-
Dynamic Partial Sufficient Dimension Reduction
Sufficient dimension reduction aims for reduction of dimensionality of a...
09/26/2019 ∙ by Lu Li, et al. ∙
0
∙
share
read it
-
Simultaneous Variable Selection, Clustering, and Smoothing in Function on Scalar Regression
We address the problem of multicollinearity in a function-on-scalar regr...
06/25/2019 ∙ by Suchit Mehrotra, et al. ∙
0
∙
share
read it
-
Impossibility of dimension reduction in the nuclear norm
Let S_1 (the Schatten--von Neumann trace class) denote the Banach space ...
10/24/2017 ∙ by Assaf Naor, et al. ∙
0
∙
share
read it
-
Supervised Coarse-Graining of Composite Objects
We consider supervised dimension reduction for regression with composite...
01/01/2019 ∙ by Shaobo Han, et al. ∙
0
∙
share
read it
-
A framework for streamlined statistical prediction using topic models
In the Humanities and Social Sciences, there is increasing interest in a...
04/15/2019 ∙ by Vanessa Glenny, et al. ∙
0
∙
share
read it
-
Supporting Multi-point Fan Design with Dimension Reduction
Motivated by the idea of turbomachinery active subspace performance maps...
10/20/2019 ∙ by Pranay Seshadri, et al. ∙
15
∙
share
read it
-
A New Covariance Estimator for Sufficient Dimension Reduction in High-Dimensional and Undersized Sample Problems
The application of standard sufficient dimension reduction methods for r...
09/28/2019 ∙ by Kabir Opeyemi Olorede, et al. ∙
0
∙
share
read it
Sufficient Dimension Reduction for Interactions
05/30/2020 ∙ by Hyung Park, et al. ∙
0
∙
share
Dimension reduction lies at the heart of many statistical methods. In regression, dimension reduction has been linked to the notion of sufficiency whereby the relation of the response to a set of predictors is explained by a lower dimensional subspace in the predictor space. In this paper, we consider the notion of a dimension reduction in regression on subspaces that are sufficient to explain interaction effects between predictors and another variable of interest. The motivation for this work is from precision medicine where the performance of an individualized treatment rule, given a set of pretreatment predictors, is determined by interaction effects.
READ FULL TEXT
Comments
There are no comments yet.