The following pages link to High-dimensional variable selection (Q834336):
Displaying 50 items.
- Sure independence screening in the presence of missing data (Q2066525) (← links)
- In defense of the indefensible: a very naïve approach to high-dimensional inference (Q2075709) (← links)
- Mining events with declassified diplomatic documents (Q2078743) (← links)
- Spatially relaxed inference on high-dimensional linear models (Q2080369) (← links)
- Network differential connectivity analysis (Q2080732) (← links)
- Projection-based high-dimensional sign test (Q2131148) (← links)
- Iterative algorithm for discrete structure recovery (Q2131266) (← links)
- Self-semi-supervised clustering for large scale data with massive null group (Q2131891) (← links)
- Post-model-selection inference in linear regression models: an integrated review (Q2137823) (← links)
- Thresholding tests based on affine Lasso to achieve non-asymptotic nominal level and high power under sparse and dense alternatives in high dimension (Q2143028) (← links)
- Hierarchical inference for genome-wide association studies: a view on methodology with software (Q2184390) (← links)
- Debiasing the debiased Lasso with bootstrap (Q2192302) (← links)
- Fundamental limits of exact support recovery in high dimensions (Q2203616) (← links)
- Which bridge estimator is the best for variable selection? (Q2215760) (← links)
- Exact tests via multiple data splitting (Q2216942) (← links)
- Variable selection techniques after multiple imputation in high-dimensional data (Q2220289) (← links)
- Dynamic tilted current correlation for high dimensional variable screening (Q2222224) (← links)
- A significance test for the lasso (Q2249837) (← links)
- Discussion: ``A significance test for the lasso'' (Q2249838) (← links)
- Rejoinder: ``A significance test for the lasso'' (Q2249839) (← links)
- High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)
- A global homogeneity test for high-dimensional linear regression (Q2263711) (← links)
- Feature selection for high-dimensional data (Q2271790) (← links)
- Bootstrapping and sample splitting for high-dimensional, assumption-lean inference (Q2284380) (← links)
- Inference for \(L_2\)-boosting (Q2302490) (← links)
- Selective inference via marginal screening for high dimensional classification (Q2303502) (← links)
- A scalable nonparametric specification testing for massive data (Q2317283) (← links)
- Spectral analysis of high-dimensional time series (Q2326992) (← links)
- A knockoff filter for high-dimensional selective inference (Q2328050) (← links)
- On the impact of model selection on predictor identification and parameter inference (Q2358941) (← links)
- Predictor ranking and false discovery proportion control in high-dimensional regression (Q2418511) (← links)
- Variable selection procedures from multiple testing (Q2423858) (← links)
- Empirical likelihood test for high dimensional linear models (Q2452783) (← links)
- Variable screening in predicting clinical outcome with high-dimensional microarrays (Q2455462) (← links)
- Endogeneity in high dimensions (Q2510821) (← links)
- Tolerance intervals from ridge regression in the presence of multicollinearity and high dimension (Q2520528) (← links)
- Tests for high-dimensional single-index models (Q2681748) (← links)
- Detection of gene-gene interactions using multistage sparse and low-rank regression (Q2805184) (← links)
- Variable selection using stepdown procedures in high-dimensional linear models (Q2833627) (← links)
- Estimation for high-dimensional linear mixed-effects models using \(\ell_1\)-penalization (Q2911662) (← links)
- Optimality of Graphlet Screening in High Dimensional Variable Selection (Q2934100) (← links)
- Statistical learning and selective inference (Q2962284) (← links)
- Two-Stage Procedures for High-Dimensional Data (Q3106536) (← links)
- Integrative analysis and variable selection with multiple high-dimensional data sets (Q3165548) (← links)
- Feature selection in finite mixture of sparse normal linear models in high-dimensional feature space (Q3303656) (← links)
- Debiased Inference on Treatment Effect in a High-Dimensional Model (Q3304865) (← links)
- Selection of the Regularization Parameter in Graphical Models Using Network Characteristics (Q3391115) (← links)
- A Selective Overview of Variable Selection in High Dimensional Feature Space (Invited Review Article) (Q3405559) (← links)
- Estimation and Inference of Heterogeneous Treatment Effects using Random Forests (Q4559704) (← links)
- Goodness-of-Fit Tests for High Dimensional Linear Models (Q4603816) (← links)
