Cross projection test for mean vectors via multiple random splits in high dimensions

Cites Work

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A two sample test in high dimensional data
A high dimensional two-sample test under a low dimensional factor structure
Two-sample Behrens-Fisher problems for high-dimensional data: a normal reference approach
High-dimensional variable selection
A test for the mean vector with fewer observations than the dimension under non-normality
On two-sample mean tests under spiked covariances
Multivariate tests based on left-spherically distributed linear scores
A test for the mean vector in large dimension and small samples
Testing proportionality of two high-dimensional covariance matrices
A two-sample test for high-dimensional data with applications to gene-set testing
A test for the mean vector with fewer observations than the dimension
Regularized estimation of large covariance matrices
A Behrens-Fisher problem for general factor models in high dimensions
Two-Stage Procedures for High-Dimensional Data
A Powerful Bayesian Test for Equality of Means in High Dimensions
Cauchy Combination Test: A Powerful Test With Analytic p-Value Calculation Under Arbitrary Dependency Structures
Two-sample behrens-fisher problem for high-dimensional data
Exact t and F Tests for Analyzing Studies with Multiple Endpoints
The Generalization of Student's Ratio
Two-sample tests for high-dimension, strongly spiked eigenvalue models
Power Enhancement in High-Dimensional Cross-Sectional Tests
Two-Sample Test of High Dimensional Means Under Dependence
Linear Hypothesis Testing in Linear Models With High-Dimensional Responses

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