Paper Info
Title
Tests for the parallelism and flatness hypotheses of multi-group profile analysis for high-dimensional elliptical populations.
Abstract
This paper is concerned with tests for the parallelism and flatness hypotheses in multi-group profile analysis for high-dimensional data. We extend to elliptical distributions the procedures developed for normal populations by Harrar and Kong (2016). Specifically, we prove that their statistics continue to be asymptotically normal when the underlying population is elliptical, and we obtain new tests by improving their estimator of the asymptotic variance. Using asymptotic normality, we show that the asymptotic size of the proposed tests is equal to the nominal significance level, and we also derive the asymptotic power. Finally, we present simulation results and find that the power of the new tests is superior to that of the original Harrar–Kong procedure.
Year
DOI
Venue
2017
10.1016/j.jmva.2017.09.004
Journal of Multivariate Analysis
Keywords
Field
DocType
primary,secondary
Flatness (systems theory),Econometrics,Population,Profile analysis,Statistics,Delta method,Mathematics,Asymptotic distribution,Estimator
Journal
Volume
Issue
ISSN
162
C
0047-259X
Citations 
PageRank 
References 
0
0.34
3
Authors
1
Name
Order
Citations
PageRank
Masashi Hyodo123.21