scholarly journals Sufficient dimension reduction via random‐partitions for the large‐ p ‐small‐ n problem

Biometrics ◽  
2018 ◽  
Vol 75 (1) ◽  
pp. 245-255
Author(s):  
Hung Hung ◽  
Su‐Yun Huang
Keyword(s):  
Dimension Reduction ◽  
Sufficient Dimension Reduction ◽  
Random Partitions ◽  
Large P Small N ◽  
Small N

scholarly journals Cumulative Median Estimation for Sufficient Dimension Reduction

Stats ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 138-145
Author(s):  
Stephen Babos ◽  
Andreas Artemiou
Keyword(s):  
Dimension Reduction ◽  
Real Data ◽  
Sufficient Dimension Reduction

In this paper, we present the Cumulative Median Estimation (CUMed) algorithm for robust sufficient dimension reduction. Compared with non-robust competitors, this algorithm performs better when there are outliers present in the data and comparably when outliers are not present. This is demonstrated in simulated and real data experiments.

scholarly journals Penalized orthogonal-components regression for large p small n data

2009 ◽  
Vol 3 (0) ◽  
pp. 781-796 ◽  
Author(s):  
Dabao Zhang ◽  
Yanzhu Lin ◽  
Min Zhang
Keyword(s):  
Large P Small N ◽  
Orthogonal Components ◽  
Small N
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