The following pages link to (Q4217298):
Displaying 40 items.
- Discussion on ‘Review of sparse sufficient dimension reduction’ (Q5880038) (← links)
- A review and computer code for assessing the structural dimension of a regression model: uncorrelated 2D views. (Q5940998) (← links)
- The dual central subspaces in dimension reduction (Q5964282) (← links)
- Comment (Q5965645) (← links)
- A new reproducing kernel‐based nonlinear dimension reduction method for survival data (Q6049799) (← links)
- A structured covariance ensemble for sufficient dimension reduction (Q6050762) (← links)
- Variable-dependent partial dimension reduction (Q6051849) (← links)
- Strong consistency of kernel method for sliced average variance estimation (Q6053855) (← links)
- Sufficient dimension reduction for populations with structured heterogeneity (Q6055712) (← links)
- Missing data analysis with sufficient dimension reduction (Q6059465) (← links)
- A note on marginal coordinate test in sufficient dimension reduction (Q6067031) (← links)
- An Efficient Convex Formulation for Reduced-Rank Linear Discriminant Analysis in High Dimensions (Q6069866) (← links)
- Are bond returns predictable with real-time macro data? (Q6090593) (← links)
- Partial least squares for simultaneous reduction of response and predictor vectors in regression (Q6097544) (← links)
- A selective review of sufficient dimension reduction for multivariate response regression (Q6105773) (← links)
- Adaptive-to-Model Hybrid of Tests for Regressions (Q6107227) (← links)
- Robust matrix estimations meet Frank-Wolfe algorithm (Q6134341) (← links)
- Tail inverse regression: dimension reduction for prediction of extremes (Q6137714) (← links)
- Nonlinear interaction detection through partial dimension reduction with missing response data (Q6163579) (← links)
- Model checking for parametric single-index models with massive datasets (Q6172090) (← links)
- Asymptotic distribution of one-component partial least squares regression estimators in high dimensions (Q6490391) (← links)
- Data-driven slicing for dimension reduction in regressions: A likelihood-ratio approach (Q6492450) (← links)
- Model checking for parametric single-index quantile models (Q6541603) (← links)
- Mixed effects envelope models (Q6541614) (← links)
- Estimating average treatment effect on the treated via sufficient dimension reduction (Q6541778) (← links)
- Model averaging-based sufficient dimension reduction (Q6543884) (← links)
- High-dimensional sparse single-index regression via Hilbert-Schmidt independence criterion (Q6547751) (← links)
- Intensity estimation for inhomogeneous Gibbs point process with covariates-dependent chemical activity (Q6552787) (← links)
- Semiparametric recovery of central dimension reduction space with nonignorable nonresponse (Q6555339) (← links)
- Envelope methods (Q6601083) (← links)
- Higher-order sliced inverse regressions (Q6604461) (← links)
- A Projective Approach to Conditional Independence Test for Dependent Processes (Q6620861) (← links)
- High-Dimensional Elliptical Sliced Inverse Regression in Non-Gaussian Distributions (Q6620940) (← links)
- Efficient Integration of Sufficient Dimension Reduction and Prediction in Discriminant Analysis (Q6621641) (← links)
- Matching Using Sufficient Dimension Reduction for Causal Inference (Q6626364) (← links)
- Conditional mean dimension reduction for tensor time series (Q6626670) (← links)
- Aggregate Inverse Mean Estimation for Sufficient Dimension Reduction (Q6631903) (← links)
- A high-dimensional single-index regression for interactions between treatment and covariates (Q6640075) (← links)
- New forest-based approaches for sufficient dimension reduction (Q6643208) (← links)
- A slicing-free perspective to sufficient dimension reduction: selective review and recent developments (Q6663974) (← links)
