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Sufficient dimension reduction

In statistics, sufficient dimension reduction (SDR) is a paradigm for analyzing data that combines the ideas of dimension reduction with the concept… 
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Papers overview

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2016
2016
In this article, we propose to use sparse sufficient dimension reduction as a novel method for Markov blanket discovery of a… 
2014
2014
University of Minnesota Ph.D. dissertation. June 2014. Major: Statistics. Advisor: Ralph Dennis Cook. 1 computer file (PDF); xi… 
2011
2011
The purpose of sufficient dimension reduction (SDR) is to find the low-dimensional subspace of input features that is sufficient… 
2008
2008
This thesis makes contributions to the statistical research field of causal inference in observational studies. The results… 
2006
2006
Summary.  Sliced inverse regression is one of the widely used dimension reduction methods. Chiaromonte and co‐workers extended…