A Computational Approach Test for the Equality of Two Multivariate Normal Mean Vectors under Heterogeneity of Covariance Matrices

Autor:	Esra Gökpınar, Sezen Karanfil, Meral Ebegil, Yaprak Arzu Ozdemir, Fikri Gökpınar
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Computational Approach Test Parametric Bootstrap Approach Simulation Study Statistics HA1-4737 Probabilities. Mathematical statistics QA273-280
Zdroj:	Revstat Statistical Journal, Vol 20, Iss 2 (2022)
Druh dokumentu:	article
ISSN:	1645-6726 2183-0371
DOI:	10.57805/revstat.v20i2.368
Popis:	In this paper, a computational approach test (CAT) was proposed to test the equality of two multivariate normal mean vectors under heterogeneity of covariance matrices. The proposed test was compared with the other popular tests as well as their CAT versions in terms of estimated type I error rate and power. Simulation study shows that the proposed test and CAT versions of tests can be used as a good alternative test to test the equality of two multivariate normal mean vectors under heterogeneity of covariance matrices.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/843f72e41afc453f86ffbc77fed9b96b Zobrazit plný text záznamu View record in DOAJ