High-dimensional integrative copula discriminant analysis for multiomics data
From MaRDI portal
Publication:6617435
DOI10.1002/SIM.8758zbMATH Open1546.62312MaRDI QIDQ6617435
Jiadong Ji, Xinsheng Zhang, Lei Liu, Hao Chen, Hao Sun, Yufeng Shi, Yong He
Publication date: 10 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
Cites Work
- Title not available (Why is that?)
- High dimensional discrimination analysis via a semiparametric model
- Discriminant analysis on high dimensional Gaussian copula model
- The meta-elliptical distributions with given marginals
- High-dimensional classification using features annealed independence rules
- Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
- Sparse integrative clustering of multiple omics data sets
- The Dantzig selector: statistical estimation when \(p\) is much larger than \(n\). (With discussions and rejoinder).
- The nonparanormal: semiparametric estimation of high dimensional undirected graphs
- Identification of cancer genomic markers via integrative sparse boosting
- Integrative analysis and variable selection with multiple high-dimensional data sets
- A direct approach to sparse discriminant analysis in ultra-high dimensions
- A Direct Estimation Approach to Sparse Linear Discriminant Analysis
- Discriminant analysis through a semiparametric model
- Integrative linear discriminant analysis with guaranteed error rate improvement
- High Dimensional Semiparametric Latent Graphical Model for Mixed Data
- Model Selection and Estimation in Regression with Grouped Variables
- A Road to Classification in High Dimensional Space: The Regularized Optimal Affine Discriminant
- Integrating approximate single factor graphical models
This page was built for publication: High-dimensional integrative copula discriminant analysis for multiomics data
Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6617435)