E(Y|X).”
• Sufficient dimension reduction based on an ensemble of minimum average variance estimators (2011, methodology): “To implement RMAVE-FC , we modify the code for the sliced regression in Wang and Xia (2008) based on a gradual descending algorithm; the random vectors T1, . . . , Tm are an independent sample from N(0, Is).”
• Sequential sufficient dimension reduction for large p, small n problems (2015, background): “See Chiaromonte and Martinelli (2002), Li and Yin (2008), Cook et al. (2007) and Zhu et al. (2010a).”
• Sufficient Dimension Reduction via Distance Covariance (2016, methodology): “Model B: This model has been previously studied by Chen and Li (1998), and Wang and Xia (2008). The predictors for Part (2) and Part (3) are generated as follows: Part (2), xi ∼ Uniform(−2, 2), i = 1, .”
• Inverse Moment Methods for Sufficient Forecasting Using High-Dimensional Predictors (2016, unknown): “…tests (Li 1991, Li and Wang 2007), the permutation test (Cook and Weisberg 1991), the bootstrap procedure (Ye and Weiss, 2003), the cross-validation method (Xia et al., 2002; Wang and Xia, 2008), the BIC type procedure (Zhu, Miao and Peng 2006), and the ladle estimator (Luo and Li, 2016).”
• The EFM approach for single-index models (2011, methodology): “A similar modeling setup was also used in Wang and Xia (2008), Example 5.”