An Alternative Solution to Hotelling T Square under the Heteroscedasticity of the Dispersion Matrix

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dc.contributor.authorAdebayo, P. O.
dc.contributor.authorOyeyemi, G. M.
dc.date.accessioned2023-07-27T09:14:52Z
dc.date.available2023-07-27T09:14:52Z
dc.date.issued2019
dc.description.abstractThis work focuses on developing an alternative procedure to multivariate Behrens–Fisher problem by using approximate degree of freedom test which was adopted from Satterthwaite univariate procedure. The proposed procedure was compared via R package simulation and real-life data used by Timm with six (6) existing procedures namely: Johanson, Yao, Krishnamoorthy, Hotelling T square, Nel and Van der Merwe, and Yanagihara. It was discovered that the proposed procedure performed better in terms of power of the test, then all existing procedures considered in all the scenarios that include at different: (i) random variables (p), (ii) variance co–variance matrix, (iii) sample size, and (iv) significance level (α). The proposed procedure is completely favorably, well in terms of type I error rate with Johanson, Yao, Krishnamoorthy, Nel, and Van der Merween_US
dc.description.sponsorshipSelf-sponsoreden_US
dc.identifier.citationPacific Journal of Science and Technologyen_US
dc.identifier.urihttps://uilspace.unilorin.edu.ng/handle/20.500.12484/11648
dc.language.isoenen_US
dc.publisherAkamai University, U.S.Aen_US
dc.relation.ispartofseries20(1);112 - 126
dc.subjectVariance, co-variance matrix, Linear combination, Type 1 error rate, Power the test, Heteroscedasticity, R statistical packageen_US
dc.titleAn Alternative Solution to Hotelling T Square under the Heteroscedasticity of the Dispersion Matrixen_US
dc.typeArticleen_US

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