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On the Identification of Extreme Elements in a Residual for the GMANOVA-MANOVA Model
Linköpings universitet, Matematiska institutionen, Tillämpad matematik. Linköpings universitet, Tekniska fakulteten. Department of Mathematics, University of Rwanda, Kigali, Rwanda.
Linköpings universitet, Matematiska institutionen, Tillämpad matematik. Linköpings universitet, Tekniska fakulteten. Department of Energy and Technology, Swedish University of Agricultural Sciences, Uppsala, Sweden.
Linköpings universitet, Matematiska institutionen, Tillämpad matematik. Linköpings universitet, Tekniska fakulteten. (Matematisk statistik)ORCID-id: 0000-0001-9896-4438
2022 (engelsk)Inngår i: Innovations in Multivariate Statistical Modeling: Navigating Theoretical and Multidisciplinary Domains / [ed] Andriëtte Bekker, Johannes T. Ferreira, Mohammad Arashi and Ding-Geng Chen, Cham: Springer Cham , 2022, s. 119-135Kapittel i bok, del av antologi (Fagfellevurdert)
Abstract [en]

Two different matrix residuals in a special GMANOVA-MANOVA model have previously been established (see Byukusenge et al., 2021, “On residual analysis in the GMANOVA-MANOVA model”). The residual that is studied in this article is constructed via the difference of the observed group means and the estimated mean structure. The residual provides information about the appropriateness of the model assumptions concerning the mean structure. The aim of this paper is to study the distribution of the largest elements (by absolute value) of the residual via two data sets. Parametric bootstrap is used to identify thresholds so that extreme elements of the residuals can be identified.

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Cham: Springer Cham , 2022. s. 119-135
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Emerging Topics in Statistics and Biostatistics, ISSN 2524-7735, E-ISSN 2524-7743 ; 1
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URN: urn:nbn:se:liu:diva-198562DOI: 10.1007/978-3-031-13971-0_6Libris ID: 0hnn46zkx6svcq1wISBN: 9783031139710 (tryckt)OAI: oai:DiVA.org:liu-198562DiVA, id: diva2:1805528
Tilgjengelig fra: 2023-10-17 Laget: 2023-10-17 Sist oppdatert: 2023-11-21bibliografisk kontrollert

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