Testing the Linear Mean and Constant Variance Conditions in Sufficient Dimension Reduction
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Publication:5037808
DOI10.5705/ss.202019.0095OpenAlexW3038024976MaRDI QIDQ5037808
Tingyou Zhou, Yuexiao Dong, Li-ping Zhu
Publication date: 4 March 2022
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.5705/ss.202019.0095
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Cites Work
- Unnamed Item
- Measuring and testing dependence by correlation of distances
- Efficient estimation in sufficient dimension reduction
- Model-Free Feature Screening for Ultrahigh-Dimensional Data
- A CONSISTENT DIAGNOSTIC TEST FOR REGRESSION MODELS USING PROJECTIONS
- A consistent test of functional form via nonparametric estimation techniques
- A constructive approach to the estimation of dimension reduction directions
- Coordinate-independent sparse sufficient dimension reduction and variable selection
- Brownian distance covariance
- Dimension reduction for nonelliptically distributed predictors
- Consistent model specification tests for time series econometric models
- Nonparametric model checks for regression
- Minimum distance regression model checking
- Dimension reduction for conditional mean in regression
- Consistent specification tests for semiparametric/nonparametric models based on series estimation methods
- Sufficient dimension reduction and graphics in regression
- Kernel dimension reduction in regression
- Contour regression: a general approach to dimension reduction
- Shrinkage Inverse Regression Estimation for Model-Free Variable Selection
- Dimension reduction for non-elliptically distributed predictors: second-order methods
- On Directional Regression for Dimension Reduction
- Determining the Dimension in Sliced Inverse Regression and Related Methods
- Sliced Inverse Regression for Dimension Reduction
- On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma
- Reweighting to Achieve Elliptically Contoured Covariates in Regression
- Variance Estimation Using Refitted Cross-Validation in Ultrahigh Dimensional Regression
- Feature Screening via Distance Correlation Learning
- An Adaptive Estimation of Dimension Reduction Space
- A Semiparametric Approach to Dimension Reduction
- Martingale Difference Correlation and Its Use in High-Dimensional Variable Screening
- Dimension Reduction in Regressions Through Cumulative Slicing Estimation
- Model Checking for Parametric Single-index Models: A Dimension Reduction Model-Adaptive Approach
- Sparse sufficient dimension reduction
