Dimension reduction in regression without matrix inversion

By R. Dennis Cook, Bing Li, Francesca Chiaromonte. 2007

105 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/cf8c428770782b314df755bbe12f2ec13db99f82

How researchers see this paper

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

In Genetics

1. Liliana Forzani
2. R. Dennis Cook
3. Yingcun Xia

In Molecular Biology

1. Liliana Forzani
2. R. Dennis Cook
3. Zhihua Su

Citations in the corpus

• Principal fitted components for dimension reduction in regression (2008, methodology): “Cook, Li and Chiaromonte (2007) developed methodology for estimating the central”
• Envelopes and partial least squares regression (2013, background): “The overarching goal of this paper is to show that there is a very close connection between PLS and the recently developed envelopes of Cook et al. (2007, 2010).”
• Partial least squares prediction in high-dimensional regression (2019, background): “This corollary, which follows from Cook, Li and Chiaromonte ([13], Theorem 1), says in effect that rank(G∞) = d if and only if aH has a nonzero projection onto each of the d eigenspaces of V .”