On central matrix based methods in dimension reduction
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Publication:2851577
DOI10.1002/cjs.11181zbMath1273.62094OpenAlexW1574204554MaRDI QIDQ2851577
Publication date: 11 October 2013
Published in: Canadian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/cjs.11181
Nonparametric regression and quantile regression (62G08) Estimation in multivariate analysis (62H12) Nonparametric estimation (62G05)
Cites Work
- Unnamed Item
- Sliced Regression for Dimension Reduction
- On hybrid methods of inverse regression-based algorithms
- Slicing regression: A link-free regression method
- An asymptotic theory for sliced inverse regression
- Dimension reduction for conditional mean in regression
- Model-based SIR for dimension reduction
- Contour regression: a general approach to dimension reduction
- Sufficient dimension reduction through discretization-expectation estimation
- On Directional Regression for Dimension Reduction
- Exploratory Projection Pursuit
- Sliced Inverse Regression for Dimension Reduction
- On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
- Using the Bootstrap to Select One of a New Class of Dimension Reduction Methods
- An Adaptive Estimation of Dimension Reduction Space
- Dimension Reduction for the Conditionalkth Moment in Regression
- Dimension Reduction in Regressions Through Cumulative Slicing Estimation
- Likelihood-Based Sufficient Dimension Reduction
- Sliced Inverse Regression with Regularizations
- Sufficient Dimension Reduction via Inverse Regression
- On Sliced Inverse Regression With High-Dimensional Covariates
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