RAPTT: An Exact Two-Sample Test in High Dimensions Using Random Projections

2014/05/08 by Radhendushka Srivastava, Ping Li, Srivastava, Radhendushka +3 · 2 citations
Biochemistry, Genetics and Molecular Biology · Mathematics · #Computation (stat.CO) #FOS: Computer and information sciences #Gene expression and cancer classification #Methodology (stat.ME) #Random Matrices and Applications #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.1405.1792

openalex publication_date 2014/05/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

In high dimensions, the classical Hotelling's T² test tends to have low power or becomes undefined due to singularity of the sample covariance matrix. In this paper, this problem is overcome by projecting the data matrix onto lower dimensional subspaces through multiplication by random matrices. We propose RAPTT (RAndom Projection T-Test), an exact test for equality of means of two normal populations based on projected lower dimensional data. RAPTT does not require any constraints on the dimension of the data or the sample size. A simulation study indicates that in high dimensions the power of this test is often greater than that of competing tests. The advantage of RAPTT is illustrated on high-dimensional gene expression data involving the discrimination of tumor and normal colon tissues.

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