Pages that link to "Item:Q449741"

The following pages link to Fisher lecture: Dimension reduction in regression (Q449741):

Displaying 50 items.

• Central subspaces review: methods and applications (Q2172454) (← links)
• Sparse SIR: optimal rates and adaptive estimation (Q2176608) (← links)
• On principal graphical models with application to gene network (Q2242158) (← links)
• Feature filter for estimating central mean subspace and its sparse solution (Q2242163) (← links)
• A sliced inverse regression approach for data stream (Q2259777) (← links)
• The sliced inverse regression algorithm as a maximum likelihood procedure (Q2272112) (← links)
• Principal envelope model (Q2301089) (← links)
• Groupwise sufficient dimension reduction via conditional distance clustering (Q2303753) (← links)
• On principal components regression with Hilbertian predictors (Q2304260) (← links)
• A theoretical note on optimal sufficient dimension reduction with singularity (Q2344874) (← links)
• Sufficient dimension reduction and prediction in regression: asymptotic results (Q2418522) (← links)
• Minimax adaptive dimension reduction for regression (Q2451628) (← links)
• On surrogate dimension reduction for measurement error regression: An invariance law (Q2466685) (← links)
• A robust proposal of estimation for the sufficient dimension reduction problem (Q2666070) (← links)
• UNIFORM BAHADUR REPRESENTATION FOR NONPARAMETRIC CENSORED QUANTILE REGRESSION: A REDISTRIBUTION-OF-MASS APPROACH (Q2981831) (← links)
• Heteroscedastic BART via Multiplicative Regression Trees (Q3391438) (← links)
• Statistical challenges of high-dimensional data (Q3559944) (← links)
• Sufficient dimension reduction and prediction in regression (Q3559952) (← links)
• Dimension Reduction for Gaussian Process Emulation: An Application to the Influence of Bathymetry on Tsunami Heights (Q4636407) (← links)
• (Q4637072) (← links)
• Minimum average deviance estimation for sufficient dimension reduction (Q4960553) (← links)
• Sufficient dimension reduction and prediction through cumulative slicing PFC (Q4960600) (← links)
• (Q4969067) (← links)
• (Q4969180) (← links)
• Nonsparse Learning with Latent Variables (Q4994162) (← links)
• (Q5004040) (← links)
• Dimension reduction via adaptive slicing (Q5037837) (← links)
• Graph-Assisted Inverse Regression for Count Data and Its Application to Sequencing Data (Q5065992) (← links)
• Model-Based Microbiome Data Ordination: A Variational Approximation Approach (Q5066487) (← links)
• Rates of convergence in conditional covariance matrix with nonparametric entries estimation (Q5077524) (← links)
• Learning Subspaces of Different Dimensions (Q5084432) (← links)
• Independent screening in high-dimensional exponential family predictors’ space (Q5130151) (← links)
• Response dimension reduction: model-based approach (Q5147572) (← links)
• Robust Variable and Interaction Selection for Logistic Regression and General Index Models (Q5229910) (← links)
• Sparse Minimum Discrepancy Approach to Sufficient Dimension Reduction with Simultaneous Variable Selection in Ultrahigh Dimension (Q5242475) (← links)
• Sufficient dimension reduction for censored predictors (Q5347421) (← links)
• Pruning a sufficient dimension reduction with a<i>p</i>-value guided hard-thresholding (Q5739663) (← links)
• Nonlinear Level Set Learning for Function Approximation on Sparse Data with Applications to Parametric Differential Equations (Q5864754) (← links)
• A Semiparametric Approach to Model Effect Modification (Q5885101) (← links)
• Comment: Fisher lecture: Dimension reduction in regression (Q5965648) (← links)
• Comment: Fisher lecture: Dimension reduction in regression (Q5965649) (← links)
• Sufficient dimension reduction for populations with structured heterogeneity (Q6055712) (← links)
• Generalized Liquid Association Analysis for Multimodal Data Integration (Q6077588) (← links)
• Generalized matrix decomposition regression: estimation and inference for two-way structured data (Q6138615) (← links)
• Memoryless quasi-Newton methods based on the spectral-scaling Broyden family for Riemannian optimization (Q6161550) (← links)
• On a nonlinear extension of the principal fitted component model (Q6168914) (← links)
• Sufficient dimension reduction for a novel class of zero-inflated graphical models (Q6573301) (← links)
• Variable selection using data splitting and projection for principal fitted component models in high dimension (Q6573303) (← links)
• Envelope methods (Q6601083) (← links)
• Merging two cultures: deep and statistical learning (Q6604368) (← links)