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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… Expand
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Related topics

9 relations
Basis (linear algebra)Convex setCurse of dimensionalityDimensionality reduction
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Robust estimation and variable selection in sufficient dimension reduction
Dimension reduction and variable selection play important roles in high dimensional data analysis. Minimum Average Variance… Expand
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2014
2014
Gradient-Based Kernel Dimension Reduction for Regression
This article proposes a novel approach to linear dimension reduction for regression using nonparametric estimation with positive… Expand
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2011
2011
Sufficient dimension reduction based on an ensemble of minimum average variance estimators
We introduce a class of dimension reduction estimators based on an ensemble of the minimum average variance estimates of… Expand
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Highly Cited
2010
Highly Cited
2010
Coordinate-independent sparse sufficient dimension reduction and variable selection
Sufficient dimension reduction (SDR) in regression, which reduces the dimension by replacing original predictors with a minimal… Expand
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Highly Cited
2009
Highly Cited
2009
Likelihood-Based Sufficient Dimension Reduction
We obtain the maximum likelihood estimator of the central subspace under conditional normality of the predictors given the… Expand
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Highly Cited
2009
Highly Cited
2009
Dimension reduction for nonelliptically distributed predictors
Sufficient dimension reduction methods often require stringent conditions on the joint distribution of the predictor, or, when… Expand
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Highly Cited
2005
Highly Cited
2005
Sufficient Dimension Reduction via Inverse Regression
A family of dimension-reduction methods, the inverse regression (IR) family, is developed by minimizing a quadratic objective… Expand
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Highly Cited
2004
Highly Cited
2004
Testing predictor contributions in sufficient dimension reduction
We develop tests of the hypothesis of no effect for selected predictors in regression, without assuming a model for the… Expand
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2004
2004
Cluster-based estimation for sufficient dimension reduction
Sufficient dimension reduction (SDR) approaches such as ordinary least squares (OLS), sliced inverse regression, sliced average… Expand
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Highly Cited
2002
Highly Cited
2002
Sufficient dimension reduction in regressions with categorical predictors
Though partial sliced inverse regression (partial SIR: Chiaromonte et al. [2002. Sufficient dimension reduction in regressions… Expand
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