Pages that link to "Item:Q3069884"

The following pages link to Forward Regression for Ultra-High Dimensional Variable Screening (Q3069884):

Displaying 50 items.

• Global solutions to folded concave penalized nonconvex learning (Q282459) (← links)
• An analysis of penalized interaction models (Q282572) (← links)
• Testing a single regression coefficient in high dimensional linear models (Q311657) (← links)
• Rank-based score tests for high-dimensional regression coefficients (Q364206) (← links)
• Statistical significance in high-dimensional linear models (Q373525) (← links)
• Penalized profiled semiparametric estimating functions (Q377668) (← links)
• Variable selection in high-dimensional quantile varying coefficient models (Q391871) (← links)
• Goodness-of-fit testing-based selection for large-\(p\)-small-\(n\) problems: a two-stage ranking approach (Q393551) (← links)
• A Bayesian information criterion for portfolio selection (Q429627) (← links)
• On efficient calculations for Bayesian variable selection (Q434881) (← links)
• FIRST: combining forward iterative selection and shrinkage in high dimensional sparse linear regression (Q440113) (← links)
• Estimation in high-dimensional linear models with deterministic design matrices (Q447831) (← links)
• Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models (Q512003) (← links)
• Robust rank screening for ultrahigh dimensional discriminant analysis (Q518270) (← links)
• Consistent tuning parameter selection in high dimensional sparse linear regression (Q548648) (← links)
• On model selection from a finite family of possibly misspecified time series models (Q666592) (← links)
• Testing covariates in high-dimensional regression (Q743995) (← links)
• Conditional distance correlation screening for sparse ultrahigh-dimensional models (Q821654) (← links)
• Forward variable selection for sparse ultra-high-dimensional generalized varying coefficient models (Q825321) (← links)
• Model-free variable selection for conditional mean in regression (Q830544) (← links)
• A scalable surrogate \(L_0\) sparse regression method for generalized linear models with applications to large scale data (Q830734) (← links)
• A selective overview of feature screening for ultrahigh-dimensional data (Q892795) (← links)
• Testing covariates in high dimension linear regression with latent factors (Q901275) (← links)
• Testing predictor significance with ultra high dimensional multivariate responses (Q1623800) (← links)
• Ultrahigh dimensional feature screening via projection (Q1658358) (← links)
• Adjusted Pearson chi-square feature screening for multi-classification with ultrahigh dimensional data (Q1683647) (← links)
• Covariance-insured screening (Q1727857) (← links)
• Variable screening for ultrahigh dimensional heterogeneous data via conditional quantile correlations (Q1742727) (← links)
• Feature screening for nonparametric and semiparametric models with ultrahigh-dimensional covariates (Q1757685) (← links)
• Broken adaptive ridge regression and its asymptotic properties (Q1795597) (← links)
• Factor-adjusted multiple testing of correlations (Q1796926) (← links)
• Feature screening for multi-response varying coefficient models with ultrahigh dimensional predictors (Q1796954) (← links)
• Feature screening for ultrahigh dimensional categorical data with covariates missing at random (Q2008118) (← links)
• High-dimensional integrative analysis with homogeneity and sparsity recovery (Q2008216) (← links)
• Variable selection for partially linear models via Bayesian subset modeling with diffusing prior (Q2022563) (← links)
• Simultaneous feature selection and clustering based on square root optimization (Q2028812) (← links)
• Learning sparse conditional distribution: an efficient kernel-based approach (Q2044348) (← links)
• Multivariate variable selection by means of null-beamforming (Q2044421) (← links)
• The de-biased group Lasso estimation for varying coefficient models (Q2046473) (← links)
• A sequential feature selection procedure for high-dimensional Cox proportional hazards model (Q2087405) (← links)
• Unified mean-variance feature screening for ultrahigh-dimensional regression (Q2095721) (← links)
• Sparse spatio-temporal autoregressions by profiling and bagging (Q2106397) (← links)
• Revisiting feature selection for linear models with FDR and power guarantees (Q2111958) (← links)
• RCV-based error density estimation in the ultrahigh dimensional additive model (Q2133638) (← links)
• Model-free conditional screening via conditional distance correlation (Q2175650) (← links)
• Ultra-high dimensional variable screening via Gram-Schmidt orthogonalization (Q2203408) (← links)
• Model selection for high-dimensional linear regression with dependent observations (Q2215720) (← links)
• Dynamic tilted current correlation for high dimensional variable screening (Q2222224) (← links)
• A sequential approach to feature selection in high-dimensional additive models (Q2242862) (← links)
• Forward regression for Cox models with high-dimensional covariates (Q2274944) (← links)