Pages that link to "Item:Q147375"

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

Displaying 50 items.

• A Bayesian hierarchical model for identifying significant polygenic effects while controlling for confounding and repeated measures (Q1670295) (← links)
• Regularized estimation in GINAR(\(p\)) process (Q1674041) (← links)
• Relaxed sparse eigenvalue conditions for sparse estimation via non-convex regularized regression (Q1677029) (← links)
• On the oracle property of a generalized adaptive elastic-net for multivariate linear regression with a diverging number of parameters (Q1679561) (← links)
• Estimation and variable selection for quantile partially linear single-index models (Q1679574) (← links)
• Exponentially tilted likelihood inference on growing dimensional unconditional moment models (Q1680189) (← links)
• A doubly sparse approach for group variable selection (Q1680797) (← links)
• B spline variable selection for the single index models (Q1685210) (← links)
• Bayesian analysis of penalized quantile regression for longitudinal data (Q1685287) (← links)
• Quantile regression for additive coefficient models in high dimensions (Q1686242) (← links)
• A generalized elastic net regularization with smoothed \(\ell _{q}\) penalty for sparse vector recovery (Q1687319) (← links)
• Genetic algorithm versus classical methods in sparse index tracking (Q1693854) (← links)
• An effective method to reduce the computational complexity of composite quantile regression (Q1695421) (← links)
• A penalized likelihood method for structural equation modeling (Q1695631) (← links)
• Variable selection and estimation using a continuous approximation to the \(L_0\) penalty (Q1695760) (← links)
• Local variable selection of nonlinear nonparametric systems by first order expansion (Q1697155) (← links)
• Variable selection and prediction in biased samples with censored outcomes (Q1698943) (← links)
• Model-free conditional independence feature screening for ultrahigh dimensional data (Q1702189) (← links)
• Model-free feature screening for ultrahigh dimensional censored regression (Q1703810) (← links)
• A group adaptive elastic-net approach for variable selection in high-dimensional linear regression (Q1705570) (← links)
• The Bayesian adaptive Lasso regression (Q1711960) (← links)
• Feature selection and tumor classification for microarray data using relaxed Lasso and generalized multi-class support vector machine (Q1717062) (← links)
• Efficient LED-SAC sparse estimator using fast sequential adaptive coordinate-wise optimization (LED-2SAC) (Q1718121) (← links)
• Automatic variable selection for partially linear functional additive model and its application to the Tecator data set (Q1721105) (← links)
• Fast Bayesian variable selection for high dimensional linear models: marginal solo spike and slab priors (Q1722055) (← links)
• A systematic review on model selection in high-dimensional regression (Q1726155) (← links)
• High-dimensional grouped folded concave penalized estimation via the LLA algorithm (Q1726165) (← links)
• Robust conditional nonparametric independence screening for ultrahigh-dimensional data (Q1726739) (← links)
• Covariance-insured screening (Q1727857) (← links)
• Sparse-group independent component analysis with application to yield curves prediction (Q1727895) (← links)
• Simultaneous variable selection and class fusion with penalized distance criterion based classifiers (Q1727900) (← links)
• Modal regression statistical inference for longitudinal data semivarying coefficient models: generalized estimating equations, empirical likelihood and variable selection (Q1727913) (← links)
• Bayesian model selection for generalized linear models using non-local priors (Q1727917) (← links)
• Fusion learning algorithm to combine partially heterogeneous Cox models (Q1729358) (← links)
• Variable selection for spatial Poisson point processes via a regularization method (Q1731184) (← links)
• Modified SCAD penalty for constrained variable selection problems (Q1731229) (← links)
• Shrinkage, pretest, and penalty estimators in generalized linear models (Q1731260) (← links)
• A note on the adaptive Lasso for zero-inflated Poisson regression (Q1733128) (← links)
• Variable selection via the composite likelihood method for multilevel longitudinal data with missing responses and covariates (Q1737998) (← links)
• ArCo: an artificial counterfactual approach for high-dimensional panel time-series data (Q1739593) (← links)
• Knowing factors or factor loadings, or neither? Evaluating estimators of large covariance matrices with noisy and asynchronous data (Q1739632) (← links)
• Determination of vector error correction models in high dimensions (Q1739869) (← links)
• A multiple testing approach to the regularisation of large sample correlation matrices (Q1739875) (← links)
• Portal nodes screening for large scale social networks (Q1740287) (← links)
• Regularization parameter selection for penalized empirical likelihood estimator (Q1741726) (← links)
• Variable screening for ultrahigh dimensional heterogeneous data via conditional quantile correlations (Q1742727) (← links)
• Bayesian analysis of dynamic panel data by penalized quantile regression (Q1742844) (← links)
• Variable screening for high dimensional time series (Q1746535) (← links)
• Convex and non-convex regularization methods for spatial point processes intensity estimation (Q1746561) (← links)
• Pathwise coordinate optimization for sparse learning: algorithm and theory (Q1747736) (← links)