Testing the equality of several covariance matrices with fewer observations than the dimension

Muni S. Srivastava and Hirokazu Yanagihara

Journal of Multivariate Analysis, 2010, vol. 101, issue 6, 1319-1329

Abstract: For normally distributed data from the k populations with mxm covariance matrices [Sigma]1,...,[Sigma]k, we test the hypothesis H:[Sigma]1=...=[Sigma]k vs the alternative A[not equal to]H when the number of observations Ni, i=1,...,k from each population are less than or equal to the dimension m, Ni

Keywords: Comparison; of; powers; Equality; of; several; covariance; matrices; Equality; of; two; covariances; High-dimensional; data; Normality; Sample; size; smaller; than; the; dimension (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (28)

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