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-dimensional Gaussian model selection on a Gaussian design (Q985331) (← links)
- Penalized variable selection procedure for Cox models with semiparametric relative risk (Q987999) (← links)
- Variable selection in nonparametric additive models (Q988006) (← links)
- SPADES and mixture models (Q988014) (← links)
- Sparse regulatory networks (Q993240) (← links)
- Feature selection guided by structural information (Q993274) (← links)
- Estimation of covariance matrix via the sparse Cholesky factor with lasso (Q993832) (← links)
- When do stepwise algorithms meet subset selection criteria? (Q995431) (← links)
- Lasso-type recovery of sparse representations for high-dimensional data (Q1002157) (← links)
- Rank reducible varying coefficient model (Q1007481) (← links)
- Gaussian model selection with an unknown variance (Q1020973) (← links)
- On the distribution of the adaptive LASSO estimator (Q1022011) (← links)
- Subset selection for vector autoregressive processes using Lasso (Q1023702) (← links)
- A note on adaptive group Lasso (Q1023903) (← links)
- High-dimensional additive modeling (Q1043712) (← links)
- Sparsistency and rates of convergence in large covariance matrix estimation (Q1043730) (← links)
- Estimating the dimension of a model (Q1247128) (← links)
- Interquantile shrinkage and variable selection in quantile regression (Q1615197) (← links)
- Nonnegative-Lasso and application in index tracking (Q1615217) (← links)
- Model detection for functional polynomial regression (Q1615229) (← links)
- Stabilizing the Lasso against cross-validation variability (Q1615230) (← links)
- Variable selection and semiparametric efficient estimation for the heteroscedastic partially linear single-index model (Q1615234) (← links)
- Modeling financial durations using penalized estimating functions (Q1615270) (← links)
- Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients (Q1615281) (← links)
- A new self-adaptive CQ algorithm with an application to the LASSO problem (Q1615350) (← links)
- Change-point detection in high-dimensional covariance structure (Q1616311) (← links)
- Tuning parameter selection in sparse regression modeling (Q1621202) (← links)
- Penalized likelihood and Bayesian function selection in regression models (Q1621251) (← links)
- Fast Bayesian model assessment for nonparametric additive regression (Q1621314) (← links)
- Data mining for longitudinal data under multicollinearity and time dependence using penalized generalized estimating equations (Q1621346) (← links)
- Estimation and variable selection for partially functional linear models (Q1622116) (← links)
- Group subset selection for linear regression (Q1623472) (← links)
- Monotone splines Lasso (Q1623607) (← links)
- Variable and boundary selection for functional data via multiclass logistic regression modeling (Q1623638) (← links)
- Regularization and model selection for quantile varying coefficient model with categorical effect modifiers (Q1623652) (← links)
- Estimation of an oblique structure via penalized likelihood factor analysis (Q1623658) (← links)
- Partially linear structure identification in generalized additive models with NP-dimensionality (Q1623710) (← links)
- Selection of fixed effects in high dimensional linear mixed models using a multicycle ECM algorithm (Q1623713) (← links)
- Variable selection in general multinomial logit models (Q1623760) (← links)
- Domain selection for the varying coefficient model via local polynomial regression (Q1623796) (← links)
- The cluster graphical Lasso for improved estimation of Gaussian graphical models (Q1623817) (← links)
- Model selection consistency of Lasso for empirical data (Q1624086) (← links)
- Laplace error penalty-based M-type model detection for a class of high dimensional semiparametric models (Q1631432) (← links)
- Variable selection via penalized credible regions with Dirichlet-Laplace global-local shrinkage priors (Q1631579) (← links)
- Variable selection in censored quantile regression with high dimensional data (Q1635848) (← links)
- Penalised inference for lagged dependent regression in the presence of autocorrelated residuals (Q1640650) (← links)
- Variable selection via generalized SELO-penalized linear regression models (Q1640691) (← links)
- Censored cumulative residual independent screening for ultrahigh-dimensional survival data (Q1642144) (← links)
- Statistics for big data: a perspective (Q1642374) (← links)
- Conditional quantile correlation screening procedure for ultrahigh-dimensional varying coefficient models (Q1643796) (← links)
