Projection Test for Mean Vector in High Dimensions
From MaRDI portal
Publication:6154029
DOI10.1080/01621459.2022.2142592MaRDI QIDQ6154029
Wei Zhong, Run-Ze Li, Xiufan Yu, Wanjun Liu
Publication date: 19 March 2024
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://scholarsphere.psu.edu/resources/87fc12ad-ac94-489a-a8a5-e76dde29ff6f
Cites Work
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- Distributed Optimization and Statistical Learning via the Alternating Direction Method of Multipliers
- Global solutions to folded concave penalized nonconvex learning
- One-step sparse estimates in nonconcave penalized likelihood models
- An overview of tests on high-dimensional means
- A two-sample test for high-dimensional data with applications to gene-set testing
- Central limit theorems and bootstrap in high dimensions
- Calibrating nonconvex penalized regression in ultra-high dimension
- A test for the mean vector with fewer observations than the dimension
- Strong oracle optimality of folded concave penalized estimation
- Generalized alternating direction method of multipliers: new theoretical insights and applications
- Exact t and F Tests for Analyzing Studies with Multiple Endpoints
- Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
- Simulation‐based hypothesis testing of high dimensional means under covariance heterogeneity
- Regularized Estimation of Linear Functionals of Precision Matrices for High-Dimensional Time Series
- Two-Sample Test of High Dimensional Means Under Dependence
- An overview of the estimation of large covariance and precision matrices
- Statistical Foundations of Data Science
- An adaptive two-sample test for high-dimensional means
- Regularized M-estimators with nonconvexity: Statistical and algorithmic theory for local optima
