Testing hypotheses about covariance matrices using bootstrap methods
- 1 January 1993
- journal article
- research article
- Published by Taylor & Francis in Communications in Statistics - Theory and Methods
- Vol. 22 (3) , 723-739
- https://doi.org/10.1080/03610929308831051
Abstract
The usual chi-squared approximation to test statistics based on normal theory for testing covariance structures of multivariate populations is very sensitive to the normality assumption. Two general bootstrap procedures are developed in this paper to obtain approximately valid critical values for these test statistics when the data are not normally distributed. The first is based on separate sampling from individual samples, and the second is based on sampling from pooled samples. Although the second method requires more assumptions, its small sample properties are better.Keywords
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