Extended GMANOVA Model with a Linearly Structured Covariance Matrix
2015 (English)In: Mathematical Methods of Statistics, ISSN 1066-5307, E-ISSN 1934-8045, 1-15 p.Article in journal (Refereed) Accepted
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
2015. 1-15 p.
Estimation; extended growth curve model; GMANOVA; linearly struc- tured covariance matrix; residuals.
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:liu:diva-123370OAI: oai:DiVA.org:liu-123370DiVA: diva2:882130