Pages that link to "Item:Q147375"

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

Displaying 50 items.

• High dimensional censored quantile regression (Q1747740) (← links)
• Bayesian estimation of sparse signals with a continuous spike-and-slab prior (Q1747745) (← links)
• DC programming and DCA: thirty years of developments (Q1749443) (← links)
• Covariance estimation via sparse Kronecker structures (Q1750103) (← links)
• Logistic regression: from art to science (Q1750250) (← links)
• I-LAMM for sparse learning: simultaneous control of algorithmic complexity and statistical error (Q1750288) (← links)
• Uniformly valid confidence sets based on the Lasso (Q1753143) (← links)
• On penalized estimation for dynamical systems with small noise (Q1753155) (← links)
• Robust variable selection for finite mixture regression models (Q1753969) (← links)
• Penalized indirect inference (Q1754510) (← links)
• Sparse inference of the drift of a high-dimensional Ornstein-Uhlenbeck process (Q1755107) (← links)
• Optimal estimation of slope vector in high-dimensional linear transformation models (Q1755121) (← links)
• Equivalent Lipschitz surrogates for zero-norm and rank optimization problems (Q1756795) (← links)
• Recovery of seismic wavefields by an \(l_{q}\)-norm constrained regularization method (Q1785033) (← links)
• High-dimensional inference: confidence intervals, \(p\)-values and R-software \texttt{hdi} (Q1790302) (← links)
• Irregular N2SLS and Lasso estimation of the matrix exponential spatial specification model (Q1792447) (← links)
• Estimation of large dimensional factor models with an unknown number of breaks (Q1792477) (← links)
• Variable selection for structural equation with endogeneity (Q1794305) (← links)
• An RKHS-based approach to double-penalized regression in high-dimensional partially linear models (Q1795582) (← links)
• Time-varying correlation structure estimation and local-feature detection for spatio-temporal data (Q1795586) (← links)
• Broken adaptive ridge regression and its asymptotic properties (Q1795597) (← links)
• Stability monitoring of batch processes with iterative learning control (Q1798445) (← links)
• Pursuit of dynamic structure in quantile additive models with longitudinal data (Q1799871) (← links)
• Shrinkage variable selection and estimation in proportional hazards models with additive structure and high dimensionality (Q1800064) (← links)
• Sufficient dimension reduction in multivariate regressions with categorical predictors (Q1800068) (← links)
• Variable selection in high-dimensional partially linear additive models for composite quantile regression (Q1800107) (← links)
• Model selection via standard error adjusted adaptive Lasso (Q1934485) (← links)
• LAD variable selection for linear models with randomly censored data (Q1936296) (← links)
• Variable selection via RIVAL (removing irrelevant variables amidst lasso iterations) and its application to nuclear material detection (Q1937489) (← links)
• Variable selection in linear mixed effects models (Q1940766) (← links)
• Needles and straw in a haystack: posterior concentration for possibly sparse sequences (Q1940767) (← links)
• Multi-parametric solution-path algorithm for instance-weighted support vector machines (Q1945116) (← links)
• Shrinkage estimation analysis of correlated binary data with a diverging number of parameters (Q1945499) (← links)
• Remodeling and estimation for sparse partially linear regression models (Q1949496) (← links)
• Regularized \(k\)-means clustering of high-dimensional data and its asymptotic consistency (Q1950809) (← links)
• Theoretical properties of the overlapping groups Lasso (Q1950815) (← links)
• High-dimensional additive hazards models and the lasso (Q1950827) (← links)
• Fixed and random effects selection in nonparametric additive mixed models (Q1950841) (← links)
• Variable selection of varying coefficient models in quantile regression (Q1950855) (← links)
• Sparse least trimmed squares regression for analyzing high-dimensional large data sets (Q1951528) (← links)
• Bootstrap inference for network construction with an application to a breast cancer microarray study (Q1951540) (← links)
• On the asymptotic properties of the group lasso estimator for linear models (Q1951765) (← links)
• Honest variable selection in linear and logistic regression models via \(\ell _{1}\) and \(\ell _{1}+\ell _{2}\) penalization (Q1951794) (← links)
• Inferring sparse Gaussian graphical models with latent structure (Q1951974) (← links)
• Thresholding-based iterative selection procedures for model selection and shrinkage (Q1951984) (← links)
• On Lasso for censored data (Q1951988) (← links)
• Forest Garrote (Q1952025) (← links)
• On the conditions used to prove oracle results for the Lasso (Q1952029) (← links)
• Confidence sets based on penalized maximum likelihood estimators in Gaussian regression (Q1952055) (← links)
• Self-concordant analysis for logistic regression (Q1952060) (← links)