Pages that link to "Item:Q147375"

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

Displaying 50 items.

• Model detection and variable selection for mode varying coefficient model (Q2152192) (← links)
• High-dimensional regression with potential prior information on variable importance (Q2152561) (← links)
• Change points detection and parameter estimation for multivariate time series (Q2153567) (← links)
• Weighted Lasso estimates for sparse logistic regression: non-asymptotic properties with measurement errors (Q2154741) (← links)
• Random weighting in LASSO regression (Q2154956) (← links)
• Nonparametric estimation of the random coefficients model: an elastic net approach (Q2155297) (← links)
• On LASSO for predictive regression (Q2155298) (← links)
• Multiple change-points estimation in linear regression models via an adaptive Lasso expectile loss function (Q2156002) (← links)
• High-dimensional causal mediation analysis based on partial linear structural equation models (Q2157518) (← links)
• Robust reduced rank regression in a distributed setting (Q2158850) (← links)
• Single-index composite quantile regression for ultra-high-dimensional data (Q2161022) (← links)
• Determine the number of clusters by data augmentation (Q2161184) (← links)
• A unifying framework of high-dimensional sparse estimation with difference-of-convex (DC) regularizations (Q2163076) (← links)
• Estimation of multivariate dependence structures via constrained maximum likelihood (Q2163514) (← links)
• Benchmarking penalized regression methods in machine learning for single cell RNA sequencing data (Q2163973) (← links)
• Real-time detection of a change-point in a linear expectile model (Q2165847) (← links)
• Gene set priorization guided by regulatory networks with p-values through kernel mixed model (Q2170131) (← links)
• A joint estimation approach to sparse additive ordinary differential equations (Q2172119) (← links)
• Robust change point detection method via adaptive LAD-Lasso (Q2175643) (← links)
• Block average quantile regression for massive dataset (Q2175645) (← links)
• Model-free conditional screening via conditional distance correlation (Q2175650) (← links)
• Poisson autoregressive process modeling via the penalized conditional maximum likelihood procedure (Q2175651) (← links)
• Estimation and variable selection for partial functional linear regression (Q2176333) (← links)
• Envelope-based sparse partial least squares (Q2176612) (← links)
• Estimating the health effects of environmental mixtures using Bayesian semiparametric regression and sparsity inducing priors (Q2179967) (← links)
• Nonconcave penalized estimation in sparse vector autoregression model (Q2180066) (← links)
• Consistent model selection criteria and goodness-of-fit test for common time series models (Q2180087) (← links)
• General matching quantiles M-estimation (Q2181544) (← links)
• On Kendall's regression (Q2181725) (← links)
• Model-free feature screening for ultrahigh dimensional classification (Q2181726) (← links)
• Nonparametric variable selection and its application to additive models (Q2183769) (← links)
• Hierarchical inference for genome-wide association studies: a view on methodology with software (Q2184390) (← links)
• Bayesian variable selection for mixed effects model with shrinkage prior (Q2184407) (← links)
• Efficient inexact proximal gradient algorithms for structured sparsity-inducing norm (Q2185635) (← links)
• Projective inference in high-dimensional problems: prediction and feature selection (Q2188473) (← links)
• The LASSO on latent indices for regression modeling with ordinal categorical predictors (Q2189591) (← links)
• Debiasing the debiased Lasso with bootstrap (Q2192302) (← links)
• Adaptive penalized weighted least absolute deviations estimation for the accelerated failure time model (Q2194752) (← links)
• Identifying local differences with fused-MCP: an apartment rental market case study on geographical segmentation detection (Q2195532) (← links)
• Matrix completion with nonconvex regularization: spectral operators and scalable algorithms (Q2195855) (← links)
• Estimating sparse networks with hubs (Q2196140) (← links)
• GRID: a variable selection and structure discovery method for high dimensional nonparametric regression (Q2196249) (← links)
• Sequential feature screening for generalized linear models with sparse ultra-high dimensional data (Q2200110) (← links)
• Variable selection for sparse logistic regression (Q2202033) (← links)
• New insights on the optimality conditions of the \(\ell_2-\ell_0\) minimization problem (Q2203360) (← links)
• Bayesian fusion estimation via \(t\) shrinkage (Q2206752) (← links)
• On the asymptotic properties of SLOPE (Q2206758) (← links)
• Conditional SIRS for nonparametric and semiparametric models by marginal empirical likelihood (Q2208382) (← links)
• A robust and efficient estimation and variable selection method for partially linear models with large-dimensional covariates (Q2208404) (← links)
• A penalized h-likelihood variable selection algorithm for generalized linear regression models with random effects (Q2210294) (← links)