Journal article
Order test for high-dimensional two-sample means
Journal of statistical planning and inference, Vol.142(9), pp.2719-2725
09/01/2012
DOI: 10.1016/j.jspi.2012.03.001
Abstract
We propose a new method to test the order between two high-dimensional mean curves. The new statistic extends the approach of Follmann (1996) to high-dimensional data by adapting the strategy of Bai and Saranadasa (1996). The proposed procedure is an alternative to the non-negative basis matrix factorization (NBMF) based test of Lee et al. (2008) for the same hypothesis, but it is much easier to implement. We derive the asymptotic mean and variance of the proposed test statistic under the null hypothesis of equal mean curves. Based on theoretical results, we put forward a permutation procedure to approximate the null distribution of the new test statistic. We compare the power of the proposed test with that of the NBMF-based test via simulations. We illustrate the approach by an application to tidal volume traces. (C) 2012 Elsevier B.V. All rights reserved.
Details
- Title: Subtitle
- Order test for high-dimensional two-sample means
- Creators
- Sang H Lee - Nathan Kline Institute for Psychiatric ResearchJohan Lim - Seoul National UniversityErning Li - University of IowaMarina Vannucci - Rice UniversityEva Petkova - New York University
- Resource Type
- Journal article
- Publication Details
- Journal of statistical planning and inference, Vol.142(9), pp.2719-2725
- Publisher
- ELSEVIER
- DOI
- 10.1016/j.jspi.2012.03.001
- ISSN
- 0378-3758
- eISSN
- 1873-1171
- Number of pages
- 7
- Grant note
- National Research Foundation of Korea (NRF) 1007871 / NSF-DMS 2011-0029104 / Korea Government (MEST)
- Language
- English
- Date published
- 09/01/2012
- Academic Unit
- Statistics and Actuarial Science
- Record Identifier
- 9984257617802771
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