Pages that link to "Item:Q3559952"

The following pages link to Sufficient dimension reduction and prediction in regression (Q3559952):

Displaying 50 items.

• Estimating sufficient reductions of the predictors in abundant high-dimensional regressions (Q116954) (← links)
• A simple measure of conditional dependence (Q128731) (← links)
• High-dimensional regression with Gaussian mixtures and partially-latent response variables (Q261018) (← links)
• Group-wise sufficient dimension reduction with principal fitted components (Q311294) (← links)
• Predictive power of principal components for single-index model and sufficient dimension reduction (Q391676) (← links)
• Dimensionality reduction by feature clustering for regression problems (Q528696) (← links)
• Inverse regression-based uncertainty quantification algorithms for high-dimensional models: theory and practice (Q726930) (← links)
• Conditionally specified models and dimension reduction in the exponential families (Q943598) (← links)
• Exploiting predictor domain information in sufficient dimension reduction (Q961692) (← links)
• A sequential test for variable selection in high dimensional complex data (Q1623732) (← links)
• Sufficient dimension reduction constrained through sub-populations (Q1654239) (← links)
• Supervised dimension reduction for ordinal predictors (Q1662936) (← links)
• Nonlinear multi-output regression on unknown input manifold (Q1680851) (← links)
• Inverse regression approach to robust nonlinear high-to-low dimensional mapping (Q1686148) (← links)
• Sufficient dimension reduction in regressions through cumulative Hessian directions (Q1927284) (← links)
• Estimating multi-index models with response-conditional least squares (Q2044313) (← links)
• A slice of multivariate dimension reduction (Q2062766) (← links)
• The ensemble conditional variance estimator for sufficient dimension reduction (Q2136654) (← links)
• Conditional variance estimator for sufficient dimension reduction (Q2137046) (← links)
• Targeted principal components regression (Q2140873) (← links)
• On weighted multivariate sign functions (Q2146460) (← links)
• Sufficient dimension reduction in the presence of controlling variables (Q2169100) (← links)
• Estimating covariance and precision matrices along subspaces (Q2219236) (← links)
• High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)
• Inverse regression for ridge recovery: a data-driven approach for parameter reduction in computer experiments (Q2302488) (← links)
• Gauss-Christoffel quadrature for inverse regression: applications to computer experiments (Q2329776) (← links)
• Sufficient dimension reduction and prediction in regression: asymptotic results (Q2418522) (← links)
• Prediction of multivariate responses with a selected number of principal components (Q2445634) (← links)
• Single-index importance sampling with stratification (Q2684956) (← links)
• Transformed sufficient dimension reduction (Q2934763) (← links)
• Sufficient dimension reduction through informative predictor subspace (Q2953449) (← links)
• Diagnostic studies in sufficient dimension reduction (Q3455804) (← links)
• Sufficient Dimension Reduction With Missing Predictors (Q3632696) (← links)
• Flexible dimension reduction in regression (Q4639590) (← links)
• Sufficient dimension reduction and prediction through cumulative slicing PFC (Q4960600) (← links)
• Dimension Reduction via Gaussian Ridge Functions (Q4960976) (← links)
• Sufficient dimension folding in regression via distance covariance for matrix‐valued predictors (Q4970311) (← links)
• (Q5004040) (← links)
• Dimension Reduction Forests: Local Variable Importance Using Structured Random Forests (Q5057244) (← links)
• Dimensionality Reduction, Regularization, and Generalization in Overparameterized Regressions (Q5065466) (← links)
• Graph-Assisted Inverse Regression for Count Data and Its Application to Sequencing Data (Q5065992) (← links)
• Generalized Tensor Decomposition With Features on Multiple Modes (Q5083368) (← links)
• Calibrating sufficiently (Q5085225) (← links)
• Independent screening in high-dimensional exponential family predictors’ space (Q5130151) (← links)
• Dealing with big data: comparing dimension reduction and shrinkage regression methods (Q5138553) (← links)
• Gradient-Based Dimension Reduction of Multivariate Vector-Valued Functions (Q5220403) (← links)
• Lurking Variable Detection via Dimensional Analysis (Q5228357) (← links)
• Structured Ordinary Least Squares: A Sufficient Dimension Reduction approach for regressions with partitioned predictors and heterogeneous units (Q5283308) (← links)
• Dimension folding PCA and PFC for matrix-valued predictors (Q5413267) (← links)
• Dimension reduction in regression without matrix inversion (Q5447650) (← links)