Response variable selection in multivariate linear regression
From MaRDI portal
Publication:6593365
DOI10.5705/SS.202022.0127MaRDI QIDQ6593365
Publication date: 26 August 2024
Published in: STATISTICA SINICA (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- A penalized matrix decomposition, with applications to sparse principal components and canonical correlation analysis
- A sparse conditional Gaussian graphical model for analysis of genetical genomics data
- Reduced rank regression via adaptive nuclear norm penalization
- The Adaptive Lasso and Its Oracle Properties
- Simultaneous multiple response regression and inverse covariance matrix estimation via penalized Gaussian maximum likelihood
- A Bayesian graphical modeling approach to microRNA regulatory network inference
- Coordinate-independent sparse sufficient dimension reduction and variable selection
- Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer
- A note on adaptive group Lasso
- The control of the false discovery rate in multiple testing under dependency.
- On the asymptotic properties of the group lasso estimator for linear models
- Parametric and semiparametric reduced-rank regression with flexible sparsity
- Joint mean-covariance estimation via the horseshoe
- Simultaneous selection of predictors and responses for high dimensional multivariate linear regression
- Penalized Generalized Estimating Equations for High-Dimensional Longitudinal Data Analysis
- Sparse Matrix Inversion with Scaled Lasso
- Joint estimation of sparse multivariate regression and conditional graphical models
- A Constrainedℓ1Minimization Approach to Sparse Precision Matrix Estimation
- Efficient parameter estimation in longitudinal data analysis using a hybrid GEE method
- Simultaneous Variable and Covariance Selection With the Multivariate Spike-and-Slab LASSO
- Performance of Generalized Estimating Equations in Practical Situations
- Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection
- A Convex Pseudolikelihood Framework for High Dimensional Partial Correlation Estimation with Convergence Guarantees
- Sparse envelope model: efficient estimation and response variable selection in multivariate linear regression
- Indirect multivariate response linear regression
- Sparse precision matrix estimation via lasso penalized D-trace loss
- Model Selection and Estimation in Regression with Grouped Variables
- An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias
This page was built for publication: Response variable selection in multivariate linear regression
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6593365)