A test for the mean vector in large dimension and small samples

Junyong Park; Deepak Nag Ayyala

doi:10.1016/j.jspi.2012.11.001

A test for the mean vector in large dimension and small samples

Junyong Park, Deepak Nag Ayyala

Research output: Contribution to journal › Article › peer-review

61 Scopus citations

Abstract

In this paper, we consider the problem of testing the mean vector in the multivariate setting where the dimension p is greater than the sample size n, namely a large p and small n problem. We propose a new scalar transform invariant test and show the asymptotic null distribution and power of the proposed test under weaker conditions than Srivastava (2009). We also present numerical studies including simulations and a real example of microarray data with comparison to existing tests developed for a large p and small n problem.

Original language	English (US)
Pages (from-to)	929-943
Number of pages	15
Journal	Journal of Statistical Planning and Inference
Volume	143
Issue number	5
DOIs	https://doi.org/10.1016/j.jspi.2012.11.001
State	Published - May 2013
Externally published	Yes

Keywords

Asymptotic distribution
High dimension
Scalar transform invariant test
Testing mean vector

ASJC Scopus subject areas

Statistics and Probability
Statistics, Probability and Uncertainty
Applied Mathematics

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10.1016/j.jspi.2012.11.001

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A test for the mean vector in large dimension and small samples

Abstract

Keywords

ASJC Scopus subject areas

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