Large-scale multivariate sparse regression with applications to UK Biobank
DOI10.1214/21-AOAS1575zbMath1498.62135OpenAlexW4286484355MaRDI QIDQ2170442
Yosuke Tanigawa, Manuel A. Rivas, Robert Tibshirani, Ruilin Li, Junyang Qian, Trevor Hastie
Publication date: 5 September 2022
Published in: The Annals of Applied Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1214/21-aoas1575
sparse regressionreduced-rank regressionlarge-scale algorithmpolygenic risk scoreUK Biobankultrahigh-dimensional problem
Computational methods for problems pertaining to statistics (62-08) Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Learning and adaptive systems in artificial intelligence (68T05)
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- Leveraging mixed and incomplete outcomes via reduced-rank modeling
- Fast identification of biological pathways associated with a quantitative trait using group lasso with overlaps
- Statistics for high-dimensional data. Methods, theory and applications.
- Blind separation of sources. I: An adaptive algorithm based on neuromimetic architecture
- Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer
- Input selection and shrinkage in multiresponse linear regression
- Multivariate reduced-rank regression
- Independent component analysis, a new concept?
- Persistene in high-dimensional linear predictor-selection and the virtue of overparametrization
- Simultaneous analysis of Lasso and Dantzig selector
- Support union recovery in high-dimensional multivariate regression
- High-dimensional graphs and variable selection with the Lasso
- Computer Age Statistical Inference
- Large-Scale Machine Learning with Stochastic Gradient Descent
- Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection
- Sparse Reduced-Rank Regression for Simultaneous Dimension Reduction and Variable Selection
- Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
- Adaptive Estimation in Two-way Sparse Reduced-rank Regression
- Integrative multi‐view regression: Bridging group‐sparse and low‐rank models
- Regularization and Variable Selection Via the Elastic Net
- Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling
- Model Selection and Estimation in Regression with Grouped Variables
- The biplot graphic display of matrices with application to principal component analysis
- Strong Rules for Discarding Predictors in Lasso-Type Problems
- RELATIONS BETWEEN TWO SETS OF VARIATES
- Estimating Linear Restrictions on Regression Coefficients for Multivariate Normal Distributions
