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

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 pro...

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Bibliographic Details
Published in:	Journal of statistical planning and inference Vol. 143; no. 5; pp. 929 - 943
Main Authors:	Park, Junyong, Ayyala, Deepak Nag
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01-05-2013
Subjects:	Asymptotic distribution High dimension Scalar transform invariant test Testing mean vector Testing mean vector High dimension Scalar transform invariant test Asymptotic distribution
Online Access:	Get full text
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Summary:	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.
ISSN:	0378-3758 1873-1171
DOI:	10.1016/j.jspi.2012.11.001