Pages that link to "Item:Q147375"

The following pages link to The Adaptive Lasso and Its Oracle Properties (Q147375):

Displaying 50 items.

• Adaptive elastic-net selection in a quantile model with diverging number of variable groups (Q4999858) (← links)
• (Q5004043) (← links)
• (Q5004047) (← links)
• Calibrated zero-norm regularized LS estimator for high-dimensional error-in-variables regression (Q5004050) (← links)
• Iterative gradient descent for outlier detection (Q5010123) (← links)
• Monitoring sequential structural changes in penalized high-dimensional linear models (Q5012705) (← links)
• Efficient Sparse Hessian-Based Semismooth Newton Algorithms for Dantzig Selector (Q5021412) (← links)
• High-dimensional generalized semiparametric model for longitudinal data (Q5023861) (← links)
• Univariate measurement error selection likelihood for variable selection of additive model (Q5023864) (← links)
• Graph-Based Regularization for Regression Problems with Alignment and Highly Correlated Designs (Q5027037) (← links)
• Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions (Q5030952) (← links)
• WLAD-LASSO method for robust estimation and variable selection in partially linear models (Q5031688) (← links)
• Firth's penalized method in Cox proportional hazard framework for developing predictive models for sparse or heavily censored survival data (Q5033935) (← links)
• The adaptive normal-hypergeometric-inverted-beta priors for sparse signals (Q5033960) (← links)
• Stock return predictability: A factor-augmented predictive regression system with shrinkage method (Q5034238) (← links)
• Selecting the regularization parameters in high-dimensional panel data models: Consistency and efficiency (Q5034246) (← links)
• Investigating competition in financial markets: a sparse autologistic model for dynamic network data (Q5035721) (← links)
• Bayesian bridge regression (Q5035746) (← links)
• Bayesian variable selection and coefficient estimation in heteroscedastic linear regression model (Q5036373) (← links)
• A novel bagging approach for variable ranking and selection via a mixed importance measure (Q5036437) (← links)
• Model selection with distributed SCAD penalty (Q5036460) (← links)
• Robust feature screening for high-dimensional survival data (Q5036548) (← links)
• Modeling association between multivariate correlated outcomes and high-dimensional sparse covariates: the adaptive SVS method (Q5036571) (← links)
• Variable selection in proportional hazards cure model with time-varying covariates, application to US bank failures (Q5036647) (← links)
• Projection correlation between scalar and vector variables and its use in feature screening with multi-response data (Q5036832) (← links)
• The information detection for the generalized additive model (Q5036871) (← links)
• Long-tailed graphical model and frequentist inference of the model parameters for biological networks (Q5036879) (← links)
• An empirical threshold of selection probability for analysis of high-dimensional correlated data (Q5036882) (← links)
• Variable selection of partially linear varying coefficient spatial autoregressive model (Q5036902) (← links)
• Penalized profile quasi-maximum likelihood method of partially linear spatial autoregressive model (Q5036903) (← links)
• Variable selection under multicollinearity using modified log penalty (Q5036976) (← links)
• Robust signed-rank estimation and variable selection for semi-parametric additive partial linear models (Q5037022) (← links)
• Sparse graphical models via calibrated concave convex procedure with application to fMRI data (Q5037034) (← links)
• Stability enhanced variable selection for a semiparametric model with flexible missingness mechanism and its application to the ChAMP study (Q5037060) (← links)
• Variable selection and estimation for the additive hazards model subject to left-truncation, right-censoring and measurement error in covariates (Q5037116) (← links)
• Graphical group ridge (Q5037126) (← links)
• Tensor Regression Using Low-Rank and Sparse Tucker Decompositions (Q5037550) (← links)
• Sparseness, consistency and model selection for Markov regime-switching Gaussian autoregressive models (Q5037794) (← links)
• Partitioned Approach for High-dimensional Confidence Intervals with Large Split Sizes (Q5037796) (← links)
• Bayesian inference in high-dimensional linear models using an empirical correlation-adaptive prior (Q5037803) (← links)
• Efficient kernel-based variable selection with sparsistency (Q5037806) (← links)
• An Approximate Bayesian Approach to Model-assisted Survey Estimation with Many Auxiliary Variables (Q5037836) (← links)
• Sparse Sliced Inverse Regression via Cholesky Matrix Penalization (Q5040485) (← links)
• Conditional sparse boosting for high-dimensional instrumental variable estimation (Q5040523) (← links)
• Semi-Standard Partial Covariance Variable Selection When Irrepresentable Conditions Fail (Q5041338) (← links)
• Automated Estimation of Heavy-Tailed Vector Error Correction Models (Q5041351) (← links)
• Adaptive singular value shrinkage estimate for low rank tensor denoising (Q5041692) (← links)
• Robust sparse functional regression model (Q5042091) (← links)
• Automatic variable selection in a linear model on massive data (Q5042096) (← links)
• Model-free survival conditional feature screening (Q5042162) (← links)