The following pages link to glmnet (Q20169):
Displaying 50 items.
- Rejoinder: ``A significance test for the lasso'' (Q2249839) (← links)
- Sparse optimization in feature selection: application in neuroimaging (Q2250090) (← links)
- Lasso with long memory regression errors (Q2250693) (← links)
- Incrementally updated gradient methods for constrained and regularized optimization (Q2251572) (← links)
- Shrinkage estimation and variable selection in multiple regression models with random coefficient autoregressive errors (Q2251707) (← links)
- Ridge estimation for multinomial logit models with symmetric side constraints (Q2255916) (← links)
- Fast and adaptive sparse precision matrix estimation in high dimensions (Q2256755) (← links)
- Sparse semiparametric discriminant analysis (Q2256757) (← links)
- Multinomial logit models with implicit variable selection (Q2256779) (← links)
- High-dimensional variable screening and bias in subsequent inference, with an empirical comparison (Q2259726) (← links)
- Sparse distance metric learning (Q2259733) (← links)
- Forecasting mortality rate improvements with a high-dimensional VAR (Q2273994) (← links)
- Joint estimation of conditional quantiles in multivariate linear regression models with an application to financial distress (Q2274932) (← links)
- Financial, macro and micro econometrics using R (Q2280040) (← links)
- Network classification with applications to brain connectomics (Q2281212) (← links)
- Oblique random survival forests (Q2281237) (← links)
- A kernel-based trend pattern tracking system for portfolio optimization (Q2287718) (← links)
- Variance prior forms for high-dimensional Bayesian variable selection (Q2290703) (← links)
- Bayesian functional forecasting with locally-autoregressive dependent processes (Q2290704) (← links)
- Ensemble quantile classifier (Q2291292) (← links)
- A novel Bayesian approach for variable selection in linear regression models (Q2291315) (← links)
- Efficient computation for differential network analysis with applications to quadratic discriminant analysis (Q2291319) (← links)
- Robust elastic net estimators for variable selection and identification of proteomic biomarkers (Q2291496) (← links)
- Scalable high-resolution forecasting of sparse spatiotemporal events with kernel methods: a winning solution to the NIJ ``Real-time crime forecasting challenge'' (Q2291539) (← links)
- Numerical analysis for conservation laws using \(l_1\) minimization (Q2291861) (← links)
- ROS regression: integrating regularization with optimal scaling regression (Q2292391) (← links)
- Lasso meets horseshoe: a survey (Q2292393) (← links)
- Distributed simultaneous inference in generalized linear models via confidence distribution (Q2293540) (← links)
- On the sparsity of Mallows model averaging estimator (Q2295365) (← links)
- High-dimensional posterior consistency for hierarchical non-local priors in regression (Q2297241) (← links)
- Variable selection with spatially autoregressive errors: a generalized moments Lasso estimator (Q2297950) (← links)
- Regularization methods for high-dimensional sparse control function models (Q2301081) (← links)
- MCEN: a method of simultaneous variable selection and clustering for high-dimensional multinomial regression (Q2302492) (← links)
- Regularized estimation for highly multivariate log Gaussian Cox processes (Q2302515) (← links)
- High-dimensional regression in practice: an empirical study of finite-sample prediction, variable selection and ranking (Q2302521) (← links)
- Optimal designs in sparse linear models (Q2303755) (← links)
- The \(\delta \)-machine: classification based on distances towards prototypes (Q2304085) (← links)
- Perturbation bootstrap in adaptive Lasso (Q2313280) (← links)
- Non-concave penalization in linear mixed-effect models and regularized selection of fixed effects (Q2316730) (← links)
- A modified generalized Lasso algorithm to detect local spatial clusters for count data (Q2316749) (← links)
- Bootstrapping Lasso-type estimators in regression models (Q2317244) (← links)
- Computational and statistical analyses for robust non-convex sparse regularized regression problem (Q2317291) (← links)
- Tuning parameter calibration for \(\ell_1\)-regularized logistic regression (Q2317308) (← links)
- Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case (Q2318820) (← links)
- PLS for Big Data: a unified parallel algorithm for regularised group PLS (Q2323935) (← links)
- A two-stage sparse logistic regression for optimal gene selection in high-dimensional microarray data classification (Q2324259) (← links)
- A variable selection approach in the multivariate linear model: an application to LC-MS metabolomics data (Q2324950) (← links)
- Stochastic proximal-gradient algorithms for penalized mixed models (Q2329762) (← links)
- Selection of sparse vine copulas in high dimensions with the Lasso (Q2329765) (← links)
- A consistent and numerically efficient variable selection method for sparse Poisson regression with applications to learning and signal recovery (Q2329779) (← links)
