Pages that link to "Item:Q147375"
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The following pages link to The Adaptive Lasso and Its Oracle Properties (Q147375):
Displaying 50 items.
- High-frequency estimation of the Lévy-driven graph Ornstein-Uhlenbeck process (Q2084463) (← links)
- Sparse linear mixed model selection via streamlined variational Bayes (Q2084474) (← links)
- Penalized robust estimators in sparse logistic regression (Q2084709) (← links)
- Bankruptcy prediction: evidence from Vietnam (Q2086202) (← links)
- Lasso regression and its application in forecasting macro economic indicators: a study on Vietnam's exports (Q2086244) (← links)
- Robust Lasso and its applications in healthcare data (Q2087104) (← links)
- A sequential feature selection procedure for high-dimensional Cox proportional hazards model (Q2087405) (← links)
- Multivariate response regression with low-rank and generalized sparsity (Q2089029) (← links)
- Robust moderately clipped LASSO for simultaneous outlier detection and variable selection (Q2091331) (← links)
- Generalization error bounds of dynamic treatment regimes in penalized regression-based learning (Q2091828) (← links)
- Information criteria bias correction for group selection (Q2093122) (← links)
- Penalized wavelet estimation and robust denoising for irregular spaced data (Q2095705) (← links)
- Unified mean-variance feature screening for ultrahigh-dimensional regression (Q2095721) (← links)
- Flexible, non-parametric modeling using regularized neural networks (Q2095735) (← links)
- Classification of COVID19 Patients using robust logistic regression (Q2096398) (← links)
- High-dimensional linear regression with hard thresholding regularization: theory and algorithm (Q2097492) (← links)
- Visualization and assessment of model selection uncertainty (Q2101381) (← links)
- Coordinate descent algorithm of generalized fused Lasso logistic regression for multivariate trend filtering (Q2103275) (← links)
- LASSO for streaming data with adaptative filtering (Q2104007) (← links)
- Scalable estimation and inference for censored quantile regression process (Q2105200) (← links)
- Regression with adaptive Lasso and correlation based penalty (Q2109879) (← links)
- High-dimensional variable screening through kernel-based conditional mean dependence (Q2112254) (← links)
- Shrinkage estimation of semi-parametric spatial autoregressive panel data model with fixed effects (Q2112273) (← links)
- Asset selection based on high frequency Sharpe ratio (Q2116331) (← links)
- Constrained estimation using penalization and MCMC (Q2116360) (← links)
- Robust estimation of semiparametric transformation model for panel count data (Q2121176) (← links)
- Variable selection for functional linear models with strong heredity constraint (Q2121450) (← links)
- Penalized and constrained LAD estimation in fixed and high dimension (Q2122803) (← links)
- Bayesian empirical likelihood inference and order shrinkage for autoregressive models (Q2122804) (← links)
- Variable selection of higher-order partially linear spatial autoregressive model with a diverging number of parameters (Q2122813) (← links)
- Regularization and variable selection in Heckman selection model (Q2122823) (← links)
- An adaptive group Lasso approach for domain selection in functional generalized linear models (Q2123251) (← links)
- \(\ell_0\)-regularized high-dimensional accelerated failure time model (Q2129574) (← links)
- Nonparametric feature selection by random forests and deep neural networks (Q2129580) (← links)
- Distributed optimization and statistical learning for large-scale penalized expectile regression (Q2131987) (← links)
- Sparse vector heterogeneous autoregressive modeling for realized volatility (Q2132003) (← links)
- Bayesian high-dimensional semi-parametric inference beyond sub-Gaussian errors (Q2132004) (← links)
- Robust distributed estimation and variable selection for massive datasets via rank regression (Q2135513) (← links)
- Bayesian sparse convex clustering via global-local shrinkage priors (Q2135928) (← links)
- Bayesian joint inference for multivariate quantile regression model with \(L_{1/2}\) penalty (Q2135947) (← links)
- On sufficient variable screening using log odds ratio filter (Q2136614) (← links)
- Post-model-selection inference in linear regression models: an integrated review (Q2137823) (← links)
- Penalized quasi-likelihood estimation of generalized Pareto regression -- consistent identification of risk factors for extreme losses (Q2138617) (← links)
- Neural network training using \(\ell_1\)-regularization and bi-fidelity data (Q2138992) (← links)
- Distributed estimation in heterogeneous reduced rank regression: with application to order determination in sufficient dimension reduction (Q2140870) (← links)
- Variable selection for case-cohort studies with informatively interval-censored outcomes (Q2143007) (← links)
- Dynamical modeling for non-Gaussian data with high-dimensional sparse ordinary differential equations (Q2143016) (← links)
- A truncated Newton algorithm for nonconvex sparse recovery (Q2143093) (← links)
- Likelihood theory for the graph Ornstein-Uhlenbeck process (Q2144193) (← links)
- Regularized linear censored quantile regression (Q2151602) (← links)
