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Extended GMANOVA Model with a Linearly Structured Covariance Matrix
Linköping University, Department of Mathematics. University of Rwanda, Department of Mathematics.
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering. Department of Energy and Technology Swedish University of Agricultural Sciences Uppsala, Sweden..
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0001-9896-4438
2015 (English)In: Mathematical Methods of Statistics, ISSN 1066-5307, E-ISSN 1934-8045, Vol. 24, no 4, 280-291 p.Article in journal (Refereed) Published
Abstract [en]

In this paper we consider the extended generalized multivariate analysis of variance (GMANOVA) with a linearly structured covariance matrix. The main theme is to find explicit estimators for the mean and for the linearly structured covariance matrix. We show how to decompose the residual space, the orthogonal complement to the mean space, into m + 1 orthogonal subspaces and how to derive explicit estimators of the covariance matrix from the sum of squared residuals obtained by projecting observations on those subspaces. Also an explicit estimator of the mean is derived and some properties of the proposed estimators are studied. 

Place, publisher, year, edition, pages
Allerton Press, Inc. , 2015. Vol. 24, no 4, 280-291 p.
Keyword [en]
Estimation; extended growth curve model; GMANOVA; linearly struc- tured covariance matrix; residuals.
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-123370DOI: 10.3103/S1066530715040031Scopus ID: 2-s2.0-84951741568OAI: oai:DiVA.org:liu-123370DiVA: diva2:882130
Available from: 2015-12-14 Created: 2015-12-14 Last updated: 2017-03-22Bibliographically approved

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Nzabanita, Josephvon Rosen, DietrichSingull, Martin
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