Abstract
We consider testing whether the mean vectors of two or more populations have parallel, coincident, or flat profiles when the validity of normality is not known, and the sample sizes are moderate. Using some properties of multivariate moments and matrix manipulations, we obtain the asymptotic expansions for the null distribution of the Lawley-Hotelling statistics. We also derive the corresponding results in the situation where interest lies in coincidence and flatness alone. Accuracy of all the asymptotic expansions in approximating the exact null distributions is examined via simulation. Profile analysis of SO4 concentrations from a forestry experiment is used to illustrate the methods.
| Original language | English |
|---|---|
| Pages (from-to) | 3553-3573 |
| Number of pages | 21 |
| Journal | Communications in Statistics - Theory and Methods |
| Volume | 43 |
| Issue number | 17 |
| DOIs | |
| State | Published - 2014 |
Bibliographical note
Funding Information:The research of Jin Xu was supported by National Natural Science Foundation of China Grant 10701036. The authors are thankful to the anonymous reviewer whose comments and suggestions have led to a significant improvement over the original version.
Keywords
- Asymptotic expansion
- MANOVA
- Multivariate kurtosis
- Multivariate skewness
- Repeated Measures
- Robustness
ASJC Scopus subject areas
- Statistics and Probability