Tests for Multivariate Analysis of Variance in High Dimension Under Non-Normality

Muni S. Srivastava and Tatsuya Kubokawa
Additional contact information
Muni S. Srivastava: Department of Statistics, University of Toronto
Tatsuya Kubokawa: Faculty of Economics, University of Tokyo

No CIRJE-F-831, CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo

Abstract: In this article, we consider the problem of testing the equality of mean vectors of dimension ρ of several groups with a common unknown non-singular covariance matrix Σ, based on N independent observation vectors where N may be less than the dimension ρ. This problem, known in the literature as the Multivariate Analysis of variance (MANOVA) in high-dimension has recently been considered in the statistical literature by Srivastava and Fujikoshi[7], Srivastava [5] and Schott[3]. All these tests are not invariant under the change of units of measurements. On the lines of Srivastava and Du[8] and Srivastava[6], we propose a test that has the above invariance property. The null and the non-null distributions are derived under the assumption that ( N , ρ) → ∞ and N may be less than ρ and the observation vectors follow a general non-normal model.

Pages: 21 pages
Date: 2011-12
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.cirje.e.u-tokyo.ac.jp/research/dp/2011/2011cf831.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tky:fseres:2011cf831

Access Statistics for this paper

More papers in CIRJE F-Series from CIRJE, Faculty of Economics, University of Tokyo Contact information at EDIRC.
Bibliographic data for series maintained by CIRJE administrative office ().