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Estimation equations for multivariate linear models with Kronecker structured covariance matrices
Poznan University of Life Science, Poland.
Shanghai University of Int Business and Econ, Peoples R China.
Stat Sweden, Sweden.
Linköping University, Department of Mathematics, Mathematical Statistics . Linköping University, Faculty of Science & Engineering. Swedish University of Agriculture Science, Sweden.
2017 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 46, no 16, 7902-7915 p.Article in journal (Refereed) Published
Abstract [en]

The aim of the paper is to determine maximum-likelihood estimation equations. Observations follow a multivariate normal distribution, X-i similar to N-p,N-q (mu, Psi, Sigma), where D[X-i] = Sigma circle times Psi, Psi and Sigma describe the unknown covariance structure between rows and columns of X-i, respectively. Imposing restrictions on Psi and Sigma four types of covariance structures will be considered.

Place, publisher, year, edition, pages
TAYLOR & FRANCIS INC , 2017. Vol. 46, no 16, 7902-7915 p.
Keyword [en]
Compound symmetric structure; Kronecker product; matrix derivatives; maximum-likelihood estimation
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:liu:diva-139645DOI: 10.1080/03610926.2016.1165852ISI: 000405910600009OAI: oai:DiVA.org:liu-139645DiVA: diva2:1133702
Available from: 2017-08-16 Created: 2017-08-16 Last updated: 2017-08-16

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