Factor-adjusted tests for generalized linear models with multimodal data: an application to breast cancer data

DOI10.1007/s11425-023-2218-4MaRDI QIDQ6668586

Lei Wang, Dongyu Li

Publication date: 22 January 2025

Published in: Science China. Mathematics (Search for Journal in Brave)

zbMATH Keywords

high-dimensional datafactor modelintegrative analysisdecorrelated scorepartial penalized Wald test

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Parametric inference under constraints (62F30)

Cites Work

• Unnamed Item
• Nearly unbiased variable selection under minimax concave penalty
• Factor-Adjusted Regularized Model Selection
• A general theory of hypothesis tests and confidence regions for sparse high dimensional models
• Factor models and variable selection in high-dimensional regression analysis
• Sparse integrative clustering of multiple omics data sets
• Sufficient dimension reduction in the presence of controlling variables
• Linear hypothesis testing for high dimensional generalized linear models
• Augmented factor models with applications to validating market risk factors and forecasting bond risk premia
• Nearly optimal Bayesian shrinkage for high-dimensional regression
• Embracing the Blessing of Dimensionality in Factor Models
• Imputed Factor Regression for High-dimensional Block-wise Missing Data
• Determining the Number of Factors in Approximate Factor Models
• Large Covariance Estimation by Thresholding Principal Orthogonal Complements
• Covariate‐driven factorization by thresholding for multiblock data
• Orthogonalized Kernel Debiased Machine Learning for Multimodal Data Analysis
• Integrative Factor Regression and Its Inference for Multimodal Data Analysis

This page was built for publication: Factor-adjusted tests for generalized linear models with multimodal data: an application to breast cancer data