Pages that link to "Item:Q2466686"

The following pages link to On the ``degrees of freedom'' of the lasso (Q2466686):

Displaying 50 items.

• The dual and degrees of freedom of linearly constrained generalized Lasso (Q1663318) (← links)
• Generalized network psychometrics: combining network and latent variable models (Q1695733) (← links)
• Variable selection and estimation using a continuous approximation to the \(L_0\) penalty (Q1695760) (← links)
• Fast state-space methods for inferring dendritic synaptic connectivity (Q1704795) (← links)
• Spatial weights matrix selection and model averaging for spatial autoregressive models (Q1706440) (← links)
• Variable selection via generalized SELO-penalized Cox regression models (Q1738526) (← links)
• Review: Reversed low-rank ANOVA model for transforming high dimensional genetic data into low dimension (Q1740304) (← links)
• Regularization parameter selection for penalized empirical likelihood estimator (Q1741726) (← links)
• On the sensitivity of the Lasso to the number of predictor variables (Q1790389) (← links)
• On the exponentially weighted aggregate with the Laplace prior (Q1800807) (← 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 and parameter estimation for partially linear models via Dantzig selector (Q1938499) (← links)
• Sparse least trimmed squares regression for analyzing high-dimensional large data sets (Q1951528) (← links)
• Penalized wavelets: embedding wavelets into semiparametric regression (Q1952243) (← links)
• Scale-constrained approaches for maximum likelihood estimation and model selection of clusterwise linear regression models (Q1985960) (← links)
• Sparsity-promoting elastic net method with rotations for high-dimensional nonlinear inverse problem (Q1986778) (← links)
• Debiasing the Lasso: optimal sample size for Gaussian designs (Q1991670) (← links)
• On the degrees of freedom of mixed matrix regression (Q1993055) (← links)
• Generalized \(\ell_1\)-penalized quantile regression with linear constraints (Q2008107) (← links)
• A century of economic policy uncertainty through the French-Canadian Lens (Q2043137) (← links)
• Boosted nonparametric hazards with time-dependent covariates (Q2054480) (← links)
• Degrees of freedom for regularized regression with Huber loss and linear constraints (Q2062389) (← links)
• Information criteria bias correction for group selection (Q2093122) (← links)
• On the grouping effect of the \(l_{1-2}\) models (Q2093808) (← links)
• High-dimensional asymptotics of likelihood ratio tests in the Gaussian sequence model under convex constraints (Q2119233) (← links)
• Aggregated hold out for sparse linear regression with a robust loss function (Q2136632) (← links)
• De-biasing the Lasso with degrees-of-freedom adjustment (Q2136990) (← links)
• Degrees of freedom for off-the-grid sparse estimation (Q2137058) (← links)
• Computing the degrees of freedom of rank-regularized estimators and cousins (Q2180064) (← links)
• Generalized co-clustering analysis via regularized alternating least squares (Q2189610) (← links)
• Prediction error after model search (Q2196193) (← links)
• Best subset, forward stepwise or Lasso? Analysis and recommendations based on extensive comparisons (Q2225312) (← links)
• On rereading Stein's lemma: its intrinsic connection with Cramér-Rao identity and some new identities (Q2241516) (← links)
• Sparse regression for large data sets with outliers (Q2242288) (← links)
• A significance test for the lasso (Q2249837) (← links)
• Discussion: ``A significance test for the lasso'' (Q2249838) (← links)
• Rejoinder: ``A significance test for the lasso'' (Q2249839) (← links)
• Local behavior of sparse analysis regularization: applications to risk estimation (Q2252165) (← links)
• From simple structure to sparse components: a review (Q2259727) (← links)
• Discriminative variable selection for clustering with the sparse Fisher-EM algorithm (Q2259731) (← links)
• Functional concurrent linear regression model for spatial images (Q2260207) (← links)
• Estimating the rate constant from biosensor data via an adaptive variational Bayesian approach (Q2291491) (← links)
• Degrees of freedom in submodular regularization: a computational perspective of Stein's unbiased risk estimate (Q2293382) (← links)
• Effective new methods for automated parameter selection in regularized inverse problems (Q2301416) (← links)
• AIC for the group Lasso in generalized linear models (Q2303501) (← links)
• A note on the forward-Douglas-Rachford splitting for monotone inclusion and convex optimization (Q2311106) (← links)
• Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects (Q2316730) (← links)
• Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case (Q2318820) (← links)
• A note on rank reduction in sparse multivariate regression (Q2323156) (← links)