Likelihood Ratio Test in Multivariate Linear Regression: from Low to High Dimension
From MaRDI portal
Publication:5155185
DOI10.5705/ss.202019.0056zbMath1478.62194arXiv1812.06894OpenAlexW3037381413MaRDI QIDQ5155185
Jiyang Wen, Gongjun Xu, Yinqiu He, Tiefeng Jiang
Publication date: 6 October 2021
Published in: Statistica Sinica (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1812.06894
Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Hypothesis testing in multivariate analysis (62H15)
Related Items
A fast and consistent variable selection method for high-dimensional multivariate linear regression with a large number of explanatory variables ⋮ Moderate deviation principle for likelihood ratio test in multivariate linear regression model
Cites Work
- Unnamed Item
- Unnamed Item
- Sure independence screening in generalized linear models with NP-dimensionality
- Reduced rank regression via adaptive nuclear norm penalization
- Sparse principal component analysis and iterative thresholding
- Valid post-selection inference
- Central limit theorems for classical likelihood ratio tests for high-dimensional normal distributions
- High-dimensional sparse MANOVA
- Central limit theorems for linear spectral statistics of large dimensional \(F\)-matrices
- Likelihood ratio tests for covariance matrices of high-dimensional normal distributions
- On testing the equality of high dimensional mean vectors with unequal covariance matrices
- Multivariate analysis of variance with fewer observations than the dimension
- Approximate null distribution of the largest root in multivariate analysis
- Regularized multivariate regression for identifying master predictors with application to integrative genomics study of breast cancer
- Multivariate analysis and Jacobi ensembles: largest eigenvalue, Tracy-Widom limits and rates of convergence
- Corrections to LRT on large-dimensional covariance matrix by RMT
- Generalized additive models
- High-dimensional general linear hypothesis tests via non-linear spectral shrinkage
- High-dimensional general linear hypothesis testing under heteroscedasticity
- Testing linear hypotheses in high-dimensional regressions
- Statistical learning and selective inference
- p-Values for High-Dimensional Regression
- Deterministic Parallel Analysis: An Improved Method for Selecting Factors and Principal Components
- Likelihood Ratio Tests for High‐Dimensional Normal Distributions
- Sure Independence Screening for Ultrahigh Dimensional Feature Space
- Stability Selection
- Dimension Reduction and Coefficient Estimation in Multivariate Linear Regression
- High Dimensional Ordinary Least Squares Projection for Screening Variables
- Indirect multivariate response linear regression
- On a Heuristic Method of Test Construction and its use in Multivariate Analysis
